Does the stock market influence investor everyday decisions? The case of parking violations

We explore in this study whether stock market returns influence investor decisions in their everyday life. We find that past and contemporaneous US stock market returns are related negatively to the registered number of parking violations in New York City between 2014 and 2020. We support as the channel of this relationship the level of investor anxiety. These results support extensions of the utility theory demonstrating the significance of emotions on individuals' decisions. Overall, this study shows evidence of the societal impact of finance.     

Does stock exchange consolidation improve market liquidity? A study of stock exchange acquisition in Russia

The last couple of decades have witnessed significant institutional and structural changes in financial sector within a worldwide trend toward consolidation. In the segment of organized trading stock exchanges merge and develop into large and diversified publicly traded companies. These processes are rather complicated in case of a transition economy like Russia. In December 2011 MICEX, the first largest and state-controlled stock exchange acquired RTS, the second largest and privately owned stock exchange primarily designed for foreign investors. We empirically investigate whether the acquisition resulted in improved liquidity of the Russian stock market which was one of the declared acquisition objectives. We use the Kolmogorov–Smirnov and the Wilcoxon tests to compare market-wide liquidity in several discrete periods pre and post acquisition. A deep and thorough insight into liquidity performance is ensured by assessing liquidity from limit order book data of tick frequency along three dimensions (tightness, immediacy, and elasticity).     

Does investor recognition predict returns?

Merton [1987. A simple model of capital market equilibrium with incomplete information. Journal of Finance 42, 483–510] shows that stocks about which not all investors are informed should yield a return premium. This premium depends on the shadow cost of incomplete information which in turn depends on the shareholder base, relative market size, and idiosyncratic risk. Utilizing a comprehensive database of Swedish shareholdings, we demonstrate that stock returns are positively related to the shadow cost. We also find that the shareholder base is negatively related to returns when controlling for size and idiosyncratic risk. Zero-cost portfolios based on the shadow cost/shareholder base yield substantial trading profits that are never positively correlated with the market and are only modestly explained by the four-factor model.     

When does investor sentiment predict stock returns?

We examine the asymmetry in the predictive power of investor sentiment in the cross-section of stock returns across economic expansion and recession states. We test the implication of behavioral theories and evidence that the return predictability of sentiment should be most pronounced in an expansion state when investors' optimism increases. We segregate economic states according to the NBER business cycles and further implement a multivariate Markov-switching model to capture the unobservable dynamics of the changes in the economic regime. The evidence suggests that only in the expansion state does sentiment perform both in-sample and out-of-sample predictive power for the returns of portfolio formed on size, book-to-market equity ratio, dividend yield, earnings-to-price ratio, age, return volatility, asset tangibility, growth opportunities, and 11 widely documented anomalies. In a recession state, however, the predictive power of sentiment is generally insignificant.     

Are stock market crises contagious? The role of crisis definitions

Financial contagion studies generally examine whether co-movement between markets increases during a crisis. We use a flexible co-movement measure to examine how conclusions of such analyses depend on the sample chosen as the ‘crisis’. To this end, we analyse stock market co-movement during the 1997 Asian crisis and the 2007 global financial crisis for all possible source countries and for all possible time periods or extreme return quantiles. This way we account for the main crisis dating approaches adopted in the literature. Our results suggest there is no clear relationship between excess co-movement and commonly used crisis samples.     

Stock market aversion? Political preferences and stock market participation

We find that left-wing voters and politicians are less likely to invest in stocks, controlling for income, wealth, education, and other relevant factors. This finding from unique data sets in Finland is robust both at the zip code and at the individual level. A moderate left voter is 17–20% less likely to own stocks than a moderate right voter. The results are consistent with the idea that personal values are a factor in important investment decisions, in this case leading to “stock market aversion.” The results are inconsistent with alternative explanations such as wealth effects, risk aversion, reverse causality, return expectations, or social capital.     

How do banks price liquidity? The role of market power.

We empirically examine the effects of different measures of liquidity on interest margins of a sample of U.S. commercial banks from 2001 to 2018. Overall, the results reveal that liquidity ratios exert a positive influence on bank margins. Furthermore, the study investigates the role of market power in the relationship between liquidity and interest margins. It is documented that dominant banks incorporate the costs associated with investing in liquidity into the bank margins to a lesser extent than banks with less market power, suggesting that the cost of complying with regulatory liquidity standards is reduced when the competition in the banking sector is less intense. The study highlights that market competition might be important in the design and implementation of liquidity regulations.     

Does volume help in predicting stock returns? An analysis of the Australian market

This paper presents an analysis of the relationship between trading volume and stock returns in the Australian market. We test this hypothesis by using data from a sample of firms listed on the Australian stock market for a period of 5 years from January 2001 to December 2005. We explore this relationship by focusing on the level of trading volume and thin trading in the market. Our results suggest that trading volume does seem to have some predictive power for high volume firms and in certain industries of the Australian market. However, for smaller firms, trading volume does not seem to have the same predictive power to explain stock returns in Australia.     

