Illiquidity Measure Research Articles

Industry peers stock liquidity and M&A

AbstractThis study examines the impact of mergers and acquisitions on the liquidity of shares of industry peers of the target firm. The results document, on average, an improvement in the liquidity of industry peer firms' shares: bid‐ask spreads of industry peers decline, the Amihud illiquidity measure declines, and their trading volumes increase around the merger announcement relative to a control sample. Industry peers of the target firm experience significant cumulative abnormal returns (CARs) that are increasing with the improvement in liquidity of the firms' shares. Our findings are consistent with the notion that the publicity and attention around the announcement of an acquisition involving a close industry peer results in benefits arising from increased liquidity of shares and offers a possible explanation for the positive CARs experienced by industry peers of the target firm around merger announcements.

Funding Illiquidity Implied by S&P 500 Derivatives

Based on the typical positions of S&P 500 option market makers, we derive a funding illiquidity measure from quoted prices of S&P 500 derivatives. Our measure significantly affects the returns of leveraged managed portfolios; hedge funds with negative exposure to changes in funding illiquidity earn high returns in normal times and low returns in crisis periods when funding liquidity deteriorates. The results are not driven by existing measures of funding illiquidity, market illiquidity, and proxies for tail risk. Our funding illiquidity measure also affects leveraged closed-end mutual funds and, to an extent, asset classes where leveraged investors are marginal investors.

An extension analysis of Amihud's illiquidity premium: Evidence from the Taiwan stock market

This study proposes a novel illiquidity measure that excludes overnight returns and incorporates the recency effect, and investigates whether this new metric more effectively captures the illiquidity premium in the Taiwan stock market relative to Amihud's (2002) measure and other illiquidity measures that exclude overnight returns or account for the recency effect. Cross-sectional and time-series asset pricing tests reveal that our measure dominates other illiquidity measures, yielding a more profitable long–short strategy. Vector autoregressive analysis confirms these results for the aggregate market. Our study contributes to the measurement of liquidity in emerging markets and suggests potential improvements for portfolio management and asset pricing models.

Relationships among return and liquidity of cryptocurrencies

The cryptocurrency market is a complex and rapidly evolving financial landscape in which understanding the inter- and intra-asset dependencies among key financial variables, such as return and liquidity, is crucial. In this study, we analyze daily return and liquidity data for six major cryptocurrencies, namely Bitcoin, Ethereum, Ripple, Binance Coin, Litecoin, and Dogecoin, spanning the period from June 3, 2020, to November 30, 2022. Liquidity is estimated using three low-frequency proxies: the Amihud ratio and the Abdi and Ranaldo (AR) and Corwin and Schultz (CS) estimators. To account for autoregressive and persistent effects, we apply the autoregressive integrated moving average-generalized autoregressive conditional heteroscedasticity (ARIMA-GARCH) model and subsequently utilize the copula method to examine the interdependent relationships between the return on and liquidity of the six cryptocurrencies. Our analysis reveals strong cross-asset lower-tail dependence in return and significant cross-asset upper-tail dependence in illiquidity measures, with more pronounced dependence observed in specific cryptocurrency pairs, primarily involving Bitcoin, Ethereum, and Litecoin. We also observe that returns tend to be higher when liquidity is lower in the cryptocurrency market. Our findings have significant implications for portfolio diversification, asset allocation, risk management, and trading strategy development for investors and traders, as well as regulatory policy-making for regulators. This study contributes to a deeper understanding of the cryptocurrency marketplace and can help inform investment decision making and regulatory policies in this emerging financial domain.

Is illiquidity priced in an international factor pricing model? A dynamic panel data application with robust IV

AbstractIn the setting of a dynamic panel data framework, we investigate the international five‐factor Fama–French (2017) model augmented with traditional illiquidity factors (Amihud, Journal of Financial Markets, 2002, 5, 31–56; Amihud, Critical Finance Review, 2019, 8, 203–221; Pástor and Stambaugh, Journal of Political Economy, 2003, 111, 642–685; Pástor and Stambaugh, Critical Finance Review, 2019, 8, 277–299) to determine if any of these factors are priced. Since illiquidity measures are endogenous, we propose an algorithm that generates robust instruments which are combined with a GMM estimator to cope with both the endogeneity issues surrounding illiquidity and other eventual specification errors. In this dynamic framework, we generally find that the most significant factors correspond to market and size but illiquidity may matter depending on the level of the beta. We find that illiquidity has more impact on returns in expansion than in recession. However, the bid‐ask spread seems to behave differently from the other illiquidity measures.

