CRACK, Timothy Falcon, 1999. A Classic Case of "Data Snooping" for Classroom DiscussionJournal of Financial Education, Vol. 25, Fall 1999, pages 92-97. [not cited]
Abstract: "Data snooping (mistaking spurious statistical relationships for genuine ones) is an important and dangerous by-product of financial analysis. However, data snooping is a difficult concept to explain to students of financial economics because, by its very nature, it is difficult to illustrate by example (a strong statistical relationship between complex financial variables is difficult to refute). To overcome this pedagogical difficulty, I present an example of data snooping where one variable is non-financial: I show that near both new moon and full moon, stock market volatility is higher and stock market returns are lower than away from the new or full moon. The simple and off-beat nature of this example enables substantial classroom discussion."
DICHEV, Ilia D. and Troy D. JANES, 2003. Lunar Cycle Effects in Stock Returns, The Journal of Private Equity, Fall 2003. [Cited by 20] (4.72/year)
Abstract: "We find strong lunar cycle effects in stock returns. Specifically, returns in the 15 days around new moon dates are about double the returns in the 15 days around full moon dates. This pattern of returns is pervasive; we find it for all major U.S. stock indexes over the last 100 years and for nearly all major stock indexes of 24 other countries over the last 30 years. Taken as a whole, this evidence is consistent with popular beliefs that lunar cycles affect human behavior."
McAVITY, Ian, 1982. Full Moon & The Market, Deliberations: The Ian McAvity Market Letter, A Special Report, 1 May 1982. [not cited]
YUAN, Kathy, Lu ZHENG and Qiaoqiao ZHU, 2001. Are Investors Moonstruck? Lunar Phases and Stock Returns, Journal of Empirical Finance, Volume 13, Issue 1, January 2006, Pages 1-23. [Cited by 25] (16.23/year)
Abstract: "This paper investigates the relation between lunar phases and stock market returns of 48 countries. The findings indicate that stock returns are lower on the days around a full moon than on the days around a new moon. The magnitude of the return difference is 3% to 5% per annum based on analyses of two global portfolios: one equal-weighted and the other value-weighted. The return difference is not due to changes in stock market volatility or trading volumes. The data show that the lunar effect is not explained away by announcements of macroeconomic indicators, nor is it driven by major global shocks. Moreover, the lunar effect is independent of other calendar-related anomalies such as the January effect, the day-of-week effect, the calendar month effect, and the holiday effect (including lunar holidays)."