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This article will shows how this works, and how IV can affect your decision on what type of trade to open. Directional Spreads Let’s start with the simplest of options spreads, the put or call vertical spread which is often used as to place a trade for a stock to move in a certain direction. Here’s a slightly OTM (Out of The Money) call vertical debit spread on AAPL about a month away from expiration (a popular spread to play for stock price to rise). The stock price is $182 and the call vertical is long the 185 call and short the 190 call. Note the highlighted Vega section that will illustrate some important points regarding IV: When the spread strikes are OTM (stock price is below both long and short call strikes) the trade is vega positive. This means while the spread remains OTM, increasing IV will help it retain more of its value. As the stock price rises toward the spread strikes the degree of vega positive becomes less. It eventually becomes vega neutral at roughly the break-even point for the spread at expiration. As the stock price rises even farther, approaching the higher short strike and beyond, the trade will become vega negative. This means when the spread is ITM (In The Money), decreasing IV will help the value get closer to the spread width (the max gain). How can this factor into a trade opening decision? When opening a bullish call vertical spread when IV is elevated it may help to enter near the vega neutral position with the long strike ITM and short strike OTM. This will be likely be a setup where the max gain is equivalent to the max loss. If the stock price rises then you’ll hit the point where the spread becomes vega negative sooner, so any drop in IV won’t hurt. Conversely, if opening when IV is lower you can start out with both legs of the call vertical being OTM. This will give you a setup where the max gain is higher than the max loss, but you know that any further IV decline is less likely and therefore the downside risk due to dropping IV is not as high so it can be ok even though it will take more of a stock price rise to get to the point where the trade turns vega neutral and then vega negative. Spreads for Minimal Stock Price Movement I’m now going to focus on common spreads to play for minimal stock price movement. The Iron Condor (IC) is one such spread and shown in the following chart, it consists of both an OTM put credit spread and an OTM call credit spread. When the stock price is in the winning position between the wings it is vega negative meaning an IV drop will accelerate profit growth above the level that just time decay would generate. Conversely, an IV rise will decelerate profit growth. Also note that when the stock price gets to the losing zones within and beyond the wings, the IC becomes vega positive meaning an IV rise would help keep the losses smaller. How can this impact a trade opening decision? Opening an IC when IV is low means that you’ll have to use closer to ATM strikes to get the same opening credit compared to times when IV is higher when you can get the same credit with farther OTM strikes. Also, when opening with low IV a further IV decline is less likely, so you won’t get the accelerated profit growth when IV drops. Opening an IC when IV is somewhat elevated means to can go farther out with strikes (so a bigger stock price move is required to get to the losing zones) and any IV decline can accelerate profit growth provided the stock price doesn’t make a significant move. Many people don’t like Iron Condors due to their risk vs reward where the max loss is higher than the max gain. Let’s look at two other common spreads to play for minimal stock price movement that have more equal risk vs reward and how IV can factor into which one to use. The first is the calendar spread, which commonly uses the ATM strike when playing for minimal stock price movement. The primary gain catalyst is theta decay (and minimal stock price movement) but IV can also factor in. As shown on the chart below, its vega positive everywhere meaning that rising IV will always help the trade. Rising IV will both increase the gain potential and widen the profit tent. Declining IV will lower the gain potential and tighten the profit tent. The other common spread to play for minimal stock price movement is the butterfly spread. Its PnL chart looks very similar to that of the calendar with a balanced risk vs reward and similar break-even points. The primary gain catalyst is the same as the calendar, theta decay and minimal stock price movement. But there is one important difference, the butterfly is vega negative when in the winning zone meaning that declining IV will allow gains to grow at a quicker rate. How can this impact a trade opening decision. When IV is lower, further IV decline is less likely so using a calendar is a good choice as any rise in IV can help the trade. However, when IV is elevated and IV decline is more likely then a butterfly can be a good choice as any decline in IV can help the trade. Spreads for Stock Price Movement in any direction I’m now going to focus on common spreads to play for significant stock price movement, either up or down. A long straddle or long strangle consists of only long legs, so they are always vega positive. Rising IV will lessen the impact of negative theta, falling IV will add more price decrease to that of negative theta alone. This is why straddles and strangles are typically used in the timeframe before earnings where you have the virtually guaranteed IV increase to counteract some of the negative theta. A reverse iron condor (RIC) is the inverse of the iron condor. It consists of and OTM call debit vertical spread and an OTM put debit vertical. How far away from ATM you go impacts the risk vs reward setup. Note that the RIC is vega positive when in the losing zone between the put and call wings, so any IV decline will accelerate losses. The trade becomes vega negative when the stock price moves into a winning zone, so if you get the stock price to move then you are guaranteed to have a winning trade regardless of what happens with IV. There are certainly more complex trade setups to use in any of these scenarios, but I’ve covered some of the most popular trades and you can see how current IV can impact your decision to use one trade setup instead of another.

