Liquidity and equity returns in Borsa Istanbul

We investigate the relationship between expected returns and liquidity measures in Borsa Istanbul. To do so, we gather a wide range of illiquidity measures that can be applied to the market. Firm-level cross-sectional regressions indicate that there is a positive relationship between various illiquidity measures and one- to six-month ahead stock returns. Findings of the article are robust after using different sample periods and controlling for well-known priced factors, such as market beta, size, book-to-market ratio and momentum. The portfolio analysis reveals that stocks that are in the highest illiquidity quintile earn 7.2%–19.2% higher risk-adjusted annual returns than those in the lowest illiquidity quintile. The illiquidity premium is stronger for small stocks and stocks with higher return volatility and it increases (decreases) during periods of extremely low (high) market returns.     

A novel measure of liquidity premium: application to the Korean stock market

This study proposes a novel measure for an asset’s liquidity premium. Applying Brownian first-passage time distribution properties, we derive an explicit form of liquidity premium embedded in the asset price. Our liquidity premium measure is intuitive because it assesses the extent to which the value of the asset should be increased from the current market price if investors were allowed to retain the asset until they achieve an investment goal. This measure is readily available for assessing an asset’s liquidity because it does not require information on the asset’s transactional characteristics. Our empirical experiment using Korean stock market data suggests that the liquidity premium in this study is inversely related to Amihud’s (2002) illiquidity ratio, which is commonly used to measure stocks’ illiquidity.     

ILLIQUIDITY COMPONENT OF CREDIT RISK – THE 2015 LAWRENCE R. KLEIN LECTURE

We provide a theoretical decomposition of bank credit risk into insolvency risk and illiquidity risk, defining illiquidity risk to be the counterfactual probability of failure due to a run when the bank would have survived in the absence of a run. We show that illiquidity risk is (i) decreasing in the “liquidity ratio”—the ratio of realizable cash on the balance sheet to short‐term liabilities; (ii) decreasing in the excess return of debt; and (iii) increasing in the solvency uncertainty—a measure of the variance of the asset portfolio.     

Conditional volatility and correlations of weekly returns and the VaR analysis of 2008 stock market crash

Modelling of conditional volatilities and correlations across asset returns is an integral part of portfolio decision making and risk management. Over the past three decades there has been a trend towards increased asset return correlations across markets, a trend which has been accentuated during the recent financial crisis. We shall examine the nature of asset return correlations using weekly returns on futures markets and investigate the extent to which multivariate volatility models proposed in the literature can be used to formally characterize and quantify market risk. In particular, we ask how adequate these models are for modelling market risk at times of financial crisis. In doing so we consider a multivariate t version of the Gaussian dynamic conditional correlation (DCC) model proposed by Engle (2002), and show that the t-DCC model passes the usual diagnostic tests based on probability integral transforms, but fails the value at risk (VaR) based diagnostics when applied to the post 2007 period that includes the recent financial crisis.     

Liquidity premia in dynamic bargaining markets

This paper develops a search-theoretic model of the cross-sectional distribution of asset returns, abstracting from risk premia and focusing exclusively on liquidity. In contrast with much of the transaction-cost literature, it is not assumed that different assets carry different exogenously specified trading costs. Instead, different expected returns, due to liquidity, are explained by the cross-sectional variation in tradeable shares. The qualitative predictions of the model are consistent with much of the empirical evidence.     

