Return Comovement Research Articles

Retail traders and co-movement: Evidence from Robinhood trading activity

We find evidence that retail trading activity by Robinhood traders is associated with lower levels of return co-movement and liquidity co-movement. We demonstrate the significance of these relationships primarily employing a two-way fixed effects panel data regression model covering cross-sectional and time-series observations of US stock trades from May 2018 to July 2020. The findings hold true across various cross-sectional subsamples and across subperiods before and after March 2020, coinciding with the stock market crash induced by heightened risks of the COVID-19 pandemic. With regard to returns, our analysis identifies three co-movement channels: 1) increased correlated trading by retail traders, 2) extended delay in incorporating market-wide information, and 3) a direct effect influenced by the integration of firm-specific information into prices. In contrast, for liquidity co-movement, we fail to identify evidence of plausible channels relating to either volatility or correlated trading. However, it appears that the significant direct effects that we document stem from a broadened array of trading strategies when retail traders contribute to the market. Collectively, these findings have important implications as return co-movement limits investors' ability to diversify investments and manage risks, while liquidity co-movement heightens market vulnerability to crashes.

Asymmetric trading restriction and return comovement

This study decomposes the overall return comovement into intraday and overnight comovement based on a model-free framework. It shows that intraday return comovement contributes the most to the overall return comovement, but the impact of overnight return comovement is persistent. Investors under the market with asymmetric trading restrictions (ATR) tend to sell stocks early in the market and buy them near the end of the market. This correlated trading behavior contributes to the specific comovement in stock returns, especially the overnight return. Our findings remain solid even after controlling for more stock attributes and changing the proxies for return comovement and investor trading behavior. We also document a weakening (reinforcing) effect of the short-selling mechanism (disposition effect) on the ATR-induced return comovement. Our results provide a deeper understanding of investors’ trading behavior under ultra-short-term trading restrictions and the source of return comovement in the literature.

Public real estate returns and inflation shocks: The central role of inflation nonneutrality

AbstractWe study the comovement of public real estate returns and inflation shocks over 1981–2022, using both survey‐based expected inflation and the Consumer Price Index (CPI). We find a complex relation that is: strongly negative during weaker‐economic (WE) times over the 1980s and 1990s, when stagflation was more a concern; strongly positive during WE times over roughly 2000–2022, when low growth with low inflation tended to be more a concern; and marginally negative otherwise. Linking inflation to both macroeconomic fundamentals and real estate operational data, we show that inflation shocks comove with changing beliefs about the underlying economic‐growth state and/or the risk premium. Thus, we argue that inflation nonneutrality has a central role in understanding our findings.

Game in another town: Geography of stock watchlists and firm valuation

Beyond a bias toward local stocks, investors prefer companies in certain cities over others. This study uses the geographic network of investor-followed stocks from stock watchlists to identify intercity investment preferences in China. We measure the city-pair connectivity by its likelihood of sharing an investor in common whose stock watchlist is highly concentrated in the firms of that city pair. We find that a higher connectivity-weighted aggregate stock demand-to-supply ratio across connected cities is associated with higher stock valuations, higher turnover, better liquidity, and lower cost of equity for firms in the focal city. The effects are robust to controls for geographic proximity and the broad investor base, are stronger among small firms, extend to stock return predictability, and imply excess intercity return comovement. Our results suggest that city connectivity revealed on the stock watchlist helps identify network factors in asset pricing.

Investor network and stock return comovement: Information-seeking through intragroup and intergroup followings

Vast amounts of firm-specific information are now available to investors on social media. One primary conduit for investors to seek for these information is through forging following links in their social networks. In particular, intragroup followings spread news of a specific stock while intergroup followings circulate stories of other stocks. Whether this following behavior contributes to information diffusion and further connects to stock return comovement, however, still remains unclear. Here, over a large scale of social network examining investors information-seeking in intragroups and intergroups we show that information-seeking of both kinds is negatively associated with stock return comovement. We further demonstrate that the relationship is pronounced by investors’ experiences but is weaker for larger size stocks. Implications in both theory and management are also discussed.

