A financial CCAPM and economic inequalities

This paper considers a wealth heterogeneous multi-agent (MA) financial pricing CCAPM model. It is based on the following observations: (a) A distinction between what agents are willing to pay for consumption and what they actually pay. The former is a function of a number of factors including the agent’s wealth and risk preferences and the latter is a function of all other agents’ aggregate consumption or equivalently, their wealth committed to consumption. (b) Unlike traditional pricing models that define a representative agent underlying the pricing model, this paper assumes that each agent is in fact ‘Cournot-gaming’ a market defined by all other agents. This results in a decomposition of an n-agents game into n games of two agents, one a specific agent and the other a synthetic agent (a proxy for all other agents), on the basis of which an equilibrium consumption price solution is defined. The paper’s essential results are twofold. First, a Martingale pricing model is defined for each individual agent expressing the consumer willingness to pay (his utility price) and the market price—the price that all agents pay for consumption. In this sense, price is unique defined by each agent’s ‘Cournot game’ Agents’ consumption are then adjusted accordingly to meet the market price. Second, the pricing model defined is shown to account for agents wealth distribution pointing out that all agents valuations are a function of their and others’ wealth, the information they have about each other and other factors which are discussed in the text. When an agent has no wealth or cannot affect the market price of consumption, then this pricing model is reduced to the standard CCAPM model while any agent with an appreciable wealth compared to other agents, is shown to value returns (and thus future consumption) less than wealth-poor agents. As a result, this paper will argue that even in a financial market with an infinite number of agents, if there are some agents that are large enough to affect the market price by their decisions, such agents have an arbitrage advantage over the poorer agents. The financial CCAPM MA pricing model has a number of implications, some of which are considered in this paper. Finally, some simple examples are considered to highlight the applicability of this paper to specific financial issues.     

Pricing jump risk with utility indifference

This paper is concerned with option pricing in an incomplete market driven by a jump-diffusion process. We price options according to the principle of utility indifference. Our main contribution is an efficient multi-nomial tree method for computing the utility indifference prices for both European and American options. Moreover, we conduct an extensive numerical study to examine how the indifference prices vary in response to changes in the major model parameters. It is shown that the model reproduces ‘crash-o-phobia’ and other features of market prices of options. In addition, we find that the volatility smile generated by the model corresponds to a zero mean jump size, while the volatility skew corresponds to a negative mean jump size.     

Testing Conditional Asset Pricing Models Using a Markov Chain Monte Carlo Approach

We use Markov Chain Monte Carlo (MCMC) methods for the parameter estimation and the testing of conditional asset pricing models. In contrast to traditional approaches, it is truly conditional because the assumption that time variation in betas is driven by a set of conditioning variables is not necessary. Moreover, the approach has exact finite sample properties and accounts for errors‐in‐variables. Using S&P 500 panel data, we analyse the empirical performance of the CAPM and the Fama and French (1993) three‐factor model. We find that time‐variation of betas in the CAPM and the time variation of the coefficients for the size factor (SMB) and the distress factor (HML) in the three‐factor model improve the empirical performance. Therefore, our findings are consistent with time variation of firm‐specific exposure to market risk, systematic credit risk and systematic size effects. However, a Bayesian model comparison trading off goodness of fit and model complexity indicates that the conditional CAPM performs best, followed by the conditional three‐factor model, the unconditional CAPM, and the unconditional three‐factor model.     

Cross‐sectional Tests of Conditional Asset Pricing Models: Evidence from the German Stock Market

We study the performance of conditional asset pricing models and multifactor models in explaining the German cross‐section of stock returns. We focus on several variables, which (according to previous research) are associated with market expectations on future market excess returns or business cycle conditions. Our results suggest that the empirical performance of the Capital Asset Pricing Model (CAPM) can be improved when allowing for time‐varying parameters of the stochastic discount factor. A conditional CAPM using the term spread explains the returns on our size and book‐to‐market sorted portfolios about as well as the Fama‐French three‐factor model and performs best in terms of the Hansen‐Jagannathan distance. Structural break tests do not necessarily indicate parameter instability of conditional model specifications. Another major finding of the paper is that the Fama‐French model – despite its generally good cross‐sectional performance – is subject to model instability. Unconditional models, however, do a better job than conditional ones at capturing time‐series predictability of the test portfolio returns.     

