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Purpose: The purpose of this study is to determine stock market reactions to the news about innovations and other types of publications for illiquid stocks. Design/methodology/approach: (1) The authors opt for machine learning techniques and expert analysis and propose their own lexicon of innovations based on the news articles published on the professional website; (2) the dataset consists of the data on 2,000 US companies for 6 years; (3) the text analysis including BERT and Top2 Vec models which are superior to Latent Dirichlet allocation (LDA) in information criteria allows for more accurate evaluation of news sentiment and idea; and (4) furthermore, random forest and gradient boosting were applied to increase validity of results and demonstrate factor importance. Findings: (1) The paper presents theoretical findings adding to signalling theory and efficient market hypothesis for US illiquid stocks; (2) this study suggests that information on product innovations (unlike other types of innovations) has a direct and significant effect on the return of illiquid stocks; (3) the results also give evidence that under uncertainty innovation-related publications do not affect the return of illiquid stocks; and (4) the analysis of the news topics (narratives) demonstrates that only the narrative related to important corporate announcements has a positive impact on the return of illiquid stocks. Originality/value: (1) The authors are the first to conduct a large-scale study of the impact of various information on the return of illiquid stocks; (2) the paper focuses on information on several types of innovations with regard to the return of illiquid stocks; (3) based on Top2 Vec model, this study identifies the key topics-narratives discussed by investors and assesses their impact on the return of illiquid stocks; and (4) as an information source, the authors use the sample comprising a total of 1.4m news articles released on the professional website for investors "Benzinga". [ABSTRACT FROM AUTHOR]

This study aims to explore the impact of systematic liquidity risk on the averaged cross-sectional equity return of the Indian equity market. It also examines the effects of illiquidity and decomposed illiquidity on the conditional volatility of the equity market. The present study employs the Liquidity Adjusted Capital Asset Pricing Model (LCAPM) for pricing systematic liquidity risk using the Fama & MacBeth cross-sectional regression model in the Indian stock market from January 1, 2012, to March 31, 2021. Further, the study employed an exponential generalized autoregressive conditional heteroscedastic (1,1) model to observe the impact of decomposed illiquidity on the equity market’s conditional volatility. The study also uses the Ordinary Least Square (OLS) model to illuminate the return-volatility-liquidity relationship. The study’s findings indicate that the commonality between individual security liquidity and aggregate liquidity is positive, and the covariance of individual security liquidity and the market return negatively affects the expected return. The study’s outcome specifies that illiquidity time series analysis exhibits the asymmetric effect of directional change in return on illiquidity. Further, the study indicates a significant impact of illiquidity and decomposed illiquidity on conditional volatility. This suggests an asymmetric effect of illiquidity shocks on conditional volatility in the Indian stock market. This study is one of the few studies that used the World Uncertainty Index (WUI) to measure liquidity and market risks as specified in the LCAPM. Further, the findings of the reverse impact of illiquidity and decomposed higher and lower illiquidity on conditional volatility confirm the presence of price informativeness and its immediate effects on illiquidity in the Indian stock market. The study strengthens earlier studies and offers new insights into stock market liquidity to clarify the association between liquidity and stock return for effective policy and strategy formulation that can benefit investors.

We identify a comprehensive list of thirty-eight characteristics for predicting cross-sectional FX options returns. We find that three factors—long-term straddle momentum, implied volatility, and illiquidity—can generate economically and statistically significant risk premia not explained by other return predictors. Meanwhile, the predictability of the other characteristics becomes insignificant after accounting for the FX option three-factor model. The significance of the three factors is confirmed through a series of robustness tests covering different data sources, alternative options strategies, diversification effects, bootstrapping, and omitting crisis years. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In the early 2000s, the market for private-label residential mortgage-backed securities was built upon a pyramid of risk, and at the foundation of this pyramid were hedge funds. Few post-mortems recognise the critical role played by these institutional investors. This paper uncovers this essential piece of the puzzle and demonstrates that it is a natural outgrowth of the inherent operational freedom that defines hedge funds. It breaks these foundational risks down into two components—illiquidity risk and tail risk—and proposes solutions to prevent them from spilling over into systemic crises without eliminating the benefits that society reaps from this unique risk-taking. It concludes with important lessons for securitisation markets to consider during and after the COVID-19 recession. [ABSTRACT FROM AUTHOR]