The origin of return correlation networks

Abstract Financial networks are constructed from asset price comovements. There is a large literature that takes these networks as given, for example, for portfolio optimization. But what exactly is the origin of these networks? We exploit a unique database with matched asset price and order imbalance data, allowing us to observe the trade orders placed and reveal excess demands along with the resulting prices. Empirically, we find that order imbalance comovement has a positive and statistically significant effect on return comovement. Filtering out the latent market factors from both order imbalance and return leads to a drastic drop in explanatory power. We infer that the market factor of order imbalance is the primary driver of return comovement—robust to model specifications as well as fixed effects. We present complementary results with market volatility and the decomposition of traders in terms of strategic heterogeneity. Our work brings forth the role of order imbalance networks in explaining asset return networks.

External shocks’ effects on the co-movements of currency and stock returns in three Southern African Development Community states

External shocks’ effects on the co-movements of currency and stock returns in three Southern African Development Community states

Return comovement and price volatility: a study of the US dairy commodity futures markets

ABSTRACT US dairy markets have become increasingly volatile, which presents a challenge for dairy farmers and industry participants to manage risk, disturbing the stability of the industry. However, the study of dairy volatility is limited. This article investigates the return comovement and price volatility of four major US dairy commodities: butter, cheese, Class III milk, and dry whey. We also investigate the COVID-19 pandemic’s impact on dairy volatility. Our results show that dairy commodities returns and volatilities are positively correlated, but only cheese and Class III milk correlate strongly. The volatilities of butter, cheese, and Class III milk are impacted comparably by return shocks and past volatility. However, dry whey volatility is predominantly driven by past volatility. Using multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) models, we demonstrate that return comovements are time-varying and volatilities are interdependent among dairy commodities. Volatility spillover effects are observed among dairy commodities, especially between dry whey and cheese. The COVID-19 pandemic amplifies dairy volatilities and spillover effects, with a more substantial impact on cheese and milk. Interestingly, dry whey experiences the least impact and performs better during the pandemic. Our results aid market participants in risk management and inform policymakers’ decision-making processes.

Carbon Awareness and Return Co-movement

Carbon Awareness and Return Co-movement

Impact of Oil Price Volatility on Selected Sectors of the Polish Stock Market

The commodity market has a significant impact on the global economy. Crude oil is one of the most important energy commodities, used to produce gasoline, diesel fuel, jet fuel and many other products. Changes in oil prices can have several different economic effects, by affecting inflation, trade balance, exchange rate, and many other macro- and micro-economic indicators. The main aim of the research is to identify the impact of oil prices on the Polish capital market. The co-movement of WTI Brent returns in relation to the sector indices of the Warsaw Stock Exchange was examined. The oil price impact assessment considers the period from 2014 to 2023. The research shows that out of fourteen indices, a significant relationship was observed in the case of four sectors: WIG Banks, WIG Chemicals, WIG Mining and WIG Fuel. In the case of most of the remaining indices, the correlation coefficients were positive but low.

Synchronized Shifts: Decoding the Co-movement of Stock and Bitcoin Returns

Synchronized Shifts: Decoding the Co-movement of Stock and Bitcoin Returns

Corporate Culture and Stock Return Comovement

Corporate Culture and Stock Return Comovement

Interstate migration networks and stock return comovement

AbstractWe document sizable and robust excess return comovement between migration‐flow receiving and sending states at the state‐portfolio level. Migration comovement is not fully explained by economic fundamentals and strengthens with the size of the migration network. Consistent with the view that it is partially driven by correlated trading of a common investor base within migration networks, migration comovement a) increases substantially when there is an exogenous positive shock to migration flows, b) is greater with old firms in migration‐sending states, and c) strengthens when retail investors display “old home” bias in addition to local bias.

Realized semibetas and international stock return predictability

We decompose traditional betas into semibetas based on the signed covariation between the returns of individual stocks in an international market and the returns of three risk factors: local, global, and foreign exchange. Using high-frequency data, we empirically assess stock return co-movements with these three risk factors and find novel relationships between these factors and future returns. Our analysis shows that only semibetas derived from negative risk factor and stock return downturns command significant risk premia. Global downside risk is negatively priced in the international market and local downside risk is positively priced.

