Search the Community
Showing results for tags 'volatility'.
Found 18 results
Cyclical versus Historical Volatility
Michael C. Thomsett posted a article in Trading BlogIn this belief system, historical volatility is backward-looking and refers strictly to the price behavior of the underlying. Implied volatility is an estimate of the option premium’s future degree of movement (without knowing whether it will increase or decrease). It is based on application of known and unknown factors. The parametric version of historical volatility involves developing a series of assumptions about returns based on how price has behaved in the past. A non-parametric version is based on direct observation of recent price changes, without applying any other assumptions about future behavior. The often cited rule that “past returns do not reflect future returns” is part of the development of historical volatility. The two versions above can be combined as a form of hybrid analysis. However, both are based on recent prices and involve specific and known outcomes. Implied volatility relies on estimates of future option premium behavior and is not based directly on historical changes. However, known past volatility is likely to influence the assumptions applied to develop the estimate. Implied volatility is intended to predict and is based on the controversial Black-Scholes pricing model. This model contains numerous flaws, the greatest of which is implied volatility and the methods for arriving at its assumptions. But there is more. Most traders do not consider cyclical volatility in attempts to pin down likely future premium movement. In fact, beyond variance over time, in one important respect, volatility is predictable. One profound observation revealed that when it comes to how price behaves, “large changes tend to be followed by large changes- of either sign – and small changes tend to be followed by small changes.” [Mandelbrot, Benoit (October 1963). The Variation of Certain Speculative Prices. The Journal of Business, Volume 36, No. 4, pp. 394-419] This claim aids in identifying not only potential returns from options trading, but also of risks involved. The magnitude of price movement in the direct and immediate past is a predictor of how it is likely to behave in the future (although direction of movement cannot be known). Traders seeking low risk should therefore select options on underlyings with low historical volatility; and those willing to behave more speculatively may seek out options whose underlying has been much higher in historical volatility. In both cases, the most recent data are going to yield the most reliable analysis. Because historical volatility is easily identified, it is a sensible starting point for articulating cyclical volatility. Few underlying issues are consistent in their historical price behavior. Therefore, the most recent trends are most useful. This claim that large or small changes are likely to indicate future movement, should be apparent once it is expressed. Even so, options traders are not always likely to apply this observation in selecting one option trade over the other. It might not even be used to select a strategy at any moment. When a favorite underlying has exhibited low volatility, this may be sed to select a list of strategies that are appropriate, given the trader’s risk tolerance. Likewise, when volatility has been high recently, it may indicate a completely different list of possible strategies. When volatility changes dramatically, it could also be used to signal the timing of entering no new trades or closing current trades. This risk analysis is perhaps among the most useful traders can use to manage market risks for options. This explains use of the term “cyclical” in describing volatility. It is the most recent trend toward higher or lower volatility in the underlying. This directly affects option premium values, but because no form of volatility provides information about the direction of changes, it is limited to an understanding of the changes in risk and return. This is extremely valuable information, and it adds context to the observation of historical volatility levels. It makes the analysis not only sensitive to time, but also to how risks change as volatility adjusts. Can the same cyclical approach be used to estimate implied volatility? To a degree it can, but because IV is always an assumption, the most sensible method for cyclical analysis would be to base future estimates on historical option pricing. In other words, the degree of risk in implied volatility may be based on price changes in the option itself. This is a form of option-based historical volatility. It is complicated, however, because time decay distorts and determines volatility, notably as expiration approaches. The sensible determination of cyclical implied volatility would have to be based on past option volatility as specific moments. For example, selecting times to expiration (4, 3, or 2 weeks, for example), how has one option behaved compared to another. Applying identical assumptions of implied volatility, how accurate have these been in understanding premium movement? This becomes difficult to apply, because – as options traders know – the behavior of one option is different than that of another, even given the same circumstances and timing. For these reasons, a starting point of cyclical analysis is more sensible based on the underlying in the moment. A comparison between several underlying issues and the historical volatility of each will indicate the recent and current volatility (risk) levels and help traders to improve their selection of underlying securities and option strategies. The intention in implied volatility has always been to accurately estimate future volatility levels, but the reliance on this estimate is flawed and not as reliable as traders would wish. However, when the analysis is based on cyclical historical volatility of the underlying, risks are better understood. It makes sense when recalling the nature of options. They are called derivatives because they are derived from price movement in the underlying (historical volatility). Overlaying the cyclical component improves the application of volatility in selection of both the underlying and the option strategy. Michael C. Thomsett is a widely published author with over 80 business and investing books, including the best-selling Getting Started in Options, coming out in its 10th edition later this year. He also wrote the recently released The Mathematics of Options. Thomsett is a frequent speaker at trade shows and blogs on his website at Thomsett Publishing as well as on Seeking Alpha, LinkedIn, Twitter and Facebook. Related articles Implied Volatility Collapse Pricing Models and Volatility Problems Types of Volatility Fundamental Volatility and Stock Prices How to Trade Options Volatility Volatility During Crises How To Profit From A Volatile Market
Option Volatility and the Underlying
Michael C. Thomsett posted a article in Trading BlogEven if you are accurate in assigning a volatility assumption, it only indicates the degree of change, not the direction. The underlying might move up or down, even while the option volatility has been accurately guessed. Secondly, volatility assumption is always based on guesswork, and not on anything reliable. Past price behavior and volatility does not indicate how future volatility will change (or in which direction). It is fair to assume that an underlying that has been volatile in recent weeks, will be volatile in the future as well. This is also a guess, of course, but a reasonable one. By the same argument, you may assume that a low-volatility stock is likely to remain at the same low level in the immediate future. However, if trades are made solely based on recent price activity, it is a risky venture. The option volatility is always independent of the underlying volatility and price movement. If you assume that volatility is going to be at 30% in the future, this means you expect the option to behave at the 30% volatility level. But this could translate to a premium increase or decrease (before even considering time decay). A broad assumption is that when markets are declining, an issue is going to be more volatile than when they are rising. Is this accurate? Again, as noted previously, volatility is not really a factor of whether markets are rising or falling. For example, this year the stock market has been extremely volatile even as index-based prices have generally moved to the upside. The true nature of volatility is not determined by price direction, but by the degree of movement (in either direction). Where markets at one time tended to change by 50 points or less each day, the current markets have often moved in hundreds of points. The direction has not determined volatility, but the degree of movement has. This translates to implied volatility in every option contract, but it is an error to assume that volatility tells a trader the likely direction of movement. Assuming the level of volatility depends on whether underlying prices are rising or falling, is an inaccurate method for estimating future volatility. Even if experience has indicated higher volatility in a falling market, that could change in the next move. Option traders often focus on volatility to such an extent that the assumed relationship between underlying price direction and option volatility is clearly demonstrated. It is not. It may easily vary over time and on a marketwide basis. Volatility also varies between one issue and another. A related error in observations depends on the price of the underlying. Traders may easily believe that higher-priced underlying issues are more volatile than lower-priced issues. For example, a $3,000 stock might change in one session by 40 points, whereas a $30 stock might move only 10 points. But even though the higher-priced stock moved four times more points, it is not reasonable to compare the two on point value alone. The 40 point movement represents a move of only 1.3%, but the 10-point move represents 33.3%, more than 25 times more: 40 ÷ $3,000 = 1.3% 10 ÷ $30 = 33.3% Most traders understand this distinction but may still react to thew difference and assume the 40-point move is so substantial that it must mean the higher-price stock is more volatile. This is likely to be an unconscious observation, but it is flawed. Traders tend to think in terms of dollars and cents, and a higher dollar value may be assumed to represent more volatility rather than less. This also applies when a different number of underlying shares are compared. For example, 10 shares of the $3,000 stock will cost $30,000. If you own 1,000 shares of the $30 stock, it also is worth $30,000. It is all too easy to fall into the trap of making inaccurate assumptions, even for a trader who is skilled in math. The more advanced application of a price model may assist in deciding to what degree the underlying price and volatility can be estimated. The constant elasticity of variance (CEV) model accomplishes this, but it is esoteric, and its application to trading decisions might not be so reliable that it can lead to an informed decision. [Schroder, Mark (March 1989). “Computing the Constant Elasticity Model of Variance Option Pricing Model.” Journal of Finance, Volume 44, No. 1, pp. 211-219] This model is intended to determine a probability modeling of price movement at varying magnitude, to volatility reaction in option premium. Because the actual price of the underlying relative to option premium varies among each issue, there are two problems with this model. First, it is complex and difficult to calculate. Second, it is practically impossible to compare outcomes among different underlyings. This means the time required to complete an analysis is not compatible with the split second timing traders often face in deciding to trade one option or another (especially when base don volatility or other estimations). For these reasons, CEV is not used widely. It is interesting as a method for studying the relationship between underlying price behavior and volatility, but for most applications, it is not a reliable modeling system. As with all models for options pricing, the academic purpose is more applicable than any practical considerations. Michael C. Thomsett is a widely published author with over 80 business and investing books, including the best-selling Getting Started in Options, coming out in its 10th edition later this year. He also wrote the recently released The Mathematics of Options. Thomsett is a frequent speaker at trade shows and blogs on his website at Thomsett Publishing as well as on Seeking Alpha, LinkedIn, Twitter and Facebook. Related articles Implied Volatility Collapse Pricing Models and Volatility Problems Types of Volatility Fundamental Volatility and Stock Prices How to Trade Options Volatility Volatility During Crises How To Profit From A Volatile Market
Managing Volatility Spreads
