Do relative leverage and relative distress really explain size and book-to-market anomalies?

In a capital asset pricing model (CAPM) framework, Ferguson and Shockley [2003. Equilibrium “anomalies”. Journal of Finance 58, 2549–2580] propose two factors constructed on relative leverage and relative distress, and show that the two factors subsume Fama and French's [1993. Common risk factors in the returns on stocks and bonds. Journal of Financial Economics 33, 3–56] factors constructed on size and book-to-market (BM) in explaining the cross-sectional average returns of the 25 size-BM portfolios. Based on tests on individual securities, we find that all factors fail to fully explain the common asset-pricing anomalies. In the spirit of Merton's [1973. An intertemporal capital asset pricing model. Econometrica 41, 867–887] intertemporal CAPM, we propose an augmented five-factor model, which incorporates Ferguson and Shockley's [2003. Equilibrium “anomalies”. Journal of Finance 58, 2549–2580] factors into the Fama–French three-factor model. The empirical results show that a simple conditional version of the augmented model is able to explain most well-known asset-pricing anomalies.     

Robustifizierung des Chain-Ladder-Verfahrens über ein skalares Zustandsraummodell

Applications of state space models and the Kalman filter are comparatively underrepresented in stochastic claims reserving. This is usually caused by their high complexity due to matrix-based approaches, which complicate their applications. In order to facilitate the implementation of state space models in practice, we present a state space model for cumulative payments in the framework of a scalar-based approach. In addition to a comprehensive presentation of this scalar state space model, some empirical applications and comparisons with popular stochastic claims reserving methods are performed, which show the strengths of the scalar state space model in practical applications. This model is a robustified extension of the well-known Chain Ladder method under the assumption, that the observations in the upper triangle are based on unobservable states. Using Kalman-filter recursions for prediction, filtering and smoothing of cumulative payments, the entire unobservable lower and upper run-off triangles can be determined. Moreover, the model provides an easy way to find and smooth outliers and to interpolate gaps in the data. Thus, the problem of missing values in the upper triangle is also solved in a natural way.     

Applications of Fuzzy Regression in Actuarial Analysis

In this article, we propose several applications of fuzzy regression techniques for actuarial problems. Our main analysis is motivated, on the one hand, by the fact that several articles in the financial and actuarial literature suggest using fuzzy numbers to model interest rate uncertainty but do not explain how to quantify these rates with fuzzy numbers. Likewise, actuarial literature has recently focused some of its attention in analyzing the Term Structure of Interest Rates (TSIR) because this is a key instrument for pricing insurance contracts. With these two ideas in mind, we show that fuzzy regression is suitable for adjusting the TSIR and discuss how to apply a fuzzy TSIR when pricing life insurance contracts and property‐liability policies. Finally, we reflect on other actuarial applications of fuzzy regression and develop with this technique the London Chain Ladder Method for obtaining Incurred But Not Reported Reserves.     

INTEGRATED METAHEURISTIC OPTIMIZATION OF 130–30 INVESTMENT‐STRATEGY‐BASED LONG–SHORT PORTFOLIOS

A 130–30 strategy is an attractive and viable equity investment strategy for building long–short portfolios and notionally expected to enhance investment exposure and market protection. However, the amalgamation of the strategy in the portfolio optimization problem model poses complex constraints which render the problem model difficult for solving using traditional methods, thus justifying the application of metaheuristic solutions. We discuss a metaheuristic and integrated optimization of long–short portfolios, when the 130–30‐strategy‐based constraint, besides other investor preferential constraints, is incorporated in the problem's formulation. In the absence of reported work and for reasons of performance comparison and analysis, two metaheuristic strategies have been proposed in order to solve the problem: (i) evolution strategy with hall of fame and (ii) differential evolution (rand/1/bin) with hall of fame. The experimental studies were undertaken on the Bombay Stock Exchange (BSE200) and Tokyo Stock Exchange (Nikkei 225) data sets and specifically for the period March 1999–March 2009, which included both upturns and downturns in the global markets. The efficiencies of the portfolios obtained by the two metaheuristic methods were analysed using an efficiency improvement possibility function, a portfolio productivity indicator which is a variation of Luenberger's shortage functions. Copyright © 2012 John Wiley & Sons, Ltd.     

Evidence of Discrimination in Lending: An Extension

We generalize the model of Ferguson and Peters (1995) to allow for unequal recovery rates in the event of default by majority borrowers versus minority borrowers. This simple extension has two direct implications: (i) a uniform credit policy, as defined by Ferguson and Peters, entails cross-subsidization across groups; and (ii) it is possible for a profit-maximizing (and therefore economically nondiscriminatory) lending policy to generate lower average default rates among minority borrowers than among majority borrowers.     

A model study about the applicability of the Chain Ladder method

Loss Reserving is a major topic of actuarial sciences with a long tradition and well-established methods – both in science and in practice. With the implementation of Solvency II, stochastic methods and modelling the stochastic behaviour of individual claim portfolios will receive additional attention. The author has recently proposed a three-dimensional (3D) stochastic model of claim development. It models a reasonable claim process from first principle by integrating realistic processes of claim occurrence, claim reporting and claim settlement. This paper investigates the ability of the Chain Ladder (CL) method to adequately forecast outstanding claims within the framework of the 3D model. This allows one to find conditions under which the CL method is adequate for outstanding claim prediction, and others in which it fails. Monte Carlo (MC) simulations are performed, lending support to the theoretic results. The analysis leads to additional suggestions concerning the use of the CL method.     

Investment–cash flow sensitivity measures investment thirst,but not financial constraint

Literature streams disagree about the capacity of investment–cash flow sensitivity (ICFS) to measure both investment thirst and financial constraint. We argue that ICFS measures the former but not the latter. Therefore, we use Fazzari et al.'s study (1988) to develop a model to test the relationship between ICFS and financial constraint, but extend that model using Kornai (1979) to include investment thirst. We demonstrate: because the ICFS–financial constraint relationship varies, ICFS cannot measure financial constraint. Conversely, using a natural experiment of China's Four Trillion Stimulus policy, we show ICFS significantly and positively correlates with investment thirst after controlling for financial constraint.     

Constructing and Testing Alternative Versions of the Fama–French and Carhart Models in the UK

This paper constructs and tests alternative versions of the Fama–French and Carhart models for the UK market with the purpose of providing guidance for researchers interested in asset pricing and event studies. We conduct a comprehensive analysis of such models, forming risk factors using approaches advanced in the recent literature including value‐weighted factor components and various decompositions of the risk factors. We also test whether such factor models can at least explain the returns of large firms. We find that versions of the four‐factor model using decomposed and value‐weighted factor components are able to explain the cross‐section of returns in large firms or in portfolios without extreme momentum exposures. However, we do not find that risk factors are consistently and reliably priced.     

基于钢铁企业的价值链分析及模型构建

对波特的价值链理论进行较深入的剖析，进而根据钢铁企业独特的生产特点，构建基于价值链优势环节整合的钢铁企业价值链模型，并探讨二者之间的内在联系和相互作用机理。     

The Australian asset‐pricing debate

Utilising a comprehensive data set for Australian firms, we examine a range of competing asset‐pricing models, including the four‐ and five‐factor models where the equity‐risk premium is augmented by size, value, momentum and liquidity premia, and find that none of the models tested appears to adequately explain the cross section of Australian returns. A model accounting for Australia's integration with the US equity market appears to be the best of the competing models we study. Our argument that a model recognising Australia's integration with the USA is supported when we apply the portfolio and factor construction methodology suggested by Brailsford et al. (2012a,b).     

Sectoral Comovement,Monetary Policy Shocks,and Input–Output Structure

The comovement of output across the sector producing nondurables (i.e., nondurable goods and services) and the sector producing durables is well established in the monetary business cycle literature. However, standard sticky‐price models that incorporate sectoral heterogeneity in price stickiness (i.e., sticky nondurables prices and flexible durables prices) cannot generate this feature. We argue that an input–output (I–O) structure provides a solution to this problem. Here, we develop a two‐sector model with an I–O structure, which is calibrated to the U.S. economy. In the model, each sector’s output affects those of the others by acting as an intermediate input. This connection between the sectors provides a channel through which sectoral comovement is induced.     

Aggregation Bias in Estimates of Conditional Conservatism: Theory and Evidence

This paper documents a study about the influence of the aggregation effect on the estimates of models based on the original Basu model – specifically the Ball, Kothari and Nikolaev model (Ball et al., 2013b). We provide an analytical study of the effect, showing that it can produce two biases: an omitted‐variable bias and a truncated‐sample bias. Using separate proxies for good and bad news for each company and year, we estimate the empirical sign and magnitude of those biases. Our results show that the estimates of conditional conservatism based on regressions of (unexpected) earnings on (unexpected) returns, as in the paper by Ball et al., are contaminated by substantial aggregation bias. More specifically, the aggregation effect causes these models to underestimate good‐news timeliness and overestimate bad‐news timeliness, thereby overestimating differential timeliness. Moreover, when we use proxies that provide better control for the aggregation effect, the differential timeliness coefficient tends to 0, showing that the influence of conditional conservatism on the returns–earnings relationship is, at best, marginal.     

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.     

