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Found 5 results

  1. cwelsh

    Leveraged Anchor Update

    First, what did we add and why did we do it? Anchor has been performing quite well the past couple of years, particularly after some of the better minor adjustments we made. But as discussed in earlier blogs, it has some definite flaws, the biggest one being that, even in the best conditions, it will always lag the stock market by at least ten percent or so. This is because the strategy is only ninety percent long. Anchor consists of investing ninety percent of capital in SPY, or a series of highly correlated ETFs, and the other ten percent in the long hedge (the long hedge varies from seven percent to ten percent depending on when entered). This means if the market is up 10%, the most Anchor can be up is 9%. This is just how the strategy is designed. In our recent historically long bull market, this has frustrated many investors and has been considered a major defect in the strategy by a few investors (even if it is a conservative strategy). So we began tracking leveraged versions of the strategy, using options. We came up with two different versions of a leveraged strategy. The first using a synthetic stock position – short an at the money put and long an at the money call. Synthetic stock is significantly cheaper than buying actual stock, which enables you to put leveraged onto an account. The second version was simply purchasing a deep in the money call (over fifty percent in the money). By varying how far in the money we went, you can also lever up your account. After close to six months of tracking the two levered accounts, the first thing that jumped out is just how poorly the synthetic stock position has performed when compared to the deep in the money long call position. Our synthetic stock portfolio utilized a leverage ratio of about 5x. We were long 20 contracts of the 275 SPY options. Whereas our deep in the money portfolio only utilized leverage of about 2x, being long 7 SPY contacts. This leverage difference would account for some of the discrepancy in the two options, but not all of it. At its low point the synthetic portfolio, dropped in value to $95,000 (low points measured by days on which trades actually occurred, not every day of the portfolio). At this same point, the deep in the money portfolio was actually up almost one percent. Theory does not suggest this should happen, but it did. Going back through previous Anchor downturns, and plugging in similar portfolios, verifies that this actually will happen fairly regularly. The way the short puts and long calls interact in the synthetic structure is simply more inefficient than deep in the money long calls. Further, as the hedge does not perform well for the first 5% to 10% of market declines, the increased leverage is particularly detrimental. Conclusion? We’re abandoning the synthetic stock tracking and only tracking the deep in the money call position. In reviewing the deep in the money call position, it performed spectacularly well through the most recent downturn. Several factors contributed to that. The first does contain an element of “luck.” By implementing the rules on going to a 28 day short put position and rolling it after a fifty percent gain, we were able to “ride out” losses on the short puts and have them recover, thereby not realizing a loss. If the downturn had lasted another 7-10 days, we would have had to realize the loss. Luck is included in quotes though because the changes we implemented had already proven, more often than not, that this is exactly what would happen. Typically if the market is down 2%-3%, the long puts don’t increase in value fast enough to offset the losses in our long positions. In the most recent market moves though, the decline was quite rapid, more than 3%, and volatility significantly spiked. This means that the value of our long puts did increase at a fast enough rate to offset the losses in the long position. The fact that the long position values also slowdown their decline (as delta drops below 1), also benefited the portfolio, providing an added benefit that doesn’t exist in the normal Anchor. As of November 1, the market was actually down from the day we started tracking the leveraged Anchor portfolio (about 1%), but the leveraged Anchor version was up – outperforming even regular Anchor, which is a truly spectacular result. All in and all, we’re quite happy with how the leveraged Anchor portfolio is going and we’re going to continue to track it. Once there is a full year in, we’ll do further analysis on the amount of leverage used and determine if the “ideal” amount is 1.5x, 2.0x, 2.5x, or something else all together. Related articles Defining The Anchor Strategy Leveraged Anchor Is Boosting Performance Anchor Trades Strategy Performance Revisiting Anchor (Thanks To ORATS Wheel) Revisiting Anchor Part 2
  2. cwelsh

    Defining the Anchor Strategy

