Liquidity Proxies Research Articles

A Market-Based Funding Liquidity Measure

In this paper, we construct a traded funding liquidity measure from stock returns. Using a stylized model, we show that the expected return of a beta-neutral portfolio, which exploits investors' borrowing constraints (Black (1972)), depends on both the market-wide funding liquidity and stocks' margin requirements. We extract the funding liquidity shock as the return spread between two beta-neutral portfolios constructed using stocks with high and low margin. Our return-based measure is correlated with other funding liquidity proxies derived from various markets. It delivers a positive risk premium, which cannot be explained by existing risk factors. Positive correlation also exists between the funding liquidity measure and market liquidity measures. Using our measure, we find that while hedge funds in general are inversely affected by funding liquidity shocks, some funds exhibit funding liquidity management skill and thus earn higher returns.

Noise as Information for Illiquidity

ABSTRACTWe propose a market‐wide liquidity measure by exploiting the connection between the amount of arbitrage capital in the market and observed “noise” in U.S. Treasury bonds—the shortage of arbitrage capital allows yields to deviate more freely from the curve, resulting in more noise in prices. Our noise measure captures episodes of liquidity crises of different origins across the financial market, providing information beyond existing liquidity proxies. Moreover, as a priced risk factor, it helps to explain cross‐sectional returns on hedge funds and currency carry trades, both known to be sensitive to the general liquidity conditions of the market.

Economic valuation of liquidity timing

This paper conducts a horse-race of different liquidity proxies using dynamic asset allocation strategies to evaluate the short-horizon predictive ability of liquidity on monthly stock returns. We assess the economic value of the out-of-sample power of empirical models based on different liquidity measures and find three key results: liquidity timing leads to tangible economic gains; a risk-averse investor will pay a high performance fee to switch from a dynamic portfolio strategy based on various liquidity measures to one that conditions on the Zeros measure (Lesmond et al., 1999); the Zeros measure outperforms other liquidity measures because of its robustness in extreme market conditions. These findings are stable over time and robust to controlling for existing market return predictors or considering risk-adjusted returns.

Liquidity effects in corporate bond spreads

Corporate bond spreads are affected by both credit risk and liquidity and it is difficult to disentangle the two factors empirically. In this paper we separate out the credit risk component by examining bonds that are issued by the same firm and that trade on the same day, allowing us to examine the effects of liquidity in a sample of bond pairs. We examine standard liquidity measures to determine how well they explain the differences in the two bonds’ yield spreads and find that the proxies do a poor job of measuring liquidity effects. Incorporating liquidity proxies related to other bonds issued by the firm and those for bonds of other firms can significantly improve the explanatory power. Still, a significant portion of the spread is left unexplained and it is largely driven by a common unknown factor. We conclude that good proxies for the liquidity component of corporate bond spreads remain elusive.

Low-dimensional Characterisation of Liquidity of Individual Stocks in the Indian Market

There is no single, definitive and universally accepted measure of a stock’s ‘liquidity’. The literature proposes a large number of proxy measures for liquidity. Suitable low dimensional characterisation of liquidity may improve understanding and enable better market regulation. We present factor analyses of stock-specific liquidity measures, using cross-sectional data from the National Stock Exchange of India, for two time periods reflecting different market conditions. Day-wise analyses of eleven liquidity proxies suggest five factors, interpretable as spread, depth, volume, price elasticity and relative activity. Consistency in the results obtained from the two periods suggests that the factor structure is stable. JEL Classification: G11, C38

Liquidity in asset pricing: New Australian evidence using low-frequency data

Employing a new proxy for liquidity, this paper examines its impact on stock returns in the context of the Fama-French framework. We augment the Carhart four-factor model with a liquidity factor in our asset pricing tests. Using an extensive dataset drawn from the Australian equities market, we find that liquidity explains a portion of the common variation in stock returns even after controlling for size, book-to-market and momentum. However, our findings suggest that the liquidity factor only adds marginal explanatory power to contemporary asset pricing models.

