Uncovering the time-varying relationship between commonality in liquidity and volatility

This study examines the dynamic linkages between commonality in liquidity in international stock markets and market volatility. Using a recently proposed liquidity measure as input in a variance decomposition exercise, we show that innovations to liquidity in most markets are induced predominately by inter-market innovations. We also find that commonality in liquidity peaks immediately after large market downturns, coinciding with periods of crisis. The results from a dynamic Granger causality test indicate that the relationship between commonality in liquidity and market volatility is bi-directional and time-varying. We show that while volatility Granger-causes commonality in liquidity throughout the entire sample period, market volatility is enhanced by commonality in liquidity only in sub-periods. Our results are helpful for practitioners and policy makers.     

Reprint of: Market liquidity in the financial crisis: The role of liquidity commonality and flight-to-quality

We examine the dynamics and the drivers of market liquidity during the financial crisis, using a unique volume-weighted spread measure. According to the literature we find that market liquidity is impaired when stock markets decline, implying a positive relation between market and liquidity risk. Moreover, this relationship is the stronger the deeper one digs into the order book. Even more interestingly, this paper sheds further light on so far puzzling features of market liquidity: liquidity commonality and flight-to-quality. We show that liquidity commonality varies over time, increases during market downturns, peaks at major crisis events and becomes weaker the deeper we look into the limit order book. Consistent with recent theoretical models that argue for a spiral effect between the financial sector’s funding liquidity and an asset’s market liquidity, we find that funding liquidity tightness induces an increase in liquidity commonality which then leads to market-wide liquidity dry-ups. Therefore our findings corroborate the view that market liquidity can be a driving force for financial contagion. Finally, we show that there is a positive relationship between credit risk and liquidity risk, i.e., there is a spread between liquidity costs of high and low credit quality stocks, and that in times of increased market uncertainty the impact of credit risk on liquidity risk intensifies. This corroborates the existence of a flight-to-quality or flight-to-liquidity phenomenon also on the stock markets.     

Market liquidity in the financial crisis: The role of liquidity commonality and flight-to-quality

We examine the dynamics and the drivers of market liquidity during the financial crisis, using a unique volume-weighted spread measure. According to the literature we find that market liquidity is impaired when stock markets decline, implying a positive relation between market and liquidity risk. Moreover, this relationship is the stronger the deeper one digs into the order book. Even more interestingly, this paper sheds further light on so far puzzling features of market liquidity: liquidity commonality and flight-to-quality. We show that liquidity commonality varies over time, increases during market downturns, peaks at major crisis events and becomes weaker the deeper we look into the limit order book. Consistent with recent theoretical models that argue for a spiral effect between the financial sector’s funding liquidity and an asset’s market liquidity, we find that funding liquidity tightness induces an increase in liquidity commonality which then leads to market-wide liquidity dry-ups. Therefore our findings corroborate the view that market liquidity can be a driving force for financial contagion. Finally, we show that there is a positive relationship between credit risk and liquidity risk, i.e., there is a spread between liquidity costs of high and low credit quality stocks, and that in times of increased market uncertainty the impact of credit risk on liquidity risk intensifies. This corroborates the existence of a flight-to-quality or flight-to-liquidity phenomenon also on the stock markets.     

LIQUIDITY COMMONALITY BEYOND BEST PRICES

Previous market microstructure research focuses on commonality in liquidity at the inside spread. However, liquidity at the inside spread only determines the systematic liquidity risk of small and medium trades. We study commonality in displayed liquidity beyond best prices, which determines the systematic liquidity risk of large trades. We show that it is much larger than commonality at the inside spread. The deeper we look into the order book, the higher is the level of commonality. In addition, it rises in the morning and when markets fall.     

Stock Market Declines and Liquidity

Consistent with recent theoretical models where binding capital constraints lead to sudden liquidity dry-ups, we find that negative market returns decrease stock liquidity, especially during times of tightness in the funding market. The asymmetric effect of changes in aggregate asset values on liquidity and commonality in liquidity cannot be fully explained by changes in demand for liquidity or volatility effects. We document interindustry spillover effects in liquidity, which are likely to arise from capital constraints in the market making sector. We also find economically significant returns to supplying liquidity following periods of large drops in market valuations.     

The Cross-Section of Volatility and Expected Returns

We examine the pricing of aggregate volatility risk in the cross‐section of stock returns. Consistent with theory, we find that stocks with high sensitivities to innovations in aggregate volatility have low average returns. Stocks with high idiosyncratic volatility relative to the Fama and French (1993, Journal of Financial Economics 25, 2349) model have abysmally low average returns. This phenomenon cannot be explained by exposure to aggregate volatility risk. Size, book‐to‐market, momentum, and liquidity effects cannot account for either the low average returns earned by stocks with high exposure to systematic volatility risk or for the low average returns of stocks with high idiosyncratic volatility.     