Herd behavior in cryptocurrency market: evidence of network effect

PurposeThis study examines herd behavior in the cryptocurrency market at the aggregate level and the determinants of herd behavior, such as asymmetric market returns, the coronavirus disease 2019 (COVID-19) pandemic, 2021 cryptocurrency's bear market and the network effect.Design/methodology/approachThe authors applied the Google Search Volume Index (GSVI) as a proxy for the network effect. Since investors who are interested in a particular issue have a common interest, they tend to perform searches using the same keywords in Google and are on the same network. The authors also investigated the daily returns of cryptocurrencies, which are in the top 100 market capitalizations from 2017 to 2022. The authors also examine the association between return dispersion and portfolio return based on aggregate market herding model and employ interactions between herding determinants such as, market direction, market trend, COVID-19 and network effect.FindingsThe empirical results indicate that herding behavior in the cryptocurrency market is significantly captured when the market returns of cryptocurrency tend to decline and when the network effect of investors tends to expand (e.g. such as during the COVID-19 pandemic or 2021 Bitcoin crash). However, the results confirm anti-herd behavior in cryptocurrency during the COVID-19 pandemic or 2021 Bitcoin crash, regardless of the network effect.Practical implicationsThese findings help investors in the cryptocurrency market make more rational decisions based on their determinants since cryptocurrency is an alternative investment for investors' asset allocation. As imitating trades lead to return comovement, herd behavior in the cryptocurrency has a direct impact on the effectiveness of portfolio diversification. Hence, market participants or investors should consider herd behavior and its underlying factors to fully maximize the benefits of asset allocation, especially during the period of market uncertainty.Originality/valueMost previous studies have focused on herd behavior in the stock market. Although some researchers have recently begun studying herd behavior in the cryptocurrency market, the empirical results are inconclusive due to an incorrectly specified model or unclear determinants.

Disclosure Similarity and Future Stock Return Comovement

Existing research often assumes that firms’ financial reporting choices influence their return comovement with other firms. We examine the validity of that assumption. First, we provide initial evidence suggesting that similarity in two firms’ disclosures not only predicts but influences future return comovement between those two firms. Second, we show that this predictive ability aggregates to the market level; disclosure similarity can be used to estimate more accurate forward-looking market betas. Taken together, these two results suggest that firms’ reporting decisions can influence their firms’ betas even in the absence of changes to capital structure or operations. This paper was accepted by Suraj Srinivasan, accounting. Funding: The authors are grateful for financial support from the Brigham Young University Marriott School of Business and the Fisher College of Business, Ohio State University. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4915 .

High-speed rail and stock return comovement in China

This study explores the impact of China’s high-speed rail network on reducing local bias and fostering capital market integration. Our research reveals that implementing high-speed rail in a city decreases the return comovement of its local stocks but increases its return comovement with the national stock market. Our results are robust and consistent across various model specifications. After examining the underlying economic mechanism, we find that the impact of high-speed rail on stock return comovement is stronger for small firms, non-state-owned enterprises (non-SOEs), firms with poor corporate governance, and firms’ headquarters in more segmented and less-developed regions. This effect did not change after controlling for other information-dissemination channels and regional economic development. Overall, geographical proximity contributes to information transfer and market efficiency.

Aerospace competition, investor attention, and stock return comovement

Fierce aerospace competition among global superpowers has resulted in strong public attention on satellite launch events in the U.S. Given limited attentional resources, U.S. investors pay more attention to market-level shocks than to firm-specific shocks, making stock returns comove more with the market on satellite launch days than on other days. We find that the effect is significantly stronger for military-related satellite launches, launches before the dissolution of the former Soviet Union, and international satellite launches by other competitors, highlighting a greater concern for national security. A trading strategy that exploits the potential satellite-induced mispricing yields an annualized abnormal risk-adjusted return of up to 17% within the three-day window around launch date. Our results are robust to a battery of robustness analyses that consider the different characteristics of satellite launches, the exclusion of aerospace firms, and stock return comovement with industries.

Is the cash-returns relationship risk induced?

Whether there is a cash anomaly and what drives the cash–returns relationship are unclear. By constructing a cash risk factor, this study explores the cash–returns relationship and the mechanisms underlying it. We find that the cash factor is pervasive and captures co-movement in stock returns, indicating a significant cash–returns relationship. The factor loading cannot predict returns after controlling for the cash characteristic and has a negative relationship with the implied cost of capital. Also, the cash factor does not reflect future macroeconomic risk. These results are not consistent with rational capital asset pricing theories and cast doubts on the role of the risk explanation while supporting the role of the mispricing effect in the cash–returns relationship.

Industry regulation and the comovement of stock returns

Industry regulation and the comovement of stock returns