We consider an optimal investment problem to maximize expected utility of the terminal wealth, in an illiquid market with search frictions and transaction costs. In the market model, an investor's attempt of transaction is successful only at arrival times of a Poisson process, and the investor pays proportional transaction costs when the transaction is successful. We characterize the no-trade region describing the optimal trading strategy. Our asymptotic analysis implies that the effects of the transaction costs are more pronounced (more widening effect of the no-trade region and more diminishing effect of the value function) in the market with less search frictions. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the impact of liquidity on the return dynamics between the carbon emission trading market and the stock market in China from 2013 to 2021. In the carbon emission trading market, we find that liquidity on any given day can significantly predict the cross-section returns the next day. Furthermore, we examine the spillover effect between the two markets and find the carbon market has a greater impact on the stock market. We also find evidence that stock market liquidity can significantly improve the liquidity of the carbon market. Finally, we observe that the volatility in the stock market not only deteriorates the liquidity of the stock market but also the carbon market, where the impact for the latter is from decreasing trading volume and increasing prices. [ABSTRACT FROM AUTHOR]

In most financial markets, prices for long-maturity derivatives are not readily available due to illiquidity. This reality is particularly common in bond markets, as it is very challenging to model prices consistently???for medium-to-long-term bonds under a single specification of the underlying interest rate process. We develop a bond market state-space model that incorporates uncertainty in the underlying interest rate process parameters. Our state-space representation, coupled with the complementary Kalman filtering, provides a modeling configuration that permits for liquidity risk management and pricing that is designed in a consistent fashion for both medium- and long-term bonds. As an example, we constructed a state-space bond market modeling system formulated on the two-factor Vasicek interest rate model. Wherein, the interest rate model is subject to noise for medium-to-long-term bond maturities and follows an unobservable process. We demonstrate our Kalman filter algorithm using the observed United States (US) 10 year bond yield data. [ABSTRACT FROM AUTHOR]

This paper presents a rational expectation equilibrium model to explore how the financial contagion occurs between the unlinked markets that do not share common fundamentals. In the proposed model, the authors assume two of the three risky assets share no common fundamental factors, but are connected by one intermediate asset via cross fundamentals. Through this channel, investors transmit fundamental risk from one asset to another by dint of the cross fundamentals. This mechanism causes liquidity comovement and subsequently becomes a source of market crisis: Through the contagion mechanism, an initial liquidity shock in one asset can result in a drop tendency in liquidity and price informativeness for another asset. Such comovement in liquidity offers a new explanation for idiosyncratic assets in financial contagion. [ABSTRACT FROM AUTHOR]

According to recent research, liquidity of major financial markets across the globe have been different over time. Unpredictability of liquidity in these markets is a crucial source of risk for investors. Such liquidity shock in financial markets affect macroeconomics. In this research, the analysis of relationship between illiquidity shocks in financial markets and macroeconomics dynamics in Iran with a self-regression vector with variable coefficients over time (TVP-VAR) approach. The research findings have been yielded by using seasonal time series data during the period 2008:4-2020:3, where the findings suggest that growth's reaction in studied periods to illiquidity shocks has been negative and decreasing. Moreover, illiquidity shocks have increasing effects on inflation while liquidity growth impact on these shocks have been relatively increasing during the period. Eventually, the impact of security market's illiquidity shock on unemployment rate increased at the beginning of the period while it was decreasing at the end of the period. [ABSTRACT FROM AUTHOR]

