Andrew Falde’s Strategy Set Theory Updated 2/19/2016 Core Concept The following ideas revolve around one core concept: Intelligent combinations of simple strategies should be more effective than elaborate efforts to create one perfect strategy. The reason is because one strategy on one asset class is not likely to be effective at hedging its own risk and diversify performance as effectively as a combination of strategies in different asset classes. Conceptual Example An iron condor has positive expectancy, but does poorly during periods of rapidly expanding price volatility. Attempting to create an iron condor strategy that will perform in all market environments will usually end up creating an iron condor strategy that has reduced or even negative performance over time. Instead of fixing an iron condor so that it will perform in all market environments ­­ it should be designed to perform best for the market environment that it is best suited for, and additional strategies should be deployed that thrive in the variety of market conditions that the iron condor is not best suited for. The net effect of a combined set of diversified simple strategies should produce superior risk adjusted returns compared to an independent complex strategy. Analogy The quarterback of a professional football team is often considered the key player. However, there are 10 additional players required to effectively compete. Although the quarterback is often the key player, attempting to fill the remaining 10 spots with more quarterbacks would be foolish. Re­training 10 additional quarterbacks to fulfill the roles of linemen, receivers, and running backs would be far less effective than finding good linemen, receivers, and running backs that naturally fit those roles. Many traders are fixated on the strategies and concepts they understand or that they believe provide the best chance of success. Maybe the iron condor is their quarterback. When they learn about the limitations of their iron condor, they attempt to re­train it to be good at tackling and blocking. But ultimately, the iron condor should just be there to throw. Tackling and blocking may best be left to a completely different set of strategies; some of which may not be in the same underlying market, or may not be options trades at all. I believe that if the NFL took the top 11 quarterbacks and told them to play defense against the worst NFL offense… the worst offense would dominate the field every time. Similarly, 11 very simple trading strategies that are appropriately designed for 11 different market environments should beat the most elaborately designed market neutral options system available. Rudimentary Case Study The following data was gathered from a first round test that combined bearish, bullish, and neutral approaches using a variety of underlying markets and timeframes. The combination was not targeted to create a net smooth equity curve, but it did so anyway ­­ providing evidence that the core concept has merit. Standalone Bearishly Positioned Butterfly using Weekly Contracts on SPX ­­ (Bearish / Neutral). Thanks to David Wilt for providing this hypothetical back test. Portfolio of Put Credit Spreads and Straddles ­­ (Bullish / Neutral). Thanks to Cameron Schwartz for providing this hypothetical back test. (On a Basket of 8 Stocks and Indexes using Bullish Momentum Filter) This portfolio was tested manually and includes a mix of put credit spreads on weekly and monthly contracts while the momentum filter was positive. Additionally, a short straddle was included to simulate the addition of a neutral component. After this test was completed, we combined it with the weekly Butterfly strategy that was part of a completely different test. The combination was not designed to fit well together, which makes the following chart all the more interesting. Combined (70% Momentum Put Spreads/Straddle & 30% Weekly Butterfly) S&P 500 During the Time of this Study Although the market was generally bullish during this five year study, the Summer of 2011 (about one sixth of the way through this chart) included a correction of more than 15% in the SPX. During that event, the momentum signals triggered a reduction in the portfolio of Put Credit Spreads and Short Straddles while the Butterfly position remained constant. All in all, the equity curve was hardly affected by the high volatility event of Summer 2011. A couple notes about this Strategy Set: ● The Butterfly strategy is an optimized variation specifically designed for bearish performance. It was optimized to perform well on its own, but designed independent from the set. ● The Put Credit Spread / Straddle portfolio was the first iteration ­­ with no optimization ● The combination of the two is the very first iteration ­­ with no optimization related to the combination or sizing. The next chart shows the two sets of strategies plotted separately on the same chart. Because both strategies include positive Theta and negative Vega (although it’s doubtful a butterfly is a true negative Vega trade ­­ but more on that in a different study), these two often perform well at the same time. Several times, their performances diverge because of their net Delta. And, it’s rare to see them both drawdown at the same time ­­ but it does happen. Limitations of the Previous Case Study A Butterfly is an effective standalone strategy that performs well in most market conditions ­­ especially ​
bearish ​
trends. At first blush, a good pairing to a Butterfly would be a Put Credit Spread; because it too is an effective standalone strategy that performs in most market conditions ­­ particularly ​
bullish trends. The combined set provided a smoother equity curve, but there are still several periods of simultaneous drawdown. That is because the primary risks in a Butterfly are not effectively offset by a Put Credit Spread. The primary risks in a Butterfly are: ● Persistent bull market trends with minimal pullbacks or consolidation periods ●
Extreme crashing scenarios that blow through the downside range of the Butterfly. Regarding persistent bull market risk:​
A Put Credit Spread provides limited returns during very strong bull markets because the defined credit received provides declining positive Delta during bullish moves. So, when the Butterfly needs upside protection most, the Put Credit Spread offers less and less protection. Regarding extreme crashing scenarios: ​
The Put Credit Spread accentuates the downside risk that the Butterfly has and with an outsized drawdown compared to its normal return. While a strategy of combining them has shown a more favorable return over time than each strategy alone, there may be more efficient, effective, and strategic ways to combine bullish and bearish strategies to reduce the volatility of portfolio returns ­­ especially during the larger up and down moves in the broad market. Additionally, it is doubtful that the addition of the straddle to the individual stocks in the portfolio provided much value. I suspect that the short straddle portion could be reduced or eliminated in favor of a larger butterfly position in the index. Next Steps for Developing These Ideas Further studies should have the primary goal of ​
