AlgorithmicTrading Session 3 Trade Signal Generation I FindingTrading Ideas and Common Pitfalls Oliver Steinki, CFA, FRM Outline  Introduction  FindingTrading Ideas  Common Pitfalls of Trading Strategies  Summary and Questions  Sources Contact Details: [email protected] or +41 76 228 2794 2 Introduction Where Do We Stand in the Algo Prop Trading Framework? SIGNAL GENERATION  As we have seen, algorithmic proprietary trading strategies can be broken down into three subsequent steps: Signal Generation, Trade Implementation and Performance Analysis DECIDE WHEN AND HOW TO TRADE  The first step, Signal Generation, defines when and how to trade. For example, in a moving average strategy, the crossing of the shorter running moving average over the longer running moving average triggers when to trade. Next to long and short, the signal can also be neutral (do nothing). Using moving averages to generate long/short trading TRADE signals is an example choice of how to trade IMPLEMENTATION  Sessions 3 – 6 deal with the question of deciding when and how to trade SIZE AND EXECUTE ORDERS, INCL. EXIT – Today’s Session 3: Finding Suitable Trading Strategies and Avoiding Common Pitfalls – Session 4: Backtesting – Session 5: Mean Reversion Strategies – Session 6: Momentum Strategies PERFORMANCE ANALYSIS RETURN, RISK AND EFFICIENCY RATIOS 3 Introduction Signal Generation  Signal Generation describes the process of deciding when and how to trade  Finding a trading idea is actually not the hardest part of building a quantitative trading strategy.There are hundreds, if not thousands, of trading ideas that are in the public sphere at any time, accessible to anyone at little or no cost. Many authors of these trading ideas will tell you their complete methodologies in addition to their backtest results. There are finance and investment books, newspapers and magazines, mainstream media web sites, academic papers available online or in the nearest public library, trader forums,blogs etc.  However,you have to choose a strategy that is suitable to your constraints  Avoid common trading strategy pitfalls. Several checks can tell you quite quickly whether you should further investigate a strategy or not 4 Finding Trading Ideas Where can you find good trading ideas?  Finding prospective quantitative trading strategies is not difficult.There are:  Academic research websites  Finance web sites and blogs  Trader Forums  Newspapers and Magazines 5 Table taken from the book How to Build Your Own Algorithmic Trading Business by E. Chan Finding Trading Ideas Which Strategy Suits You?  Finding a viable strategy that suits you often does not have anything to do with the strategy itself, rather with your constraints:  How much time do you have for baby-sitting your trading programs? Do you trade part time? If so, you would probably want to consider only strategies that hold overnight and not the intraday strategies. Otherwise,you may have to fully automate your strategies  How good a programmer are you? If you know some programming languages such as Visual Basic, MATLAB, R or even Java, C#, or C++, you can explore high-frequency strategies, and you can also trade a large number of securities. Otherwise, settle for strategies that trade only once a day, or trade just a few stocks,futures,or currencies  How much capital do you have available for trading? Do you have a lot of capital available for trading as well as expenditure on infrastructure and operation? In general, I would not recommend quantitative trading for an account with less than EUR 50,000  Is your goal to earn steady monthly income or to strive for a large, long-term capital gain? Most people who choose to become traders want to earn a steady (hopefully increasing) monthly, or at least quarterly, income. But you may be independently wealthy, and long-term capital gain is all that matters to you 6 Finding Trading Ideas How Does Capital Availability Affect Your Choices?  Ernest Chan lists a number of considerations dependent on your capital available: 7 Table taken from the book How to Build Your Own Algorithmic Trading Business by E. Chan Common Pitfalls of Trading Strategies Quick Checks  Before doing an in-depth backtest of the strategy, you can quickly filter out unsuitable strategies if they fail one or more of these tests:  Does it outperform a benchmark?  Does it have a high enough Sharpe/Sortino ratio?  Does it have a small enough drawdown and short enough drawdown duration?  Does the backtest suffer from survivorship bias?  Does the backtest suffer from data snooping bias? 8 Common Pitfalls of Trading Strategies Benchmark Outperformance and Performance Consistency  How compares the strategy with a benchmark and how consistent are its returns? Return comparisons are easy for long- only stock strategies,but more difficult for advanced strategies such as long/short equity  Another issue to consider is the consistency of the returns generated by a strategy. Though a strategy may have the same average return as the benchmark, perhaps it delivered positive returns every month while the benchmark occasionally suffered some very bad months. In this case, we would still deem the strategy superior than the benchmark. Always use measures such as Information, Sharpe (Information ratio with benchmark returns equal to the risk free asset) or Sortino ratio to measure risk adjusted performance,never return alone 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑜𝑓𝐸𝑥𝑐𝑒𝑠𝑠𝑅𝑒𝑡𝑢𝑟𝑛𝑠  Information ratio: 𝑆𝑡𝑎𝑛𝑑𝑎𝑟𝑑𝐷𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛𝑜𝑓𝐸𝑥𝑐𝑒𝑠𝑠𝑅𝑒𝑡𝑢𝑟𝑛𝑠 𝐴𝑣𝑒𝑟𝑎𝑔𝑒𝑜𝑓𝐸𝑥𝑐𝑒𝑠𝑠𝑅𝑒𝑡𝑢𝑟𝑛𝑠  Sortino ratio: 𝐷𝑜𝑤𝑛𝑠𝑖𝑑𝑒 𝐷𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛𝑜𝑓𝐸𝑥𝑐𝑒𝑠𝑠𝑅𝑒𝑡𝑢𝑟𝑛𝑠 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑜𝑓 𝐸𝑥𝑐𝑒𝑠𝑠 𝑅𝑒𝑡𝑢𝑟𝑛𝑠 = 𝑃𝑜𝑟𝑡𝑓𝑜𝑙𝑖𝑜 𝑅𝑒𝑡𝑢𝑟𝑛𝑠 − 𝐵𝑒𝑛𝑐ℎ𝑚𝑎𝑟𝑘 𝑅𝑒𝑡𝑢𝑟𝑛𝑠 9 Common Pitfalls of Trading Strategies Drawdowns  How deep and long is the drawdown? A strategy suffers a drawdown whenever it has lost money recently. A drawdown at a given time t is defined as the difference between the current equity value (assuming no redemption or cash infusion) of the portfolio and the global maximum of the equity curve occurring on or before time t.The maximum drawdown is the difference between the global maximum of the equity curve with the global minimum of the curve after the occurrence of the global maximum  Are there any client specific or risk management imposed drawdown constraints? 10 Graph taken from the book How to Build Your Own Algorithmic Trading Business by E. Chan