Extreme dependence in investor attention and stock returns – consequences for forecasting stock returns and measuring systemic risk

We characterize co-movements in investor attention by modeling multivariate internet search volume data. Using a variety of copula models that can capture both asymmetric and skewed dependence, we find empirical evidence of strong non-linear and asymmetric dependence in the attention investors give to companies. Modeling three years of daily stock returns and search volumes from Google Trends for 29 bank names, we find a striking similarity between the dependence structure inherent in stock returns and the dependence in the corresponding time series of search queries. We then document the existence of significant asymmetric and skewed tail dependence in the joint distribution of stock returns and investor attention. Finally, stock returns and internet search volumes appear to evolve concurrently in real time with neither one leading the other. Our findings have important implications, e.g. for the analysis of banks' interconnectedness based on equity data and the pricing of investor attention in the cross-section of stock returns.     

Does global liquidity drive commodity prices?

This paper tackles the question of whether a cross-sectional perspective on monetary policy is capable of explaining movements in global commodity prices. In this vein, we contribute to the rich literature on global liquidity in two different ways: on the one hand, to achieve a global series in terms of common monetary policy shocks, we propose a distinction between common and idiosyncratic factors across economies, as proposed by Bai and Ng (2004). Our second innovation stems from the consideration of a Markov-switching vector error correction model when analyzing time-varying short-run dynamics. Having identified the long-run structure which includes a proportional relationship between commodity prices and global liquidity in the first step, our results indeed show that the impact of a global liquidity measure on different commodity prices is significant and varies over time. One regime approximately accounts for times where commodity prices significantly adjust to disequilibria, while the second regime is characterized by either a weak or no commodity price adjustment. The fact that global liquidity also reacts to disequilibria in a specific regime demonstrates the two-way causality between monetary policy and commodity prices.     

Does monetary policy determine stock market liquidity? New evidence from the euro zone

The recent financial crisis has been characterized by unprecedented monetary policy interventions of central banks with the intention to stabilize financial markets and the real economy. This paper sheds light on the actual impact of monetary policy on stock liquidity and thereby addresses its role as a determinant of commonality in liquidity. Our results suggest that an expansionary monetary policy of the European Central Bank leads to an increase of aggregate stock market liquidity in the German, French and Italian markets. Furthermore, the effect of monetary policy is significantly stronger for smaller stocks, suggesting a non-linear impact of monetary policy on stock liquidity.     

Does program trading contribute to excess comovement of stock returns?

Daily returns of stocks with high program trading comove more with each other but less with others. This significant comovement is disconnected with market movements and news of fundamentals and becomes stronger when market uncertainty is higher. It can be explained by neither the hypotheses of gradual information diffusion and liquidity provision nor the effects of quantitative trading signals, earnings announcements and index fund trading. Its non-fundamental nature is further demonstrated by the observation of program trading stimulating return reversals. Underlying this comovement is the high persistence of program trading. Our findings support the theory of habitat investing and demonstrate program trading creates a distinct source of excess return comovement.     

When does attention matter? The effect of investor attention on stock market volatility around news releases

We empirically investigate how retail and institutional investor attention is related to the way stock markets process information. With a focus on 360 US stocks in the S&P 500 universe, our results show that higher retail investors’ attention around news releases increases the post-announcement stock return volatility, whereas institutional investor attention has a small but negative impact on volatility on days following news releases on average over the cross-section of companies. These findings are in line with the hypotheses that attention of retail investors slows price-adjustments to new information and attention of institutional investors results in the opposite reaction. We show that these effects are heterogeneous in the type of news and the topic of the information being released. A portfolio allocation application highlights that these results are not only statistically significant but also sizeable in economic terms and can lead to an overperformance as large as dozens of basis points.     

Does futures trading increase stock market volatility? The case of the Nikkei stock index futures markets

We propose new tests to examine whether stock index futures affect stock market volatility. These tests decompose spot portfolio volatility into the cross-sectional dispersion and the average volatility of returns on the portfolio's constituent securities. Our tests show that for Nikkei stocks spot portfolio volatility increased and cross-sectional dispersion decreased compared with average volatility when Nikkei futures began trading on the Osaka Securities Exchange, but not on the Singapore International Monetary Exchange. For non-Nikkei stocks, no shift occurred when futures trading began on either exchange. These findings are consistent with the hypotheses that futures trading increases spot portfolio volatility but that there is no volatility “spillover” to stocks against which futures are not traded. However, the increase in volatility attributable to futures trading is small compared with volatility shifts induced by changes in broad economic factors.     

Does the investment horizon of institutional investors matter for stock liquidity?