Arbitrage asymmetry, mispricing and the illiquidity premium

AbstractIlliquid assets require a return premium; illiquidity is also a limit‐to‐arbitrage. We find that Amihud's illiquidity premium is significantly higher among underpriced stocks than among overpriced stocks. Excluding the most mispriced stocks leads to a higher and more reliably estimated illiquidity premium. Amihud's illiquidity measure is positively correlated with overpricing, consistent with arbitrage asymmetry, while inconsistent with Lou and Shu's contention that the return premium associated with the Amihud measure reflects mispricing rather than compensation for illiquidity. Our results demonstrate that it is important to account for their role as limits‐to‐arbitrage when evaluating the pricing of illiquidity measures.

Dynamic Autoregressive Liquidity (DArLiQ)

We introduce a new class of semiparametric dynamic autoregressive models for the Amihud illiquidity measure, which captures both the long-run trend in the illiquidity series with a nonparametric component and the short-run dynamics with an autoregressive component. We develop a generalized method of moments (GMM) estimator based on conditional moment restrictions and an efficient semiparametric maximum likelihood (ML) estimator based on an iid assumption. We derive large sample properties for our estimators. Finally, we demonstrate the model fitting performance and its empirical relevance on an application. We investigate how the different components of the illiquidity process obtained from our model relate to the stock market risk premium using data on the S&P 500 stock market index.

Illiquidity and the cost of equity capital: Evidence from actual estimates of capital cost for U.S. data

AbstractIlliquidity measures appear to be related to monthly realized returns but do they impact long‐run costs of capital (CoC) for firms? Using U.S. data, we find cross‐sectional evidence that, controlling for market capitalization, the Amihud (2002, Journal of Financial Markets, 5, 31) measure of illiquidity is negatively related to CoC estimates. A difference‐in‐differences analysis around exogenous brokerage closures reveals that Amihud illiquidity increases without an impact on CoC. Nonetheless, other illiquidity measures, such as those based on serial covariances, zero returns, and price impact, do show a strong positive relation with CoC. However, we do not find evidence that liquidity risk and the probability of informed trade influence CoC. Overall, our results advance our understanding of precisely which illiquidity measures influence required firm returns.

The Liquidity Effect of the U.S. QE on Sovereign Yield Spreads of Commodity-Exporting Countries

This paper investigates the liquidity effect of the U.S. QE on the sovereign yield spreads of commodity-exporting countries by employing the two-stage least squares approach. The key contributions of the paper are in terms of our empirical findings. First, our results show that the U.S. QE has an economically and statistically significant liquidity effect in terms of both the HPW illiquidity measure and the TIPS liquidity premium. This is of policy importance because adjusting for the liquidity premium is a key stage in modeling inflationary expectations. Second, our results show that the U.S. QE reduced the liquidity premium with improved market liquidity and hence reduce sovereign yield spreads of most commodity-exporting countries. This finding is of macroeconomic importance as reduced sovereign yield spreads have been shown to lead to higher real activity and higher credit activity.

Estimating Risk in Illiquid Markets: A Model of Market Friction with Stochastic Volatility

Abstract This article deals with the problem of estimating the volatility of a financial security in a market with frictions. We propose a microstructural model with time-varying fundamental price volatility in which the trading price varies only if the value of the information signal is large enough to guarantee a profit in excess of transaction costs. Using transaction data only, the proposed approach allows to recover: (i) the conditional volatility of the information signal, which is thus cleaned out by market frictions and (ii) an estimate of transaction costs. Our analysis reveals that, after correcting for frictions, the risk of illiquid securities is substantially different from what is predicted by traditional volatility models. Furthermore, using a big dataset of intraday returns, we show that our transaction cost estimate is highly correlated with the main illiquidity measures and that such correlations are significant under different volatility regimes.

