The Impact of Transaction Costs on Forecast-Based Trading Strategy Performance

Active investing strategies have poor historical long-term performance compared to passive strategies. Furthermore, many active strategies use forecasting of various signals even though the efficient market hypothesis posits that stock prices rapidly incorporate information. Despite this, recent studies continue to explore the use of forecast-based strategies and report positive evaluation results. We closely investigate several inter-day active management strategies based on forecasting models via a test set and a U.S. market backtest. We approximated transaction costs via bid and ask prices and percentage costs. Test metrics indicated that models could not forecast over week-long horizons but demonstrated some forecasting ability over monthly and quarterly horizons. Backtest results indicate a null correlation between test metrics and strategy performance. For low transaction cost rates, several strategies achieved higher Sharpe ratios than a benchmark passive strategy. At 25 basis points a single strategy had comparable performance to the benchmark. It is unclear to what extent this observation of superior strategy performance was due to the quantity of strategies we evaluated. Our findings emphasise the importance of evaluating strategies under realistic trading conditions and suggest further investigation into the null correlation between forecast accuracy and strategy performance.