Pricing of Liquidity Risks: Evidence from Multiple Liquidity Measures

We investigate the pricing implication of liquidity risks in the liquidity-adjusted capital asset pricing model of Acharya and Pedersen (2005), using multiple liquidity measures and their principal component. While we find that the empirical results are sensitive to the liquidity measure used in the test, we find strong evidence of pricing of liquidity risks when we estimate liquidity risks based on the first principal component across eight measures of liquidity, both in the cross-sectional and factor-model regressions. Our finding implies that the systematic component measured by each liquidity proxy is correlated across measures and the shocks to the systematic and common component of liquidity are an undiversifiable source of risk.

Commonality in Liquidity and its Determinants: An Empirical Examination of Stocks Listed on National Stock Exchange of India

A stock’s liquidity and its variability over time are of major concern for all the stakeholders of capital markets. Literature shows that market participants prefer liquid stocks and a stock’s exposure to liquidity commonality is inversely proportional to market returns. Although the burgeoning literature on liquidity commonality shows that stocks have significant commonality, the major sources that cause it are yet unknown. Some studies have shown evidence for the supply-side determinants of liquidity commonality driven by funding constraints faced by market participants and some studies show evidence for the demand-side sources of liquidity commonality related to the correlated trading activity, level of institutional ownership. In this paper, we study the evolution of liquidity commonality over time by using quarterly data from 2001-2009 for NSE listed stocks and then determine the supply-side and demand-side sources of systematic liquidity. We construct Amihud’s liquidity measure using daily data as a proxy for liquidity and estimate liquidity commonality of each stock on a quarterly basis from the market model time series regression of Chordia, Roll, and Subrahmanyam (2000). We find significant evidence of liquidity commonality for the sample period and also size effects in liquidity commonality. We find that supply-side sources of liquidity commonality significantly explain liquidity commonality, whereas, the demand-side sources are not significant in explaining liquidity commonality.

An Examination of Macroeconomic Effects on the Liquidity of REITs

In this research, we investigate the effects of changes in and levels of selected macroeconomic variables on the liquidity of Real Estate Investment Trust (REIT, henceforth) stocks. We study in particular REIT market trading liquidity and REIT funding liquidity. We use debt service coverage ratios, loan-to-value ratios and the number of loans on commercial commitments as proxies for the funding liquidity of REITs. We use Amihud Illiquidity measurement and Turnover Ratio measurement to estimate REIT market trading liquidity. Our results are fourfold: one, funding liquidity is influenced by changes in macroeconomic factors; two, macroeconomic effects are different across phases of the business cycle; three, funding liquidity is significantly positively related to REIT market liquidity (this is supportive of Brunnermeier and Petersen’s Review of Financial Studies, 22:2201–2238 (2009) findings); and four, these effects vary across economic regimes. A key outcome of this work is that increases in debt to equity reduce market liquidity for REIT stocks.

Motivated sellers and predation in the housing market

We develop an equilibrium search model of the housing market where sellers may become distressed as they are unable to sell. A unique steady state equilibrium exists where distressed sellers attempt liquidation sales by accepting prices that are substantially below fundamental values. During periods where a large number of sellers are forced to liquidate customers exhibit ‘predation’: they hold off purchasing and strategically slow down the speed of trade, which in turn causes more sellers to become distressed. The model naturally suggests several proxies of liquidity. Interestingly, the average time on the market (TOM), one of the most frequently used statistics in the literature, does a poor job within the context of liquidation sales and predation. Specifically we show that TOM falls during periods of predatory buying, which, if interpreted on face value, indicates that the market becomes more liquid with predation. We propose an alternative proxy – the profit loss in fire sales – which appears to be a more robust measure of liquidity than TOM.

Corporate Governance and Liquidity: Pre- and Post-Crisis Analysis from the MENA Region

This paper examines the impact of corporate governance mechanisms on liquidity in the MENA region, i.e. Morocco, Egypt, Saudi Arabia, United Arab Emirates, Jordan, Kuwait, and Bahrain. Using turnover as a proxy for liquidity, we document significant difference in liquidity between the pre- and the post-crisis periods in the MENA region. In addition, our results show that bulk of this reduction in turnover can be explained due to weaknesses of corporate governance mechanisms. For example, that dividend payout ratio and choice of auditors – proxies for agency problems – can explain the entire difference in liquidity between the two periods. Furthermore, our results indicate that more than 50% of this difference between the two periods can be explained by operational and informational complexity of a firm – proxy for transparency. We argue that poor corporate governance mechanisms increase information asymmetries between insiders and outsiders. Outsiders, being liquidity providers, therefore do not trade in stocks for which they have no information. Therefore, firms with poor governance mechanisms usually experience higher decline in liquidity during periods of market-wide uncertainty.