In America's thrall: the effects of the US market and US security characteristics on Australian stock returns

Can Australian equity returns be modelled by ‘home‐grown’ factors? We examine the indigenous capital asset pricing model, the indigenous Fama–French three‐factor model, and extensions to the latter, and find them all wanting. We find evidence of domestic market segmentation in Australia. For the smallest firms, all the models we study fail. For the largest Australian firms, we find that the US Fama–French three factors (downloaded from French's website: http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/ ) provide a successful model of Australian returns. It is as if the largest firms in the Australian market are simply part of the larger US market.     

Misspecification of capital asset pricing: Empirical anomalies based on earnings' yields and market values

This study documents empirical anomalies which suggest that either the simple one-period capital asset pricing model (CAPM) is misspecified or that capital markets are inefficient. In particular, portfolios based on firm size or earnings/price (E/P) ratios experience average returns systematically different from those predicted by the CAPM. Furthermore, the ‘abnormal’ returns persist for at least two years. This persistence reduces the likelihood that these results are being generated by a market inefficiency. Rather, the evidence seems to indicate that the equilibrium pricing model is misspecified. However, the data also reveals that an E/P effect does not emerge after returns are controlled for the firm size effect; the firm size effect largely subsumes the E/P effect. Thus, while the E/P anomaly and value anomaly exist when each variable is considered separately, the two anomalies seem to be related to the same set of missing factors, and these factors appear to be more closely associated with firm size than E/P ratios.     

The systematic pricing of market sentiment shock

ABSTRACT

We show that market sentiment shocks create demand shocks for risky assets and a systematic risk for assets. We measure a market sentiment shock as the unexpected portion of the University of Michigan Consumer Sentiment Index’s growth. This shock prices stock returns in arbitrage pricing theory framework at 1% after controlling for market, size, value, momentum, and liquidity risk factors. Its premium lowered the implied risk aversion by 97.9% to 11.46 between 1978 and 2009 in our sentiment consumption-based capital-asset-pricing model. Merton’s [1973. “An Intertemporal Capital Asset Pricing Model.” Econometrica 41: 867–887]. intertemporal capital-asset-pricing model reconfirms our finding that this market sentiment shock is a systematic risk factor that provides investment opportunities.     

Option Coskewness and Capital Asset Pricing

This article shows how the market coskewness model of Rubinstein(1973) and Kraus and Litzenberger (1976) is altered when a nonredundantcall option is optimally traded. Owing to the option’snonredundancy, the economy’s stochastic discount factor(SDF) depends not only on the market return and the square ofthe market return but also on the option return, the squareof the option return, and the product of the market and optionreturns. This leads to an asset pricing model in which the expectedreturn on any risky asset depends explicitly on the asset’scoskewness with option returns. The empirical results show thatthe option coskewness model outperforms several competing benchmarkmodels. Furthermore, option coskewness captures some of thesame risks as the Fama–French factors small minus big(SMB) and high minus low (HML). These results suggest that thefactors that drive the pricing of nonredundant options are alsoimportant for pricing risky equities.(JEL G11, G12, D61)     

Performance,stock selection and market timing of the German equity mutual fund industry

We investigate the performance of the German equity mutual fund industry over 20 years (monthly data 1990–2009) using the false discovery rate (FDR) to examine both model selection and performance measurement. When using the Fama–French three factor (3F) model (with no market timing) we find that at most 0.5% of funds have truly positive alpha-performance and about 27% have truly negative-alpha performance. However, the use of the FDR in model selection implies inclusion of market timing variables and this results in a large increase in truly positive alpha funds. However, when we use a measure of “total” performance, which includes the contribution of both security selection (alpha) and market timing, we obtain results similar to the 3F model. These results are largely invariant to different sample periods, alternative factor models and to the performance of funds investing in German and non-German firms — the latter casts doubt on the ‘home-bias’ hypothesis of superior performance in ‘local’ markets.     

An application of a random level shifts model to the volatility of Peruvian stock and exchange rate returns

The literature has shown that the volatility of stock and forex rate market returns shows the characteristic of long memory. Another fact that is shown in the literature is that this feature may be spurious and volatility actually consists of a short memory process contaminated with random level shifts (RLS). In this paper, we follow recent econometric approaches estimating an RLS model to the logarithm of the absolute value of stock and forex returns. The model consists of the sum of a short-term memory component and a component of level shifts. The second component is specified as the cumulative sum of a process that is zero with probability ‘1-alpha’ and is a random variable with probability ‘alpha’. The results show that there are level shifts that are rare, but once they are taken into account, the characteristic or property of long memory disappears. Also, the presence of General Autoregressive Conditional Heteroscedasticity (GARCH) effects is eliminated when included or deducted level shifts. An exercise of out-of-sample forecasting shows that the RLS model has better performance than traditional models for modelling long memory such as the models ARFIMA (p,d,q).     

