Timing Chinese Equity Index Exposure with Forecast Time-Varying Sharpe Ratios

Summary

This note describes using a forecast of the time-varying Sharpe ratio as a monthly signal for switching between cash and Chinese equity indices. It outlines two forecasting approaches: a regression model associated with Robert Whitelaw and an ARMA model. The strategy buys the index when the forecast exceeds an upper threshold, moves to cash below a lower threshold, and holds its current position between those levels. Thresholds are optimized for cumulative return.

For the reported test from 2008 to 2012, the note gives trade counts, signal success rates, and cumulative returns for the two approaches on the CNI 1000 index, and reports results for CSI 300 and CSI 800 applications. The figures exclude transaction costs, and the test window is limited. Since the thresholds are chosen to maximize cumulative return on the stated test period, the reported results may reflect in-sample optimization and do not establish performance in other periods or after costs.

Key ideas

• The time-varying Sharpe ratio is used as a forecast signal for monthly index allocation.
• The strategy enters the index above an upper threshold, exits to cash below a lower threshold, and otherwise makes no change.
• The note compares a Whitelaw-style regression forecast with an ARMA forecast.
• Thresholds are optimized for cumulative return, creating a risk of in-sample overfitting.
• Reported backtests omit transaction costs and cover a limited historical period.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.