Funding Liquidity, Market Liquidity and TED Spread: A Two-Regime Model

We investigate the effect of market liquidity on equity-collateralized funding accounting for endogeneity. Theory suggests market liquidity can affect funding liquidity in stabilizing and destabilizing manners. Using the average fee on stock loans as a proxy for equity-collateralized funding liquidity, we confirm the existence of these two regimes over the period of July 2006-May 2011. Furthermore, we show that we can separate the two regimes using the yield spread of Eurodollars over T-bills (TED spread) and that a regime switch seems to occur near a TED spread of 48 basis points.

On downside risk predictability through liquidity and trading activity: A dynamic quantile approach

Abstract Most downside risk models implicitly assume that returns are a sufficient statistic with which to forecast the daily conditional distribution of a portfolio. In this paper, we analyze whether the variables that proxy for market-wide liquidity and trading conditions convey valid information for forecasting the quantiles of the conditional distribution of several representative market portfolios, including volume- and value-weighted market portfolios, and several Book-to-Market- and Size-sorted portfolios. Using dynamic quantile regression techniques, we report evidence of conditional tail predictability in terms of these variables. A comprehensive backtesting analysis shows that this link can be exploited in dynamic quantile modelling, in order to considerably improve the performances of day-ahead Value at Risk forecasts.

Composite Liquidity: Characteristics and Risk

Liquidity is a multidimensional concept with most liquidity measures proxying for only one of the many facets. Using nine low-frequency liquidity proxies, this study calculates composite liquidity measures by extracting the commonality across liquidity dimensions. As a stock characteristic, composite liquidity is priced cross-sectionally and most individual measures are not priced in addition. While five-factor models that include the liquidity factors from Pastor and Stambaugh (2003) or Sadka (2006) are insufficient to explain the returns of composite liquidity sorted portfolios, a liquidity risk factor constructed as factor mimicking portfolio describes the distribution of composite liquidity sorted returns well. Between characteristics and risk, however, it is the characteristics that bear a stronger relation to returns rather than liquidity factor loadings.

Exchange Traded Funds, Liquidity, and Market Volatility

We propose a simple model of trading based on the Kyle (1985) framework for securities that are included in Exchange Traded Funds (ETFs). The model postulates that trading in ETFs will increase volatility in their component stocks, and that volatility spillovers will be increasing in liquidity and the relative proportion of each stock held by the fund. An empirical analysis of trading in the S&P 500 SPDR and three heavily traded industry ETFs confirms these hypotheses, using both Amihud’s (2002) measure of illiquidity as well as stock turnover as proxies for liquidity. The results are consistent with a positive volume-volatility relation as well as tradingbased explanations of volatility. The findings are relevant to market practitioners, regulators and investors in these increasingly popular products, since ETFs may in fact contribute to volatility in their underlying component stocks, and thus to the stock market in general.

Hedge Fund Liquidity and Performance: Evidence from the Financial Crisis

In this paper, we investigate how share restrictions affect hedge fund performance in crisis and non-crisis periods. Consistent with prior research, we find that more illiquid funds produce both higher returns and alphas in the pre-crisis period. Hence, funds generate a share illiquidity premium for investors as a compensation for limited liquidity. In contrast, in the crisis period, this share illiquidity premium turns into an illiquidity discount. Hedge funds with more stringent share restrictions invest more heavily in illiquid assets. While share restrictions enable funds to manage these illiquid assets effectively in the pre-crisis period, they do not seem to be sufficient to ensure effective management of illiquid portfolios in a crisis. In a crisis period, funds holding illiquid portfolios experience lower returns and alphas, also when share restrictions are controlled for. Funds with an asset-liability mismatch, i.e., funds holding illiquid asset portfolios combined with weak share restrictions, perform particularly poorly and experience the strongest outflows in a crisis. However, share restrictions are not only a proxy for asset portfolio liquidity but also for incentives. Funds with stronger share restrictions and greater managerial discretion have fewer incentives to perform better because investors cannot immediately withdraw their money after poor performance. We show that hedge funds with stricter share restrictions and higher incentive fees do not experience a share illiquidity discount in the crisis period.