Conservatism in the CAPM and L-CAPM standards often emphasizes systematic risk to explain the phenomenon of the risk-return relationship and ignores idiosyncratic risk with the assumption that the risk can be diversified. The effect of the Covid-19 outbreak raises the question of whether the idiosyncratic risk can still be ignored considering that the risk has a close relationship to firm-specific risk. This study sets a portfolio consisting of 177 active public firms in the Indonesia Stock Exchange before and after the Covid-19 pandemic. On portfolio set, idiosyncratic risk is estimated by the standard CAPM and L-CAPM in the observation range from January 2, 2019, to June 30, 2021. The results of the analysis show that L-CAPM and CAPM produce significantly different idiosyncratic risks. Empirical evidence shows that the highest firm-specific risk is in the third period and has a stable condition since the fourth period. This condition is confirmed by regression results that idiosyncratic risk together with systematic risk positively affects stock returns in the fourth period as suggested by the efficient market hypothesis. Uniquely, both systematic risk and idiosyncratic risk based on L-CAPM do not show a significant effect on stock returns in the fifth period, so it is a strong indication that liquidity is an important factor that must be considered in making investments.

Underlying idiosyncratic and illiquidity risks are suppressed in infrequently reported indexes of house prices and rents. Idiosyncratic risks result from bid–ask spreads for prices and rents. Time series autocovariances generate a distribution of prices and rents. Capital gains and rent-price ratios are transforms of these distributions, generating cross-sectional idiosyncratic volatility. Housing data are infrequent and usually made available every month. The monthly–quarterly volatility ratios of house prices and rents and their spreads estimate unobserved daily fluctuations and illiquidity risks. Including idiosyncratic and illiquidity risks, a U.S. house has a standard deviation in returns of 8.7% annually for three decades after 1990. With a mean excess return of 3.7%, the Sharpe ratio of 0.42 is comparable to the S&P 500. Excluding spreads, the house Sharpe ratio is 0.69. House returns respond to liquidity. A 1% increase in volume raises returns by 0.8%. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the effects of information asymmetry and illiquidity related to cluster trading on market efficiency and examine the mediating roles of these two variables in the relationship between noise trading and market efficiency. To measure the information asymmetry, Adj PIN and illiquidity related to cluster trading obtained from PSOS models were used. Also, market return based on trade volume imbalances was utilized as the indicator of market efficiency. The sample include 146 companies, which were listed in Tehran Stock Exchange between 2014 and 2020. The results showed significant inverse effects of information asymmetry and illiquidity related to cluster trading and market return. However, the effect of illiquidity related to cluster trading on market return was stronger than that of information asymmetry. In addition, the findings showed that noise trading had direct and significant effects on information asymmetry and illiquidity related to cluster trading. Thus, the relationship between noisy trading and market return through information asymmetry and illiquidity relevant to cluster trading, as well as the mediating roles of these two variables, was confirmed.IntroductionBased on the previous research, liquidity is one of the fundamental factors affecting market efficiency and proper pricing of the capital assets (Wei, 2018; Ibikunle et al., 2016; Han, Tang, & Yang, 2016; Liu et al., 2019). On the other hand, one of the characteristics of an ideal efficient market is the lack of trading cost consequently leading to high liquidity. Stock liquidity can be suggested as an indicator for market return. It is broadly incorporated into the investigation of the effective factors presenting positive information (Rahmani, Hosseini, & Rezapour, 2019). Information asymmetry affects market value of the companies listed in the stock market (Muslim, 2021 & Setiawan). It can lead to wrong financial decision-makings of the management and reductions of the shareholders` wealth (Aflatooni, 2020). Information asymmetry concerning adverse selection occurs when one party of the deal enjoys more valuable information than the other party over the dealing process and this leads to an increase in trading cost (Hu & Prigent, 2017). Another important impact of information asymmetry on the market is the orientation of market performance toward disruption and inefficiency because the asymmetric information can affect market price fluctuations and the assets prices. Information asymmetry can reduce efficiency and prevent market formation in extreme cases, which make the two parties to the transaction lose in the end (Miskin, 2015). In the modern financial world, a great deal of trades is done unknowingly by disruptive traders, who enjoy a limited trading strategy based on rumors and other people's mere advice. These disruptive traders are called noisy traders whose major feature is the lack of adequate information in the transaction, i.e., their buying and selling are independent from the inherent value of