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Return Predictability and Market-Timing: A One-Month Model

Last Updated on 10 February, 2024 by Rejaul Karim

In their paper “Return Predictability and Market-Timing: A One-Month Model,” Blair Hull, Xiao Qiao, and Petra Bakosova introduce a dynamic market-timing strategy. Utilizing 15 diverse variables and employing sophisticated statistical methods, the authors craft a model that anticipates market excess returns one month ahead.

From 2003 to 2017, their strategy outshines the S&P 500, yielding a 16.6% annual return, a 0.92 Sharpe ratio, and a 20.3% maximum drawdown.

When combined with a six-month model, the synergy enhances returns and resilience, resulting in a combined strategy with a 15% annual return, a Sharpe ratio of 1.12, and a maximum drawdown of 14%. The authors share daily forecasts from their one-month model in a comprehensive Daily Report.

Abstract Of Paper

We propose a one-month market-timing model constructed from 15 diverse variables. We use weighted least squares with stepwise variable selection to build a predictive model for the one-month-ahead market excess returns. From our statistical model, we transform our forecasts into investable positions to build a market-timing strategy. From 2003 to 2017, our strategy results in 16.6% annual returns with a 0.92 Sharpe ratio and a 20.3% maximum drawdown, whereas the S&P 500 has annual returns of 10%, a 0.46 Sharpe ratio, and a maximum drawdown of 55.2%. When our one-month model is used in conjunction with Hull and Qiao’s (2017) six-month model, the Sharpe ratio of the combined strategy exceeds the individual model Sharpe ratios. The combined model has 15% annual returns, a Sharpe ratio of 1.12, and a maximum drawdown of 14%. We publish forecasts from our one-month model in our Daily Report.

Original paper – Download PDF

Here you can download the PDF and original paper of Return Predictability and Market-Timing: A One-Month Model.

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Author

Blair Hull
HTAA, LLC

Xiao Qiao
School of Data Science, City University of Hong Kong; Paraconic Technologies US Inc.

Petra Bakosova
Hull Tactical

Conclusion

In conclusion, our one-month market-timing model, based on 15 diverse variables, proves robust and effective. From 2003 to 2017, it delivers a notable annual return of 16.6%, a high Sharpe ratio of 0.92, and a limited maximum drawdown of 20.3%, surpassing the S&P 500. Integration with Hull and Qiao’s six-month model enhances performance, resulting in a Sharpe ratio of 1.12, 15% annual returns, and a minimal maximum drawdown of 14%. These findings highlight the model’s success in forecasting market excess returns, offering valuable insights for strategic asset allocation and equity premium forecasting.

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FAQ

1. What is the primary focus of the paper, “Return Predictability and Market-Timing: A One-Month Model”?

The paper focuses on the development and performance evaluation of a one-month market-timing model. Constructed from 15 diverse variables, the model aims to anticipate market excess returns one month ahead, and the authors employ sophisticated statistical methods in its creation.

2. What are the key performance metrics of the one-month market-timing strategy from 2003 to 2017?

During the specified period, the one-month market-timing strategy outperforms the S&P 500, yielding an annual return of 16.6%, a Sharpe ratio of 0.92, and a maximum drawdown of 20.3%. In comparison, the S&P 500 has annual returns of 10%, a Sharpe ratio of 0.46, and a maximum drawdown of 55.2%.

3. How does the combination of the one-month model with Hull and Qiao’s six-month model impact performance?

Combining the one-month model with Hull and Qiao’s six-month model enhances performance. The synergistic effect results in a combined strategy with a Sharpe ratio of 1.12, 15% annual returns, and a maximum drawdown of 14%. This combination surpasses the individual model Sharpe ratios and demonstrates improved resilience and returns.

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