An Empirical Comparison of Asset-Pricing Models in the Shanghai A-Share Exchange Market

This paper evaluates and compares the performance of three-asset pricing models—the capital asset pricing model of Sharpe (J Finance 19:425–442, 1964), the three-factor model of Fama and French (J Financ Econ 33:3–56, 1993), and the five-factor model (Fama and French in J Financ Econ 123:1–22, 2015)—in the Shanghai A-share exchange market. Our results do not support the superiority of the five-factor model and show that the three-factor model outperforms the other models. We also verify the redundancy of the book-to-market factor and confirm the findings of Fama and French (2015).     

Pricing Model Performance and the Two‐Pass Cross‐Sectional Regression Methodology

Over the years, many asset pricing studies have employed the sample cross‐sectional regression (CSR) R² as a measure of model performance. We derive the asymptotic distribution of this statistic and develop associated model comparison tests, taking into account the impact of model misspecification on the variability of the CSR estimates. We encounter several examples of large R² differences that are not statistically significant. A version of the intertemporal capital asset pricing model (CAPM) exhibits the best overall performance, followed by the Fama–French three‐factor model. Interestingly, the performance of prominent consumption CAPMs is sensitive to variations in experimental design.     

Asset-pricing anomalies and spanning: Multivariate and multifactor tests with heavy-tailed distributions

In this paper we propose a multivariate regression based assessment of the multifactor model first developed by Fama and French (1993). We study mean-variance efficiency and spanning, as well as factor relevance. In particular, we assess the relative contribution of the factors in accounting for asset pricing anomalies. Our tests are motivated by a finite-sample distributional theory, invariant to portfolio repackaging, and achieve size control exactly conditioning on observed factors, in normal and non-normal contexts. We focus on the multivariate normal and Student-t distributions, in which case we rely on the simulation procedure proposed and applied in Beaulieu et al. (2007). We also assess, from a finite-sample and multivariate test perspective, the specification and fit of the model and error distributions considered. In its most general form, the model considered includes six factors: the market portfolio, size, the ratio of book equity to market equity as well as term structure variables (a term premium and a default premium) and momentum. Portfolio returns (coming from assets traded at NYSE, AMEX and NASDAQ) from Fama and French's data base are analyzed on monthly frequencies from 1961–2000.Our results show the following. (1) Normality in model residuals becomes more dependable as a working hypothesis, over short time spans, when the book to market equity and size factors or when the momentum factor are accounted for. (2) Allowing for heavy tailed distributions empirically accommodates some stylized asset pricing anomalies. (3) Loadings on the term structure variables and the momentum factor seem (jointly, across portfolios) statistically insignificant at usual levels in many sub-periods. (4) Mean-variance efficiency is rejected in fewer subperiods allowing for non-normal errors in multi-factor settings; the book to market equity and size factors contribute importantly in reinforcing efficiency. (5) Enlarging the set of assets [from a one factor to a six factor model] does not reinforce the mean-variance spanning hypothesis, which is globally rejected at usual levels.     

Use of the Proceeds and Long‐term Performance of French SEO Firms

This paper examines the long‐term stock performance of French SEO with rights by looking at the intended use of the proceeds. Firms that raise equity for pure capital structure motives are separated from the ones that use the SEO proceeds to finance specific investment projects. Issuers in the first category are concerned about preserving their financial flexibility and they are expected to evolve in a capital structure irrelevancy framework. On the other hand, issuers in the second category are more inclined to be sensitive to adverse selection problems or agency conflicts and thus, they should be more exposed to under‐reaction on the long‐run. According to a matching firm methodology, ‘Financing New Investment’ issuers underperform their benchmark at a rate of 4% to 8% per year over a 36‐month horizon while ‘Capital Structure’ issuers do not show any abnormal performance. These results are robust according to alternative Beta pricing models. In addition, managers of both issuer's types time the SEO after a period of positive abnormal performance in order to sell overpriced securities. However, only the ‘Financing New Investment’ sample experiences a performance reversal; the abnormal returns decreasing gradually from the issue on, to become significantly negative 24 months after the event.     

Weighing asset pricing factors: a least squares model averaging approach

Empirical evidence has demonstrated that certain factors in asset pricing models are more important than others for explaining specific portfolio returns. We propose a technique that evaluates the factors included in popular linear asset pricing models. Our method has the advantage of simultaneously ranking the relative importance of those pricing factors through comparing their model weights. As an empirical verification, we apply our method to portfolios formed following Fama and French [A five-factor asset pricing model. J. Financ. Econ., 2015, 116, 1–22] and demonstrate that models accommodated to our factor rankings do improve their explanatory power in both in-sample and out-of-sample analyses.     

