Overnight Drift Phenomenon

In today's post, we delve into the intriguing world of the "overnight drift" phenomenon in stock markets.

The phenomenon known as the "overnight drift" refers to a consistent pattern where stock returns tend to be higher during the night than during the trading day. This has been a subject of intrigue among investors and academics alike. Through an exploration of current academic research, we can shed some light on this phenomenon and its implications for market participants.

Overnight drift of stock prices, as imagined by DALL-E

What is the Overnight Drift Phenomenon?

The "overnight drift" refers to the tendency for stock prices to increase more overnight than they do during the trading day. This effect has been documented extensively within U.S. stock indices and presents an intriguing anomaly against the traditional understanding of market efficiency.

Overnight vs cash session returns of SPDR S&P 500 ETF (%)

In recent years, American stock market behavior has been peculiar, with the bulk of returns accumulating after-hours rather than during regular trading hours, defying conventional expectations. This trend is clearly illustrated by graphs highlighting the significant discrepancy in returns between night and day. This phenomenon, known as the "overnight drift," has puzzled economists, leading to various studies, including a notable one by Boyarchenko et al. from the Federal Reserve Bank of New York.

The unusual pattern of overnight returns, which don't distribute evenly but instead follow a U-shape across different global market opening times, sheds light on this trend. These periods align with the opening times of Asian, European, and American markets, respectively. The dynamics behind these movements relate to the concept of inventory risk, as market makers, preferring to avoid risk, adjust prices to manage the higher risks of holding positions overnight, especially after significant intraday sell-offs or rallies. This behavior reflects the round-the-clock nature of trading, intensified by futures contracts, leading to the demand for a risk premium by market makers from new market entrants seeking immediate liquidity.

Evidence from Recent Studies

Recent research has provided significant insights into the overnight drift phenomenon:

1. Market Dynamics and Inventory Risk: A study by Boyarchenko, Larsen, and Whelan (2020) revealed that U.S. equity returns are notably higher during the opening hours of European markets. This pattern is linked with order imbalances at the close of the preceding U.S. trading day. The study supports inventory risk models and highlights an asymmetric reaction to demand shocks, suggesting that market sell-offs tend to lead to strong positive overnight reversals, while the opposite is observed after market rallies. This demonstrates a demand shock asymmetry potentially due to varying market maker risk-bearing capacities throughout the day (Boyarchenko, Larsen, & Whelan, 2020).

2. Post-Earnings Announcement and Information Processing: The phenomenon is not isolated to overnight returns but is also reflected in the post-earnings-announcement drift. This refers to stock prices continuing to move in the direction of an earnings surprise well after the announcement has been made. While this drift traditionally covers longer periods, it intersects with overnight drift patterns by highlighting market inefficiencies in processing and reacting to new information (Bernard & Thomas, 1989).

3. Information Accumulation and Market Reaction: Tsiakas (2008) emphasizes the role of information gathered during nontrading hours in shaping market dynamics. The study suggests that information accumulated overnight can significantly predict stock returns, providing a backbone for the overnight drift phenomenon (Tsiakas, 2008).

Implications for Investors and Traders

The overnight drift phenomenon has profound implications for trading strategies and market understanding. It challenges the traditional view of market efficiency and suggests that investors might gain by considering the timing of trades in relation to market close and open times. Additionally, the role of information asymmetry and inventory risk in creating the overnight drift offers avenues for further research and strategy development.

Conclusion

The overnight drift in US stock indices is a well-documented phenomenon that continues to challenge traditional market theories. By understanding the underlying factors contributing to this pattern, investors and researchers can better navigate the complexities of the market. The studies highlighted provide a foundation for further exploration and understanding of this intriguing market behavior.

In TradeMachine, we like to translate academic theories into practice and implement practical trading strategies based on well-documented market anomalies. Based on this practical approach, we have developed several variants of mechanical trading strategies based on the overnight drift effect.

You can find an example of the effective use of this effect in the post below: