Heterogeneous Expectations,Short Sales Regulation,and the Risk-Return Relationship

This paper examines, in a Canadian context, the effect of short sales regulation on the risk-return relationship. It shows that, theoretically, the opportunity cost induced by short sales regulation is positively related to the dispersion of agents' beliefs and negatively related to the security's liquidity level. The model is tested over the sixty-month period from January 1985 through December 1989. All the 13,079 observations are pooled into a time series cross-sectional model. The results corroborate that a negative linear relationship links expected risky asset returns and the divergence of agents' beliefs. This negative relationship is consistent with the presence of opportunity costs resulting from short sales regulation when return beliefs are heterogeneous. However, the negative relationship between security returns and dispersion of beliefs is essentially confined to illiquid securities, that is, those monitored by a small number of analysts.     

Sensitivity of Multivariate Tests of the Capital Asset-Pricing Model to the Return Measurement Interval

The capital asset-pricing model's (CAPM) primary empirical implication is a positively sloped linear relation between a security's expected rate of return and its relative risk (beta). Recent research indicates that inferences about the risk-return relation are sensitive to the choice of the return measurement interval. We perform multivariate tests of the Sharpe-Lintner CAPM using monthly and annual returns on market-value-ranked portfolios. The CAPM is rejected using monthly returns, a result consistent with previous research. In contrast, we fail to reject the CAPM when annual holding period returns are used.     

Asset liquidity and stock returns

We document the significant predictive power of firms' asset liquidity in the cross section of subsequent stock returns. The annual return spread between portfolios featuring the highest and lowest levels of asset liquidity is significantly positive. Our proposed measure of asset liquidity outperforms those measures developed by Gopalan et al. (2012) in predicting returns. The asset liquidity anomaly also provides significantly positive alphas when controlling for the asset pricing factors in the Fama and French (1993) three-factor model and the Carhart (1997) four-factor model. Asset liquidity exhibits strong return forecasting power even after controlling for acknowledged cross-sectional determinants of return. The positive relation between asset liquidity and future returns tends to be stronger for firms with greater asset productivity, higher quality cash flow and lower capital investment.     

The world price of liquidity risk

This paper empirically tests the liquidity-adjusted capital asset pricing model of Acharya and Pedersen (2005) on a global level. Consistent with the model, I find evidence that liquidity risks are priced independently of market risk in international financial markets. That is, a security’s required rate of return depends on the covariance of its own liquidity with aggregate local market liquidity, as well as the covariance of its own liquidity with local and global market returns. I also show that the US market is an important driving force of global liquidity risk. Furthermore, I find that the pricing of liquidity risk varies across countries according to geographic, economic, and political environments. The findings show that the systematic dimension of liquidity provides implications for international portfolio diversification.     

Stock and Bond Liquidity and its Effect on Prices and Financial Policies

An asset is liquid if it can be traded at the prevailing market price quickly and at low cost. We show that in addition to risk, liquidity affects asset prices and returns. Theories of asset pricing suggest that the expected return of an asset is increasing in its risk, because risk-averse investors require compensation for bearing more risk. Because investors are also averse to the costs of illiquidity and want to be compensated for bearing them, asset returns are increasing in illiquidity. Thus, asset prices should depend on two asset characteristics: risk and liquidity. This paper surveys research on the effects of liquidity on asset prices and returns, showing that liquidity is an important factor in capital asset pricing.     

The Market Reaction to Stock Splits

In this paper, a model of market reaction to stock splits is presented and tested. We argue that the announcement of a split sets off the following chain of events. The market recognizes that, subsequent to the (reverse) split ex-day, the daily number of transactions along with the raw volume of shares traded will increase (decrease). This increase in volume results in an increase in the noisiness of the security's return process. The increase in noise raises the tax-option value of the stock, and it is this value that generates the announcement effect of stock splits. Empirical evidence using security returns, daily trading volume, and shareholder data strongly supports this theory. The evidence, in conjunction with this theory, also agrees with extant literature that splits result in decreased liquidity, but there is no evidence that this reduction in liquidity is priced.     

Asset liquidity,business risk,and beta

Extant literature posits that because of leverage, equity beta estimates from a single factor capital asset pricing model based on an equity-only market index are biased. We show analytically that this leverage bias is intimately related to the firm's asset structure per se, the firm's asset liquidity (i.e., cash holdings) and business risk. This is mainly because riskless cash holdings and risky real assets jointly determine the relevant risk for asset pricing. We empirically confirm that asset liquidity and business risk can marginally explain the leverage bias in the cross-section of stocks returns.     