Financial Intermediaries and the Cross‐Section of Asset Returns

Financial intermediaries trade frequently in many markets using sophisticated models. Their marginal value of wealth should therefore provide a more informative stochastic discount factor (SDF) than that of a representative consumer. Guided by theory, we use shocks to the leverage of securities broker‐dealers to construct an intermediary SDF. Intuitively, deteriorating funding conditions are associated with deleveraging and high marginal value of wealth. Our single‐factor model prices size, book‐to‐market, momentum, and bond portfolios with an R² of 77% and an average annual pricing error of 1%—performing as well as standard multifactor benchmarks designed to price these assets.     

The relationship between return and market value of common stocks

This study examines the empirical relationship between the return and the total market value of NYSE common stocks. It is found that smaller firms have had higher risk adjusted returns, on average, than larger firms. This ‘size effect’ has been in existence for at least forty years and is evidence that the capital asset pricing model is misspecified. The size effect is not linear in the market value; the main effect occurs for very small firms while there is little difference in return between average sized and large firms. It is not known whether size per se is responsible for the effect or whether size is just a proxy for one or more true unknown factors correlated with size.     

Corporate social responsibility reports: topic analysis and big data approach

ABSTRACT

This paper performs topic modeling using all publicly available CSR (Corporate Social Responsibility) reports for all constituent firms of the major stock market indices of 15 industrialized countries included in MSCI Europe for the sample period from 1999 to 2016. Our text mining results and LDA analyses indicate that ‘employees safety’, ‘employees training support’, ‘carbon emission’, ‘human right’, ‘efficient power’, and ‘healthcare medicines’ are the common topics reported by publicly listed companies in Europe and the UK. There is a clear sector bias with industrial firms emphasizing ‘employee safety’, Utilities concentrating on ‘efficient power’ while consumer discretionary and consumer staples highlighting ‘food waste’ and ‘food packaging.’ To produce these results, we used a battery of python code to organize the hundreds of reports downloaded from Bloomberg and the internet, the latest R-algorithm to estimate LDA (Latent Dirichlet Allocation) model and the LDAvis interactive tool to visualize and refine the LDA model.     

In search of distress risk in China's stock market

We examine the significance of size, book-to-market, and momentum factors in capturing financial distress risk in China's stock market. Consistent with the market underreaction hypothesis, we find that the momentum factor proxies for distress risk in China's stock market and that the explanatory power of momentum is subsumed when a distress factor is included in the asset pricing model. Our analysis demonstrates no evidence that size and book-to-market effects are driven by financial distress risk.¹     

A model of returns for the post-credit-crunch reality: hybrid Brownian motion with price feedback

Recent market events have reinvigorated the search for realistic return models that capture greater likelihoods of extreme movements. In this paper we model the medium-term log-return dynamics in a market with both fundamental and technical traders. This is based on a trade arrival model with variable size orders and a general arrival-time distribution. With simplifications we are led in the jump-free case to a local volatility model defined by a hybrid SDE mixing both arithmetic and geometric or CIR Brownian motions, whose solution in the geometric case is given by a class of integrals of exponentials of one Brownian motion against another, in forms considered by Yor and collaborators. The reduction of the hybrid SDE to a single Brownian motion leads to an SDE of the form considered by Nagahara, which is a type of ‘Pearson diffusion’, or, equivalently, a hyperbolic OU SDE. Various dynamics and equilibria are possible depending on the balance of trades. Under mean-reverting circumstances we arrive naturally at an equilibrium fat-tailed return distribution with a Student or Pearson Type~IV form. Under less-restrictive assumptions, richer dynamics are possible, including time-dependent Johnson-SU distributions and bimodal structures. The phenomenon of variance explosion is identified that gives rise to much larger price movements that might have a priori been expected, so that ‘25σ’ events are significantly more probable. We exhibit simple example solutions of the Fokker–Planck equation that shows how such variance explosion can hide beneath a standard Gaussian facade. These are elementary members of an extended class of distributions with a rich and varied structure, capable of describing a wide range of market behaviors. Several approaches to the density function are possible, and an example of the computation of a hyperbolic VaR is given. The model also suggests generalizations of the Bougerol identity. We touch briefly on the extent to which such a model is consistent with the dynamics of a ‘flash-crash’ event, and briefly explore the statistical evidence for our model.