the traded property (Han, Tang, & Yang, 2016; Peress & Schmidt, 2021). Nonetheless, we cannot say whether a trader has enjoyed his/her access to information in a particular trade only based on the empiric and routine levels of information about trades. In this circumstance, from the type of information, researchers usually speculate whether the trades have been based on information or not (Chung et al., 2013). Noises have always existed in financial markets. These noises, which are based on daily fluctuations in the stock price, are caused by factors like the spread of news or information, mass behavior, and/or fundamental parameters. Based on one important assumption of behavioral theory, trades of these noisy traders are not independent from each other and have a systematic correlation. Therefore, we cannot neglect their roles in and impacts on financial markets and construe them as the trivial part of the process of investing in those markets (Saranj et al, 2018). Information asymmetry is related to price clustering and cluster trades. In an efficient ideal market, price clustering and cluster trades are at their minimum possible levels. By cluster trades, we mean noisy traders’ tendency to do trades when there is no real and good quality information. With the increase of noisy trades in a time period, even knowable traders tend to trade more, while this gives noisy traders more incentive to do more trades, which in turn, leads to an increase in trade cost and a decrease in market efficiency (Duarte & Young, 2009). The findings of a study showed that due to the existence of noisy traders and spread of confidential information, knowable traders trade in a particular period after the spread of information and reduce their trades after its gradual effect on prices. This leads to the reduction of liquidity (market illiquidity) (Foster & Viswanathan, 1990). Therefore, it is expected that stocks go higher with information asymmetry, while the higher levels of cluster trades lead to less efficiency of the market (Hu & Prigent, 2019). Market efficiency is affected by several stock features, such as the market value, price volatility, trading volume, institutional trade, and trading cost. It is also influenced by trading cost due to information asymmetry and illiquidity due to cluster and noisy trades. Since no research has been done to investigate the impacts of information asymmetry and illiquidity concerning cluster trades on market returns in Iran Stock Exchange, this essay aimed to determine if the impacts of information asymmetry and illiquidity concerning cluster trades on the returns of companies listed in TSE market were based on a model that could show the degree of market efficiency and intended to answer these questions: do information asymmetry and illiquidity concerning cluster and noisy trades affect the market? Is the meditating role of illiquidity concerning cluster trades in the relationship between noisy trades and market returns confirmed in Iran stock exchange market? Method and DataTo test the research hypotheses, 146 companies among those listed In Tehran Stock Exchange during the years of 2014-2020 were examined. To this goal, a multivariate regression model and pooled data were utilized. FindingsThe results displayed the significant inverse effects of information asymmetry and illiquidity related to cluster trading and market returns. The effect of illiquidity related to cluster trading was stronger than that of information asymmetry. In addition, the findings revealed that noise trading had direct and significant impacts on information asymmetry and illiquidity related to cluster trading. Thus, the relationship between noisy trading and market return through information asymmetry and illiquidity relevant to cluster trading and the mediating roles of these two variables were corroborated. Conclusion and discussion The results demonstrated that noisy trades reduced market efficiency by enhancing the trading and illiquidity costs due to information asymmetry and cluster trades, respectively. Information asymmetry and illiquidity affected market efficiency as independent variables, which gave us some evidence on the information motivation model. When new information enters the market, trades increase due to the initial advantage and motivation of using information as long as it is integrated into the stock price. However, the impact of information on the prices in the period of no new good-quality information (increase of noisy investigators’ trades due to concerns about liquidity) leads to enhancement of trading costs concerning illiquidity, which in turn, results in the reduction of market efficiency. Therefore, the supervising institution must pay attention to such factors as the accounting quality and information disclosure of the companies listed in TSE, as well as promotion of their supervising mechanisms in general. They should also take steps to making some policies for the growth and development of financial institutions active in the capital market like investment consulting firms, investment funds and companies, portfolio management, and financial information processing companies. In addition, the investors should pay attention to the management team qualities of companies responsible for preparing financial statements, company size, disclosure level, and growth opportunities as the factors affecting information asymmetry.