Performance Dissected Check out the Performance page to see the full results. Please note that those results are based on real fills, not hypothetical performance, and exclude commissions, so your actual results will be lower, depending on the broker and number of trades. Please read 2024 Year End Performance By Trade Type for full analysis of our 2024 performance. We have extensive discussions about brokers and commissions on the Forum (like this one) and help members to select the best broker. The 116% annual return was pretty typical, compared to our long term averages. We are very pleased with this return. We continue delivering the most consistent and stable performance 13 years in a row! It's nice to call a 116% return "typical". And the beauty of our trading philosophy is having different strategies in our model portfolio that compliment each other. As I mentioned in one of the discussion topics, our performance reporting is very conservative. We rarely have more than 5 trades open at the same time, but with 5 trades open, you are basically only 50% invested. If you made 10% on the invested capital, we would report as 5% return on the total account. No service is doing it, but this is the only correct way to do it. But it also means that members can invest more than 10% per trade on trades that are more conservative and more liquid. Also there are tons of unofficial trades that don't make it to the official portfolio due to their size.being too large for 10k portfolio. If we reported performance like most other services do (return on investment and not on the whole portfolio), our reported performance would be 300%+. More details: How We Calculate Returns? Thank you again to everyone for their support, and of course special thanks to our contributors @Yowster @krisbee @TrustyJules @cwelsh and @Romuald After 13 years in business, SteadyOptions maintains its position as the most stable and consistent options trading service, with 122.5% Compounded Annual Growth Rate. We proved again that we can make money in any market. As one of our members mentioned: "I would rate the 3% profit for March 2020 as even MORE successful than the 25% profits for Jan/Feb. If someone can make a profit in a month when there was total carnage in the markets, then that shows resilience and security in the trading strategies. It shows that even during a black swan event, the system works, and the account will not be blown." Our strategies SteadyOptions uses a mix of non-directional strategies: earnings plays, Long Straddle, Long Strangle, Calendar Spread, Bitterly, Iron Condor, etc. We constantly adding new strategies to our arsenal, based on different market conditions. SO model portfolio is not designed for speculative trades although we might do some in the speculative forum. SO is not a get-rich-quick-without-efforts kind of newsletter. I'm a big fan of the "slow and steady" approach. We aim for many singles instead of a few homeruns. My first goal is capital preservation instead of doubling your account. Think about the risk first. If you take care of the risk, the profits will come. What makes SO different? We use a total portfolio approach for performance reporting. This approach reflects the growth of the entire account, not just what was at risk. We balance the portfolio in terms of options Greeks. SteadyOptions provides a complete portfolio solution. We trade a variety of non-directional strategies balancing each other. You can allocate 60-70% of your options account to our strategies and still sleep well at night. Our performance is based on real fills. Each trade alert comes with a screenshot of our broker fills. We put our money where our mouth is. Our performance reporting is completely transparent. All trades are listed on the performance page, with the exact entry/exit dates and P/L percentage. It is not a coincidence that SteadyOptions is ranked #1 out of 723 Newsletters on Investimonials, a financial product review site. The reviewers especially mention our honesty and transparency, and also tremendous value of our trading community. We place a lot of emphasis on options education. There is a dedicated forum where every trade is discussed before the trade is placed. We discuss different strategies and potential trades. Unlike most other services that just send the trade alerts, our members understand the rationale behind the trades and not just blindly follow the alerts. SO actually helps members to become better traders. Other services In addition to SteadyOptions, we offer the following services: Anchor Trades - Stocks/ETFs hedged with options for conservative long term investors. Simple Spreads - simple spread strategies like diagonal spreads and vertical spreads. Steady Collars - our version of lower risk collar trades SteadyVIX - Volatility based trades. SteadyYields - Treasures trading We offer all services bundle at $3,100 per year. This represents up to 63% discount compared to individual services rates and you will be grandfathered at this rate as long as you keep your subscription active. Details on the subscription page. More bundles are available - click here for details. You can also get the yearly bundle with one month trial at $100. Subscribing to all services provides excellent diversification since those services have low correlation. We also offer Managed Accounts