There are three basic ways to test an investment strategy. Each has its own unique set of pros and cons, but only one is practical.
The best approach is to develop a strategy and then run it with real money out of sample for at least 3 to 5 years. Longer is even better. That’s the gold standard, but that takes time, and so there are obvious limitations. Be careful not to confuse this version of out-of-sample testing with its pseudo-out-of-sample cousin, which uses a portion of historical data to build a model and then tests it on the remaining unused “out of sample” historical numbers. Useful, but no substitute for the genuine article.
The weakest alternative is to develop a strategy and paper trade to decide if it passes the smell test. Relatively easy and quick, but here too, there are clear challenges, namely, the transition from theory to empirical usually brings many surprises.
The best (or should we say the least worst) alternative is to backtest a strategy. The idea here is that you can have the best of both worlds: a rough approximation in the here and now of how a strategy would have fared if implemented at some point decades ago. Alas, this is no silver bullet either since no backtest can flawlessly tell you how a strategy will perform in the years ahead. But short of acquiring the powers to see into the future, it’s the best that mere mortals can do.
Indeed, the key advantage to historical backtesting: you don’t have to wait years to determine if a strategy is a winner or a dog. Another plus: you’re not totally reliant on theory for assessing how the future may unfold.
The critical issue, of course, is designing a backtest that comes close to replicating the real world through a historical lens. Easier said
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