Valuation of GNMA Mortgage-Backed Securities

GNMA mortgage-backed pass-through securities are supported by pools of amortizing, callable loans. Additionally, mortgagors often prepay their loans when the market interest rate is above the coupon rate of their loans. This paper develops a model for pricing GNMA securities and uses it to examine the impact of the amortization, call, and prepayment features on the prices, risks and expected returns of GNMA's. The amortization and prepayment features each have a positive effect on price, while the call feature has a negative impact. All three features reduce a GNMA security's interest rate risk and, consequently, its expected return.     

考虑流动性的三阶矩资本资产定价的理论模型与实证研究

本文把流动性风险、偏态风险引进传统CAPM模型中,推导出基于流动性的三阶矩资本资产定价的理论模型。本文的模型表明,证券(组合)的收益依赖于它的期望流动性成本、其流动性成本和市场流动性成本的协方差以及其收益和市场收益的协方差与协偏态。本文采用我国A股市场的股票收益数据对模型进行了实证检验.检验结果表明,我国A股市场的证券(组合)的风险溢价在大盘升降区间体现了不同的特征,无论是在全样本区间还是两个子样本区间,基于流动性的三阶矩资本资产定价模型都能更好的拟合资产收益,说明了流动性和偏态因素在我国A股市场的资产定价中有重要影响。     

The Effects of Beta,Bid-Ask Spread,Residual Risk,and Size on Stock Returns

Merton's [26] recent extension of the CAPM proposed that asset returns are an increasing function of their beta risk, residual risk, and size and a decreasing function of the public availability of information about them. Associating the latter with asset liquidity and following Amihud and Mendelson's [2] proposition that asset returns increase with their illiquidity (measured by the bid-ask spread), we jointly estimate the effects of these four factors on stock returns.     

Does liquidity drive stock market returns? The role of investor risk aversion

In this paper, we explore the relations between liquidity, stock returns, and investor risk aversion as captured by the variance risk premium (VRP). This is motivated by theoretical and empirical evidence in the literature which suggests that investor risk aversion negatively correlates with asset liquidity, and ample empirical evidence documenting liquidity risk premium. We use monthly US data from January 1999 to December 2018 and show that innovations in the VRP Granger-cause stock returns, which in turn drive liquidity. Our findings are consistent with predictions of prior theories and highlight the predictability of the VRP. They also contribute to the on-going debate on the causal relation between stock returns and liquidity. Finally, we explore the channels through which the VRP impacts liquidity and find that the VRP influences market and momentum factors, and that movements in these factors lead to changes in liquidity.

     

A comparison among various dimensions of illiquidity effect: A case study of Finland

We study different dimensions of the illiquidity effect on asset returns in the Finnish market. The market illiquidity is measured as unexpected rises and falls in average monthly zero returns across all stocks. We find that for the returns on the specific class of assets, a flight to the liquidity effect is the most important systematic risk among all dimensions of the illiquidity effect. In other words, higher returns for illiquid assets in good times compensate for a pronounced drop in those returns in bad times and vice versa. Furthermore, only one illiquidity-related factor has a similar pricing capacity as Fama and French's (1993) three-factor model and Carhart's (1997) four-factor model in the context of this study.     

Return and volatility co-movement in commodity futures markets: the effects of liquidity risk

Commodity markets are a widely researched topic in the field of finance. In this paper, we investigate the co-movement of return and volatility measures in different commodity futures markets and how these measures are affected by liquidity risk. First, we find that commodity returns display co-movement and that liquidity risk plays a key role in shaping asset return patterns. Moreover, we show that the volatilities of commodity returns co-move, and we demonstrate the role of liquidity risk in this joint pattern. We also find that the commodity markets we investigated share a common volatility factor that determines their joint volatility co-movement. Because liquidity risk affects both commodity returns and volatility shocks, it might be interpreted as the common causal factor driving both measures simultaneously. Therefore, we affirm the view that liquidity shocks are firmly related to two residual risks originating from both market return and market volatility. Finally, we also show that liquidity spillovers can significantly drive cross-sectional correlation dynamics.     

Liquidity risk and stock performance during the financial crisis

We investigate whether and how ex-ante liquidity risk affects realized stock returns during the global financial crisis of 2008–2009 in international equity markets. We find that stocks with higher pre-crisis return exposure to global market liquidity shocks experience larger price reductions during the crisis period. Our findings provide further insight into the comprehensive picture of the effect of liquidity risk on asset prices, especially in an international context and under different market conditions.     