for Anchor Trades. Summary 2024 was another excellent year for our members. We are very pleased with our performance. SteadyOptions is now 11 years old. We’ve come a long way since we started. We are now recognized as: #1 Ranked Newsletter on Investimonials Top Rated Newsletter on Stockgumshoe Steady Options Review: In-Depth Analysis Top 10 Option Trading Blogs by Options Trading IQ Top 4 Options Newsletters by Benzinga Top 40 Options Trading Blogs by Feedspot Top 15 Trading Forums by Feedspot Top 20 Trading Forums by Robust Trader Top Twitter Accounts to Follow by Options Trading IQ I see the community as the best part of our service. We have the best and most engaged options trading community in the world. We now have over 10,000 registered members from over 50 counties. Our members posted over 190,000 posts in the last 13 years. Those facts show you the tremendous added value of our trading community. I want to thank each of you who’ve joined us and supported us. We continue to strive to be the best community of options traders and continuously improve and enhance our services. Let me finish with my favorite quote from Michael Covel: "Profits come in bunches. The trick when going sideways between home runs is not to lose too much in between." If you are not a member and interested to join, you can click here to join our winning team. When you join SteadyOptions, we will share with you all we know about options. We will never try to sell you any additional "proprietary systems", training, webinars etc. All our "secrets" are included in your monthly fee.

While the past cannot guarantee future outcomes, it remains our most reliable resource for understanding market behavior. Previously, I outlined how Monte Carlo simulations can be used to estimate these probabilities. But relying solely on one method is limiting. Diversifying the ways we calculate probabilities adds robustness to the analysis. In this article, I will delve deeply into three additional methods for calculating probabilities: Hidden Markov Models (HMM), seasonality-based probabilities, and implied probabilities derived from options prices. Each method has distinct advantages and complements the Monte Carlo approach, providing a comprehensive framework for assessing Credit Put Spreads. 1. Hidden Markov Models (HMM): Unveiling Hidden Market Dynamics Hidden Markov Models (HMM) are a sophisticated machine learning technique designed to analyze time-series data. They operate on the assumption that observed data (e.g., ticker prices) are generated by an underlying set of "hidden states" that cannot be directly observed. These states represent distinct market conditions, such as bullish trends, bearish trends, or periods of low volatility. How HMM Works Defining Observations and States: The observed data in this context are the historical closing prices of the ticker. The hidden states are abstract conditions influencing price movements. For example: State 1 (Bullish): Higher probabilities of upward price movements. State 2 (Bearish): Higher probabilities of downward price movements. State 3 (Neutral): Limited price movement or consolidation. Training the Model: The HMM is trained on historical price data to learn the transition probabilities between states and the likelihood of observing specific price changes within each state. For example, the model might learn that a bullish state is likely to transition to a neutral state 30% of the time, and remain bullish 70% of the time. Making Predictions: Once trained, the HMM can estimate the current state of the market and use this information to predict future price movements. It calculates the probability of the ticker being above a specific threshold on a given date by analyzing likely state transitions and their associated price changes. Advantages of HMM in Options Trading Pattern Recognition: HMM excels at identifying non-linear patterns in price movements, which are often overlooked by simpler models. Dynamic Analysis: Unlike static models, HMM adapts to changing market conditions by incorporating state transitions. Probability Estimation: For a Credit Put Spread, HMM provides a probabilistic measure of whether the underlying will remain above the short strike based on historical market behavior. By capturing hidden dynamics, HMM offers a more nuanced view of market probabilities, making it a valuable tool for assessing risk and reward in Credit Put Spreads. 2. Seasonality-Based Probabilities: Unlocking Historical Patterns Seasonality refers to recurring patterns in price movements influenced by factors such as economic cycles, investor behavior, or external events. In options trading, seasonality-based probabilities quantify how often a ticker's price has exceeded a certain percentage of its current value over a specific time horizon. How to Calculate Seasonality-Based Probabilities Define the Threshold: The threshold is expressed as a percentage relative to the current price (e.g., -2%, +0%, +2%). This normalization ensures the probability calculation is independent of the absolute price level. Analyze Historical Data: For a given holding period (e.g., 30 days), calculate the percentage change in price for each historical observation. Example: If the current price is $100, and the threshold is +2%, count how often the price exceeded $102 after 30 days in the historical