Monthly Bias Map
The NASDAQ 100, represented by the futures ticker NQ=F, offers intriguing insights when viewed through the lens of seasonality over the past 20 years. Each month shows a probabilistic bias that traders can use as a prior when planning strategies. May, the current month, historically yields an average return of +1.55% with a 65% win-rate. However, it's crucial to remember that these patterns are probabilistic, not deterministic.
Why Seasonality Exists
Seasonality in financial markets often arises from a combination of factors, including institutional rebalancing, tax-driven flows, and broader economic cycles. For instance, January’s moderate performance (+0.63%, 65% win-rate) may be influenced by new capital allocations at the start of the year. In contrast, April's strong average performance (+3.10%, 75% win-rate) often coincides with post-tax season investment flows and earnings season optimism.
Best and Worst Months
July: The Standout Month
July emerges as the most favorable month historically, with an average return of +3.56% and an impressive win-rate of 85%. This could be attributed to mid-year portfolio rebalancing and the so-called "summer rally," where lower trading volumes can lead to outsized moves.
September: The Cautionary Tale
Conversely, September shows a slight negative bias, averaging -0.19% despite a 60% win-rate. This month is notorious for its volatility, possibly due to the end of the fiscal year for many funds and the onset of pre-election jitters in U.S. mid-term and presidential election years.
Day-of-Week Tilts
Analyzing the day-of-week performance, Monday stands out with an average gain of +0.238% and a win-rate of 62%, while Thursday shows a negative tilt with an average loss of -0.201% and a win-rate of only 45%. These patterns can stem from weekend news digestion affecting Monday, while mid-week trading often sees more volatility as traders position for weekly closes.
Where Seasonality Breaks
While seasonal patterns can provide a useful framework, they are not immune to disruption. Macroeconomic shocks, such as unexpected central bank actions or geopolitical events, can override historical trends. Additionally, changes in market structure or investor behavior can lead to regime shifts that render past patterns less reliable.
Where This Fits
Understanding the NASDAQ 100's seasonality is one piece of the puzzle for traders. It should be used alongside other technical and fundamental analyses. For a comprehensive, real-time view of the NASDAQ 100, visit AlphaTRADER's live dashboard, which integrates these insights with current market conditions.