Do Proprietary Algorithmic Traders Withdraw Liquidity during Market Stress?

We investigate the role of proprietary algorithmic traders in facilitating liquidity in a limit order market. Using order‐level data from the National Stock Exchange of India, we find that proprietary algorithmic traders increase limit order supply following periods of both high short‐term stock‐specific volatility and extreme stock price movement. Even following periods of high marketwide volatility, they do not decrease their supply of liquidity. We define orders from high‐frequency traders as a subclass of orders from proprietary algorithmic traders that are revised in less than three milliseconds. The behavior of high‐frequency trading mimics the behavior of its parent class. This is inconsistent with the theory that fast traders leave the market when stress situations arise, although their limit‐order‐supplying behavior becomes weaker when the increase in short‐term volatility is more informational than transitory. Agency algorithmic traders and nonalgorithmic traders behave opposite to proprietary algorithmic traders by reducing the supply of liquidity during stress situations. The presence of faster traders in the market possibly instills the fear of adverse selection in them. We document that the order imbalance of agency algorithmic traders is positively related to future short‐term returns, whereas the order imbalance of proprietary algorithmic traders is negatively related to future short‐term returns.     

Limit order books and trade informativeness

In the microstructure literature, information asymmetry is an important determinant of market liquidity. The classic setting is that uninformed dedicated liquidity suppliers charge price concessions when incoming market orders are likely to be informationally motivated. In limit order book (LOB) markets, however, this relationship is less clear, as market participants can switch roles, and freely choose to immediately demand or patiently supply liquidity by submitting either market or limit orders. We study the importance of information asymmetry in LOBs based on a recent sample of 30 German Deutscher Aktienindex (DAX) stocks. We find that Hasbrouck's (1991) measure of trade informativeness Granger causes book liquidity, in particular that required to fill large market orders. Picking-off risk due to public news-induced volatility is more important for top-of-the book liquidity supply. In our multivariate analysis, we control for volatility, trading volume, trading intensity and order imbalance to isolate the effect of trade informativeness on book liquidity.     

Stock Liquidity Risk and the Cross‐sectional Earnings‐Returns Relationship

We argue that a higher sensitivity to aggregate market‐wide liquidity shocks (i.e., a higher liquidity risk) implies a tendency for a stock's price to converge to fundamentals. We test this intuition within the framework of the earnings‐returns relationship. We find a positive liquidity risk effect on the relationship between return and expected change in earnings. This effect on the earnings‐returns relationship is distinct from the negative effect observed for stock illiquidity level. Notably, the liquidity risk effect is evident (absent) during periods of neutral/low (high) aggregate market liquidity. We also show that the liquidity risk effect is dominant in firms that: (a) are of intermediate size; (b) are of intermediate book‐to‐market; and (c) are profit making.     

COMMONALITY IN LIQUIDITY OF NEARBY FIRMS

In this article, we examine commonality in liquidity of firms headquartered in the same states and how the local liquidity commonality is influenced by firm‐ and state‐level characteristics. We document strong liquidity comovement of nearby firms. Moreover, firms that change headquarters location experience a decrease in their liquidity commonality with firms in the old states and an increase in their liquidity commonality with firms in the new states. Our findings show that both firm‐ and state‐level characteristics determine local liquidity comovement. Local liquidity commonality is stronger for firms with smaller size and lower level of institutional ownership. Our results also suggest that state‐level volatility, state personal income, state investment income, and state turnover commonality explain the local component of liquidity commonality. We further document that the four state‐level factors perform differently during volatile market periods.     

Option market liquidity: Commonality and other characteristics

This study examines option market liquidity using Ivy DB's OptionMetrics data. We establish convincing evidence of commonality for various liquidity measures based on the bid–ask spread, volumes, and price impact. The commonality remains strong even after controlling for the underlying stock market's liquidity and other liquidity determinants such as volatility. Smaller firms and firms with a higher volatility exhibit stronger commonalities in option liquidity. Aside from commonality, we also uncover several other important properties of the option market's liquidity. First, information asymmetry plays a much more dominant role than inventory risk as a fundamental driving force of liquidity. Second, the market-wide option liquidity is closely linked to the underlying stock market's movements. Specifically, the options liquidity responds asymmetrically to upward and downward market movements, with calls reacting more in up markets and puts reacting more in down markets.     

Liquidity distribution in the limit order book on the stock exchange of Thailand

The liquidity distribution, or the shape of the limit order book, influences trading behavior and choice of order submission by public liquidity suppliers. The present study seeks to discover whether liquidity providers are concerned about being picked off by informed traders, and whether they are less willing to supply liquidity at the market or demand higher price spreads. The results show that liquidity at the market is a small portion of total liquidity, and that firm size, minimum tick size, volatility, and trading volume play significant roles in determining the liquidity distribution within an order book.     