Using a panel of indices for five developed market and five emerging markets for the period from 31 December 2019 to 19 June 2020, the relationship between stock market liquidity and COVID-19 pandemic is examined. The study is the first to interrogate nexus using three measures of liquidity, the percentage spread, market depth and Amihud’s (2002) ILLIQ measure. The pandemic is a global health condition with financial market implications, the results indicate that, stock market liquidity improved as we found a negative and significant relationship between illiquidity and COVID-19 across all the liquidity measures in all markets. However, improvements in stock market liquidity were more prevalent in developed markets relative to emerging markets. The results show that volatility negatively affected liquidity when illiquidity was measured by spread. Future research should focus on the impact of quantitative easing on stock markets liquidity during market turmoil.

In this study, we analyze illiquidity premia and their effect on the expected returns of German real estate securities. To this end, we use a unique data set that includes real estate stocks, real estate investment trusts (REITs), and open- and closed-end real estate funds for 2003–2017. We follow Amihud's (JFM 5:31–56, 2002) structural approach; specifically, we estimate Amihud's illiquidity factors, investigate the relationships between expected returns and illiquidity, and analyze the effects of expected and unexpected market illiquidity on future returns. We show that illiquidity plays an important role in expected returns for real estate stocks and investment trusts (REITs); however, it has less clear effects on open- and closed-end funds. We find that the adjusted ILLIQ includes appropriate correction factors for securities with low trading activity and is a useful improvement. We also find evidence of structural breaks in the relationship between returns and illiquidity. [ABSTRACT FROM AUTHOR]

This article examines variations in illiquidity in the Indian stock market, using intraday data. Panel regression reveals prevalent day-of-the-week, month, and holiday effects in illiquidity across industries, especially during exogenous shock periods. Illiquidity fluctuations are higher during the second and third quarters. The ranking of most illiquid stocks varies, depending on whether illiquidity is measured using an adjusted or unadjusted Amihud measure. Using pooled quantile regression, we note that illiquidity plays an important asymmetric role in explaining stock returns under up- and down-market conditions in the presence of open interest and volatility. The impact of illiquidity is more severe during periods of extreme high and low returns. JEL Classification: G10, G12 [ABSTRACT FROM AUTHOR]

Stock‐level liquidity shocks have a positive cross‐sectional relation to not only contemporaneous returns but also one‐month‐ahead returns in the Korean stock market, which implies that the stock market underreacts to liquidity shocks. However, the return continuation after the arrival of liquidity shocks is short‐lived and disappears in two months in Korea, unlike in the United States. The positive relation between liquidity shocks and one‐month‐ahead returns is most pronounced for illiquid stocks but not present for liquid stocks, independently of the level of investor attention. However, the effect of limited attention on the positive relation differs somewhat across alternative attention proxies and becomes insignificant after controlling for liquidity. This evidence suggests that the short‐lived underreaction to liquidity shocks in the Korean stock market is primarily driven not by inattention but by illiquidity. [ABSTRACT FROM AUTHOR]

As a result of technological innovations in data processing, the exploitation of Internet usage data in relation to search engines or social networks is becoming increasingly intriguing for understanding and anticipating stock market movements. We analyze the impact of three alternative investor attention variables, i. e. Google search volume, Wikipedia page views, and stock market-relevant news on the rapidly growing FinTech sector. The result of the simultaneous correlation analysis reveals a highly significant correlation between the trading activities of the FinTech sector and the three investor attention variables. The time-delayed regression analysis complements the results by identifying substantial changes of the effects within one week considering the order of magnitude and sign. Furthermore, multivariate regression analysis highlights that the explanatory power for future stock trading activities and illiquidity primarily depends on Google search volume and stock market-relevant news volume, while the simultaneous correlations are best explained by the number of visits to the corresponding Wikipedia page. [ABSTRACT FROM AUTHOR]

The objective of this study to determine the relationship between illiquidity and stock returns of industry sector companies listed at the Amman Exchange stock. The research design was descriptive using Illiquidity ratio, the study was undertaken to ascertain the nature of this relationship at the ASE for a5 year period 2013-2018. The data was obtained from the Amman Stock Exchange in a daily format, which was then converted to a monthly format to fit with the research design, the Sample comprised from stocks that were continuously traded during this period. The Illiquid test shows there is effect of illiquidity in the returns of the shares of companies listed on the Amman Stock Exchange at the level of the industry sector. [ABSTRACT FROM AUTHOR]