data. Aggregate the Results: Divide the number of times the threshold was exceeded by the total number of observations to calculate the probability. Example: If the price exceeded the threshold in 70 out of 100 instances, the probability is 70%. Applications in Credit Put Spreads Seasonality-based probabilities answer the question: "In similar conditions, how often has this ticker remained above the breakeven?" This approach is particularly useful for ETFs, which often exhibit more predictable patterns than individual stocks. For example, certain sectors might perform better during specific times of the year, providing an additional layer of insight. Limitations to Consider Seasonality probabilities rely entirely on historical data and assume that past patterns will persist. While this is often true for ETFs, it may be less reliable for individual stocks or during periods of market disruption. 3. Implied Probabilities from Options Prices: Extracting Market Sentiment Options prices are more than just numbers; they encapsulate the collective beliefs of market participants about future price movements. By analyzing the prices of puts and calls across various strikes for a given expiration date, we can derive the implied probabilities of the ticker being in specific price ranges. Steps to Calculate Implied Probabilities Collect Options Data: Obtain the bid-ask prices for puts and calls at different strike prices for the desired expiration date. Calculate Implied Volatility: Use the options prices to derive the implied volatility (IV) for each strike. IV reflects the market's expectations of future price volatility. Estimate Probabilities: For each strike, calculate the probability of the ticker being at or above that level by using IV and the Black-Scholes model (or similar methods). The probabilities are then aggregated to construct a distribution of expected prices at expiration. Why Implied Probabilities Matter Market Consensus: Implied probabilities reflect what the market "thinks" about the future, offering a forward-looking perspective. Dynamic Adjustments: Unlike historical methods, implied probabilities adapt in real-time to changes in market sentiment, such as news events or macroeconomic data. Application to Credit Put Spreads For a Credit Put Spread, implied probabilities can answer questions such as: "What is the market-implied likelihood that the ticker will remain above the short strike?" This insight helps traders align their strategies with prevailing market sentiment. Conclusion By integrating these three methods—Hidden Markov Models, seasonality-based probabilities, and implied probabilities from options prices—into my existing Monte Carlo framework, I’ve developed a robust system for evaluating Credit Put Spreads. This approach enables a comprehensive analysis of Out-of-the-Money (OTM) Credit Put Spreads among a selection of ETFs, filtering for: Gain/loss ratios within specific thresholds, Expiration dates within a defined range, A minimum credit of $0.50. The result is what I like to call a “stellar map” of selected spreads: accompanied by a summary table: These tools provide clarity and actionable insights, helping traders identify the best trades—those offering the highest probability of success while maximizing potential returns relative to risk. Looking ahead, the next step will involve calculating the expected value ($EV) of these trades, combining probabilities and potential outcomes to further refine the selection process. The ultimate goal remains the same: to stack the odds in our favor—not by predicting exact prices, but by estimating probabilities with precision and rigor. Stay tuned as I continue refining these methods and expanding their applications!

There are good ways and bad ways to diversify your portfolio. Yes, you shouldn’t put all your funds into one stock. But the types of other stocks you choose and the amount of stocks in your portfolio matters too. Below are just a few important dos and don’ts to help you diversify efficiently. The Dos of Diversification DO spread your investments across different sectors You’ll find companies from many different industry sectors in the S&P 500. A big mistake that some amateur traders make when diversifying is choosing lots of stocks from one single sector. A common example of this is investing purely in tech stocks (such as Microsoft, Apple, Nvidia, Palantir and Alphabet). The tech sector might be booming right now, but what if there’s one day a calamity that affects the entire tech sector? Investing into a few stocks from other sectors such as healthcare, consumer goods and energy could protect you from a sector-specific downturn. Your tech stocks might lose value, but your healthcare stocks could stay strong. DO invest in international markets Beyond the NYSE and Nasdaq are a range of international stock exchanges that can also be worth exploring. These include Euronext, The Shanghai Stock Exchange, The Tokyo Stock Exchange, The London Stock Exchange and The Saudi Exchange. While it’s comforting to stick to familiar waters, investing in stocks from other countries could offer an extra layer of security. If there’s a domestic downturn, your European stocks or Chinese stocks might just come to the rescue. Just remember that foreign exchanges are open at different times of the day, so you might have to