Michael C. Thomsett posted a article in Trading BlogA popular feature of spread selection is the assumption that mispriced options are found frequently. This observation leads to a natural conclusion, that is makes sense to take up a market position opposing the option while, at the same time, entering a position in the option. This popular hedge may involve trading in the underlying, or in other options that are equivalent to positions in the underlying. In this way, the volatility spread facilitates risk management while also exploiting a mispriced option. Beginning with a study of delta, how can a trader hedge an underpriced option? There are several ways. If, for example, the first step is to buy 3 options, they can by hedged by: (a) selling 300 shares of the underlying, (b) buying puts with the same or similar delta, (c) selling calls of a different strike and with the same delta, or (d) combining the above moves in ways that create the same delta as the original long calls. In setting up a volatility spread in one of several methods, the outcome creates several attributes that are shared by the strategies themselves. These include al overall delta neutral result, sensitivity to any price change in the underlying as well as to changes in implied volatility, and time decay that affects both sides of the spread equally (and based on amount of time remaining to expiration). This last attribute, time decay, can lead to some interesting variations in the volatility spread when it is set up horizontally (different expirations) or diagonally (different expirations and strikes) rather than vertically (same expiration and strike). This adds great variety in how a volatility spread can be created. Among the consideration are collateral requirements, cost of the underlying when held or traded, and richness of premium on either long or short sides. The selection of a volatility spread is complicated by the possibility of many different ones. The range of spreads includes: Ratio backspreads (also called long ratio spreads) – combining a greater number of long options than short, with the sale expiration. The long positions should have higher delta value than the short positions. Either calls or puts can be used. Ratio vertical spreads (also called front spreads or short ratio spreads) – This involves a higher number of short positions than long positions, all with the same expiration. Butterfly and condor spreads, either long or short – unlike basic two-position spreads, butterfly and condor spreads involve more complex multiples, and may be either long or short. Butterflies involve three strikes, and condors use four. Calendar spreads (horizontal or time spreads), long or short – the strikes are the same on both sides, but expiration is not. Typically, the shorter-term strikes are short and the longer-term are long. This exploits more rapid time decay on the short side, but it sets up a net debit. Diagonal spreads (different expiration and strike) – in this variety, both strike and expiration are different. It is set up to exploit expected underlying movement as well as time decay. Shorter-term are normally short, and longer-term are long. By using different strikes, the net debit can be reduced or largely eliminated. Ratio calendar or diagonal spreads – varying the number of positions in calendar or diagonal spreads allows an otherwise net debit to be converted to a net credit. Using shorter-term short options greater in number than longer-term long options, risks are manageable. Movement to ITM is managed by rolling forward and creating a different version of the volatility spread. Collar – in this volatility spread, three positions are opened. They are a long position in the underlying, a short covered call, and a long put. The call’s strike is higher than the cost of the underlying, and the put’s strike is lower. This position makes sense when the original cost of the underlying was well below current market value. Gut spread (both sides in the money) – this spread assumes the underlying will move significantly before option expiration, but the trader is not certain about the direct of the price movement. Synthetic long and short stock – these consist of one long and one short option, which in combination mirror movement in the underlying security. A long stock synthetic consists of a long call and a short stock; and a short stock synthetic is made up of a long put and a short call. The net cost to open this position is close to zero if the strike is close to the money. The combined change in net value will track the underlying point for point. Given the many variations in the volatility spread, traders must be especially concerned with the degree of movement in the underlying. In the ideal hedge, the direction of underlying price change does not matter, because one side offsets the other. Most volatility spreads will perform better when movement takes place in a desired direction. But even in the perfect hedge, a large movement can create either exceptional profits or losses, as well as undesired changes in the collateral requirement. This is especially concerning to traders using multiple contracts on either side, when a large underlying movement could outpace available capital, resulting in having part or all the position closed due to shortfalls in collateral. This may present a more serious risk than the option-related profitability of a spread. Even so, the unintended consequences that are always possible, may be overlooked by edging traders, or by those spending too much focus on delta and gamma and not enough on more basic matters, such as historical volatility. Volatility spreads are appealing as hedging instruments, but they also come with many risks, including some not apparent when first considered. The trader who is aware of the importance of volatility in all spreads, is more likely to also be aware of a full range of risks. Michael C. Thomsett is a widely published author with over 80 business and investing books, including the best-selling Getting Started in Options, coming out in its 10th edition later this year. He also wrote the recently released The Mathematics of Options. Thomsett is a frequent speaker at trade shows and blogs on his website at Thomsett Publishing as well as on Seeking Alpha, LinkedIn, Twitter and Facebook. Related articles Implied Volatility Collapse Pricing Models and Volatility Problems Types of Volatility Fundamental Volatility and Stock Prices How to Trade Options Volatility Volatility During Crises How To Profit From A Volatile Market
Implied Volatility Collapse
Michael C. Thomsett posted a article in Trading BlogBecause the public cannot trade options after Friday’s close, speculating on these positions must assume that price will move after last trading day but before Saturday expiration. Traders have no control over this, meaning it is taking a chance, whether going long or short. With volatility collapse a factor in how price behaves on expiration Saturday, the question becomes whether it changes rapidly or smoothly – or not at all. Because it is unlikely that high volatility will be likely to decline smoothly, most traders will not want the exposure, especially when taking short positions. It may be reasonable if the price is low enough to speculate in a long call or put, hoping that volatility moves in a favorable direction. Experienced traders will observe a predictable pattern in volatility collapse on last trading day, and this helps select a position that offers a better than average likelihood of profit. However, the profile is determined by volatility in the underling and will not be the same for all stocks. As with all option strategies, timing of last-minute trades based on volatility collapse must be done with familiarity of the underlying and its historical volatility. This assumes that implied volatility will closely follow that trend. It normally does, but given that expiration is about to occur, this is not always going to occur as expected. If the analysis is limited at ATM options on last trading day, it should be kept in mind that these positions are overly sensitive to even the smallest change in the underlying price, notably in the final hours of trading. Because this takes place on Friday, even non-option stock traders behave with full awareness that they will not be able to trade for three days. This affects potential value of both the stock and its options. Implied volatility in this timing is going to be noisy in the sense it will be more volatile than usual. This may be an advantage or a disadvantage, based on many factors. Most option traders are fully aware of most of these factors. Complicating matters even more, market behavior is not going to be rational in all cases, especially on expiration Friday (for option traders) and to a degree, on any Friday (for equity traders). This irrational behavior makes implied volatility noise even more intense than a trader might expect. A blind spot for many traders is the assumption that trading decision are made rationally, and this can lead to problems in timing. Implied volatility must be expected to become increasingly unreliable and unpredictable for ITM options, and for many last-minute traders, ITM options are the preferred vehicle for trades. A related observation worth making is the reliability and stability of calls and puts in this moment. Because only one of the two will be ITM, it is likely that one side (ITM) will be unpredictable, while the other side (OTM) will be more predictable. This raises some interesting possibilities for last-minute spread trading, with emphasis on OTM positions as offering less risk, and ITM positions possibly presenting more profit (or loss). Also affecting the potential profit or loss based on moneyness, is the pinning factor. If the underlying will move toward (or remain at) a price close to the strike of the closest option, how does this affect the timing of expiration trading? Pinning, like implied volatility, is not as predictable as traders would like, but it could be a factor. Some traders believe that option behavior can and does affect underlying prices. But this is only true in that very short-term time right near expiration, and not during the entire cycle. Trading on the assumption of how implied volatility will behave, tied into an assumption about price pinning, is a dangerous and often expensive strategy. Most traders would not consider expiration trading as a form of equity hedging. However, it is possible to time option positions to protect equity profits (with covered calls, for example), representing a short-term hedge. For example, if the stock position is profitable, a covered call can be opened on last trading day ITM. If the underlying price moves above the strike, exercise produces a profit from both the equity investment and the option premium. If the underling price declines, the loss is reduced due to option premium, taking net basis down; and this further allows the trader to enter another covered call or similar position. Because expiration strategy does not allow traders to close or roll after Friday’s close, entering a similar hedge with a short put is not as wise. ITM expiration means unavoidable exercise, and most short put writers do not want exercise of the position. The short put strategy has the same market risk as a covered call, but at expiration, it is not as safe. A covered call is going to be advantageous whether underlying price rises or falls. This is not true with short puts. In entering any option position, the assumed volatility collapse will occur in a predictable manner, but the speed and degree of movement toward zero is not the same in every case. This is where the interesting potential is found, either for profit or loss. Implied volatility for high-volume stocks will behave much differently for low-volatility issues. But even this does not mean the speed and degree of change is going to be predictable; it might, in fact, behave as irrationally as those traders in the market at this last step in the option’s lifespan. Perhaps the most interesting selection for expiration trading is the case where earnings announcements are made after Friday’s close. In this case, public trading is no longer possible, but volatility could change significantly by the end of expiration Saturday. The trader’s dilemma in this case is that a big earnings surprise could be either positive or negative. Anyone speculating on this situation must be ready to accept a loss if the surprise is not a pleasant or desirable one. Michael C. Thomsett is a widely published author with over 80 business and investing books, including the best-selling Getting Started in Options, coming out in its 10th edition later this year. He also wrote the recently released The Mathematics of Options. Thomsett is a frequent speaker at trade shows and blogs on his website at Thomsett Publishing as well as on Seeking Alpha, LinkedIn, Twitter and Facebook.
Trading Volatility: Why It Isn’t Always a Bad Thing
Kim posted a article in Trading BlogHowever, panicking during volatile conditions is the last thing you want to do. To an extent, volatility can even play to your favor as a trader. Volatility: Causes and Effects Volatility is simply explained as the severity and frequency of change in the value of an asset over a certain period of time. It is mostly associated with the stock market but it also applies to different markets, such as foreign exchange or commodities. Regardless, a market with low volatility means there isn’t much change in the price of an asset, certainly not enough to stir a panic. High volatility, on the other hand, indicates wide price fluctuations and heightened risk for investors. Volatility occurs when there is an imbalance of trade orders. Panic selling, for example, can trigger a sharp decline in stock prices, while panic buying can cause prices to shoot through the roof. What causes volatility, then, is the sentiment of investors that leads them to behave in a certain manner. This is influenced by a couple of factors, including economic and socio-political developments. Announcements from the central bank, inflation, and elections fall under this category. Company developments also influence the value of a certain stock. A change in corporate leadership or announcements of a new product can trigger investors to take a bullish or a bearish view on the asset. High volatility also has negative effects on the trading process as well. Because of the high volume of trading, execution of orders might be delayed. Actual prices might vary from the quoted prices from when the order was placed due to the delay in execution. Or worse, high trading activity might make it difficult to place trades in a timely fashion or even access online trading accounts. To prevent these from happening, the U.S. stock exchanges set up circuit breakers to temporarily pause trading activity during turbulent times. This happened several times in March as investors panicked over the coronavirus outbreak which fuelled market volatility. Taking advantage of volatility That said, volatility isn’t necessarily something to fear. In fact, any trader with enough experience will tell you that price movements, whether positive or negative, present more opportunities to turn a profit. This is especially true for short-term traders like day traders or swing traders who take advantage of price fluctuations. Risk moves in both directions — while volatility might mean a greater potential for loss, it can also magnify the potential for rewards. Of course, the key is making an accurate prediction of how an asset’s price will move. Short-term traders who bet on price swings use different volatility indicators to determine the best position for their trade. These indicators let investors properly time market highs and lows so they can enter and exit as necessary. Or, it can also be used to justify shorting a stock or as a hedging strategy. Another way to take advantage of market volatility is to trade derivatives instead of the underlying asset. Stock CFD trading, or trading contracts for difference, allow you to speculate on stock share prices regardless if it’s an uptrend or downtrend. For instance, instead of risking exposure in a falling market, you can profit from CFD trading by speculating on the downtrend using volatility indicators. Trading options is another way to use volatility in your favor over shorter periods of time. Whether you’re trading the primary asset or its derivative, it’s important to understand that market volatility is an inevitable part of trading. For short-term traders, it’s actually a welcome component because stagnant prices limit the potential to generate profit. But if you’re taking a long-term approach by investing, avoid panicking in turbulent conditions. Continuously review your risk tolerance and rebalance your portfolio, while also getting comfortable with riding out highs and lows.