流动性、生命周期与投资组合相异性——中国投资者行为调查实证分析

本文采用Probit和Tobit模型对中国居民的股票市场参与和投资组合的影响因素进行了分析,主要有以下的实证发现:首先,不流动性资产特别是房地产的投资显著影响了投资者的股票市场参与和投资组合,而且影响以“替代”效应或者说“挤出”效应为主。其次,投资者在进行投资组合时极少利用股票市场对其未来现金流所承担的风险进行对冲,也就是说,中国居民投资的“生命周期效应”不明显;第三,中国居民投资的“财富效应”非常显著。财富的增加既增加了居民参与股票市场的概率,也增加了居民参与股票市场的深度。     

信用风险、信息与协调

金融机构的短期债券同时被大小两种债权人持有。信用风险由流动性不足风险和破产风险组成。我们建立了一个同时包含大小两种债权人的模型来研究大的债权人、短期债券比例与市场流动性如何影响信用风险。模型的结果显示:(1)提高大的债权人的信息准确度可以让小的债权人更愿意继续借贷,因此降低了流动性不足风险;(2)短期债券比例的提高会增加流动性不足风险,也就增加了总的信用风险;(3)市场流动性越强,流动性不足风险就越小。     

Portfolio choice with internal habit formation: a life-cycle model with uninsurable labor income risk

Motivated by the success of internal habit formation preferences in explaining asset pricing puzzles, we introduce these preferences in a life-cycle model of consumption and portfolio choice with liquidity constraints, undiversifiable labor income risk and stock-market participation costs. In contrast to the initial motivation, we find that the model is not able to simultaneously match two very important stylized facts: a low stock market participation rate, and moderate equity holdings for those households that do invest in stocks. Habit formation increases wealth accumulation because the intertemporal consumption smoothing motive is stronger. As a result, households start participating in the stock market very early in life, and invest their portfolios almost fully in stocks. Therefore, we conclude that, with respect to its ability to match the empirical evidence on asset allocation behavior, the internal habit formation model is dominated by its time-separable utility counterpart.     

Portfolio choice with high frequency data: CRRA preferences and the liquidity effect

This paper suggests a new approach for portfolio choice. In this framework, the investor, with CRRA preferences, has two objectives: the maximization of the expected utility and the minimization of the portfolio expected illiquidity. The CRRA utility is measured using the portfolio realized volatility, realized skewness and realized kurtosis, while the portfolio illiquidity is measured using the well-known Amihud illiquidity ratio. Therefore, the investor is able to make her choices directly in the expected utility/liquidity (EU/L) bi-dimensional space. We conduct an empirical analysis in a set of fourteen stocks of the CAC 40 stock market index, using high frequency data for the time span from January 1999 to December 2005 (seven years). The robustness of the proposed model is checked according to the out-of-sample performance of different EU/L portfolios relative to the minimum variance and equally weighted portfolios. For different risk aversion levels, the EU/L portfolios are quite competitive and in several cases consistently outperform those benchmarks, in terms of utility, liquidity and certainty equivalent.     

Liquidity-adjusted conditional capital asset pricing model

This paper derives a liquidity-adjusted conditional two-moment capital asset pricing model (CAPM) and a liquidity-adjusted conditional three-moment CAPM respectively based on theory of stochastic discount factor. The liquidity-adjusted conditional two-moment CAPM shows that a security's conditional expected excess return consists of three parts: its conditional expected liquidity cost, the systemic risk premium and the liquidity risk premium. The liquidity-adjusted conditional three-moment CAPM shows that a security's conditional expected excess return depends on its conditional expected liquidity cost, the conditional covariance between its return and the market return, the conditional covariance between its liquidity cost and the market liquidity cost, and the conditional coskewness of its return and the market return.     

Global idiosyncratic risk moments

We investigate a global cross-sectional relation between idiosyncratic risk moments and expected stock returns by suggesting three global idiosyncratic volatility, skewness, and kurtosis risk factors. We also suggest two global small minus big and high minus low risk proxies for estimating return residuals of the test assets from a global asset pricing model. To perform robustness checks, we suggest other four global risk factors of momentum, leverage, bid-ask spread, and liquidity. We find a significant negative relation between stock portfolio returns and the global moments, and the cross section of stock returns reflects a significant negative price of risk for global idiosyncratic skewness (?0.13%) and idiosyncratic volatility (?1.85%) and a positive and significant price of risk for global idiosyncratic kurtosis. We find that our suggested risk factors are key drivers of risk premia in stock market and are robust to various checks. These factors also can forecast the gross domestic product growth over the sample period.     

