Introduction

January barometer is a calendar anomaly saying that the January performance of Equity index could foretell February to December returns on Equity index - a strong January shows strong rest of the year and otherwise. This algorithm is going to explore the estimation effect of the January barometer in Equity index market.

Method

We use the S&P500 ETF as the underlying. In January, the algorithm buys SPY and hold until the end of January. At the end of January, we calculate the January return, if the return is greater than zero, the algorithm will continue to hold the SPY. If the January return is negative instead, the algorithm will liquidate the SPY asset and invest in the treasury bill for the rest of the year. The portfolio is rebalanced every year in January by a Scheduled Event.

def rebalance(self):
    if self.time.month == 1:
        self.liquidate("BIL")
        self.set_holdings("SPY", 1)
        self.start_price = self.securities["SPY"].price
    if self.time.month == 2 and self.start_price is not None:
        returns = (self.securities["SPY"].price - self.start_price)/self.start_price
        if returns > 0:
            self.set_holdings("SPY", 1)
        else:
            self.liquidate("SPY")
            self.set_holdings("BIL", 1)

Reference

  1. Quantpedia - January Barometer