    One of the most important parts of evaluating a strategy is to appropriately set target returns and develop a good benchmark to measure relative performance. Without a known target, measuring performance internally is difficult. Without an appropriate benchmark, measuring against the competition is impossible. In order to do this, we need to break the Anchor strategy down into its key components for evaluation. Anchor is comprised of: A long ETF position that is typically 88%-92% of the total investment; A long put position that is typically 7%-10% of the investment for the hedge; and A short put position that makes up the balance to attempt to pay for the hedge. When Anchor was originally devised our goal was to slightly lag the markets in up years, stay level in flat market returns, and beat the market significantly in down years. That worked in years the market was up ten percent or less, which was the primary evaluation period. However, the past several years of bull markets have demonstrated that the term “slight lag” is not realistic or appropriate in large up markets. Given the fact that Anchor is only approximately 90% long at any given time, we automatically are behind bull market performance. For example, if the market goes up 20%, Anchor’s long ETF positions may only go up around 18%. Couple that with the fact that in significant up trending markets, the long hedge rolls multiple times per year and you end up with larger lags in rising markets – which get more pronounced the faster the market is rising. A more effective measurement would be to compare Anchor to a portfolio with comparable risk, such as a 60/40 stock/bond portfolio. However, even that is not an ideal metric, as Anchor's option hedge can significantly outperform it in bear markets, making comparisons difficult. Swan Global Investment’s Defined Risk Strategy is quite similar to Anchor. Swan does a nice job of setting expectations on their website with a “Target Return Band” shown below: The theory being that their Defined Risk Strategy should fall within or above the blue range. The red line represents the theoretical return of the S&P 500, the yellow line is the Swan’s Defined Risk Return target returns when contrasted with the S&P 500 return at the point. It is our opinion that these target bands represent an adequate projection of what results should be expected internally of the Anchor strategy as well. We will of course always work to exceed those expectations, but this will represent more realistic return projections for Anchor, particularly in large bull scenarios. Another advantage to evaluating Swan’s Defined Risk Strategy, is it now gives us an appropriate benchmark to measure against. In describing their product, Swan states: “Investing to help minimize downside risk. The market is unpredictable, making it difficult to time the markets or consistently pick outperforming stocks. That’s why we believe reducing downside risk can significantly impact wealth creation.” “The goal: to achieve positive returns while minimizing the downside risk of the equities markets.” “Key strategy elements to each of the Defined Risk Funds include: No reliance on market timing or stock selection Designed to seek consistent returns Aims to protect client assets during market downturns Always hedged, all the time, using put options” “Repeatable Four Step Investment Process Step 1: Establish Equities (using diverse ETFs) Step 2: Create the Hedge – Always hedged – We use only longer term puts, which offer the greatest cost-efficiency and stability, and then maintain that protection by rolling the hedge at least annually. As such, the DRS (Swan’s Defined Risk Strategy) is not under duress to seek protection in market downturns. Step 3: Seek to Generate Market-Neutral Cash Flow – We use options-trading expertise to provide our clients with the potential for return, regardless of market conditions. Step 4: Monitor and Adjust” To anyone who has used Anchor, this should all sound familiar. Since Swan’s impressive track record is significantly longer (going back to 1997 in different forms) than Anchor it provides proof of concept. Swan’s Class I mutual fund shares have returned the following (courtesy Morningstar) since 2013: Vs Anchor: Disclosure: Anchor's returns have not been audited by any independent third party, do not guarantee future results, and do not reflect the deduction of applicable management and/or subscription fees. Anchor’s 2013 returns were dramatically increased by the use of individual stocks which outperformed the market, as opposed to the broad market ETFs that are now used within the strategy to reduce tracking error. The following table compares Anchor returns with S&P 500 total return, expected return (as defined by Target Return Band) and Swan returns. Anchor outperformed the Swan every single year except 2014. While some investors may be frustrated that Anchor lagged the bull market in 2016 and 2017, we believe that is not so much a design flaw in Anchor, as a flaw we made in setting proper expectations. Conclusion: The Anchor objective is to produce equity like returns over a full market cycle, with reduced volatility and bear market drawdowns. Investors should expect a trade-off of reduced upside capture during extreme bull market gains. Given our belief that the long term is the only investment time frame that truly matters, we believe the strategy provides attractive mathematical and psychological benefits to investors seeking the long term growth potential of the US stock market. If you have any questions about the Anchor Strategy, how to implement it on your own, or wish to have us manage the strategy for you, contact my firm at anytime or make a post on the SteadyOptions website: Lorintine Capital Christopher Welsh: cwelsh@lorintine.com Jesse Blom: jblom@lorintine.com P: 214-800-5164 F: 214-800-5165
