The ‘other’ January effect and the presidential election cycle

Abstract

The ‘other’ January effect posits that when January's stock returns are positive (negative), the remaining 11 months of the year tend to be positive (negative) as well. While no explanation is currently offered, this departure from market efficiency carries important implications for the portfolio management decision. Other research has shown that stock returns tend to be higher during the second half of the president's term than during the first half as a result of variations in fiscal policy across time. When the ‘other’ January effect is examined in the presence of the presidential election cycle, it seems clear that January holds greater predictive power during certain years of the president's term in office. Therefore, in portfolio management decisions, investors should not view either in isolation, but consider both together.

Notes

¹ See Rozeff and Kinney (1976), Haugen and Jorion (1996), Haug and Hirschey (2006) and others.

² Going back to 1926, the S&P 500 was negative only twice–1931 and 1939. In addition, Stovall (1992) documents 1903 and 1907 as negative years in the Dow Jones Industrial Average.

³ For Year 1, the results of the CRSP (NYSE) equally weighted portfolio are not reliable.

⁴ For Year 3, there was only one negative 11-month HPR for the S&P 500 and the CRSP (NYSE) value-weighted portfolios. Thus, the binomial test cannot be conducted.

⁵ Results not reported.

⁶ With the exception of the cycle's third year for the CRSP (NYSE) equally weighted portfolio.

⁷ This series was discontinued due to fed monetary policy changes effective January 2003.

⁸ Raw changes, log changes and percentage changes were considered. Percentage change time series is chosen because it has the least first order autocorrelation of 0.05 (p-value = 0.690). The first order autocorrelation of raw changes and log changes is 0.19 and 0.11, respectively.