Risk-adjusted optimal strategies based on the Moving Average Crossover and the RSI technical trading rules : a study on the S&P 500
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- NTNU Handelshøyskolen 
This article tests the performance of optimized technical trading rules for the SPDR S&P 500 exchange traded fund in the period 2000 to 2016. To avoid data snooping, the optimization is performed on simulated time series from three different models. Two technical trading rules are optimized in this article: The dual moving average crossover and the Relative Strength Index (RSI). For both trading rules, the performance of four different trading strategies are evaluated. To measure the performance of the strategies we use the Sharpe ratio as assessment criteria. A brute-force optimization algorithm is used since the Sharpe ratio is a function of noncontinues parameters. After finding optimal parameters for each strategy based on the simulated price series, these strategies are back-tested on historical data. The results for the moving average crossover rule are mixed. Some of the trading strategies provide a higher Sharpe ratio and higher returns than a buy-and-hold strategy, but these returns are not significantly greater than the buy-and-hold returns. For the RSI rule the optimized strategies generate few trading signals on historical data, and several of the strategies do not generate any signal during the whole trading period. Some of the strategies obtain a higher Sharpe ratio compared to the buyand-hold, but this is caused by holding a risk-free position during the trading period. No strategy provides positive excess returns, and for the strategies generating negative excess returns, they are not significantly different from zero. Our results are consistent with the weak form market efficiency for the S&P 500 index during the time period 2000 to 2016.