Market Illiquidity and Conditional Equity Premium

We examine the time‐series relation between aggregate bid‐ask spreads and conditional equity premium. We document that average marketwide relative effective bid‐ask spreads forecast aggregate market returns only when controlling for average idiosyncratic variance. This control allows us to document the otherwise elusive relation between illiquidity and returns. The reason is that idiosyncratic variance correlates positively with spreads but has a negative effect on conditional equity premium, causing an omitted variable bias. Our results are robust to standard return predictors, alternative illiquidity measures, and out‐of‐sample tests. These findings are important because they provide strong support for the literature's conjecture that marketwide liquidity is an important asset pricing risk factor.     

Carry

We apply the concept of carry, which has been studied almost exclusively in currency markets, to any asset. A security’s expected return is decomposed into its “carry,” an ex-ante and model-free characteristic, and its expected price appreciation. Carry predicts returns cross-sectionally and in time series for a host of different asset classes, including global equities, global bonds, commodities, US Treasuries, credit, and options. Carry is not explained by known predictors of returns from these asset classes, and it captures many of these predictors, providing a unifying framework for return predictability. We reject a generalized version of Uncovered Interest Parity and the Expectations Hypothesis in favor of models with varying risk premia, in which carry strategies are commonly exposed to global recession, liquidity, and volatility risks, though none fully explains carry’s premium.     

Dynamic asset–liability management in a Markov market with stochastic cash flows

This paper provides a general model to investigate an asset–liability management (ALM) problem in a Markov regime-switching market in a multi-period mean–variance (M–V) framework. Emphasis is placed on the stochastic cash flows in both wealth and liability dynamic processes, and the optimal investment and liquidity management strategies in achieving the M–V bi-objective of terminal surplus are evaluated. In this model, not only the asset returns and liability returns, but also the cash flows depend on the stochastic market states, which are assumed to follow a discrete-time Markov chain. Adopting the dynamic programming approach, the matrix theory and the Lagrange dual principle, we obtain closed-form expressions for the efficient investment strategy. Our proposed model is examined through empirical studies of a defined contribution pension fund. In-sample results show that, given the same risk level, an ALM investor (a) starting in a bear market can expect a higher return compared to beginning in a bull market and (b) has a lower expected return when there are major cash flow problems. The effects of the investment horizon and state-switching probability on the efficient frontier are also discussed. Out-of-sample analyses show the dynamic optimal liquidity management process. An ALM investor using our model can achieve his or her surplus objective in advance and with a minimum variance close to zero.     

Is there Value-Added Information in Liquidity and Risk Premiums?

Size has become a significant factor in explaining returns. According to the size effect, smaller capitalization stocks on average outperform larger capitalization stocks over long periods of time. This paper first documents the traditional size effect on the French market for the 1986–1998 period. It introduces a new proxy for size, free float, which is argued to be the appropriate measure of size and liquidity for most non‐US markets. Evidence is presented of a negative link between historical returns and free float. The link is significant even outside of the month of January, a notable divergence from results obtained on the NYSE. The rest of the paper is an attempt to take advantage of this 'ex‐post' phenomenon on an 'ex‐ante' basis, with an empirical study of the link between expected return, risk, and liquidity in a sample consisting of the main 150 stocks quoted on the Paris Bourse between January 1986 and January 1998. Liquidity premiums are estimated for portfolios from both a univariate and a multivariate perspective. The paper shows how risk and liquidity premiums can be used separately or in tandem for market timing and asset allocation. In all cases, the use of both premiums together leads to superior performance. Results confirm our measurements of liquidity and liquidity premiums and supply evidence that liquidity premiums together with risk premiums are useful in active asset management.     

Fair wages,labor relations and asset returns

The paper investigates the nexus between labor and financial markets, focusing on how labor union’s attitude in the wage-setting process and the firm’s investment strategy affect asset returns. We assume that the labor union’s relative preferences between wage and employment depend on selected measures of firm’s financial performance. The paper shows that if the labor union ties its preference for wage to the firm’s dividends (or to any other quantity measuring available liquidity), then the volatility of the firm’s returns increases. Consequently, equities have to grant high expected returns in order to remunerate the increased volatility. This mechanism offers an explanation for the “equity premium” (that is the difference between the equity return rate and the risk free rate). It is a welcome result that the simulated excess return is about the empirical estimate and that it is obtained with a plausibly low parameterization of the shareholders’ risk aversion.     

An examination of the relation between asymmetric risk measures,prior returns and expected daily stock returns

We use a sample of individual firm stock returns over the 1988–2009 time period to determine whether: (1) expected daily returns are related to asymmetric risk measures, (2) expected daily returns are related to the directional change of the prior day's price, and (3) our results are robust to the addition of firm size, book-to-market equity and liquidity. We find that investors are compensated for asymmetric risk; however, the positive risk–return relation is present only for our smallest firm quintile. We find a short-term return reversal present in all subgroups, except for the largest firms in our sample. We also document that the low volatility anomaly may be related to firm size and liquidity.