get up earlier or stay up later if you want to buy stocks, sell stocks or monitor what’s going on. Investing in international stocks also does mean keeping up with international politics. For example, knowing what’s happening in China will give you a better idea as to where Chinese stocks are going. DO rebalance regularly You should ideally aim to keep a similar amount of funds in each stock you invest in. It’s unwise to dedicate more than 20% of your funds to a single stock - if that stock crashes, that’s one fifth of your funds gone. Modern trading platforms often allow you to visualise your portfolio as a pie made up of different slices for each of your investments. You should try to keep all of these slices a similar size. If one slice is much bigger than the others, consider rebalancing your funds. Don’t let one company guzzle all the pie! If one slice of pie is leaner than the others, you can similarly invest more funds into it if it’s making a return, or sell it and invest the funds elsewhere if it’s making a loss. DO remember your investment goals The types of stocks you invest should be dependent on your goal. Looking to build your funds quickly? Aim to invest predominantly in high growth stocks - although higher risk, they will grow the fastest. Want to build some savings for retirement? Put some money into more stable stocks from older companies that have consistently proven to make slow but steady returns in the past. That all said, it’s still worth sprinkling in a couple high-growth stocks into a long-term portfolio to add some excitement, just as it’s still worth adding a few dependable slow-growth stocks into a short-term portfolio to add some stability. The Don’ts of Diversification DON’T invest in things you don’t understand While it’s important to invest in a range of sectors, you should be careful of picking stocks from industries that you know little to nothing about. Investing in random stocks just because they’re on the rise is essentially gambling. While you don’t need to be an expert in every company you invest in, you should ideally take some time to see what products and services they provide to get a better idea of how their price is affected. Some of the strongest portfolios are often made up of stocks that traders know and love - this can give you a much more intuitive idea of when and when not to invest. DON’T over-diversify Diversification is all about balance. While you don’t want to just invest everything into one or two stocks, spreading your funds over 100 stocks isn’t sensible either. Known as over-diversifying or di-worse-ification, investing in too many different stocks often results in paltry returns. It makes it much harder to keep track of all the different companies you’ve invested in. As a result, you’re less likely to immediately notice which stocks are rising in value and which are falling unless you’re spending an hour per day trawling through them. Try to build a portfolio that is diverse but small enough to manage. Many experts recommend 20 to 30 stocks. Ideally, you should be able to name them all when asked to recall them. DON’T overlook quality You could make an argument that even 20 stocks is too much. In fact, one of the most famous investors of all time, Warren Buffet, has long used concentration risk as a strategy: all of Berkshire Hathaway’s returns come from just 12 companies. The reason Berkshire Hathaway has such strong returns year on year is because Buffet has always focused on quality over quantity. Each of the companies he invests in is strong and well established with a proven track record of making steady returns. He doesn’t take a punt on new companies and avoids companies that have a history of volatility (even if they’re currently soaring in value). Choosing high quality stocks typically involves doing research into companies and not just choosing trendy stocks. Look at how well the company has performed over the years and heed the advice of seasoned investors. DON’T make it too mathematical It’s possible to take diversification too seriously and spend too much time and effort getting the percentages just right. Yes, you should try to invest a similar amount into each company. But you don’t have to precisely divide your funds into each. Yes, you should invest in different sectors. But you don’t have to maintain an even amount of stocks in each sector. Yes, you should invest in international stocks. But you don’t have to invest an exact equal amount into each stock exchange. Unless you enjoy approaching stock trading with mathematical precision, too many calculations will likely just turn trading into a chore. Aim to divide things up a little more roughly and trust your gut as to where to put your money. This will make building a portfolio more enjoyable. You also won’t have to check in as regularly - unless trading is your job, there’s no need to be logging in every day and tweaking things. Conclusion By following these dos and don’t, you can create a diverse portfolio that is profitable and protected against various different risks. The key is to maintain balance in terms of how you divide your funds and the types of stocks you invest in. At the same time, don’t let it become overly calculated to the point that it feels like you’re following a formula as opposed to following your gut. This is a contributed post.