Эффекты неликвидности на российском рынке акций

This work examines the impact of expected and unexpected illiquidity of Russian stockstraded on the Moscow Exchange on their ex ante and simultaneous excess returns. Following quantitative predictions of the market microstructure invariance hypothesis, I calculate the ex­pected ruble costs of executing a bet in the Russian stock market. This estimate is used to compute the invariance-implied low-frequency illiquidity measure for individual stocks. The expec­ted market illiquidity is estimated by a first-order autoregressive model, and the surprise illiquidity is the residuals from this model. We use two weighting methods (equal-weighting and value-wei­ghting) to calculate market returns, market illiquidity, as well as returns on size-based portfolios. According to the empirical analysis over the period from January 2010 to December 2020, the market premium for expected illiquidity in the Russian equity market was insignificant in most specifications, unlike the effect of unexpected market illiquidity. The negative effect of market illiquidity shocks on market returns is insignificant only in the case of using equal-weighted procedure over the period from January 2010 to June 2015. The weak form of the hypothesis that illiquidity effects are stronger for small-cap stocks is confirmed only in the case of using equal-weighting method over the period from July 2015 to December 2020.

Which stock price component drives the Amihud illiquidity premium?

We examine the components of stock prices that play a key role in the pricing of the Amihud (2002) illiquidity measure. We first decompose the stock price series into permanent and transitory components and then construct the half-Amihud illiquidity measures on the days of positive and negative permanent price returns. We find that the transitory half-Amihud measure on the days of negative permanent price returns plays an important role in pricing the Amihud illiquidity even after controlling for the turnover ratio. This finding contrasts with that of Lou and Shu (2017) in that both the trading volume component and transitory price impact, drive the Amihud illiquidity premium.

Liquidity in the global currency market

We study the liquidity of the global currency market by analyzing the price impact of trading volume. We analyze a decade of CLS intraday data representative of global foreign exchange (FX) trading by developing a refinement of the popular Amihud (2002) illiquidity measure that we call realized Amihud, which is the ratio between realized volatility and trading volume. Inversely related to market depth, price impact increases with transaction costs, money market stress, uncertainty, and risk aversion. Furthermore, we analyze whether and how liquidity begets price efficiency by looking at violations of the “triangular” no-arbitrage condition. We find that dollar-based currencies offer a lower trading impact supporting price efficiency.

DOES ASYMMETRIC INFORMATION INFLUENCE FOREIGN DIRECT INVESTMENT?

The study investigates the link between asymmetric information through market micro-structures and Foreign Direct Investment (FDI) using daily stock prices of listed companies from ASEAN+3 countries. Asymmetric information in the stock market is measured using liquidity and illiquidity measures of Amivest and Amihud, respectively. The findings from static panel regression analysis reveal that Amivest has a positive relationship while Amihud has a negative relationship with FDI. This relationship infers that high stock liquidity reduces price movement, increases transparency, decreases asymmetric information and ultimately encourages FDI, Conjecture has an inverse asymmetric information-FDI relationship. The findings show the importance of policymakers and industry players in stimulating market transparency to welcome foreign investment in the economy.

Stock illiquidity and option returns

We provide evidence of a strong effect of the underlying stock's illiquidity on option returns. Conditional on end-user demand, illiquidity premiums are negative and decrease in stock illiquidity for options where end users are net buyers, while premiums are positive and tend to increase otherwise. Our results cannot be explained by common risk factors and cross-sectional differences in stock volatility or option spreads and are robust to different illiquidity measures and data periods. The observed pattern is consistent with an intermediary hedging cost channel and the magnitudes of our illiquidity premiums are in line with reasonable transaction costs.