reducing simultaneous draw down​
. A secondary goal should be to discover additional bullish and bearish strategies that can be added to (or replace) the various components of this set. This would include additional asset classes such as equities and futures. My philosophy is that it’s better to work toward something that can be implemented in real time quickly, rather than waiting until no further improvements can be found. One should never assume that there is a ​
final​
version. There is only the ​
current ​
version and the ​
next ​
improvement. By implementing the best available solution, one can gather real world experience as to the practicality of managing the trades. This experience is vital to the process of seeking the next set of pragmatic solutions. General steps to be taken ● Develop and maintain a database of separate equity curves. ○ The focus should be on simple strategies that can be described on one page. ○ The database should be able to combine any set of strategies at various sizes in order to analyze the combined results of the chosen set. ● Set benchmark metrics to evaluate the performance of strategies and strategy sets ●
○ Zephyr K­ratio for smoothness ○ Sharpe Ratio for risk adjusted return statistics ○ Average annual return ○ Max drawdown ○ Longest drawdown duration ○ Etc. Member strategies to evaluate first. ○ Short put spread on index ­­ bullish/neutral ○ Short put spreads on equities ­­ bullish/neutral ○ Long calls on equities ­­ bullish ○ Short call spreads on index ­­ bearish / neutral ○ Bearishly positioned butterfly on the index ­­ bearish/neutral ○ Long calls and call spreads on VIX ­­ bearish As more strategies are added to the database, more Strategy Sets can be generated and analyzed to find the most favorable and manageable solution. Caution should be taken to avoid the rabbit trails leading to overfitting of rules related to sizing and timing of strategy allocation. When each strategy controls its own risk, then a simple set of strategies should be able to provide very attractive performance without requiring complex timing and allocation rules. There are countless member strategies that can be considered. The following is a sample of the types of ideas that can be evaluated over time. Evaluating each item on this list would be a lengthy process. Diversifying should not be just for the sake of diversification. The goals of additional strategies should be to reduce specific risk, reduce systemic risk, steepen the portfolio equity curve, smoothen the portfolio equity curve. Sampling of strategy types to evaluate in the future ○ Options Income ■ Short put spreads on indexes ■ Short call spreads on indexes ■ Calendars on indexes ■ Short puts on value stocks ■ Short premium on events (e.g. earnings) ○ Bullish Strategies ■ Value equities (with fundamental filters) ■ Momentum equities ■ Short VXX, UVXY ○ Bearish Strategies ■ Short rallies in indexes ■ Short trend following in indexes ■ Short momentum equities/ETFs ■ Short overbought sectors ○ Neutral / Non­correlated Strategies ■
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Pairs trading relative strength Pairs trading mean reversion Long/short futures markets (including commodity and currency futures) Merger arbitrage Order imbalance arbitrage What this looks like over time 1. Month One: Create a central database of back tested equity curves 2. Month Two: Select a combination to trade in real world 3. Month Three: Begin tracking real world performance of selected set 4. Ongoing / recurring a. Continue to add to the database of theoretical sets b. As improved versions are discovered, update the real world application c. Compare real world performance to out­of­sample simulation This document is being made available to the trading community at large in order to gather critical feedback. Please send your questions and feedback to Andrew Falde ­­ [email protected] Updates will be posted on smbtraining.com/blog, optionstribe.com, and/or faldecapital.com. Follow them all so you don’t miss any updates. ~ Andrew Falde Principal Falde Capital Management, LLC faldecapital.com Contributor SMBU & SMBU Options Tribe smbu.com / optionstribe.com twitter @andrewfalde email [email protected] All information provided is hypothetical and simulated. This is not investment advice and no trade recommendations are being made. Options Risk Disclaimer​
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Forex Risk Disclaimer​
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Futures Risk Disclaimer 1. SMB TRAINING is NOT a Broker Dealer. SMB Training engages in trader education and training. SMB TRAINING offers a number of products and services, both electronical (over the internet through smbtraining.com) and in person. SMB TRAINING also offers web­based, interactive training courses on demand. 2. The seminars given by SMB TRAINING are for educational purposes only. This information neither is, nor should be construed, as an offer, or a solicitation of an offer, to buy or sell securities. You shall be fully responsible for any investment decision you make, and such decisions will be based solely on your evaluation of your financial circumstances, investment objectives, risk tolerance, and liquidity needs. 3. This material is being provided to you for educational purposes only. No information presented constitutes a recommendation by SMB TRAINING or its affiliates to buy, sell or hold any security, financial product or instrument discussed therein or to engage in any specific investment strategy. The content neither is, nor should be construed as, an offer, or a solicitation of an offer, to buy, sell, or hold any securities. You are fully responsible for any investment decisions you make. Such decisions should be based solely on your evaluation of your financial circumstances. Such decisions should be based solely on your evaluation of your financial circumstances, investment objectives, risk tolerance and liquidity needs. 4. SMB Training and SMB Capital Management, LLC are separate but affiliated companies. 5. No relevant positions 6. Please note: Hypothetical computer simulated performance results are believed to be accurately presented. However, they are not guaranteed as to accuracy or completeness and are subject to change without any notice. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Since, also, the trades have not actually been executed; the results may have been under or over compensated for the impact, if any, of certain market factors such as liquidity, slippage and commissions. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any portfolio will, or is likely to achieve profits or losses similar to those shown. All investments and trades carry risks.”