A Study on Backtest Metrics for Financial Analysis
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DOI:
https://doi.org/10.59287/ijanser.251Keywords:
Backtest, Sharpe Ratio, Profit Factor, Time Series, Financial ForecastingAbstract
Backtesting would be an example of a situation that allows the doctor to have an idea of the diagnosis by questioning the patient's history of the disease and considering a few complaints he or she has had. Backward performance metrics play an important role in the evaluation process of a trading strategy. When evaluating a trading strategy, key metrics such as sharp rate, maximum drop, profit factor, number of trades, calm rate, volatility are calculated and analyzed. Data of AAPL, AMZN, SPY, GOOG shares are obtained for this particular period presented. A simple trading strategy was applied on this structure and retrospective performance metrics were measured on it. By comparing the results of these measurements, it is observed how important and effective these measurements are on a trading strategy. It is concluded that the criteria in these observations do not always give the same result and vary from strategy to strategy, from data to data. It was concluded that performance metrics and the number of transactions should be evaluated together when performing backtesting on a trading strategy. It is recommended to consider the results of the presented study in order to make a profitable estimation with less risk.
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