Monetary policy and asset prices

The purpose of this paper is study the effect of monetary policy on asset prices. We study the properties of a monetary model in which a real asset is valued for its rate of return and for its liquidity. We show that money is essential if and only if real assets are scarce, in the precise sense that their supply is not sufficient to satisfy the demand for liquidity. Our model generates a clear connection between asset prices and monetary policy. When money grows at a higher rate, inflation is higher and the return on money decreases. In equilibrium, no arbitrage amounts to equating the real return of both objects. Therefore, the price of the asset increases in order to lower its real return. This negative relationship between inflation and asset returns is in the spirit of research in finance initiated in the early 1980s.     

Investment horizon effect on asset allocation between value and growth strategies

How does the optimal risk exposure of assets change as their investment horizons increase? Does this impact investment portfolio decision-making, in particular, optimal asset allocation between value and growth strategies over various investment horizons? This paper adopts a new approach to address these questions by examining portfolio allocation between value and growth stocks over various investment horizons. This new approach is based on wavelet analysis, which decomposes the returns of a particular investment strategy across multiple investment horizons. The key empirical results show that the success of pursuing the value strategy (short-selling growth stocks and going long on value stocks) is impacted by the approach used to classify value and growth stock returns. We explore two common alternatives: Fama-French versus Standard & Poor's (S&P) 500/Barra portfolios. The results using Fama-French portfolios show that as the investment horizon increases, the optimal mean allocation of investors tilts heavily away from growth stocks, particularly for lower and moderate levels of risk aversion. Interestingly, for S&P 500/Barra portfolios the allocation weights between value and growth do not vary much.     

A multi-period portfolio selection optimization model by using interval analysis

Due to few historical data that can be obtained in an emerging securities market, the future returns, risk and liquidity of securities cannot be forecasted precisely. The investment environment is usually fuzzy and uncertain. To handle these imprecise data, this paper discusses a fuzzy multi-period portfolio optimization problem where the returns, risk, and liquidity of securities are represented by interval variables. By taking the return, risk, liquidity and diversification degree of portfolio into consideration, an interval multi-period portfolio selection optimization model is proposed with the objective of maximizing the terminal wealth under the constraints of the return, risk and diversification degree of portfolio at each period. In the proposed model, a proportion entropy is employed to measure the diversification degree of portfolio. Using the fuzzy decision-making theory and multi-objective programming approach, the proposed model is transformed into a crisp nonlinear programming. Then, we design an improved particle swarm optimization algorithm for solution. Finally, a numerical example is given to illustrate the application of our model and demonstrate the effectiveness of the designed algorithm.     

Is market liquidity less resilient after the financial crisis? Evidence for US Treasuries

Understanding market liquidity resilience, i.e. the capacity of liquidity to absorb shocks, of United States Treasuries is crucial from a financial stability standpoint. The conventional resilience measure has limitations due to the use of the liquidity level. We propose a new complementary approach to analyze resilience based on liquidity volatility. For this purpose, we focus on the link between returns volatility and liquidity volatility, which is a relatively unexplored field. We fit a bivariate conditional correlation (CC-) GARCH model for the 10-year bond returns and five liquidity indicators from January 2003 to June 2016 to analyze persistence and spillovers between these variables in a parsimonious way. We find that after the crisis, spillovers between liquidity volatility and returns volatility are higher, feedback loops are more likely and volatility persistence is lower, which is consistent with a lower resilience. Our results help to explain recent episodes of high volatility in this market.     

Integrated Risk Management with a Filtered Bootstrap Approach

We present a multi-period risk model to measure portfolio risk that integrates market risk, credit risk and, in a simplified way, liquidity risk. Thus, it overcomes the major limitation currently shared by many risk models that are unable to give a complete picture of all portfolio risks according to a single, coherent framework. The model is based on the Filtered Bootstrap approach; hence, it captures conditional heteroskedasticity, serial correlation and non-normality in the risk factors, that is, most of the features of observed financial time series. Being a simulation risk model, it copes in a natural way with derivatives as it allows the full valuation of the probability density function of the contracts. In addition, it is a suitable and flexible way to generate future scenarios on medium‐term horizons, so this model is particularly appropriate for asset management companies.     