Pricing Models and Volatility Problems
Michael C. Thomsett posted a article in Trading BlogOf course, this makes no sense. Volatility changes constantly, ands this points out the problem with any model. It must assume that volatility remains unchanged for the math to work out. Even so, the assumption is so flawed that it makes the model unreliable. Making matter worse, the BSM has many other flaws as well. In math, one flaw is bad enough; but when you face at least 8 flaws (as BSM dies), it means there is zero reliability.  But it gets worse. Volatility is unpredictable. Even with the high number of flaws that create unaccounted for variables, the volatility problem is more severe. With fixed volatility, the degree of standard deviation is predictable, but this is not how things work in the real world. Price movement is chaotic, meaning that volatility is also chaotic and unpredictable. High and low volatility occur when price behavior is narrow and, on the other extreme, when it is broad. But how can this be predicted? It cannot. Volatility never remains unchanged, and it never changes in a predictable manner, or in a straight line. Volatility does not anticipate direction or degree of price change. Even though the BSM assumes volatility remains unchanged, another problem must be recognized. Even if the degree of today’s volatility remained unchanged, which direction will price take? Will it rise, fall, or remain unchanged? High daily volatility can occur within a range of price, but from day to day exhibit no significant movement. This is a factor never anticipated in BSM or, for that matter, in any pricing model. The flaws about volatility are more complex than the initial assumption that volatility does not change. Beyond direction of price movement, even fixed volatility does not reveal the degree of price movement in the underlying. A 5% move in a stock selling for $30 per share implies a 1½ point change. But if the price per share is $90, the same 1½ point movement is 4½ points. The assumed degree of volatility is not fixed but varies based on the underlying price range. The timing of price changes also affects volatility. Does the underlying advance and then decline, or does it move in the opposite direction? Are there extended periods of consolidation? Every underlying behaves different, causing great variability in how volatility reacts. The option contract changes based on underlying price movement, and a correlation between the timing of price trends, and the volatility of the option, cannot be overlooked. The time required and the sequence of movement are further affected by moneyness and time to expiration. Moneyness also affects volatility. The BSM assumption is normally applied to any option, regardless of its proximity to the strike. This is also unrealistic. ATM options have the highest gamma levels, so there are obvious differences between ATM, OTM and ITM contracts. And the greater the distance to strike, the greater the effect on volatility. It cannot be assumed in any situation that the option is ATM and will remain there. If it would, then no pricing model is needed. Nothing moves. But in practice, as an option moves ITM or OTM, gamma will change as well. Volatility changes as the distance grows. Time to expiration also affects volatility. A shorter-term option is likely to exhibit higher gamma than longer-term options, and the time span affects volatility directly. As expiration approaches, gamma should increase as well (assuming offsetting movement in moneyness does not change the calculation). In applying a price model, it is unrealistic to base assumptions on an option remaining ATM because, as movement occurs (and as expiration nears), the entire matter of gamma changes drastically. As expiration nears, volatility behavior also changes. Even if a trader could know the volatility level near expiration, a pricing model is likely to undervalue an ATM option as volatility rises, and to overvalue the ATM option as volatility declines. Type of option trade distorts volatility assumptions. Is the trade a long contract or a short contract? Is it a spread or a straddle? The nature and attributes of trades matter and volatility is going to vary based on the trade itself. A related issue is the historic volatility of the underlying. A highly volatile underlying price will directly affect option premium and its implied volatility. When this point is expanded to different types of trades, the overall problem also becomes clearer. Not all trades are the same, so BSM assumptions about volatility are more complex for some trades and combinations, than for others. Adjusting for stochastic volatility (SV) creates yet another variable. Under the BSM model, volatility is assumed to remain constant. Applying Stochastic volatility, the assumption is added that volatility varies as time passes. This does not make the calculation more reliable; it only adds one more random variable. This may allow for analysis of a range of possible pricing outcomes, but it remains a guess to matter how many variations of the model are used. The problem remains: No pricing model can accurately forecast option prices in the future. Those few theorists who swear by BSM must ignore the facts, but any model contains flaws and imperfections. The solution is not to develop better methods for calculating volatility, because it is entirely unpredictable. The solution is to identify strategies and risk limiting methods to survive in an uncertain world.  The 8 most serious flaws of BSM are: (1) Volatility remains constant (2) there is no restriction on buying or selling the underlying; (3) no tax consequences apply to profits; (4) interest rates are fixed and available to all; (5) no transaction costs are in effect; (6) trading is continuous without any gaps in price movement; (7) volatility is independent from underlying price; and (8) price changes are normally distributed. Michael C. Thomsett is a widely published author with over 80 business and investing books, including the best-selling Getting Started in Options, coming out in its 10th edition later this year. He also wrote the recently released The Mathematics of Options. Thomsett is a frequent speaker at trade shows and blogs on his website at Thomsett Publishing as well as on Seeking Alpha, LinkedIn, Twitter and Facebook.
Types of Volatility
Michael C. Thomsett posted a article in Trading BlogHistorical volatility The best known form of volatility is based on underlying price behavior. Historical volatility has certainty, because it reflects price activity in the recent past, with no estimates of the future. Options are derived from the underlying price activity, and option premium is derived from historical volatility. This does not tell us what will happen next, but it does provide a means for comparing risk (volatility is risk, in fact). In looking at historical volatility for several underlying issues, it becomes natural and easy to compare risks from one to the other. The historical record of volatility allows traders to estimate the likely risk level, based on possible price movement. The longer the period analyzed, the more reliable this will become. If an underlying his displayed low historical volatility over many years, it is less likely that high implied volatility of the option will follow, at least when comparted to an underlying with much higher historical volatility. It can be calculated using several variables. The most reliable are (a) the period being studied and (b) the interval between price movement and change (daily, weekly, monthly, for example). The best-known and most often used are one year and daily price changes but using a smaller number of daily sessions also focuses current volatility on the most recent information. Despite widespread popularity of implied volatility, the fact is that the underlying historical volatility is probably the most reliable measurement of risk in both the underlying and its options. Implied volatility A popular but somewhat uncertain test is implied volatility of the option. This calculation is nothing like that for historical volatility. It is strictly an estimate of future volatility, based on some assumptions (which themselves are subject to interpretation). Many options traders swear by implied volatility but questioning why this is so makes sense. Would the same trader rely on underlying price change based on recent historical volatility? Probably not. It doesn’t make any sense. The same logic can be used to question implied volatility and its value. A good question to ask is which volatility is used by the market. Few traders not using options will ever try to estimate implied volatility, because that belongs only to the options market. This does not make it reliable; in fact, can anyone say that all options traders are using the same pricing model? No. In fact, there are many pricing models, and even those using the same one (i.e., Black Scholes) are probably not using the same assumptions to determine volatility. Implied volatility is subject to a lot of interpretation and it is most loved among academics, but much less among traders. That may be the bottom line and the most revealing fact of all. Future volatility This is the volatility that every trader dreams of understanding, by whatever name it is given. This is the future distribution of prices for the underlying. No one who has followed the broader markets will be able to claim that they know what future volatility will be. In fact, one characteristic of the market is that it constantly surprises all its players, and no one can accurately predict what future volatility will be, not to mention the direction of price movement. If you can guess at the right probability, you can accurately predict future volatility. But probability is just as elusive as all other market factors, and no one can know what will happen tomorrow, next month, or next year. It is equally impossible to know ahead of time what factors will cause markets to rise or fall. There are so many, including those not yet known or understood by anyone. Forecast volatility Every market has its share of “experts,” people or companies that confidently predict volatility in coming days, weeks or months. They cite numerous justification for their opinions, but it is unlikely that anyone has gotten rich investing or trading based on estimates of forecast volatility. Ironically, many forecasters claim that they rely on the fundamentals, but forecast volatility is as technical a signal as anyone can find. It is all guesswork, and the only certainty available is that time value declines as expiration approaches, and the day after expiration, every option is worth zero. This knowledge is known in advance by every trader, but with options, the idea is to gain in-the-money value (for long options) despite the knowledge of how time works against the long position (and in favor of the short position). Forecast volatility for options is no more reliable than for the underlying, because these two are related. As the underlying behaves, so too will the option (given the added variables of time decay and expiration). Seasonal volatility A final version may be called seasonal volatility. For options on futures contracts, this is well understood for agricultural contracts, but for equity options, is there a seasonal version? There is, in fact. For example, in a political year, the season approaching election day has everything to do with risk. Which candidate will win, and how will that affect overall markets and options? The 2016 election say dramatic and sharp increases in equity value right after the election, contrary to dire predictions offered by many “experts” on market matters. Will 2020 have a similar cause and effect based on which candidate wins? The same observation can be applied to off-year politics, to future volatility guesswork, and even to the weather. The important factor to keep in mind is that volatility in most forms is largely a matter of guesswork, and at times the “educated” guess may be just as dubious as the arbitrary or uneducated guess. This is the problem with volatility. All traders, including options traders, constantly seek a reliable method for improving timing and reducing risk. If that were possible, every trader could become rich because beating the odds is an intrinsic part of the options world. But it is not actually possible for anyone. Volatility could be thought of as another word for the term “uncertainty.” Michael C. Thomsett is a widely published author with over 80 business and investing books, including the best-selling Getting Started in Options, coming out in its 10th edition later this year. He also wrote the recently released The Mathematics of Options. Thomsett is a frequent speaker at trade shows and blogs on his website at Thomsett Publishing as well as on Seeking Alpha, LinkedIn, Twitter and Facebook.
