Finding, Exploring, and Refining Trading Strategies: A Case Study by Matthew Granade and Yoshiki Obayashi
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The document discusses the process of developing and executing trading strategies, highlighting the importance of refining ideas and investing time wisely. It covers techniques such as back-testing, parameter estimation, and signal interpretation, emphasizing the need for a clear understanding of strategy mechanics. Finally, it touches on practical considerations like liquidity, transaction costs, and the transition from back-testing to live trading.
Finding, Exploring, and Refining Trading Strategies: A Case Study by Matthew Granade and Yoshiki Obayashi
- 1. 1 Finding, Exploring, and Refining Trading Strategies: A Case Study QuantCon, New York, 3.14.15 Presented by Matthew Granade and Yoshiki Obayashi
- 2. 2 FROM IDEA TO EXECUTION QUANTCON, NEWYORK, 3.14.15 What makes a good idea? (And where do good ideas come from?) How to decide if an idea is worth researching? How to move from idea to a trading strategy How to move from a trading strategy into execution As a researcher, your most valuable asset is your time. Invest it like you invest your money: thoughtfully and carefully.
- 3. 3 GOOD IDEAS QUANTCON, NEWYORK, 3.14.15 Usually some nub, often non-linear An ounce or two of evidence that it might actually work Plus some logic / some believable story for why it working would make sense Here’s the story of Eido as a trading strategy …
- 4. 4 EIDOSEARCH AT A GLANCE A web-based tool for facilitating historical pattern searches Looks for similar patterns in the past to generate a distribution of future returns A generalized expression of technical analysis QUANTCON, NEWYORK, 3.14.15
- 5. 5 HOW DO WE KNOW IF THE CONCEPT WORKS? QUANTCON, NEWYORK, 3.14.15 Jump right into back-testing trading rules incorporating the signals? • A common but mostly suboptimal practice Establish a precise mathematical definition of the “concept” • What are the parameters and inputs (what’s the difference?) • What are the outputs? Articulate what it means for the concept to “work” • In the strictest sense: • In a less strict sense, the empirical distribution may be usable even with certain biases • Even if is the true distribution, we won’t make money on every signal
- 6. 6 A STRINGENT CHI-SQURE TEST QUANTCON, NEWYORK, 3.14.15 Estimate the parameters and fix the domain of inputs For each pattern window and forecast horizon, generate the empirical distribution for every ticker each day. Calculate the cumulative probabilities Count the number of observations falling into For each pattern window and forecast horizon, calculate where . Under the null hypothesis: , hence Penalize p-values for multiple testing across numerous pattern windows and forecast horizons (FWER, FDR, etc.) Analyze the times series of correlated p-values and draw conclusions
- 7. 7 A GRAPHICAL INTERPRETATION QUANTCON, NEWYORK, 3.14.15
- 8. 8 ANYTHING-BUT-U-SHAPE! TEST DESIGN QUANTCON, NEWYORK, 3.14.15 Repeat the first four steps of the Stringent Chi-Square Test On each day, fit a beta(a,b) distribution using maximum likelihood … and test the loosened null hypothesis: a < 0.95 and b < 0.95
- 9. 9 ANYTHING-BUT-U-SHAPE! TEST RESULTS QUANTCON, NEWYORK, 3.14.15 COOL! But, what now?
- 10. 10 FROM SIGNAL TO STRATEGY QUANTCON, NEWYORK, 3.14.15 You’ve decided to invest further in an idea; next step is to find a sensible trading strategy Dimensions to think about: Whether to go long, short, or both What basket of assets to trade How strong a signal to require How many trades to make What time horizon to hold over What performance criteria to prioritize Almost always wrong to test everything; possible strategies should be driven by a deep understanding of why you think the strategy works
- 11. 11 FIRST LET’S JUST GO WILD! QUANTCON, NEWYORK, 3.14.15 Set the base case for portfolio optimization: long-short unconstrained Transaction costs, market frictions, and shattered dreams
- 12. 12 BACK-TESTING SHORT SELLING IS DICEY… QUANTCON, NEWYORK, 3.14.15 Without reliable securities-lending data, it’s difficult to estimate P&L of shorts The easiest workaround is to restrict all portfolio weights to be non-negative … or only allow shorts in the most liquid securities like benchmark index ETFs
- 13. 13 BACK TO REALITY: CONTROL TURNOVER QUANTCON, NEWYORK, 3.14.15 Many ways to penalize turnover and slippage Either model slippage roughly and conservatively or very meticulously
- 14. 14 IMPORTANCE OF INTUITION QUANTCON, NEWYORK, 3.14.15 Equivalent expression:
- 15. 15 MOMENT OF TRUTH: TOP 500 MARKET CAP ONLY! QUANTCON, NEWYORK, 3.14.15 Restricting the universe to the most liquid securities makes for the smoothest transition from back-testing to live trading But the more liquid a securities is, the more difficult it is to eek out an edge. Mounds of fool’s gold to be found in back-tests with illiquid securities.
- 16. 16 IMPLEMENTING THE STRATEGY QUANTCON, NEWYORK, 3.14.15 This is where we are now … In honor of our host, I will tell you that we are using Fetcher to pull our signals into Quantopian and then execute in IB. As a principle it’s always good to get to this stage as quickly as possible … nothing matters until you’re touching the money