One failure of the Black-Scholes valuation model is to assume that the trading activities of agents have no effect on prices, an assumption that it can only be fulfilled in perfectly liquid markets, making the model very restrictive. This element has already been considered in some studies that incorporate the effect of agents' trading activities assuming a continuous process for price dynamics, however, financial markets show that a better description of the price dynamics of Risky assets must incorporate random jumps. The contribution of this document is to consider the problem of the valuation of derivatives in illiquid markets where the price of the underlying asset follows a diffusion process with jumps. The corresponding non-linear partial differential equation of valuation is presented and the trading strategy that minimizes the variance of the hedge is described. [ABSTRACT FROM AUTHOR]

The Covid-19 crisis is unique in several respects. This devastating recession does not have an economic origin, will dance largely to the tune of non-economic factors, and is truly global. The policy response has been equally unique, in terms of speed, size and scope, eliciting an unprecedented concerted effort combining monetary, fiscal and prudential policies. This has contained the fallout. At the time of writing, financial markets have rebounded to the point of looking exuberant, but it all feels more like a truce than a peace treaty. The crisis is transitioning from the liquidity to the solvency phase in a context of limited and shrinking room for policy manoeuvre. All this raises difficult near- and longer-term challenges. Rebuilding policy buffers in all policy areas is likely to be the policy challenge of the decade ahead. [ABSTRACT FROM AUTHOR]

International Financial Reporting Standard (IFRS) is globally accepted as a high-quality reporting standard. Countries implement IFRS because they believe that more disclosure leads to agency costs reduction and may result in adverse selection costs or information asymmetry reduction. However, studies on the relationship between IFRS and information asymmetry have thus far provided mixed evidence. On the other side, there are limited studies in this area that are focused on ASEAN countries. Therefore, more studies are needed to better understand whether IFRS drives information asymmetry reduction especially in ASEAN countries as developing countries. Therefore, this study contributes to knowledge by examining the association between IFRS and information asymmetry within ASEAN-6 countries, as a setting for developing countries. The results of the OLS (Static Panel estimation technique) indicate that IFRS has a negative and significant relationship with information asymmetry. It reveals that IFRS results in information asymmetry reduction throughout ASEAN-6 countries. Besides using the OLS, this study also applies a Generalized Moment Method (GMM) as an additional test, to measure dynamic relationships and correct the potential endogeneity problem between IFRS and information asymmetry. Besides theoretical and methodological contributions, findings of this study are useful for the adopter and non-adopter countries to understand the consequences of IFRS compliance on information asymmetry. The findings provide important inputs to policymakers of Indonesia and Vietnam who are contemplating adopting IFRS. [ABSTRACT FROM AUTHOR]

We introduce a new model for pricing corporate bonds, which is a modification of the classical model of Merton. In this new model, we drop the liquidity assumption of the firm's asset value process, and assume that there is a liquidly tradeable asset in the market whose value is correlated with the firm's asset value, and all portfolios can be constructed using solely this asset and the money market account. We formulate the market price of the corporate bond as the product of the price of an optimal replicating portfolio and exp ⁡ (− κ × replication error) , where κ is a non-negative constant. The interpretation is that the representative investor uses the price of the optimal replicating portfolio as a benchmark and requests compensation for the non-hedgeable risk. We show that if the replication error is measured relative to the firm's value, the resulting formula is arbitrage free with mild restrictions on the parameters. [ABSTRACT FROM AUTHOR]