In this article, I'll introduce Monte Carlo simulations, explain their relevance in trading, and describe a specific options trading strategy I've developed using these simulations. I'll also share backtested results to illustrate the strategy's effectiveness. 1. What Are Monte Carlo Simulations? Monte Carlo simulations are a computational technique used to model the probability of different outcomes in a process that cannot easily be predicted due to the presence of random variables. Named after the famed casino, these simulations are especially useful in finance because they allow for the analysis of uncertainty and risk. The process involves running thousands or even millions of simulations based on historical price movements, where each simulation projects a possible future outcome. The resulting distribution provides traders with probabilities of price ranges over a given time horizon. 2. How Are Monte Carlo Simulations Applied in Trading? In trading, Monte Carlo simulations help to anticipate how a financial instrument, such as an ETF like SPY or QQQ, might behave over a future period. The process looks back over several years of historical price data and runs numerous simulations to project future price distributions. The outputs typically show a probability distribution of future prices, highlighting key metrics such as confidence intervals.Here is an example for SPY:  These simulations are invaluable for options traders because they offer insights into the probability that a stock or ETF will remain within above/below price bounds over a specific time frame. This information helps to craft structured options strategies, like Credit Put Spreads, which profit when an asset stays above a price threshold. 3. Example for a Credit Put Spread Here for example is the result of 10,000 simulations carried out on SPY for a prediction of the movement in 15 days by asking the algorithm to calculate what percentage of data is above the $565 threshold. For example if we consider that this value is a support or that this value would be the break even of a Credit Put Spread strategy that we would have implemented. We see that there is a probability of 77% that the ticker is above this threshold value. Recall that Monte Carlo simulations observe the past behavior of the ticker over many years, day after day, deduce a statistical distribution and perform random shots oriented like this statistical distribution in order to capture the pseudo-random nature of the market. It will be necessary to see how these predictions have come true in the past. Note that to account for the historical distribution of a ticker, we need to adjust the Monte Carlo simulation approach in the code. Rather than assuming a normal distribution for price movements, I model price changes based on the actual historical distribution of returns. This technique, often called bootstrapping, samples historical returns directly instead of generating synthetic returns based on a fixed normal distribution. This is then the kind of plot we get : 4. The Strategy: Using Monte Carlo Simulations for Options Trading Using the break evens of an Iron Condor as threshold values is not interesting because the simulations showed that credits received on the Call part were not sufficient. So let's focus on the Put part via Credit Put Spreads. For a given ETF (we will leave out stocks because of the earnings), there are many expiration dates and many strikes, each with their own price. Which ETF to choose, which strikes to buy and sell and which expiration dates? For this, the program I wrote scans the most important ETFs, ['SPY','GLD','QQQ','IWM','EEM'], all their expiration dates between two numbers of days [min_days = 30 max_days = 120] and all strikes below the OTM strike that can form a Credit Put Spread. A point is thus given by, for example, [SPY, 2024-11-15, put bought=$577, put sold=$582]. For each point, the code then performs 10,000 Monte Carlo simulations, looking back 20 years and calculating the probability that the SPY close will be higher than the break even in 29 days (=number of days remaining between now and the expiration date). Then, the program displays all the points in the form of a graph with, on the abscissa, the perceived credit and on the ordinate, the Monte Carlo probability. Credit > $0.50 and gain/loss ratio above 40% are only selected. The graph is divided into 4 quadrants, the one of most interest to us being the northeast quadrant (maximum credit and maximum probability). The program then detects the two points which, in this quadrant, have the highest probability or the highest credit. Here is an example of display: 4. Backtesting Results To validate this strategy, we performed backtests using historical data for the past 15 years. The idea was to simulate what would have happened if this strategy had been applied in the past with the break even corresponding to the probability computed in the chosen point. To use the example here above with the maximum credit,the backtest would answer this question: for the ticker QQQ at the expiration date of 2024-12-31 (corresponding to 74 days from now, the date of writing this article), the Monte Carlo simulations tell me that the Close of QQQ has a probability of 64.82% of being higher than the strategy's break even. If I had applied this strategy 15 years in the past from now, day after day with the Break Even at that time corresponding to this quantile, would the real value of QQQ have indeed been higher than this Break Even? And if so, how many times has it worked between 15 years ago and now, day after day? To be more specific, during the backtest the algorithm displays the results of the step-by-step backtests very clearly: Example of a screenshot during the backtest: and the plot of the histogram to prove the consistency of the threshold value: This systematic approach, with precise risk management, provides traders with a powerful tool to make informed decisions about structuring options trades. It's worth noting that the performance of each strategy can vary depending on market conditions, so consistent backtesting is key to keeping the strategy profitable in evolving markets. The final result of the backtest, for that strategy, is: This means that backtests give better results (83.64% win rate) than the probabilities announced by Monte Carlo simulations (64.82%) and the trade could be opened. Conclusion Monte Carlo simulations offer a scientific and data-driven way to project future price ranges in the often unpredictable world of trading. By applying these simulations, we can develop strategies that aim to capture value by accurately predicting price movements within specific time horizons. The backtests show that using this method, especially for long-term options strategies like Iron Condors, can significantly improve the likelihood of success. This approach complements other options strategies and provides a robust framework for structuring trades with a high probability of profit, while carefully managing risk.