Does illiquidity matter in residential properties?

No, it does not, despite the general perception that illiquidity matters in real estate. As expected, our evidence shows that the illiquidity costs for the U.S. residential properties are large. The costs are equivalent to 12% of the total property returns on average, ranging from 9.5% to 29.5% of property prices depending on the illiquidity level and market conditions. However, when amortized by holding periods, monthly illiquidity costs are on average 0.08%, and illiquidity risk does not appear to be priced in residential properties; illiquid properties do not show higher returns than liquid properties. On the contrary, we find evidence of flight-to-quality in bull markets, that is, high-quality illiquid properties are preferred to low-quality liquid properties in buoyant markets. These results are in sharp contrast with those in equities and bonds where flight-to-liquidity has been reported when markets are in stress.     

Markets liquidity risk under extremal dependence: Analysis with VaRs methods

Value-at-Risk (VaR) is a widely used tool for assessing financial market risk. In practice, the estimation of liquidity extreme risk by VaR generally uses models assuming independence of bid–ask spreads. However, bid–ask spreads tend to occur in clusters with time dependency, particularly during crisis period. Our paper attempts to fill this gap by studying the impact of negligence of dependency in liquidity extreme risk assessment of Tunisian stock market. The main methods which take into account returns dependency to assess market risk is Time series–Extreme Value Theory combination. Therefore we compare VaRs estimated under independency (Variance–Covariance Approach, Historical Simulation and the VaR adjusted to extreme values) relatively to the VaR when dependence is considered. The efficiency of those methods was tested and compared using the backtesting tests. The results confirm the adequacy of the recent extensions of liquidity risk in the VaR estimation. Therefore, we prove a performance improvement of VaR estimates under the assumption of dependency across a significant reduction of the estimation error, particularly with AR (1)-GARCH (1,1)-GPD model.     

Time-varying comovement and changes of comovement structure in the Chinese stock market: A causal network method

The driving force for the comovement in stock returns is a long-standing debate between classical asset pricing theory and behavioral finance theory. It has become critically important recently for understanding systemic risk and risk contagion in the market. In this study, we propose complex networks enabled new methods to measure the causal comovement of individual stocks and the comovement structure of the market, which facilitate the examination of all kinds of hypotheses of comovement theories in a unified framework. Using a sample of the Chinese stock market from Jan. 1, 2006 to Dec. 31, 2016, we find that the degree of comovement generally intensifies over time, with a drastic increase from 2011 to 2015, while the comovement structure of the market changes with different market situations. Most importantly, our study reveals the driving force of causal comovement among individual stocks; that is, sentiment-based factors related to the market index indeed induce excess causal comovement in returns beyond that can be justified by fundamental factors including beta coefficient, book-to-market ratio, liquidity, profitability and volatility. Our study also reveals the determinants of comovement structure, which are attributable to the change of investors' behaviors in different periods. It turns out that investors in the Chinese stock market care about risk-return relationship in normal periods, while they seem to care only about risk in crisis periods.     

Portfolio choice and pricing in illiquid markets

This paper studies portfolio choice and pricing in markets in which immediate trading may be impossible. It departs from the literature by removing restrictions on asset holdings, and finds that optimal positions depend significantly and naturally on liquidity: When expected future liquidity is high, agents take more extreme positions, given that they do not have to hold those positions for long when they become undesirable. Consequently, larger trades should be observed in markets with more frequent trading. Liquidity need not affect the price significantly, however, because liquidity has offsetting impacts on different agents' demands. This result highlights the importance of unrestricted portfolio choice. The paper draws parallels with the transaction-cost literature and clarifies the relationship between the price level and the realized trading frequency in this literature.