Competition for Order Flow and Smart Order Routing Systems

We study the rivalry between Euronext and the London Stock Exchange (LSE) in the Dutch stock market to test hypotheses about the effect of market fragmentation. As predicted by our theory, the consolidated limit order book is deeper after entry of the LSE. Moreover, cross‐sectionally, we find that a higher trade‐through rate in the entrant market coincides with less liquidity supply in this market. These findings imply that (i) fragmentation of order flow can enhance liquidity supply and (ii) protecting limit orders against trade‐throughs is important.     

Liquidity supply in electronic markets

We examine the supply of liquidity by proprietary trading desks and hedge funds (PTDH) versus mutual funds, index funds, and insurance companies (MII) across ten bid (ask) steps of the limit order book. We document that institutional investors simultaneously supply liquidity at multiple prices in the limit order book. We also find that PTDHs are more price aggressive liquidity suppliers than MIIs, consistent with hypothesized responses to observed changes in the cost and risk of non-execution. We investigate whether these findings are robust to fast versus slow markets, the volatility of daily returns, and aggregate depth relative to daily volume.     

Liquidity determination in an order-driven market

We exploit full order level information from an electronic FX broking system to provide a comprehensive account of the determination of its liquidity. We not only look at bid-ask spreads and trading volumes, but also study the determination of order entry rates and depth measures derived from the entire limit order book. We find strong predictability in the arrival of liquidity supply/demand events. Further, in times of low (high) liquidity, liquidity supply (demand) events are more common. In times of high trading activity and volatility, the ratio of limit to market order arrivals is high but order book spreads and depth deteriorate. These results are consistent with market order traders having better information than limit order traders.     

How is illiquidity priced in the Chinese stock market?

This study investigates the liquidity premium in the Chinese stock market. We found that the expected stock returns increase monotonically with the quintile sort on characteristic liquidity with descending patterns. The characteristic liquidity premium ranges from 0.82% to 1.28% per month, which is much higher than that of their US counterparts. Moreover, our multivariate decomposition approach highlights that characteristic illiquidity premiums can be explained mainly by size, idiosyncratic volatility and momentum. The net systematic liquidity premium reaches 0.84% per month, driven mainly by commonality beta. The finding shows that a liquidity-based strategy forecasts cross-section and time-series expected returns.     

Stock liquidity and the Taylor rule

This paper examines how stock market liquidity and commonality in liquidity are impacted by real-time output gap and inflation, as these macroeconomic variables have been shown to be the main drivers of monetary policy according to the Taylor rule. We show that an increase in the output gap and inflation lowers stock liquidity and increases commonality in liquidity, since it points to a contractionary monetary policy and is likely to lead to a decline in the liquidity providers' funding liquidity. This effect is larger for stocks with low market capitalization and low liquidity.     

Commonality in Liquidity: Evidence from an Order-Driven Market Structure

Events such as the 1997 East Asian financial crisis indicate that individual firm liquidity is strongly influenced by marketwide factors. Previous market microstructure research, however, focuses almost exclusively on the firm‐specific attributes of liquidity. Our study follows the recent shift in emphasis toward commonality by examining systematic liquidity in an order‐driven market structure. Using data from the Stock Exchange of Hong Kong, we show that commonality in liquidity includes both market and industry components, and is pervasive across size‐sorted portfolios. We also find a significant market and industry component in individual firms' order flow. In contrast to quote‐driven results, we do not find a positive relation between firm size and sensitivity to changes in marketwide bid‐ask spreads.     

Stock Market Liquidity and the Business Cycle

In the recent financial crisis we saw liquidity in the stock market drying up as a precursor to the crisis in the real economy. We show that such effects are not new; in fact, we find a strong relation between stock market liquidity and the business cycle. We also show that investors' portfolio compositions change with the business cycle and that investor participation is related to market liquidity. This suggests that systematic liquidity variation is related to a “flight to quality” during economic downturns. Overall, our results provide a new explanation for the observed commonality in liquidity.     

Do uninformed crossed and internalized trades tap into unexpressed liquidity? The case of Nokia

Crossed and internalized upstairs trades are analysed in a dataset in which institutional investors can be identified. Earlier findings that upstairs trading is uninformed, taps into unexpressed liquidity, and does not affect market quality are revisited. The permanent price effect of crossings and internalized upstairs trades is significantly lower than that of limit order book trades due to the fact that the least informed institutional trades are routed upstairs. Crossed and internalized trades affect the depth and transaction costs in the limit order book and a greater reliance is placed on the upstairs market when liquidity is low and volatility is high.