  3. cwelsh

    Revisiting Anchor Part 2

    Selling calls for a credit to help offset the cost of the hedge is, more often than not, a losing strategy over time in the Anchor strategy. It tends to hurt performance more than help it; About a month is the ideal period for selling short puts over both in bull and bear markets. This tends to be the ideal trade off between decay, being able to hold through minor price fluctuations, and available extrinsic value. Since options come out weekly, we’ll be using a 28-day period; Rolling on a set day like Friday is not the most efficient method of rolling the short puts. Rather having a profit target of between 35% to 50%, and rolling when that target is hit, leads to vastly improved outcomes. Waiting until profits get above 50% tends to start negatively impacting the trade on average. This month we’re going to look at another technique which has the possibility of increasing Anchor’s performance over time – namely reducing the hedge. Reducing the Hedge The single biggest cost to Anchor is the hedge. Depending on when the hedge is purchased, it can cost anywhere from 5% to 15% of the value of the entire portfolio. In large bull markets, which result in having to roll the hedge up several times in a year, we have seen this cost eat a substantial part of the gains in the underlying stocks and/or ETFs. There is also the issue of not being “fully” invested and this resulting in lagging the market. If the cost of the hedge is 8%, then we are only 92% long. In other words if our ETFs go up 100 points, our portfolio would only go up 92 points. A large hedge cost also has a negative impact at the start of a bear market as well due to the losses on the short puts. If the market drops a mild amount, particularly soon after purchasing the hedge, the losses on the short puts will exceed the gains on the long puts, negatively impacting performance. This loss is less noticeable as the long hedge gets nearer to expiration and/or market losses increase as delta of the long hedge and the short puts both end up about the same. However, as was seen a few years ago, if the market drops slightly, then rebounds, those losses on the short puts are realized and any gains on the long puts are lost when the market rebounds. If there was a way to reduce the cost of the hedge, without dramatically increasing risk, the entire strategy would benefit. A possible solution comes from slightly “under hedging.” Testing over the periods from 2012 to the present and from 2007 to the present has revealed if we only hedged 95% of the portfolio, returns would be significantly improved. Let’s take a look at the data from the close of market on September 14, 2018, when SPY was at 290.88. If we were to enter the hedge, we would have bought the September 20, 2019 290 Puts for $14.96. If we have a theoretical $90,000 portfolio, it would take 3.1 puts to hedge (we can’t have 3.1puts so we’ll round down to 3). At that price, three puts would cost $4,488 or 5% of the portfolio (almost historically low). However, if we were to say “I am not upset if I lose five percent of my portfolio value due to market movements; I am just really worried about large losses,” we could buy the 275 puts instead of the 290. The 275 puts are trading at $10.61 – a discount of thirty percent. This means we need less short puts to pay for the position, paying for the position is a simpler process, and rolling up in a large bull market is cheaper. Yes it comes at a cost – risking the first five percent – but given the stock markets trend positive over time, this pays off in spades over longer investment horizons. Even if you are near retirement, any planning you do should not be largely impacted by a five percent loss, but the gains which can come from (a) having a larger portion of your portfolio invested in long positions instead of the hedge (meaning less lag in market gains), (b) having less risk on the short puts in minor market fluctuations, and (c) paying for the hedge in full more frequently more than offset that over time. We will implement this in the official Anchor portfolios by simply delaying a roll up from gains. The official portfolio is in the January 19, 2019 280 puts. We’d normally roll around a 7% or 10% gain (or around SPY 300), instead we’ll just hold until we get to our five percent margin. OR when we roll the long puts around the start of December, we’ll then roll out and down to hit our target. Note – if you do want to continue to be “fully” hedged, you can do so. There’s nothing wrong with this, you just sacrifice significant upside potential and will be continuing to perform as Anchor has recently. If we had implemented this change in 2012, Anchor’s performance would have been more than five percent per year higher. This is not an insignificant difference. Related articles: Defining The Anchor Strategy Market Thoughts And Anchor Update Leveraged Anchor Is Boosting Performance Anchor Trades Strategy Performance Revisiting Anchor (Thanks To ORATS Wheel)
