January Barometer: Equity Exposure Based on January Returns

Summary

This algorithm implements a January barometer rule using a broad equity ETF and a Treasury bill ETF as alternatives. At the start of January, it liquidates the bill holding and invests in equities, recording the equity price as a reference. In February, it compares the current equity price with that reference. A positive January return keeps the portfolio in equities; a nonpositive return triggers liquidation of equities and investment in bills. The code processes the decision at the first available data point in each month and checks that recent data exists for both securities.

The example uses daily US market data and sets leverage on both securities, but the strategy targets full portfolio holdings in one asset at a time. It includes no performance results, benchmark comparison, transaction cost model, or rationale for the calendar signal. The implementation also contains data freshness and missing-data liquidation behavior that could affect live or historical results. The example therefore documents a simple seasonal allocation rule, not evidence that it reliably predicts equity returns.

Key ideas

• The strategy invests in equities during January and records a reference price for the month.
• At the February decision point, a positive January return keeps the portfolio in equities.
• A nonpositive January return moves the portfolio from equities into Treasury bills.
• The algorithm checks recent data availability and liquidates holdings when data checks fail.
• The document provides implementation logic but no evidence of profitability or robustness.

Tags

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