خرید و دانلود نسخه کامل کتاب Algorithmic Trading: Winning Strategies and Their Rationale – Original PDF

W hile the focus of this book is on specifi c categories of strategies and not on general techniques of backtesting, there are a number of im- portant considerations and common pitfalls to all strategies that need to be addressed fi rst. If one blithely goes ahead and backtests a strategy with- out taking care to avoid these pitfalls, the backtesting will be useless. Or worse—it will be misleading and may cause significant financial losses. Since backtesting typically involves the computation of an expected re- turn and other statistical measures of the performance of a strategy, it is reasonable to question the statistical significance of these numbers. We will discuss various ways of estimating statistical signifi cance using the method- ologies of hypothesis testing and Monte Carlo simulations. In general, the more round trip trades there are in the backtest, the higher will be the sta- tistical significance. But even if a backtest is done correctly without pitfalls and with high statistical signifi cance, it doesn’t necessarily mean that it is predictive of future returns. Regime shifts can spoil everything, and a few important historical examples will be highlighted. The choice of a software platform for backtesting is also an important consideration and needs to be tackled early on. A good choice not only will vastly increase your productivity, it will also allow you to backtest the broad- est possible spectrum of strategies in the broadest variety of asset classes.a