A few weeks ago we introduced a new strategy to our members. While a double diagonal spread is a well known strategy, we are trading it with a tweak. The double diagonal strategy is part of SteadyOptions service, along with straddles, strangles, calendars etc. One of our members have mentioned that "I realize they are lower risk in the sense that they can be open longer without big losses, but feels to me like playing not to lose." Here is a response from our contributor @Yowster who introduced the strategy: Well... Lay me outline reasons why I like them (and I've been doing a ton more of them in personal trades in addition to the official ones, and are tracking even more of them). They are extremely low risk, of all the trades I've had on or tracked only one (a DE personal trade) was down by 10% or more at any given time provided I exit prior to T-0, and I wound up able to close that one for a small gain. I've had many make gains of 15% or more (NVDA, SQ, PANW were recent trades I closed within the past few days that fall into this category). Of the trades I've placed since January (about 25 of them), roughly 75% of them have been winning trades with an average gain across winners and losers of ~5% (and there were a few large winners like BA and MRNA that I only tracked and didn't have on). I compare the results to straddle trades since they have similar profit targets, although holding periods can be longer. Compare a 75% win rate with ~5% average gain to our historical straddle results found here and these DD returns are very good. One of the common things heard from many members over the years is that the shorter duration straddle trades are difficult to manage when they can't be watching the market all the time. DD's don't fall into this category as they can be open for longer periods of time, you can easily have GTC orders to close at profit targets and you don't have to worry about avoiding larger losses when RV suddenly spikes downward - so DDs are very good trades for people who can't be watching the market all the time. Regarding the "playing not to lose" comment. Managing downside risk as much as possible is one of my primary goals with SO trades, as larger percentage losses can have a large negative impact on portfolio performance. I look at DDs simply like this - I can have roughly 75% of trades be profitable (some smaller gains, but quite a few over 10% and some getting to 20%), but have almost all losses limited to below 10% (most losers below 5%) and that math works out very well over the longer term. Currently, we have 4 DDs open as official trades and this will be the most you are likely to see at any given time - thereby leaving plenty of slots for other trade types. Members have different risk tolerances so not every trade type we use is a good match for all members. But for people who can't be monitoring the market all the time and for some trades where you'd like a higher capital allocation because of the lower downside risk, DDs can be a good match this category. As one of our members mentioned: "Regarding the "playing not to lose" comment. Managing downside risk as much as possible is one of my primary goals with SO trades, as larger percentage losses can have a large negative impact on portfolio performance. I look at DDs simply like this - I can have roughly 75% of trades be profitable (some smaller gains, but quite a few over 10% and some getting to 20%), but have almost all losses limited to below 10% (most losers below 5%) and that math works out very well over the longer term. Many option forums or traders will report a win percentage, total percentage over a few years. However, I will say that over long periods of time, the unlikely occurrence of a higher risk/higher return strategy of will greatly reduce a portfolio. The cost of the extra options easily is worth the alleviation of risk. If you look at their historical performance. This was once of there better performing trades over time. So thank you Yowster. I also like that some trades are large enough stocks that you can exceed the recommended allocation without significantly effecting the float with a larger trade, as a straddle/strangle under a dollar needs is less desirable for me. I completely respect this strategy is for a 100k portfolio. I may be trading occasionally more, but that's a different topic that has been discussed I believe." My 2 cents: To put things in perspective, we closed 9 DDs so far with average return of 5.1% and average holding period of 9 days. Only 2 losers, both 2-3%, and none of the trades was down more than 5% at any given time. Even when the stock doesn't move, the losses are minimal. If someone believes that 5% is not a good return for options trades, I suggest reading Is 5% A Good Return For Options Trades? Yes, some options gurus will tell you that you should aim for at least 100% gain in each option trade, otherwise it is not worth the risk. What they don't tell you is the risk you will be taking. So I would say that on risk adjusted basis, those results almost too good to be true. They are also pretty easy to open, and because the holding periods are longer than straddles, members have more time to enter. Closing