Historical crisis events have highlighted the insufficiency of Value-at-Risk (VaR) as a measure of market risk because such metric does not take liquidity into account. Unlike previous studies analyzing with only a single asset, we examine the impact of liquidity on computing VaR forecasts from a portfolio level. To this end, we use multivariate GARCH-t and GJR-GARCH-t models, as compared with univariate models, to seize the liquidity property embedded in individual stock returns and evaluate their accuracy and efficiency in computing VaR forecasts for portfolios with different liquidity levels. The empirical results indicate that computing portfolio VaR forecasts with multivariate models outperform the univariate models for full and subsample periods in terms of accuracy and efficiency evaluations, in particular for less-liquid portfolios. These results suggest the importance of liquidity in computing portfolio VaR forecasts. Ignorance of the impact of liquidity in computing portfolio VaR forecasts might result in inadequate coverage and insufficient market risk capital requirements. [ABSTRACT FROM AUTHOR]

We analyze the martingale selection problem of Rokhlin in a pointwise (robust) setting. We derive conditions for solvability of this problem and show how it is related to the classical no‐arbitrage deliberations. We obtain versions of the Fundamental Theorem of Asset Pricing in models spanning frictionless markets, models with proportional transaction costs, and models for illiquid markets. In all these models, we also incorporate trading constraints. [ABSTRACT FROM AUTHOR]

This paper shows that liquidity conditions are important determinants of the predictability of earnings. Liquid stock prices are more informative about future firm earnings growth than illiquid stock prices. Because information-related illiquidity can arise when uncertainty is high, we focus our analysis on evidence that noninformational liquidity affects price informativeness. Endogeneity is further addressed using controls for market uncertainty and several exogenous shocks as natural experiments. Thus, our results lend support for the impact of liquidity on price discovery. This paper was accepted by Lauren Cohen, finance. [ABSTRACT FROM AUTHOR]

This study examined the role of positive and negative discretionary accrual management in the stock price impact. A sample of 66 firms listed in Tehran Stock Exchange was selected for a ten-year period (2008-2017). Accrual management was found to lead to significant changes in stock prices, and uninformed investors incur trading costs caused by the stock price impact. The results showed two key points. First, the mispricing of discretionary accrual components in the market leads to an increase in the stock price impact, and second, the management of positive discretionary accruals has a greater effect on stock price impacts than negative discretionary accruals. Using positive discretionary accruals, investors overvalue the firm and engage in trading stocks. Due to the mispricing of positive discretionary accruals, an asymmetric behavior is formed in the stock price impact. [ABSTRACT FROM AUTHOR]

Abstract Background We investigate whether the success of contrarian investment strategies can be attributed to differences in the relative illiquidity of stocks categorized as value investments versus those categorized as glamour portfolios. Methods Following Lakonishok et al. (J Financ 49:1541–1578, 1994), we assess the illiquidity characteristics of portfolios that underlie contrarian investment strategies that are based on the level of stock’s book to market. Results We find strong evidence that those portfolios characterized as value investments are associated with dramatically greater levels of illiquidity than glamour portfolios. We further demonstrate that strategies based on the illiquidity in the year prior to portfolio formation result in return characteristic of ostensibly contrarian strategies. Conclusions These results suggest that the higher returns associated with contrarian investment strategies are the result of the higher illiquidity associated with value portfolios and represent compensation that the investor receives for accepting illiquidity. They also suggest that researchers should be cautious before attributing apparent anomalies to behavior-driven expectational errors rather than to other attributes unrelated to behavior, such as illiquidity.

This article examines the impact of various sources of systematic liquidity risk and idiosyncratic liquidity risk on expected returns in the Indian stock market. The study tested the liquidity-adjusted capital asset pricing model (LCAPM) which is previously tested on developed markets. Systematic liquidity risk is found to be significant in impacting asset returns through various channels, viz. commonality in liquidity and illiquidity sensitivity to market returns. Covariance between individual stock returns and associated stock liquidity has a commanding influence as an idiosyncratic liquidity risk factor. The estimated asset pricing model is found to be robust across the two sub-time periods. The findings indicate that given the multidimensional nature of risk, the alternative of LCAPM along with the idiosyncratic risk is persuasive for consideration in investment decisions.