  4. A “normal” Anchor portfolio uses about 90% of its available cash to purchase long equities, most commonly ETFs. The other 10% is used to purchase the hedge. This means, even if the strategy performs “perfectly” by paying off the hedge, in the best case scenario, it will still lag the market by at least ten percent – and we all know perfect performance is unlikely. In other words, if the market goes up 20%, Anchor will, at absolute most, go up 18% -- prior to accounting for the cost of the hedge. By replacing the ETFs with a combination of ETFs and long dated deep in the money call options we can increase performance without greatly impacting risk. Let’s take an example $100,000.00 portfolio and assume SPY is currently trading at 266.92, the end of value on the day this post was written. Using the June 21, 2019 options, a “normal” Anchor portfolio could look like: Long 6 June 21, 2019 265 Puts $16/contract ($9,600) Short 2 May 25, 2018 268.5 Put $3.34/contract $668 Long 340 shares of SPY[1] $266.92/share ($90,752.80) Left over cash $315.20 [1] SPY is being used for simplicity sake, one could just as easily use the standard blend of SDY, VIG, and RSP But what if we instead bought calls and constructed the portfolio as follows: Long 8 June 21, 2019 265 Puts $16/contract ($12,800) Short 3 May 25, 2018 286.5 Puts $3.34/contract $1,002 Long 4 June 21 2019 150 Calls $117.56/contract ($47,024) Long 100 shares of SPY $266.92/share ($26,692) Left over cash $14,486 In this case we’re essentially long an extra 47% when compared to the “normal” Anchor portfolio and have left over cash we can invest in a low paying instrument (such as BIL), yielding approximately 1.5%. The four long calls each control 100 shares, which totals 500 shares under control as opposed to only 340 shares in the “normal” Anchor model. Looking at the possible scenarios in June 2019: Now the above analysis assumes that the hedge is exactly fully paid for and that all other variables have remained the same. This assumption means we would have collected exactly $0.80.week each week – and we know that is impossible – but it still a useful analysis. The reason that the further down SPY drops, the more money “normal” Anchor makes is with our 4 long puts we are slightly over-hedged, which profits on the down side. The Leveraged portfolio is perfectly hedged. Looking at the above it is very easy to see that Anchor and the Leveraged version perform the same in down conditions but the leveraged version vastly outperforms in up markets. This only makes sense as it is a leveraged product that is still fully hedged on the downside. This doesn’t tell the whole story though – for two reasons. The first is beneficial to the leveraged version. The above model assumes a delta of one as the price of SPY drops. However, that is never the case. As the price of SPY gets closer and closer to the 150 strike, delta will go down (and volatility likely will be increasing during this time as well). As delta goes down, the long calls won’t lose dollar for dollar, as a pure long position would. This means that the above values are actually understated. The Leveraged version should outperform in down markets as well. It outperforms in flat markets due to the interest gained on the extra $14,486 cash. It would seem then that the Leveraged version is vastly superior and should always be used – and if the paying off the hedged worked perfectly, then that would be the case. But as any Anchor trader knows, paying off the hedge is always the most difficult task – particularly in large bull markets which require the hedge to be rolled several times. Because the leveraged version has more short puts, when the market goes down, those short positions are going to lose at a higher clip. Similarly, when we have to roll the long hedge, we will lose more rolling. In other words the risk increases. Is the risk worth the potential gains? That depends on both market conditions and each individual investor’s preferences. The Leveraged version is also not tax efficient. With a normal Anchor account, you hold the long ETF positions until you need to liquidate - which could be decades. The only real tax impact is from the option positions, which could easily be negative on a year the markets are up. On the other hand, the leveraged version will realize gains every year as the long calls are bought and sold - leading to tax inefficiencies. Depending on your tax bracket and situation, this could have an impact on choosing one or the other. Starting in June, we're going to start tracking a leveraged version of the Anchor portfolio for subscribers, which can also be professionally managed through Lorintine Capital. Feel free to email Chris at cwelsh@lorintine.com with any questions. Christopher Welsh is a licensed investment advisor in the State of Texas and is the president of an investment firm, Lorintine Capital, LP which is a general partner of three separate private funds. He is also an attorney practicing in Dallas, Texas. Chris has been practicing since 2006 and is a CERTIFIED FINANCIAL PLANNER™. Working with a CFP® professional represents the highest standard of financial planning advice. He offers investment advice to his clients, both in the law practice and outside of it. Chris has a Bachelor of Science in Economics, a Bachelor of Science in Computer Science from Texas A&M University, and a law degree from Southern Methodist University. Chris manages the Anchor Trades portfolio, the Steady Options Fund, and oversees Lorintine Capital's distressed real estate debt fund.