The asymmetry of the Amihud illiquidity measure on the European markets: The evidence from Extreme Value Theory

This paper explores the extreme illiquidity for a sample of stocks listed on the European stock markets. The extreme value theory tools such as an extremal index as a measure of illiquidity dependence and a return level as a measure of illiquidity risk are applied. We obtain Amihud illiquidity separately for positive and negative returns and verify if there is an asymmetry in the extreme illiquidity. This study finds that the extreme illiquidity clusters more for negative returns than positive ones. Moreover, the clustering of extreme illiquidity is observed more often on the emerging markets than on the developed ones. For stocks listed on the emerging markets, the risk of extreme illiquidity is higher in the case of negative returns than of positive ones, while for stocks listed on developed markets no such phenomena is found. Our robustness check conducted with volatility over volume as an illiquidity measure confirms results obtained for the extremal indices, but not for the return level.

Investor attention in cryptocurrency markets

We examine the relationship between investor attention, and measures of uncertainty, with the market dynamics of Bitcoin and other cryptocurrencies. We find that increases in investor attention are associated with higher returns, more volatility, and greater illiquidity in cryptocurrency markets. In contrast, cryptocurrency uncertainty (UCRY) and financial market uncertainty (VIX) are also positively related to volatility and illiquidity but have a negative contemporaneous relationship with returns. The identified relationships are accentuated during the COVID-pandemic, and are robust to different measures of investor attention, volatility, and illiquidity. Our results suggest that monitoring investor attention could assist both investors and policymakers.

Illiquid Assets and the Opacity Discount in Banks’ Valuation

The paper investigates the impact of fair value accounting for illiquid assets (so-called ‘Level 2’ and ‘Level 3’ assets by accounting rules) on banks’ valuation and focuses on the change in relative weight of Level 3 (the most opaque and illiquid assets) with respect to Level 2 assets. The boundary between Level 3 and Level 2 assets is blurred and less clear than the one between Level 1 and Level 2 assets. Such unclear borderline entails corporate governance issues and provides room for opportunistic behavior by managers to opt for less transparent instruments. The paper proposes the change in Level 3-to-Level 2 assets ratio as a new measure to capture deviations in the opacity of bank assets and suggests a negative relationship between this ratio and bank’s price-to-book value. The rationale behind this relationship is that market participants interpret growth in Level 3-to-Level 2 assets ratio as an increase in bank’s opacity, since Level 3 assets might be as illiquid as Level 2 assets with the benefit of a less transparent model-based valuation technique. Based on a sample of 33 European banks from 2009 to 2018, I find that an increase of 100[Formula: see text]bps in Level 3-to-Level 2 assets ratio is linked to a decrease of about 74[Formula: see text]bps in the price-to-book value. Results are robust for different measures of firm relative valuation and using a different measure of illiquidity in fair value assets holdings (Level 2-to-Level 1 assets ratio).

Real estate illiquidity and returns: A time-varying regional perspective

This paper proposes two new measures of illiquidity for real estate markets, utilising concepts from asset pricing. Segregating real estate through a regional lens, we provide an in-depth analysis of real estate returns and illiquidity for the US and UK. Our results provide statistically significant and economically meaningful evidence that real estate illiquidity predicts real estate returns out-of-sample over and above a variety of control variables.

The nexus between bond liquidity, stock liquidity and foreign portfolio investment

The purpose of this article was to assess the impact of financial market liquidity on international capital flows in emerging markets. Specifically, the research investigates the effect of bond market liquidity and stock market liquidity on foreign portfolio investments using data for five emerging African countries, being Egypt, Kenya, Mauritius, Nigeria and South Africa, for the period 2000 to 2020. The data was sourced from the Bloomberg and World Bank (WDI) databases. Panel data analysis (fixed effects model) was undertaken using three different liquidity measures: the effective spread; Amihud’s (2002) illiquidity measure; and market impact as measured by trading volume. Our findings revealed mixed results. It was found that stock market liquidity attracted foreign portfolio investments. Although bond market liquidity, as measured by the volume of trade, promoted foreign portfolio investment, it was different for the effective spread, as the higher the effective spread, the higher the inward FPI flows, and vice versa. Results on the effects of the bond effective spread on FPI show that as long as the bonds are above the investable grade, investors are not discouraged by the cost of trading. Our findings thus confirm that FPI inflows are predisposed on liquid and efficient host country financial markets. Further, the entrance of foreign investors in the host country’s domestic financial markets, leads to the enhancing of liquidity in the local market, thus increasing risk sharing between local and foreign investors.