Liquidity Risk and Stock Returns: A Return Decomposition Approach

We study the effect of innovations in liquidity on stock-return volatility under the return-decomposition framework. Using revisions to equity analyst consensus forecasts to measure cash-flow news directly, we contend that both cash-flow news and expected return news correlate with liquidity shocks, and the cash-flow news component is a nontrivial channel through which liquidity correlates with stock returns. Specifically, we find a positive (decrease) liquidity shock for firms that have positive (negative) cash-flow news and expected-return news. Furthermore, since the correlation between liquidity proxies and stock returns also arise from the association of liquidity proxies with the three stock return components, the R^2 from a regression of returns on liquidity proxies may understate or overstate the importance of liquidity as a source of stock-return variance. Finally, liquidity proxies tend to explain stock returns better during negative market liquidity shocks, but this additional explanatory power comes mostly from the increased correlation between liquidity proxies and cash-flow news, while the correlation between liquidity proxies and unexplained stock return variations does not change with market liquidity conditions.

Futures Trading and Spot Market Volatility: Evidence from Indian Commodity Markets

In the context of emerging Indian commodity futures markets, this paper empirically examines the effect of futures trading activity (trading volume ; proxy of futures liquidity) on spot price volatility for seven agricultural commodities (guar seeds, turmeric, soya bean, black pepper, barley, Maize and Castor Seed).We decompose the futures volume into expected and unexpected components using Hodrick–Prescott filter (HP filter) .To clearly understand the destabilization effect, the relationship of the unexpected liquidity of futures market is done with Unexpected volatility of spot market returns which is estimated by taking the residuals of the GARCH model. We find that unexpected futures trading volume is Granger causing spot price volatility and are significant for five out of seven agricultural commodities (Guarseed, Turmeric, Soybean, Maize and Castor Seed), consistent with Bessembinder and Seguin (1992).We find reversed effect for one commodity i.e. Pepper the effect of spot volatility on futures trading and for Barley no causality is revealed either from future to spot or Vice-Versa. Besides being of interest to the participants, this study is likely to be useful in addressing the concerns of policy makers in India on alleged destabilizing effect of futures markets on spot prices as for emerging futures markets. Commodity exchanges must be strengthen and put under strict and active monitoring for early detection of anomalous trading behaviour. Financial autonomy and adequate powers should be given to Forward Market Commission to penalise any insider trading and price manipulations, this will minimize price distortions. The Government support shall lead to market growth and overall economic development.

A comprehensive look at financial volatility prediction by economic variables

SUMMARYWe investigate whether return volatility is predictable by macroeconomic and financial variables to shed light on the economic drivers of financial volatility. Our approach is distinct owing to its comprehensiveness: First, we employ a data‐rich forecast methodology to handle a large set of potential predictors in a Bayesian model‐averaging approach and, second, we take a look at multiple asset classes (equities, foreign exchange, bonds and commodities) over long time spans. We find that proxies for credit risk and funding liquidity consistently show up as common predictors of volatility across asset classes. Variables capturing time‐varying risk premia also perform well as predictors of volatility. While forecasts by macro‐finance augmented models also achieve forecasting gains out‐of‐sample relative to autoregressive benchmarks, the performance varies across asset classes and over time. Copyright © 2012 John Wiley & Sons, Ltd.

Liquidity dynamics across public and private markets

In this paper we investigate cross-asset liquidity between equity markets and REITs and between REITs and private real estate markets. While many studies have investigated REIT liquidity, and there is an emerging interest in liquidity in the private real estate markets, there appears to be little knowledge of the dynamics of cross-market liquidity. We find lower levels of liquidity for REITs compared to a set of control firms matched on size and book-to-market ratios. Commonality in liquidity is also lower for REITs than the controls and the overall market. However, we do find an important difference in share turnover for REITs, which appears to have a higher level of commonality than found in other studies. We suggest that this may be due to the financial crisis. Additionally we find evidence of similar time-series variation in liquidity for public and private real estate markets. We also find significant directional causality for most liquidity proxies from the public to private real estate markets. Finally our results show that there is strong contemporaneous correlation between both public and private real estate market liquidity and the term spread and real investment and consumption spending. REIT liquidity measures based on intraday data also appear to contain important information not found in measures constructed from daily returns.