  5. It immediately became clear this could be used, not only for put selling testing, but to test Anchor over longer periods of time than previously done and try to find other areas to improve the strategy, which has been a core part of SteadyOptions for quite some time. After two weeks of testing, much of what Anchor has evolved to over the past few years was validated, but we also identified some areas for improvement that should increase performance of the strategy. In this article, and a future one next week, I will discuss the conclusions from our expanded optimization, back testing, and review. Later articles will dive into the implications for the leveraged versions of the Anchor Strategy, as well as the benefits of expanding Anchor by diversifying into IWM, QQQ, DIA, and potentially other indexes. I. Selling Calls for Credit Anyone who has been following Anchor recently knows we have been on a quest to find other ways to pay for the hedge. The biggest drag on the strategy is the hedge, and any way we can improve paying for the hedge cost helps. In this decade long bull market, paying for the hedge has been particularly problematic, more so in recent years. For the past few months, we’ve been structuring and testing a variety of call selling strategies in an effort to extract a few more basis points of performance out of Anchor. Initial paper trading had us optimistic, as well as the manual testing done over the previous nine months. Further, the CBOE maintains covered call indexes, which seemed to indicate that the strategy should work. We were optimistic enough to start tracking it on the forums in the leveraged anchor accounts. What a thorough back testing demonstrated was that selling naked calls on indexes, SPY in particular, is a losing strategy, or at best a breakeven one, since 2007. This is true over shorter periods of time as well, such as since 2012. If calls, three weeks and one standard deviation out are used, since 2012, the strategy would have lost a 1.6% per year. If data from 2007 is used, so as to capture 2008 and 2009, the strategy still would have lost 0.20% per year. Trying further out in time over periods such as 28 days, 45 days, or 60 days were all losers. What about putting in stop losses or profit targets – also all losers. In fact, only through extreme curve fitting, was I able to identify any possible profitable naked call selling strategy at all, and only if you use the data set from 2007 to the present – even then performance would only have gone to 0.55% per year. Then if you remove 2008 from the data set, results immediately went back to negative performance. Changing from an at the money position, to a 30 delta position did not help much either. Since 2007, selling a 30 delta one month call, would have netted you only 0.22% per year – essentially flat. Changing the delta to 10 or 60 did not help either. This result was initially puzzling, as the covered call index (BXM) is up over 50% over the last five years and 75% over the last ten – until those results are broken down. BXM is not naked call selling, it is covered call selling. Given over the last five years, the S&P 500 is up about 75%, which means call selling is responsible for 25%, or more, of BXM’s losses. If covered call selling was profitable, there would not be this drag. By eliminating the gains from the long stock positions, the returns go to negative – as indicated by our testing. The conclusion? Simple Anchor will not be selling calls as a way to gain additional income to help cover the cost of the hedge and such strategies will be removed from the leveraged versions of Anchor. II. 14 vs. 21 vs. 28 Days for the Short Puts A few years ago, we switched from selling puts either one or two weeks out to three weeks till expiration. Doing so gives the strategy more time to “be patient” in the event of small market moves down and not realize losses that did not have to be realized simply due to normal market fluctuations. When making the selection on how many days “was optimal” we used the past 18 months of actual Anchor data for back testing purposes. ORATS confirmed that over that 18 month period, 21 days was the optimal time to use. However, with more data at hand, we have been able to confirm that 28 days is a significantly better time period over history than a 21 day period. In testing, we used two data sets on SPY – from January 2012 to present and from January 2007 to present. January 2012 was picked because after that point, SPY weeklies were fully available. January 2007 was picked because that’s the furthest back in time the software’s data went. From January 2012 to the present, selling puts 21 days out, with a profit target of 30%, would have returned, on average, 8.87% per year with a Sharpe Ratio of 1.63. From 2007, a return of 5.32% was realized with a Sharpe Ratio of 0.42. Merely