Fundamental Volatility and Stock Prices
Michael C. Thomsett posted a article in Trading BlogFor some traders, this makes little sense. Options traders tend to be pure technical traders, concerned with implied volatility and short-term valuation of options (often ignoring how stock price behavior changes over time). This overlooks the importance of historical volatility and, equally important, of fundamental volatility as well. Fundamental volatility is the degree of reliability in fundamental trends. Items such as revenue, gross profit, net profit and net return are of little interest to many options traders but starting there is a good suggestion. How does a trader pick one or another stock for options activity? Ask several options traders and you discover that some (if not most) have never given this much thought. This should be surprising, but the culture of the options industry tends to lack the holistic appreciation of how the company directly affects option pricing. Flaws in IV versus fundamental value Implied volatility is often viewed as the "holy grail" of options trading. This ironic because IV is an estimate based on the current levels of historical volatility. The advantage is, IV is current. The disadvantage is, it is an estimate and several attributes going into IV are assumptions, often without solid foundation. The concept of fundamental volatility many apply to macroeconomic factors of an industry as it affects the company, or it refers to a company's profit and loss trends and ratios. It may also describe credit risk or return on investment. When considering options trading, the great debate is usually between IV and historical volatility. When reported revenue and earnings are steady over a decade, fundamental volatility is low. This usually is also reflected in stock price (historical) volatility and, as a result, in options premium and its implied volatility -- usually but not always. In determining which companies to pick as candidates for options trading, this is a good starting point. Depending on a trader's risk tolerance, it could be preferable to pick a company with high or with low fundamental volatility. The higher the fundamental volatility, the higher the risks in options trading, and the higher the profit potential. Some traders like it this way, but others would prefer low fundamental volatility and its effect on options trading risk. Profitability will be lower, but the level of predictability is lower as well, so potentially devastating losses are less likely when volatility at all levels is low. By mathematically calculating year to year volatility (in revenue and earnings, for example) it is easy to identify levels of fundamental volatility. A company whose revenue and earnings rise steadily over 10 years is encouraging to conservative investors; this carries over to a relative degree of safety or risk in options trading as well. Direct impacts Does fundamental volatility affect historical volatility? Everyone knows that prices rise and fall for many reasons. Some can be anticipated, and others cannot. However, low fundamental volatility tends to lead directly to low historical volatility. Strong and reliable profit and loss reports are associated directly with strong and growing stock prices and earnings per share. The correlation is not 100% predictable because other factors also are at work – competitive trends, changes in management, mergers and acquisitions, economic changes, geopolitical influences, and much more – and these also affect stock prices. However, fundamental volatility is probably a consistent influence on stock price behavior. A secondary direct impact is seen between historical volatility of the stock, and pricing of the option. The consistent trading stock with relatively narrow breadth of trading will develop option pricing with narrow bid/ask spread and with a tendency to reflect lower than average implied volatility. This all represents lower than average risk. When the opposite occurs – higher or erratic breadth of trading and unpredictable, sudden price reversals – options are richer due to higher implied volatility. Options traders are aware of this and often view the situation as an opportunity foe higher profits. However, it also means that risks are greater. The measurement of fundamental volatility and its direct effect on historical volatility and option implied volatility, essentially defines levels of risk. This is seen in variations of bid/ask spread, movement in premium levels, and open interest. A complete study of fundamental volatility should begin with the study of revenue, earnings and net return. It can be further expanded into a study of dividend yield ands the payout ratio, P/E high and low each year, and the debt to total capitalization ratio, which tests working capital more effectively and accurately than the more popular but less reliable current ratio. Of the many fundamental trends and ratios, a small number can be used to articulate fundamental volatility. Focusing on revenue and earnings, dividend trends, annual high/low of the P/E ratio, and long-term trend of the debt to total capital ratio will reveal whether a company is a conservative or high-risk candidate for options trading. This eliminates the all too common problem faced by traders: Considering themselves conservative but making trades that are high-risk. In the options world, the question of risk tolerance and methods for picking appropriate strategies and making trades on appropriate issues, should provide the method for making sure risk tolerance affects how decisions are made. This is not practiced by all options traders, and that explains why timing problems arise and why losses occur as often as they do. As long as a conservative trader makes conservative choices, leaving the speculative traders to the willing speculator, the problems of poor selection can be reduced and eliminated. Michael C. Thomsett is a widely published author with over 80 business and investing books, including the best-selling Getting Started in Options, coming out in its 10th edition later this year. He also wrote the recently released The Mathematics of Options. Thomsett is a frequent speaker at trade shows and blogs on his websiteat Thomsett Guide as well as on Seeking Alpha, LinkedIn, Twitter and Facebook.
TUR Trade Update
GavinMcMaster posted a article in Trading BlogHigh volatility such as this provides huge opportunity for option traders. In the article, I detailed out three potential trades for TUR – a Short Straddle, A Poor Man’s Covered Call, a Cash Secured Put and a Bear Call Spread. I ended up going with a Short Straddle, a neutral trade, only to see the ETF drop quite quickly from $34 to $27. As a reminder, a short strangle consists of a short put and a short call placed at-of-the-money. The thesis of the trade is that the stock will remain near the strike price for the duration of the trade and the trader will be able to close the trade for a profit thanks to time decay. However, sometimes things do not go to plan. If the stock makes a large move in either direction, the short straddle comes under pressure. In this example, TUR dropped pretty hard, all the way down to $26 at one point. Here are the details of the trade and the ensuing adjustment. Trade Date: May 30th Underlying Price: $34.34 Trade Details: Sell 2 TUR July 20th 34 Calls @ $1.65 Sell 2 TUR July 20th 34 Puts @ $2.40 Premium Received: $820 By June 13th, the trade was under a bit of pressure with TUR dropping to $29.72 which was around my initial breakeven point. This was my adjustment point and I adjusted by adding a second straddle at $27. Trade Date: June 13th Underlying Price: $29.72 Trade Details: Sell 2 TUR July 20th 27 Calls @ $2.85 Sell 2 TUR July 20th 27 Puts @ $0.80 Premium Received: $730 At this point the total premium received was $1550 and by adding a second straddle I turned the position into basically a strangle. A better was to do this perhaps would have been to turn it into a standard strangle with short calls at #4 and short puts at $27. This would have reduced the early assignment risk, but luckily I didn’t suffer any early assignment in any case. Just something to keep in mind for next time. BEFORE ADJUSTMENT AFTER ADJUSTMENT At expiration, TUR closed at $27.97 which resulted in a net profit of $160. Not a huge profit in anyone’s view, but certainly not too bad for a neutral trade on an ETF that dropped 18%. SUMMARY In summary, this adjustment strategy for short straddles may not be for everyone, but hopefully I have demonstrated to you that it is possible to still achieve a profit even when the underlying makes a big move. In this example, we achieved a small profit, but we did add more risk to the trade in terms of more contracts. Finally, I leave you with some words from Dr. Russell Richards regarding this type of adjustment: “When scrambling to manage a losing trade, especially a losing undefined risk trade, most traders are happy to exit the losing trade at a “wash” or even a small loss. You will have to decide what is appropriate for you, but don’t get greedy when managing losing trades.” What do you think about this trading strategy, let me know in the comments if you’ve tried short straddles in the past. Trade safe, Gav. Gavin McMaster has a Masters in Applied Finance and Investment. He specializes in income trading using options, is very conservative in his style and believes patience in waiting for the best setups is the key to successful trading. He likes to focus on short volatility strategies. Gavin has written 5 books on options trading, 3 of which were bestsellers. He launched Options Trading IQ in 2010 to teach people how to trade options and eliminate all the Bullsh*t that’s out there. You can follow Gavin on Twitter. The original article can be found here.
The Astonishing Story Behind XIV Debacle
Ophir Gottlieb posted a article in Trading BlogWhatever it was, the VIX went from 17% to 37% in a matter of two-hours, or up 115%. That is the largest percentage gain in the VIX in one day ever recorded. Even then, while that is a huge move, it wasn't really market disruptive in any great way other than, the market had a bad day. But then the after hours margin calls came in -- and that was an unmitigated disaster for one particular instrument of interest to us: Credit Suisse AG - VelocityShares Daily Inverse VIX Short Term ETN (NASDAQ:XIV). DON'T LISTEN TO TV The reporters on television have no understanding what XIV is -- it is not a naked short bet on VIX. No, it is an investment in the core underlying principle of market structures, driven by positive interest rates, known as Contango. Remember, the XIV is the opposite of VXX, and the expected value of VXX is zero. Here it is, from the actual VXX prospectus: This instrument is not a radical short trade, it is fundamentally an investment in an ETN that reverses the value of an investment that is ultimately expected to be zero, which made it so good, for so long, and would have for several more decades. WHEN A LINE BECOMES THE FOCUS A little detail in the prospectus of XIV is that, hypothetically, should it lose 80% of its value from the close, it would cause a "acceleration event." That means that if the XIV sunk to 20% of its value, it would go to zero and the ETN would go away (and start over later). Now, obviously, this had never happened to XIV before, but it's only a decade old. When scientists back-tested XIV all the way back to the 1987 crash and including the 9/11 terror attacks, they noted that even then, XIV would not have suffered a 80% decline in a day. But we have never seen such a market with so many naked short vol sellers as we have today. As a barometer, even as crazed as Monday was, here is how XIV closed: Down 14.32% is ugly, but, it's just a day -- a bad one, but nothing really all that crazed. Then the after hours session happened, and the best anyone can tell, as of this writing, is that some firm (or fund) had to unwind a short volatility position due to a margin call. That meant they had to buy the front month expiration of the VIX futures, leaving the second month unchanged. That little detail is everything, because the XIV is an investment on contango -- when the second month is priced higher than the first month. This is a market structure apparatus -- we could call it "normal market structure." But, with a flood of buying to cover short front month futures, the XIV started tumbling after hours. At first, social media saw it as a buying opportunity. Then it started dropping faster. Then disaster struck. The XIV dropped more than 80%: The financial press did its best to cover it, but after a 2 minute segment on CNBC, there was nothing left to say because of one major rule inside the XIV prospectus. Here it is: In that fine print, it reads that if the value of XIV dips to 20% of the closing value (if it is down 80%), the fund stops. That is, since this trade, if done with actual futures contracts, can actually go negative, the ETN stops itself out at a 80% one day loss. This is why we investors use the ETN, knowing that a 100% loss is the worst that can happen, as opposed to the futures, where much worse than 100% loss can occur. And the greatest burn of it all As of Tuesday morning the VIX is down huge (of course it is), the market structure has held (of course it did), and XIV would be having a very good day (of course it would). But, worse --- it turns out, as far as we know (still speculation), while it's hard to swallow, that the unwinding was done by none other than Credit Suisse itself. Yes, the creators of the ETN had another concern, beyond the assets under management -- and here it is -- -- look at the largest shareholder. Credit Suisse quietly became the single largest holder of the very instrument it created, and by a huge amount. So, as 4pm EST came around, a bad day in XIV, but survivable, became the death knell, because the largest holder, the XIV's custodian, panicked, and covered. But, Credit Suisse could not very well just sell millions of shares of XIV in a thinly traded after hours session, so it turned to the VIX futures market. It appears, as of this writing, that this has actually occurred. While Credit Suisse (the issuer of the ETN) has yet to comment, it appears that whatever this "flash crash" did, whatever margin calls were triggered after hours, the short vol trader was in fact the firm -- it unwound positions in a size that the market has never seen before, and that means that it looks like XIV is possibly going to some very, very low number -- like $0, low. It's with great regret that as of right now, we do believe XIV is, for all intents and purposes, gone, from a little rule hidden deep in the prospectus that no one gave much concern and that got blasted away when the top holder in the note was the custodian itself. It's a reminder that the real danger to a portfolio is not a bear market -- we recover from those quite nicely as a nation -- it's the delirium that happens when a bull market gets totally out of control and margin is used excessively in a spurt of just a few days. And by margin, we don't mean normal, everyday investors, we mean the institutions -- even the ones we entrust to be custodians of our investments. So that's it. XIV likely would have done just fine after this moment in time in the market, will not be given that opportunity to recover. It has been blown out on the heels of yet another Wall Street debacle, which no one seems to even understand, yet. The author is long shares of XIV in a family trust. Ophir Gottlieb is the CEO & Co-founder of Capital Market Laboratories. He contributes to Yahoo! Finance, CNNMoney, MarketWatch, Business Insider, and Reuters. This article was originally published here.