This paper aims to evaluate the relationship between capital and liquidity creation following the implementation of the Basel III rules. These regulatory measures target both increased capital ratios and a reduction of banks' maturity transformation risk, which could result in excessive constraints on bank liquidity creation, thereby negatively affecting economic growth. Using a simultaneous equation model, we find a bi-causal negative relationship, which suggests that banks may reduce liquidity creation as capital increases; and when liquidity creation increases, banks reduce capital ratios. Our results therefore imply a trade-off between financial stability (higher capital, reduced risk) and economic growth (liquidity creation). [ABSTRACT FROM AUTHOR]

We develop a model of illiquidity transmission from spot to futures markets that formalizes the derivative hedge theory of Cho and Engle (1999). The model shows that spot market illiquidity does not translate one to one to the futures market but, rather, interacts with price risk, liquidity risk, and the risk aversion of the market maker. The model's predictions are tested empirically with data from the stock market and markets for single‐stock futures and index futures. The results support our model and show that the derivative hedge theory provides an explanation for the liquidity link between spot and futures markets. [ABSTRACT FROM AUTHOR]

• We investigate direction and strength of relationships between liquidity and volatility. • Most liquid stocks from the Warsaw Stock Exchange listed in 2006–16 are studied. • We apply tests of Toda-Yamamoto (1995), Hatemi (2012) and Diebold-Yilmaz (2009). • High-low range (liquidity proxy) Granger causes volatility most often. • We find that volatility-liquidity causality is bidirectional; liquidity more often Granger causes volatility than volatility causes liquidity. We study dependencies between liquidity and volatility in the causality framework for stocks listed on the Warsaw Stock Exchange. Using Toda-Yamamoto and Granger causality tests we find bidirectional causality between the measures. The causal liquidity-volatility relation is more often observed than volatility-liquidity one, and both relations are frequently asymmetric. The directional spillover index suggests, that the fraction of forecast error variance due to the shock in other measure is much smaller than the response to own shocks. The choice of proxies matters: among different alternatives we find that high-low range is most often Granger cause for volatility. [ABSTRACT FROM AUTHOR]

We document the prevalence of illiquidity premium in the international equity markets, across 45 markets over the period from 1990 to 2015. The global average illiquidity premium is economically significant at 0.85% per month and it is 1.05% for the Asia- Pacific markets, after adjusting for exposure to global and regional return factors. We also find that investors demand a premium for stock illiquidity, after controlling for various firm characteristics that predict the cross-section of stock returns. [ABSTRACT FROM AUTHOR]

Abstract This paper first investigates the heterogeneous impact of liquidity on volatility by using the intraday data of the Chinese stock index futures market. Based on the quantile regression method, we obtain several noteworthy findings. First, in sample result shows that illiquidity can significantly increase volatility at the right tail, which seems to be a notable J-shaped relationship between the illiquidity and volatility in Chinese stock index futures market. Second, the effects of the illiquidity on past negative returns ("bad news") are much stronger than on past positive returns ("good news"). Third, by documenting the intraday pattern of the illiquidity, the highest impact of the illiquidity on volatility occurs in the last half-hour rather than in the first half-hour of each trading day. Highlights • First investigates the heterogeneous impact of liquidity on the volatility using the intraday data of the China. • In sample result shows that illiquidity can significantly increase volatility at the right tail. • The effects of the illiquidity on past negative returns are much stronger than on that by past positive returns. • The highest impact of the illiquidity on volatility occurs in the last half-hour. [ABSTRACT FROM AUTHOR]

This article examines the impact of various sources of systematic liquidity risk and idiosyncratic liquidity risk on expected returns in the Indian stock market. The study tested the liquidity-adjusted capital asset pricing model (LCAPM) which is previously tested on developed markets. Systematic liquidity risk is found to be significant in impacting asset returns through various channels, viz. commonality in liquidity and illiquidity sensitivity to market returns. Covariance between individual stock returns and associated stock liquidity has a commanding influence as an idiosyncratic liquidity risk factor. The estimated asset pricing model is found to be robust across the two sub-time periods. The findings indicate that given the multidimensional nature of risk, the alternative of LCAPM along with the idiosyncratic risk is persuasive for consideration in investment decisions. [ABSTRACT FROM AUTHOR]