This paper examines the role of the investment horizon of institutional investors on stock liquidity of firms. We show that an increase in long-term institutional ownership is negatively associated with firm liquidity, while an increase in short-term ownership is positively related to a firm's stock liquidity. We identify the ownership-liquidity relationship by examining two major channels: the trading activity channel and the informational friction channel. Long-term investors reduce stock liquidity through low frequency trading and access to value-enhancing and private information, which induces adverse selection bias. In contrast, short-term investors improve liquidity through trading activity and competition with other investors, which lowers transaction costs. Our findings further suggest that the effects of an increase in long-term (short-term) institutional investors on liquidity weaken (strengthen) when a firm has more publicly available information. Finally, we show that the positive impact of an increase in long-term ownership on valuation is more pronounced for firms with higher liquidity and the valuation effect is persistent.     

Does the weather affect stock market volatility?

This paper investigates the empirical association between stock market volatility and investor mood-proxies related to the weather (cloudiness, temperature and precipitation) and the environment (nighttime length). Overall, our results suggest that cloudiness and length of nighttime are inversely related to historical, implied and realized measures of volatility. The strength of association seems to vary with the location of an exchange on Earth with respect to the equator. Weather deviations from seasonal norms and dummies representing extreme weather conditions do not offer additional explanatory power in our datasets.     

The risk–return relations in the Singapore stock market

This paper examines the risk–return relations in the Singapore stock market for the period April 1986 to December 1998. Though beta is significantly related to realized returns, the explanatory power is low. Adding other stock characteristics such as skewness and kurtosis provides limited incremental benefits. However, when a conditional framework based on up and down markets is introduced, the explanatory power increases more than 100 times and there is a significant positive (negative) relation between beta and returns when the market excess returns are positive (negative). The same relation applies when unsystematic risk, total risk and kurtosis are added separately to the beta–return relation during up and down markets with increased explanatory power. Our results indicate that other stock characteristics in addition to beta are also important in pricing risky assets and investors do not hold diversified portfolios. Our results are also checked and compared with another conditional model with time-varying betas conditional on a set of economic variables.     

Are extreme returns priced in the stock market? European evidence

This paper revisits some recently found evidence in the literature on the cross-section of stock returns for a carefully constructed dataset of euro area stocks. First, we confirm recent results for US data and find evidence of a negative cross-sectional relation between extreme positive returns and average returns after controlling for characteristics such as momentum, book-to-market, size, liquidity and short term return reversal. We argue that this is the case because these stocks have lottery-like characteristics, which is attractive to certain investors. Also, these stocks tend to be very volatile so that arbitrageurs are discouraged from correcting potential mispricing. As a consequence, these stocks are often overpriced and hence face lower expected returns. Second, when we control for extreme returns, the recently found negative relationship between idiosyncratic risk and future returns is less robust. In our models, after adding maximum returns, the relationship is insignificant and sometimes even positive. We also find that idiosyncratic skewness and coskewness play an important role for asset pricing, as predicted by several theoretical models.     

Does economic policy uncertainty drive nonlinear risk spillover in the commodity futures market?

We propose the rolling tail-event driven network technique (RTENET) to measure the dynamic nonlinear tail risk spillover of 20 US commodity futures. In addition, we investigate the effect of economic policy uncertainty (EPU) on risk spillover based on quantile-on-quantile regression (QQR). We find that the risk spillover effect increases sharply and that the market is tightly connected when EPU is at a high level. Crude oil, silver and corn, the three greatest risk transmitters in the system, need more attention. More importantly, the effect of EPU on the risk spillover of the commodity futures market is asymmetric and heterogeneous. When the risk spillover falls within extremely high quantiles, a significant positive effect of EPU is observed. In addition, grain and soft crops are more sensitive to EPU. Our findings provide a reference for policy-makers and investors to manage commodity futures markets in different uncertainty periods.     

Is consumption risk priced in the stock market?

The paper examines whether the risk in the consumption of stockholders caused by incomplete consumption insurance is priced in the cross-section of average stock returns. Using Taylor series expansion of the average marginal utility of consumption, we show that the risk in the consumption of stock market participants can be decomposed into two components, insurable (hedgeable using financial assets) and uninsurable (caused by incomplete consumption insurance) consumption risks. We argue that the growth rate of average consumption may be viewed as a proxy for the insurable component of consumption risk, while the growth rates of the rescaled higher-order cross-sectional consumption distribution moments may be regarded as a multivariate proxy for uninsurable risk in consumption. Exploiting microlevel household quarterly consumption data from the US Consumer Expenditure Survey, we find that both components of consumption risk are significantly priced when the limited stock market participation is taken into account. Neither the insurable and uninsurable components of consumption risk nor the Fama–French risk factors are rejected as capturing important components of systematic risk when tested against each other in an integrated multifactor asset pricing model.