Regime switches between dividend and bond yields

The relation between bond and equity returns serves as a proxy for estimating the premia investors' demand on their equity portfolio holdings and assessing the substitution effects between the two markets. With this in mind, we examine empirically the co-movements and the underlying information between equities and bonds. Our approach relies on the comparison between bond and dividend yields — a relation better known as the gilt-equity yield ratio–GEYR — by examining the characteristics of the cointegration relation between the bond and equity yields. In this context, this paper's contribution is that it lifts the restrictions of linearity both in the long-run cointegration relations and in the underlying short-run relations presented in the VECM. Specifically, we apply the regime-switching framework of Gregory and Hansen (Gregory, A. W. & Hansen, B. E. (1996). Residual-based tests for cointegration in models with regime shifts. Journal of Econometrics 70, 99–126) for the long-run equilibriums and the Markov Switching VECM, established by Krolzig (Krolzig, H.M., 1997. Markov switching vector autoregressions. Modelling statistical inference and application to business cycle analysis. Springer, Verlag) for the short run ones. Our aim is to examine the allocation of capital among the UK bond (or else, gilt) and stock markets for the period of 01-1987 to 01-2007, in a fashion that better reflects the structural breaks and regime shifts of the underlying market conditions. Our findings confirm the substitution effects among stocks and bonds in the long run and highlight the importance of market conditions for the allocation of capital among stocks and bonds.     

Reading the smile: the message conveyed by methods which infer risk neutral densities

In this study we compare the quality and information content of risk neutral densities obtained by various methods. We consider a non-parametric method based on a mixture of log–normal densities, the semi-parametric ones based on an Hermite approximation or based on an Edgeworth expansion, the parametric approach of Malz which assumes a jump-diffusion for the underlying process, and Heston's approach assuming a stochastic volatility model. We apply those models on FF/DM exchange rate options for two dates. Models differ when important news hits the market (here anticipated elections). The non-parametric model provides a good fit to options prices but is unable to provide as much information about market participants expectations than the jump-diffusion model.     

基于贝叶斯MSSV-ST金融波动模型的股市特征及机制转移性研究

针对有偏厚尾金融随机波动模型难以刻画参数的动态时变性及结构突变的问题,设置偏态参数服从 Markov 转换过程,采用贝叶斯方法,构建带机制转移的有偏厚尾金融随机波动模型,考量股市不同波动状态间的机制转移性,捕捉股市间多重波动特性。通过设置先验分布,实现模型的贝叶斯推断,设计相应的马尔科夫链蒙特卡洛算法进行估计,并利用上证指数进行实证。结果表明：模型不仅刻画了股市的尖峰厚尾、杠杆效应等特性,发现收益率条件分布的偏度参数具有动态时变性,股市波动呈现出显著的机制转移特性,而且证实了若模型考虑波动的不同阶段性状态后,将降低持续性参数向上偏倚幅度的结论。     

Comment on “Optimal portfolio selection in a value-at-risk framework”

This comment discusses some errors in [Journal of Banking and Finance 25 (2001) 1789]. Given the portfolio rate of return is normally distributed, the following can be inferred. First, taking expected portfolio return rate as the benchmark of value-at-risk (VaR), the risk–return ratio collapses to a multiple of the Sharpe index. However, using risk-free rate as the benchmark, then above inference does not hold. Second, whether the benchmark of VaR is expected portfolio return rate or the risk-free rate, the optimal asset allocations for maximizing the risk–return ratio and Sharpe index are identical.     

Classes of Interest Rate Models under the HJM Framework

Although the HJM term structure model is widely accepted as the mostgeneral, and perhaps the most consistent, framework under which to studyinterest rate derivatives, the earlier models of Vasicek,Cox–Ingersoll–Ross, Hull–White, andBlack–Karasinski remain popular among both academics andpractitioners. It is often stated that these models are special cases ofthe HJM framework, but the precise links have not been fully establishedin the literature. By beginning with certain forward rate volatilityprocesses, it is possible to obtain classes of interest models under theHJM framework that closely resemble the traditional models listed above.Further, greater insight into the dynamics of the interest rate processemerges as a result of natural links being established between the modelparameters and market observed variables.     

Parameter estimation risk in asset pricing and risk management: A Bayesian approach

Parameter estimation risk is non-trivial in both asset pricing and risk management. We adopt a Bayesian estimation paradigm supported by the Markov Chain Monte Carlo inferential techniques to incorporate parameter estimation risk in financial modelling. In option pricing activities, we find that the Merton's Jump-Diffusion (MJD) model outperforms the Black-Scholes (BS) model both in-sample and out-of-sample. In addition, the construction of Bayesian posterior option price distributions under the two well-known models offers a robust view to the influence of parameter estimation risk on option prices as well as other quantities of interest in finance such as probabilities of default. We derive a VaR-type parameter estimation risk measure for option pricing and we show that parameter estimation risk can bring significant impact to Greeks' hedging activities. Regarding the computation of default probabilities, we find that the impact of parameter estimation risk increases with gearing level, and could alter important risk management decisions.     

Flexible Prices and the Business Cycle

Business cycles models with flexible prices face two major empirical challenges. One regards observed output dynamics: the positive, short run, autocorrelation in GNP growth, and the hump‐shaped, trend‐reverting output response to transitory shocks ( Cogley and Nason 1995 ). The other regards the alleged persistent decline in employment following a positive technology shock ( Galí 1999 ). No determinate model with flexible prices has so far been able to address all of the Cogley Nason–Galí challenges. We show that the standard RBC model can do so if it contains a signal extraction problem involving permanent and temporary supply shocks.