by increasing from 21 days to 28 days, those numbers increase to 11.08% and 2.14 for 2012 to the present and 8.52% and 0.93 for 2007 to the present. This is a massive increase. It was enough of an increase to make us question the results. If this was a more “optimum” period, as theorized, such results should hold across other, similar instruments. For both QQQ and IWM, the results held. 28 days achieved much better returns on a put selling period than 21. We also learned that rolling the short puts on a set day (Friday), anytime you can for a gain, is not close to an optimal roll period. Significant improvements can be gained by ensuring the profits are somewhere between 25%-35% prior to rolling. Interestingly, waiting till profits are in excess of 50% began to have a negative impact on results. (Profits are defined as a percentage of credit received. So if we receive $1.00 for selling a put, a thirty percent gain would occur when the price declined to $0.70) Anchor’s current put selling strategy has us making an adjustment each Friday. If there’s a gain in the position, we roll, and if not, we hold – simple rules. Unfortunately, by adhering to “simpler” rules in an effort to make the strategy easier to manage for everyone, we cost ourselves significant performance. If we rolled when a profit target was reached, regardless of day, as opposed to on a Friday at any profit point, we would have increased our returns to 11.08% and Sharpe Ratio to 2.14 from the 6.87% return and 0.7 Sharpe Ratio we have experienced since 2012 on put selling. Using the same put selling ratio we have, that means by doing Friday roles, instead of a profit target, we’ve cost ourselves between 1.5% to 2.0% per year in total performance. III. Cautionary Notes One thing to be careful with software such as ORATS is over mining and getting confused by the noise. For instance, why not pick 25% or 33% profit target instead of 30%? Once you get that granular, randomness becomes a factor. One year 25% might work significantly better and another 33% and yet another 30%. Given that there are only 12-24 trades per year, which profit target hit on that tight of a range is a bit of “luck.” For instance, if we sold a put for $1.80, a 25% profit would have the price dropping to $1.35 and at 33%, $1.21. Prices move that much intraday frequently, so trying to target the “exact” price to do everything is a fool’s errand. The inability and/or inaccuracy in trying to overly optimize is a concern in getting exact performance numbers. It is not a concern in identifying major trends. If profit targets between 1%-20% all underperform profit targets from 25%-35%, over multiple periods, clearly we should be using 25%-35%. Similarly if all results are worse over 50%, then 50% is too high. Using different instruments (IWN and QQQ) provided further verification for this process, providing a higher degree of confidence. There is also a concern that any back testing is simply “curve fitting,” and that is one hundred percent true. The data we have discussed is pulling out the optimal curve. Some of this can be combated by using different time periods (e.g. 2007 to present and 2012 to present, or even smaller periods). If the conclusions founds hold over various time periods and various instruments (QQQ and IWM), it is more likely than not that the results are not merely curve fit, but instead due to consistent trends. However, as we all know, previous results are no guarantee of future performance – they merely increase our chances. In verifying our hypothesis about 28 days and profit target rolling, we went even more granular, across SPY, QQQ, and IWM. To our relief, the results generally stood. 28 day periods are more optimal than 7, 14, 21, 35 or 45 over the vast majority of time periods. There are years “here and there” were 21 days were better and one year on IWM were 35 days was a better period. But even in those years, 28 days was the second best performing. Over any multiple year period (from 2007 to the present), our conclusions held. The same held true for profit margins. Maybe one year 20% was the best and another 45% the best, but in all multi-year periods we looked at, using a profit margin of “around” 30% was much better than a static day roll with no profit margin requirement. Because of this, starting this Friday, we will be modifying Anchor’s rolling rules. Moving forward, we will be rolling to 28 days out and rolling once profits have gotten above 30%. This means we may be rolling on days other than Friday moving forward if profit targets are obtained. We could even roll several days in a row in a bull market. If profit targets are not hit, we will continue to hold, as the strategy currently operates. Next week we’ll discuss other Anchor modifications we will be implementing to ideally further improve Anchor’s average performance.