How to Trade Options Volatility
GavinMcMaster posted a article in Trading BlogI will explain what option volatility is and why it’s important. I’ll also discuss the difference between historical volatility and implied volatility and how you can use this in your trading, including examples. I’ll then look at some of the main options trading strategies and how rising and falling volatility will affect them. This discussion will give you a detailed understanding of how you can use volatility in your trading. OPTION TRADING VOLATILITY EXPLAINED Option volatility is a key concept for option traders and even if you are a beginner, you should try to have at least a basic understanding. Option volatility is reflected by the Greek symbol Vega which is defined as the amount that the price of an option changes compared to a 1% change in volatility. In other words, an options Vega is a measure of the impact of changes in the underlying volatility on the option price. All else being equal (no movement in share price, interest rates and no passage of time), option prices will increase if there is an increase in volatility and decrease if there is a decrease in volatility. Therefore, it stands to reason that buyers of options (those that are long either calls or puts), will benefit from increased volatility and sellers will benefit from decreased volatility. The same can be said for spreads, debit spreads (trades where you pay to place the trade) will benefit from increased volatility while credit spreads (you receive money after placing the trade) will benefit from decreased volatility. Here is a theoretical example to demonstrate the idea. Let’s look at a stock priced at 50. Consider a 6-month call option with a strike price of 50: If the implied volatility is 90, the option price is $12.50 If the implied volatility is 50, the option price is $7.25 If the implied volatility is 30, the option price is $4.50 This shows you that, the higher the implied volatility, the higher the option price.Below you can see three screen shots reflecting a simple at-the-money long call with 3 different levels of volatility. The first picture shows the call as it is now, with no change in volatility. You can see that the current breakeven with 67 days to expiry is 117.74 (current SPY price) and if the stock rose today to 120, you would have $120.63 in profit. The second picture shows the call same call but with a 50% increase in volatility (this is an extreme example to demonstrate my point). You can see that the current breakeven with 67 days to expiry is now 95.34 and if the stock rose today to 120, you would have $1,125.22 in profit. The third picture shows the call same call but with a 20% decrease in volatility. You can see that the current breakeven with 67 days to expiry is now 123.86 and if the stock rose today to 120, you would have a loss of $279.99. WHY IS IT IMPORTANT? One of the main reasons for needing to understand option volatility, is that it will allow you to evaluate whether options are cheap or expensive by comparing Implied Volatility (IV) to Historical Volatility (HV). Below is an example of the historical volatility and implied volatility for AAPL. This data you can get for free very easily from www.ivolatility.com. You can see that at the time, AAPL’s Historical Volatility was between 25-30% for the last 10-30 days and the current level of Implied Volatility is around 35%. This shows you that traders were expecting big moves in AAPL going into August 2011. You can also see that the current levels of IV, are much closer to the 52 week high than the 52 week low. This indicates that this was potentially a good time to look at strategies that benefit from a fall in IV. Here we are looking at this same information shown graphically. You can see there was a huge spike in mid-October 2010. This coincided with a 6% drop in AAPL stock price. Drops like this cause investors to become fearful and this heightened level of fear is a great chance for options traders to pick up extra premium via net selling strategies such as credit spreads. Or, if you were a holder of AAPL stock, you could use the volatility spike as a good time to sell some covered calls and pick up more income than you usually would for this strategy. Generally when you see IV spikes like this, they are short lived, but be aware that things can and do get worse, such as in 2008, so don’t just assume that volatility will return to normal levels within a few days or weeks. Every option strategy has an associated Greek value known as Vega, or position Vega. Therefore, as implied volatility levels change, there will be an impact on the strategy performance. Positive Vega strategies (like long puts and calls, backspreads and long strangles/straddles) do best when implied volatility levels rise. Negative Vega strategies (like short puts and calls, ratio spreads and short strangles/ straddles) do best when implied volatility levels fall. Clearly, knowing where implied volatility levels are and where they are likely to go after you’ve placed a trade can make all the difference in the outcome of strategy. HISTORICAL VOLATILITY AND IMPLIED VOLATILITY We know Historical Volatility is calculated by measuring the stocks past price movements. It is a known figure as it is based on past data. I want go into the details of how to calculate HV, as it is very easy to do in excel. The data is readily available for you in any case, so you generally will not need to calculate it yourself. The main point you need to know here is that, in general stocks that have had large price swings in the past will have high levels of Historical Volatility. As options traders, we are more interested in how volatile a stock is likely to be during the duration of our trade. Historical Volatility will give some guide to how volatile a stock is, but that is no way to predict future volatility. The best we can do is estimate it and this is where Implied Vol comes in. – Implied Volatility is an estimate, made by professional traders and market makers of the future volatility of a stock. It is a key input in options pricing models. – The Black Scholes model is the most popular pricing model, and while I won’t go into the calculation in detail here, it is based on certain inputs, of which Vega is the most subjective (as future volatility cannot be known) and therefore, gives us the greatest chance to exploit our view of Vega compared to other traders. – Implied Volatility takes into account any events that are known to be occurring during the lifetime of the option that may have a significant impact on the price of the underlying stock. This could include and earnings announcement or the release of drug trial results for a pharmaceutical company. The current state of the general market is also incorporated in Implied Vol. If markets are calm, volatility estimates are low, but during times of market stress volatility estimates will be raised. One very simple way to keep an eye on the general market levels of volatility is to monitor the VIX Index. HOW TO TAKE ADVANTAGE BY TRADING IMPLIED VOLATILITY The way I like to take advantage by trading implied volatility is through Iron Condors. With this trade you are selling an OTM Call and an OTM Put and buying a Call further out on the upside and buying a put further out on the downside. Let’s look at an example and assume we place the following trade today (Oct 14,2011): Sell 10 Nov 110 SPY Puts @ 1.16 Buy 10 Nov 105 SPY Puts @ 0.71 Sell 10 Nov 125 SPY Calls @ 2.13 Buy 10 Nov 130 SPY Calls @ 0.56 For this trade, we would receive a net credit of $2,020 and this would be the profit on the trade if SPY finishes between 110 and 125 at expiry. We would also profit from this trade if (all else being equal), implied volatility falls. The first picture is the payoff diagram for the trade mentioned above straight after it was placed. Notice how we are short Vega of -80.53. This means, the net position will benefit from a fall in Implied Vol. The second picture shows what the payoff diagram would look like if there was a 50% drop in Implied vol. This is a fairly extreme example I know, but it demonstrates the point. The CBOE Market Volatility Index or “The VIX” as it is more commonly referred is the best measure of general market volatility. It is sometimes also referred as the Fear Index as it is a proxy for the level of fear in the market. When the VIX is high, there is a lot of fear in the market, when the VIX is low, it can indicate that market participants are complacent. As option traders, we can monitor the VIX and use it to help us in our trading decisions. Watch the video below to find out more.There are a number of other strategies you can when trading implied volatility, but Iron condors are by far my favorite strategy to take advantage of high levels of implied vol. I hope you found this information useful. Let me know in the comments below what you favorite strategy is for trading implied volatility. Here’s to your success! The following video explains some of the ideas discussed above in more detail. Gavin McMaster has a Masters in Applied Finance and Investment. He specializes in income trading using options, is very conservative in his style and believes patience in waiting for the best setups is the key to successful trading. He likes to focus on short volatility strategies. Gavin has written 5 books on options trading, 3 of which were bestsellers. He launched Options Trading IQ in 2010 to teach people how to trade options and eliminate all the Bullsh*t that’s out there. You can follow Gavin on Twitter. The original article can be found here.
There’s Volatility To Be Found….. In Turkey
GavinMcMaster posted a article in Trading BlogOne ETF that caught my eye this week for having very high implied volatility is the Turkish ETF – TUR. After bouncing 3% on Wednesday and then dropping over 5% on Thursday, this ETF has just hit a fresh 12 month high in implied volatility. So there is volatility to be found in this market after all. I tend to be more of a technical trader. I’m aware that there’s some political turmoil going on in Turkey and it’s certainly a risky place to invest. The Turkish Lira has been in freefall since late February and has fallen 28% since then. Ouchy! According to Market Watch: “On Wednesday, the Central Bank of the Republic Turkey raised its late liquidity window lending rate by 300 basis points on Wednesday, in a surprise move that put a halt to the lira selloff — at least for now. The lending rate now sits at 16.5%, compared with 13.5% before. The central bank has been operating in a peculiar environment given that Turkey’s inflation has been hitting double digits and its currency keeps sliding to historic lows. Moreover, the government of President Recep Tayyip Erdogan has been critical of the central bank, calling for lower interest rates.” On the technical side of the equation, we’ve got an ETF that is getting pummelled, dropping from near $47 in late January to just above $31 now. RSI has been hovering around 30 for the last few weeks and there was also a death cross back in mid-April. So, we have political issues and a badly broken chart, but I do like the look of that high vol. With that said, let’s look at a couple of trade ideas: BULLISH TRADE IDEAS Poor Man’s Covered Call – This is one of my favorite strategies and one that I wrote about recently here. This trade is buying the 80 delta January 2019 call and selling the 36 delta August calls. Risking only $645 for a potential profit of nearly $350 is not a bad risk reward ratio. Particular as the breakeven on the downside is just over 5% below the current price. Cash Secured Put – This trade is shorter term to try and take advantage of the accelerated time decay. Being cash secured a trader would need to have $3100 set aside in case of assignment, so the return potential in percentage terms is not nearly as good. But, the trader could always roll out to the next month to avoid taking assignment. NEUTRAL TRADE IDEA Short Straddle – With high volatility the premiums are quite juicy, so traders how prefer a neutral stance can generate some good income if they think the stock will stay flat and volatility will drop. Earlier in the week I shared the results of a delta neutral option strategy using a short straddle with a delta hedge. The delta hedge ended up costing me money but it did means less price risk. Looking at the June options again in this example to take advantage of the higher rate of time decay. This trade starts delta neutral, so it would be up to each individual trader whether or not to delta hedge. BEARISH TRADE IDEA Bear Call Spread– Traders thinking that the woes will continue for this ETF could trade a bear call spread. Using the July 33-34 spread gives traders the chance for a 53% return on capital with a 6% margin for error on the upside. Whatever your opinion, there is always a way to express it via the options market and these are just a couple of examples. Either way it’s sure to be an interesting couple of weeks for this ETF! Trade safe! Gavin McMaster has a Masters in Applied Finance and Investment. He specializes in income trading using options, is very conservative in his style and believes patience in waiting for the best setups is the key to successful trading. He likes to focus on short volatility strategies. Gavin has written 5 books on options trading, 3 of which were bestsellers. He launched Options Trading IQ in 2010 to teach people how to trade options and eliminate all the Bullsh*t that’s out there. You can follow Gavin on Twitter. The original article can be found here.
