Quote from HoundDogOne:
As a general principle...
Backtesting should be used only to verify market inefficiencies that ** can be rationally explained **.
Otherwise...
You are just practicing "data mining"...
Meaning applying brute force scanning to random data...
Which will, inevitably, result in you finding endless seemingly non-random patterns...
That you will think are significant...
But are just the worthless product of a classic statistical pitfall called "data mining".
Q
Backtesting: Interpreting the Past
http://www.investopedia.com/articles/trading/05/030205.asp
Backtesting is a key component of effective trading-system development. It is accomplished by reconstructing, with historical data, trades that would have occurred in the past using rules defined by a given strategy. The result offers statistics that can be used to gauge the effectiveness of the strategy. Using this data, traders can optimize and improve their strategies, find any technical or theoretical flaws, and gain confidence in their strategy before applying it to the real markets.
The underlying
theory is that any strategy that worked well in the past is likely to work well in the future, and conversely, any strategy that performed poorly in the past is likely to perform poorly in the future. This article takes a look at what applications are used to backtest, what kind of data is obtained, and how to put it to use!
The Data and The Tools
Backtesting can provide plenty of valuable statistical feedback about a given system. Some universal backtesting statistics include:
* Net Profit or Loss - Net percentage gain or loss.
* Time frame - Past dates in which testing occurred.
* Universe - Stocks that were included in the backtest.
* Volatility measures - Maximum percentage upside and downside.
* Averages - Percentage average gain and average loss, average bars held.
* Exposure - Percentage of capital invested (or exposed to the market).
* Ratios - Wins-to-losses ratio.
* Annualized return - Percentage return over a year.
* Risk-adjusted return - Percentage return as a function of risk.
UQ