can be done with GTC order, and many times members get better results - just check the previous DD discussion topics. Commissions impact is negligible - in today's environment, many brokers have zero commissions, and even for people who pay 0.30-0.50 per contract (which is high by the current standards), the commissions impact is less than 0.5% per trade. As for the statement "playing not to lose" - guilty as charged. Limiting losses is our main goal at SteadyOptions. And if you look at our track record, in the last 12 years we were able to produce triple digit gains while keeping the drawdowns very small. I can only salute @Yowster for constantly coming with new variations of well known strategies in every market environment. Another consideration is trade allocation. Lets say you are willing to risk 2% of the account per trade. If you know that the maximum risk is not likely to be more than 10-15%, you can easily allocate 10-12% per trade. But if your risk is 100%, your allocation should not exceed 2% per trade. So your overall performance will not necessarily be better with high risk high reward trades, but with much higher risk. So yes, we are playing not to lose. Keeping your losers small is one of the key elements in trading. Subscribe to SteadyOptions now and experience the full power of options trading at your fingertips. 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In this article, I will show why it might be not a good idea to keep those options straddles through earnings. As a reminder, a straddle involves buying calls and puts on the same stock with same strikes and expiration. Buying calls and puts with the different strikes is called a long strangle. Strangles usually provide better leverage in case the stock moves significantly. Under normal conditions, a straddle/strangle trade requires a big and quick move in the underlying. If the move doesn’t happen, the negative theta will kill the trade. In case of the pre-earnings strangle, the negative theta is neutralized, at least partially, by increasing IV. The problem is you are not the only one knowing that earnings are coming. Everyone knows that some stocks move a lot after earnings, and everyone bids those options. Following the laws of supply and demand, those options become very expensive before earnings. The IV (Implied Volatility) jumps to the roof. The next day the IV crushes to the normal levels and the options trade much cheaper. Over time the options tend to overprice the potential move. Those options experience huge volatility drop the day after the earnings are announced. In many cases, this drop erases most of the gains, even if the stock had a substantial move. In order to profit from the trade when you hold through earnings, you need the stock not only to move, but to move more than the options "predicted". If they don't, the IV collapse will cause significant losses. Here is a real trade that one of the options "gurus" recommended to his followers before TWTR earnings: Buy 10 TWTR Nov15 34 Call Buy 10 TWTR Nov15 28 Put The rationale of the trade: Last quarter, the stock had the following price movement after reporting earnings: Jul 29, 2015 32.59 33.24 31.06 31.24 92,475,800 31.24 Jul 28, 2015 34.70 36.67 34.14 36.54 42,042,100 36.54 I am expecting a similar price move this quarter, if not more. With the new CEO for TWTR having the first earnings report, the conference call and comments will most likely move the stock more than the actual numbers. I will be suing a Strangle strategy. 9/10. Fast forward to the next day after earnings: As you can see, the stock moved only 1.5%, the IV collapsed 20%+, and the trade was down 55%. Of course there are always exceptions. Stocks like NFLX, AMZN, GOOG tend on average to move more than the options imply before earnings. But it doesn't happen every cycle. Last cycle for example NFLX options implied 13% move while the stock moved "only" 8%. A straddle held through earnings would lose 32%. A strangle would lose even more. It is easy to get excited after a few trades like NFLX, GMCR or AMZN that moved a lot in some cycles. However, chances are this is not going to happen every cycle. There is no reliable way to predict those events. The big question is the long term expectancy of the strategy. It is very important to understand that for the strategy to make money it is not enough for the stock to move. It has to move more than the markets expect. In some cases, even a 15-20% move might not be enough to generate a profit. Jeff Augen, a successful options trader and author of six options trading books, agrees: “There are many examples of extraordinary large earnings-related price spikes that are not reflected in pre-announcement prices. Unfortunately, there is no reliable method for predicting such an event. The opposite case is much more common – pre-earnings option prices tend to exaggerate the risk by anticipating the largest possible spike.” Related Articles: How We Trade Straddle Option Strategy Buying Premium Prior to Earnings Can We Profit From Volatility Expansion into Earnings Long Straddle: A Guaranteed Win? We invite you to join us and learn how we trade our options strategies in a less risky way. Join Us