The Incredible Winning Trade in SVXY
Kim posted a article in Trading BlogBackground Shorting volatility proved to be very profitable historically. The reason is that VIX futures are drifting lower over time, so all you have to do is being short a product that is long volatility (like VXX) or being long an inverse product (like SVXY). Looking at VXX historical chart tells the whole story: So what's the catch? Well, the issue with going short VXX (or being long SVXY) is those occasional big spikes, like the one in 2008. So the trick is to find a strategy that goes short VXX or long SVXY, but at the same time, doesn't lose much during those occasional spikes. This article tells the story of an incredible SVXY trade that was a big winner despite the total collapse of SVXY. Few months ago, SteadyOptions introduced a new strategy called PureVolatility. The portfolio is managed by our veteran member and mentor, Scott Batchelar. Here is an extract from the strategy introduction: Strategy Description We will be looking to hold constant exposure to short volatility while the curve is in significant Contango in an effort to harvest volatility premium. We will also look to go long volatility when the curve is in significant Backwardation and indicators reveal the trend will continue in the short term. Because the curve is in Contango approximately 80% of the time, we will hold short exposure to volatility most of the time. The main strategy to gain this exposure will be through a Collar spread. The PureVolatility model portfolio will be based on total capital amount of $10,000 with a 5% allocation on risk. This is very important as those who are trading in a Reg-T account would on average need $10,000 in initial margin to hold the position even though the risk may only be $500. Portfolio Margin accounts would only require the $500 max loss amount. Reg-T is somewhat antiquated when it comes to margin for a Collar spread. However, this really should not be an issue because if one does not have $10,000 to put aside for this strategy it is probably not appropriate. Furthermore, the increased margin amount will keep members from over allocating to this very aggressive strategy. We will target a risk reward of better than 1:1 for a two week holding period. Here is an example of the Hedged Collar strategy sized for the model portfolio: 100 shares of SVXY at 101.93 Short 1 contract of the 11/10 110 Call at (1.35) Long 1 contract of the 11/10 103 Put at 5.54 Using the above example, here is the P/L chart of the trade: Please note that the profit potential is around $400 and risk around $300. For a strategy that wins around 80% of the time, this is an incredible risk/reward. But it gets even better. One of our other veteran members posted the following comment on the forum: After some discussion, it has been decided to modify the trade and use deep ITM calls instead of the shares. Here is an SVXY "modified" collar entered on January 30 with SVXY at 114: P/L chart: Please notice how using ITM calls instead of shares allows to reduce the risk if the stock makes a big down move. The next day SVXY moved higher and short call has been added. On February 2 SVXY started to move down. By the end of the day on February 5, SVXY went down around 40%. After few adjustments the P/L chart looked like this: The trade was down $750 or 7.5% loss on $10,000. This is completely reasonable, considering that the underlying was down 40%. Any bounce to $90 area should bring the trade back to breakeven. But then black Tuesday came. SVXY opened around $11, 60% down. The calls became nearly worthless, but the puts were the big winners, far outpacing the losses in the calls: Overall this trade produced almost 45% gain on margin or 26% gain on $10,000 portfolio. The bottom line: A trade that was long SVXY, was a big winner after SVXY went down 90%+. This is options trading at its best. And this is the power of our trading community. Read the full description of the PureVolatility strategy here. Related articles: The Astonishing Story Behind XIV Collapse The Incredible Option Trade In VXX The Lessons From The XIV Collapse The Spectacular Fall Of LJM Preservation And Growth
Volatility Trends in the DJIA
Michael C. Thomsett posted a article in Trading BlogTraders trends to be absolute in their faithfulness. They might believe in tracking the Black-Scholes pricing model even with its well-known inaccuracy, or in calculating implied volatility even with its questionable and unknown quantity called “risk-free interest rate.” Anyone who disagrees with adherence to these methods is considered a heretic. Another sect of the options faithful relies on underlying volatility to judge option valuation and also to time trades. This group looks for trends in historical volatility in order to time trades. Because volatility goes through cycles, with decreases following increases and vice versa, timing based on historical volatility is a reasonable tactic in deciding when to enter or exit trades. The simplified “rule” is to sell options when volatility is high (because this also means option premium is rich) and to buy when volatility is low (because option premium tends to be depressed), so traders using timing based on historical volatility – assuming comparisons are made based on similar moneyness and expiration timing – is not unreasonable. For example, look at how the Dow Jones Industrial Average (DJIA) has been behaving recently. The financial news announces the biggest-ever price drop in a single day, the loss of billions of dollars in market value, and the gut reaction of the market to economic news. But from a technical point of view, does any of this matter for the long term? The Dow, we should remember, is not a singular market force, but the net of 30 different companies. These may move through volatility cycles in a similar and collective manner, as seen recently, but traders also have to remember the often observed reality: Volatility changes, but it also goes back and forth over a period of time. For example, look at the six-month chart for the DJIA. For the first four months shown on the chart, the channel was exceptionally narrow, and the price trend was remarkably consistent. Given that the value of the index is between 22,250 and 26,500 on this chart, the 500-point channel was remarkable over a four-month period. The last two months presented a different story. The trading range was as high as 3,000 points and even when the early February volatility settled down, the bearish channel narrowed only slightly, with recent trading range about 1,250 points. The change in volatility is noteworthy – and visible. For those traders deeply concerned about the “end of the trend” and the unexpected explosion in volatility, it is worth remembering that volatility itself is cyclical, just like price direction. These big moves over 1,000 points over only a few days is unlikely to continue indefinitely. Volatility will calm down once the impact of recent news is absorbed. The president’s decision to impose tariffs on Chinese imports is deeply concerning to the markets, but this economic news tends to have only short-term impact on volatility. The news dominates equally important economic news including reduced tax rates, improved employment news, and much more. We also cannot know the outcome of the possible tariff war. Since it benefits no one, it could be that tariffs will be canceled with a revised trade agreement, and that the long-term impact on the markets will be positive rather than negative. The situation at the moment, in which depressed stock prices have caused panic and retreat from the market among many institutions and individuals, is a passing volatility trend. The unending tendency to “buy high and sell low” (instead of the other way around) repeats itself time again. For options traders who are aware of the evolving nature of historical volatility, when the markets are unsettled as they have been in recent weeks, this presents an exceptional trading opportunity. Options traders who consider themselves hedger rather than speculators, and who act as contrarians, will be able to recognize the opportunity this market presents. High volatility is “bargain-hunting season” for options traders, based on the easily observed changes in historical volatility.
How Does SVXY Work?
GavinMcMaster posted a article in Trading BlogUnfortunately, there is a serious lack of understanding of these products by the general public. SVXY is one such ETF, so today I’ll look at what it is, how it works and how it is priced. WHAT IS SVXY? SVXY is an ETF called ProShares Short VIX Short-Term Futures ETF. As traders can’t directly buy or sell the VIX index, numerous exchange traded products have been developed since the financial crisis as a way to hedge market volatility. Some, such as VXX have been “on a hell ride to zero”. SVXY has not had the same issue, but is has suffered dramatic falls during time of market volatility. As the name suggests (Short VIX), this ETF is short volatility, so will generally gain in value when volatility falls and drop when volatility rises. In the below chart, you can see that SVXY has generally been grinding higher during the bull market, but has experienced some precipitous falls at times. SVXY started trading on October 3rd, 2011 at a price around $10. With the ETF currently at $97.88, the ETF has had an 879% gain since inception. Even though the ETF is up big, it has experienced some big drops, such as -42% in 3 days in August 2015. HOW DOES SVXY TRADE? SVXY trades just like a stock, it can be bought, sold and even short sold whenever the market is open including pre-market and after-market trading periods. Average daily volume is currently 4.5 million and the average bid / ask spread is around 0.05%, so it is very liquid. Image Credit: ETF.com SVXY has options available to be traded with a wide array of strikes. Option spreads are similar to what you would find in RUT, maybe a little wider. HOW DOES SVXY WORK? (PRICING), WHAT DOES IT TRACK The value of SVXY is designed to return the inverse of the daily return of the most popular volatility ETF – VXX. VXX started trading on January 30th, 2009. On a split adjusted basis, it has fallen from 26,763 to 23.82 for a return of -99.91%. Taking the most recent trading day as an example (December 26th, 2016), VXX was -1.57% and SVXY was -1.35%. So, the relationship isn’t perfect due to the nature of the products and also the expense ratios. VXX has an expense ratio of 0.89% and SVXY’s is 0.95%. To understand how the price of SVXY will move, it is essential to understand how VXX is priced. I wrote a little about that here. This article on Seeking Alpha also explains it well: Therefore, as a general rule, VXX is going to decay over time and SVXY is going to rise. However, traders should not automatically assume going long SVXY and / or short VXX is a guaranteed way to make money. Sure, that trade has worked for the last few years, during a bull market, but it has experience sharp declines. The trade would also get hammered in a bear market. The reality is, if a trader was long SVXY and it dropped 75%, would they be able to continue to hold it assuming that it would to go over the long run? Maybe if you had $500 invested in it. But, what if you had $50,000 invested in it? SVXY HISTORICAL DATA AND PRICING MODEL When researching for this article I found a great spreadsheet that contains historical data for the maybe volatility products (VXX, VIXY, XIV, SVXY, UVXY, TVIX). Download the Spreadsheet The following chart also shows the performance of SVXY since inception, but also the backdated performance based on model data. Image Credit: Six Figure Investing You can see that during the financial crisis, SVXY dropped 92.5%. So simply going long SVXY is not a valid investment strategy. LONG SVXY OR SHORT VXX? Trading long SVXY or short VXX has the same underlying thesis. The trader is betting on a fall in volatility. SVXY can only go to $0. VXX can theoretically go to infinity. Profits can be made more quickly in VXX which is perhaps why some traders prefer it. In terms of risk, it is more prudent to go long SVXY rather than short VXX, but both trades can suffer potentially devastating drawdowns. Here is a great quote from Vance Harwood – “It’s interesting that an investment structurally a winner albeit with occasional setbacks is not as popular as a fund like VXX that’s structurally a loser, but holds out the promise of an occasional big win. It seems that people would rather bet on a correction, rather than the slow grind of contango.” Seems like the casino mentality is alive and well in the stock market where traders are aiming for that big win, but are generally disappointed. Gavin McMaster has a Masters in Applied Finance and Investment. He specializes in income trading using options, is very conservative in his style and believes patience in waiting for the best setups is the key to successful trading. He likes to focus on short volatility strategies. Gavin has written 5 books on options trading, 3 of which were bestsellers. He launched Options Trading IQ in 2010 to teach people how to trade options and eliminate all the Bullsh*t that’s out there. You can follow Gavin on Twitter. The original article can be found here.
Volatility During Crises
Bill Luby posted a article in Trading BlogThe events of the last three weeks are a reminder that financial crises and stock market volatility can appear almost instantaneously and mushroom out of control before some investors even have a chance to ask what is happening. A case in point: on August 3rd investors were breathing a sigh of relief after the United States had finalized an agreement to raise the debt ceiling; at that time, the VIX stood at 23.38, reflecting a relative sense of calm, yet just three days later, the VIX jumped to 48.00 as two new crises displaced the debt ceiling issue. Spanning the globe from Northern Africa, Japan, Europe and the United States, 2011 has seen no shortage of crises in the first eight months of the year. Given this pervasive crisis atmosphere, it is reasonable for investors to consider how much volatility they should anticipate during a crisis. In this article I will attempt to put crises and volatility in some historical perspective and address a variety of factors that affect the magnitude and duration of volatility during a crisis, drawing upon fundamental, technical and psychological causes. Volatility in the Twentieth Century Every generation likes to think that the issues of their time are more daunting and more complex than those faced by prior generations. No doubt investors fall prey to this kind of thinking as well. With a highly interconnected global economy, a news cycle that races around the globe at the speed of light and high-frequency and algorithmic trading systems that have transferred the task of trading from humans to machines, there is a lot to be said for the current batch of concerns. Looking at just the first half of the twentieth century, however, investors had to cope with the Great Depression, two world wars and the dawn of the nuclear age. Given that the CBOE Volatility Index (VIX) was not launched until 1993, any evaluation of the volatility component of various crises prior to the VIX must rely on measures of historical volatility (HV) rather than implied volatility. As the S&P 500 index on which the VIX is based only dates back to 1957, I have elected to use historical data for the Dow Jones Industrial Average dating back to before the Great Depression. In Figure 1 below, I have collected peak 20-day historical volatility readings for selected crises from 1929 to the present. Before studying the table, readers may wish to perform a quick exercise by making a mental list of some of the events of the 20th century that constituted immediate or deferred threats to the United States, then compare the magnitude of that threat with the peak historical volatility observed in the Dow Jones Industrial Average. If you are like most historians and investors, after looking at the data you will probably conclude that the magnitude of the crisis and the magnitude of the stock market volatility have at best a very weak correlation. [source(s): Yahoo] Any ranking of crises in which the Cuban Missile Crisis and the attack on Pearl Harbor rank in the lower half of the list is certain to raise some eyebrows. Frankly I would have been surprised if even one of these events failed to trigger a historical volatility reading of 25, but seeing that was the case for half the crises on this list certainly provides a fair amount of food for thought. Volatility in the VIX Era With the launch of the VIX it became possible not only to evaluate historical volatility, but implied volatility as well. With only 18 years of data to draw upon, there is a limited universe of crises to examine, so in the table in Figure 2 below, I have highlighted the seven crises in the VIX era in which intraday volatility has reached at least 48. Additionally, I have included five other crises with smaller VIX spikes for comparison purposes. [source(s): CBOE, Yahoo] [Some brief explanatory notes will probably make the data easier to interpret. First, the crises are ranked by maximum VIX value, with the maximum historical volatility in an adjacent column for an easy comparison. The column immediately to the right of the MAX HV data captures the number of days from the peak VIX reading to the maximum 20-day HV reading, with negative numbers (LTCM and Y2K) indicating that HV peaked before the VIX did. The VIX vs. HV column calculates the amount in percentage terms that the peak VIX exceeded the peak HV. The VIX>10%10d… column reflects how many days transpired from the first VIX close above its 10-day moving average to the peak VIX reading. The SPX Drawdown column calculates the maximum peak to trough drawdown in the S&P 500 index during the crisis period, not from any pre-crisis peak. The VIX:SPX drawdown ratio calculates the percentage change in the VIX from the SPX crisis high to the SPX crisis low relative the percentage change in the SPX during the same period (of course these are not necessarily the VIX highs and lows during the period.) The SPX low relative to the 200-day moving average is the maximum amount the SPX fell below its 200-day moving average during the crisis. Finally, the last two columns capture the number of consecutive days the VIX closed at or above 30 during the crisis and the number of days the SPX closed at least 4% above or below the previous day’s close during the crisis.] Looking at the VIX era numbers, it is not surprising that the financial crisis of 2008 dominates in many of the categories. Reading across the rows, one can get an interesting cross-section of each crisis in terms of various volatility metrics, but I think some of the more interesting analysis comes from examining the columns, where we can learn something not just about the nature of the crises, but also about volatility as well. One important caveat is that the limited number of data points does not allow for this to be a statistically valid sample, but that does not preclude the possibility of drawing some potentially valuable and actionable conclusions. Looking at the peak VIX reading relative to the peak HV reading I note that in all instances the VIX was ultimately higher than the maximum 20-day historical volatility reading. In the five lesser crises, the VIX was generally 50-80% higher than peak HV. In the seven major crises, not surprisingly HV did approach the VIX in several instances, but in the case of the 9/11 attackand the 2010 European sovereign debt crisis the VIX readings grossly overestimated future realized volatility. One of my hypotheses about the time between the first VIX close above its 10-day moving average and the ultimate maximum VIX reading was that the longer the period between the initial VIX breakout and the maximum VIX, the higher the VIX spike would be. In this case the Long-Term Capital Management (LTCM) and 2008 crises support the hypothesis, but the data is spotty elsewhere. The current European debt crisis, Asian Currency Crisis of 1997 and 9/11 attack all reflect a very rapid escalation of the VIX to its crisis high. In the case of the May 2010 ‘Flash Crash’ and the Fukushima Nuclear Meltdown, the maximum VIX reading happened just one day after the initial VIX breakout. As many traders use the level of the VIX relative to its 10-day moving averages as a trading trigger, the data in this column could be of assistance to those looking to fine-tune entries or better understand the time component of the risk management equation. Turing to the SPX drawdown data, the Asian Currency Crisis stands out as one instance where the VIX spike seems in retrospect to be out of proportion to the SPX peak to trough drawdown during the crisis. On the other side of the ledger, the drawdown during the Dotcom Crash appears to be consistent with a much higher VIX reading. Here the fact that it took some 2 ½ years for stocks to find a bottom meant that when the market finally bottomed, investors were somewhat desensitized and some of the fear and panic had already left the market, which is similar to what happened at the time of the March 2009 bottom. Note that the median VIX:SPX drawdown ratio for all twelve crises is 10.0, which is about 2 ½ times the movement in the VIX that one would expect during more normal market conditions. The data for the SPX Low vs. 200-day Moving Average is similar to that of the SPX drawdown. For the most part, any drawdown of 10% or more is likely to take the index below its 200-day moving average. In the seven major crises profiled above, all but the Asian Currency Crisis dragged the index below its 200-day moving average; on the other hand, in all but one of the lesser crises the SPX never dropped below its 200-day moving average. Based on this data at least, one might be inclined to include the 200-day moving average breach as one aspect which helps to differentiate between major and minor crises. As I see it, the last two columns – consecutive days of VIX closes over 30 and number of days in which the SPX has a 4% move – are central to the essence of the crisis volatility equation. Since the dawn of the VIX, the SPX has experienced a 2% move in about 80% of its calendar years, the VIX has spiked over 30 about 60% of the years, and the SPX has seen at least one 4% move in about 40% of those years. Those 4% moves are rare enough so that they almost always occur in the context of some sort of major crisis. In fact, one could argue that a 4% move in the SPX is a necessary condition for a financial crisis and/or a significant volatility event. Fundamental, Technical and Psychological Factors in Crisis Volatility Crises have many different causes. In the pre-VIX era, we saw a mix of geopolitical crises and stock market crashes, where the driving forces were largely fundamental ones. During the VIX era, I would argue that technical and psychological factors become increasingly important. The rise of quantitative trading has given birth to algorithmic trading, high-frequency trading and related approaches which place more emphasis on technical data than fundamental data. At the same time, retail investing has been revolutionized by a new class of online traders and the concomitant explosion in self-directed traders. This increased activity at the retail level has added a new layer of psychology to the market. In terms of fundamental factors, one could easily argue that the top nine VIX spikes from the list of VIX era crises all arise from just two meta-crises, whose causes and imperfect resolution has created an interconnectedness in which subsequent crises are to a large extent just downstream manifestations of the ripple effect of the original crisis. The first example of the meta-crisis effect was the 1997 Asian Currency Crisis, which migrated to Russia in the form of the 1998 Russian Ruble Crisis, which played a major role in the collapse of Long-Term Capital Management. The second example of meta-crisis ripples begins with the Dotcom Crash and the efforts of Alan Greenspan to stimulate the economy with ultra-low interest rates. From here it is easy to draw a direct line of causation to the housing bubble, the collapse of Bear Stearns, the 2008 Financial Crisis and the recurring European Sovereign Debt Crisis. In each case, the remedial action for one crisis helped to sow the seeds for the next crisis. In addition to the fundamental interconnectedness of these recent crises, it is also worth noting that the lower volatility crises were largely point or one-time-only events. There was, for instance, only one Hurricane Katrina, one turn of the clock for Y2K and one earthquake plus tsunami in Japan. As a result, the volatility associated with these events was compressed in time and accordingly the contagion potential was limited. By contrast, the major volatility events are more accurately thought of as systemic threats that ebbed and flowed over the course of an extended period, typically with multiple volatility spikes. In the same vein, the attempted resolution of these events generally included a complex government policy cocktail, whose effects were gradual and of largely indeterminate effectiveness. Apart from the fundamental thread running through these crises, I also believe there is a psychological thread that sometimes spans multiple crises. Specifically, I am referring to the shadow that one crisis casts on future crises that follow it closely in time. I call this phenomenon ‘disaster imprinting’ and psychologists characterize something similar as availability bias. Simply stated, disaster imprinting refers to a phenomenon in which the threats of financial and psychological disaster are so severe that they leave a permanent or semi-permanent scar in one’s psyche. Another way to describe disaster imprinting might be to liken it to a low-level financial post-traumatic stress disorder. Following the 2008 Financial Crisis, most investors were prone to overestimating future risk, which is why the VIX was consistently much higher than realized volatility in 2009 and 2010. While it is impossible to prove, my sense is that if the events of 2008 were not imprinted in the minds of investors, the current crisis atmosphere might be characterized by a much lower degree of volatility and anxiety. Conclusion As this goes to press, the current volatility storm is drawing energy from concerns about the European Sovereign Debt Crisis as well as fears of a slowdown in global economic activity. The rise in volatility has coincided with a swift and violent selloff in stocks that has seen six days in which the S&P 500 index has moved at least 4% either up or down – a rate that is unprecedented outside of the 2008 Financial Crisis. Ultimately, the severity of a volatility storm is a function of both the magnitude and the duration of the crisis, as well as the risk of contagion to other geographies, sectors and institutions. Act I of the European Sovereign Debt Crisis, in which Greece played the starring role, can trace its origins back to December 2009. In the intervening period, it has spread across Europe and has sent shockwaves across the globe. By historical standards the volatility aspect of the current crisis is more severe than at any time during World War II, the Cuban Missile Crisis and just about any crisis other than the Great Depression, Black Monday of 1987 and the 2008 Financial Crisis. In the data and commentary above, I have attempted to establish some historical context for volatility during various crises extending back to 1929 and in the process give investors some metrics for evaluating current and future volatility spikes. In addition, it is my hope that concepts such as meta-crises and disaster imprinting can help to bolster the interpretive framework for investors who are seeking a deeper understanding of volatility storms and the crises from which they arise. Bill Luby is Chief Investment Officer of Luby Asset Management LLC, an investment management company in Tiburon, California. He also publishes the VIX and More blog and an investment newsletter. His research and trading interests focus on volatility, market sentiment, technical analysis, ETPs and options. Bill was previously a business strategy consultant. He can often be found running, hiking, and kayaking in Northern California. Bill has a BA from Stanford University and an MBA from Carnegie-Mellon University. You can follow Bill Twitter.
How To Profit From A Volatile Market
Mark Wolfinger posted a article in Trading BlogThe Plan Do you buy VIX calls, betting on a big increase in the price of VIX futures? Do you buy options with lots of vega? Do you buy options with lots of gamma? Do you buy straddles/strangles, playing for either a big market move in either direction or an IV surge? Do you plan to scalp delta when the market moves both up and down with big swings? I don’t have a simple plan to recommend. Market volatility can manifest in different ways and a trader does not want to own positions that earn little or no profits when correctly predicting the future. It is a situation that is similar to a bullish trader who buys a ton of OTM calls, only to find that the market does not rise far enough or quickly enough to overcome the passage of time and the declining implied volatility of the calls he bought. Possible trade plans 1. Huge market move. It’s fine to place a bet on a big move. If the market were to rally or decline by 10% or more over a relatively short period of time, the option buyer should be able to earn a tidy profit. Buy options that are not-too-far OTM and which that will become reasonablr far ITM if your prediction comes to pass. The options may seem dear, but if you are correct they will provide a handsome profit. If you also want to bet on the direction of the move, you can save a lot of money by buying only calls or only puts. If you want to plan on a big move, but one that is not large enough for your options to move deep ITM, then consider buying a bunch of OTM spreads. Turning $0.50 or $1.00 into $5.00 is very possible. If you do not have a directional play in mind, you can buy straddles, strangles, or both put and call spreads. That latter plan is the opposite of owning iron condors. The risk: When buying premium, the trader has to be correct. If the market move does not occur; or if time passes and IV does not explode; then the options are going to waste away to nothing. 2. IV Explosion. An alternative is to place a wager that IV will move a lot higher than it is right now. That could be the result of a big market decline or simply a result of fear that comes with uncertainty. If you believe America’s dalliance with the fiscal cliff is likely to provide that fear; if you are very bearish for some different reason; if you believe something startling will be announced; then betting that IV will increase is one way to go. You could buy VIX options, but I must warn you that we have seen big (temporary) IV jumps without participation by VIX options. These options use VIX futures as the underlying asset, and when the market participants see a rising IV but believe that IV will decline again by the time the futures settle, then VIX options do not tend to provide profits for their owners. You could buy vega. The best way to do that is to own some options with a decent lifetime: perhaps three to six months. If and when IV rises, those options are vega rich and should produce a handsome profit. Obviously you must select options on an asset whose IV rises. The problem is that you have to be right without too much time passing. However, there is a second chance to win. IV may go nowhere, but if the underlying moves far enough in one direction, you could wind up with a very good profit. A third plan is to buy gamma. Near-term options cost far less than longer-term options and decay rapidly. However, they come with a lot of gamma and if you get the big move, the profits can be huge. This is similar to loading up on vega because in either strategy, you become an option owner. However, the real difference comes in choosing the lifetime of the options. Longer-term options provide vega and shorter-term options come with more gamma. Then you have the modified plan in which you buy lots of gamma but do not hold for the giant move. Instead, you plan to adjust the position with some frequency (perhaps daily) in an effort to remain near delta neutral but earn profits by selling into rallies and buying on the dips. This works very well when the market moves up and down, but provides disappointing results when the market makes a one-directional move. 3. Bet against the so-called ‘income-generating strategies.’ Sell the iron condor, take a directional stance and bet against the credit spread (by buying the spread); sell ATM calendar spreads or butterfly spreads. This plan works when the market moves far enough so that the positions produce profits. This is not the ideal plan when you anticipate a huge market move, but works nicely when the market makes frequent decent-sized moves. Not only would you gain from owning the correct delta position, but these trades come with positive vega and there could be additional profits if IV rises. No real opinion, other than ‘volatility will increase’? That makes it difficult to choose the best play. However, I’d recommend owning some OTM call/put spreads. Clearly you do not want to go too far OTM, nor do you want to pay a high price for the spreads. But there has to be some price that meets your needs. When buying the iron condor and betting against that volatility, we don’t have too much trouble knowing how much premium we must collect to make the trade viable. If your mindset is to take the opposite bet, it should not be too difficult to decide how much to pay to play the game. The bottom line for me is that I don’t know how to play for the volatile market when I have a generic feeling that volatility is coming. I’d probably choose to own double diagonals. However, if I had a fear that a big rise in market volatility was pending, I would want to own some insurance (if the price is not outrageous) in the form of 5-delta puts and perhaps 10-delta calls. If I had more than a fear; if I were a believer that volatility is coming, I’d exit my traditional plays (for protection) and simply invest a reasonable sum by buying OTM options. As someone who does not trust his market predicting skills, I doubt that I would ever own those options. I would continue as I have been doing, but would trade 50% or less of my normal position size. This was part of the original request for information: Managing risk for any trade involves the same reasoning. the most important factor that goes into a trade is deciding on position size and the maximum possible loss. When you own gamma, risk graphs provide a lot of excitement as we see how much money can be earned. The real danger in those graphs is that they may encourage a trader to overlook the risk of time passing. The next trick in risk management is to have a good feel for the chances of earning money, and more importantly, setting a profit target. Let me assure you than when the market moves your way and your $5,000 investment has become worth $15,000 and the risk graph shows you how easy it is to reach $50,000 or $200,000, it becomes very difficult to exit. I know someone who bought 2,000 shares of a stock priced in the single digits, saw it rise above $120 and who never sold a share as the stock declined back to the mid teens. In fact, on the decline he bought another 2,000 shares at $40. It is so tempting to believe you are in the midst of the trade of a lifetime and that if you hold out for more, you will get it. I urge you to have a plan. If you buy low-delta options and IV really moves higher, do not expect them to move ITM. Scale out, or have a price target for selling the whole position. That’s risk management.The ETF If you pan to trade options on a specific ETF, be very careful. Do not take a long position in the double- or triple-leveraged products. Yes, they are more volatile than the ‘regular’ ETF, but it is safer to stick with the investment that you understand. The leveraged puppies act differently and are not constructed for anyone other than the day trader. If you are going to bet on specific stocks, be careful. It is probably better to select a more volatile rather than a less volatile stock or ETF, but it is far more important to buy vega when IV is reasonably priced. If you buy vega on a product with an historical volatility (HV) of 40 when IV is 60, you would be better off paying 30 IV for an ETF with a HV of 30. At last you would not begin with a position that feels as if the premium is already too high. That is also risk management. I hope this commentary offers enough information to allow you to find a suitable plan to profit if you get that IV hike. I have no recent relevant experience with making this type of play, not having made this wager for decades. Related articles: Can We Profit From Volatility Expansion Into Earnings? Options Trading Greeks: Vega For Volatility Using VIX Options To Hedge Your Portfolio Want to learn how to trade successfully while reducing the risk? Start Your Free Trial
Trading Weekly IV Increase Over Monthly
tjlocke99 posted a topic in General BoardCould some of the senior members and/or Kim comment on this idea? Does the IV (when it moves at all) on weeklies always outpace or at least stay even with the monthlies on the earnings trades? Could you then do the opposite of a calendar and long the weeklies and short the monthlies on an earnings trade? Take this hypothetical example: AAPL underlying @ 615 let's say its 19 July and the 27 July AAPL weekly is released. Let's say we have this made up pricing: 1. 27 July AAPL 615 Call @ $10.00 2. 27 July AAPL 615 Put @ $10.00 3. 17 Aug AAPL 615 Call @ $20.00 4. 17 Aug AAPL 615 Put @ $20.00 You would do this: long qty 2 of #1 long qty 2 of #2 (creating a straddle) short qty 1 of #3 short qty 1 of #4 I am sure the theta will kill you if you don't get an IV increase, so do this on a stock like AAPL probably would not work because of the high stock price (unless your portfolio is huge). Any thoughts on a trade that could take advantage of the greater IV increase in the weeklies? Thanks!