Arithmetic versus geometric mean estimators: Setting discount rates for capital budgeting

This paper addresses an issue central to the estimation of discount rates for capital budgeting: should the geometric mean or arithmetic mean of past data be used when estimating the discount rate? the use of the arithmetic mean ignores estimation error and serial correlation in returns. Unbiased discount factors have been derived that correct for both these effects. In all cases, the corrected discount rates are closer to the arithmetic than the geometric mean.     

Optimal Estimation of the Risk Premium for the Long Run and Asset Allocation: A Case of Compounded Estimation Risk

It is well known that an unbiased forecast of the terminal valueof a portfolio requires compounding at the arithmetic mean returnover the investment horizon. However, the maximum-likelihoodpractice, common with academics, of compounding at the estimatorof mean return results in upward biased and highly inefficientestimates of long-term expected returns. We derive analyticallyboth an unbiased and a small-sample efficient estimator of long-termexpected returns for a given sample size and horizon. Both estimatorsentail penalties that reduce the annual compounding rate asthe investment horizon increases. The unbiased estimator, whichis far lower than the compounded arithmetic average, is stillvery inefficient, often more so than a simple geometric estimatorknown to practitioners. Our small-sample efficient estimatoris even lower. These results compound the sobering evidencein recent work that the equity risk premium is lower than suggestedby post-1926 data. Our methodology and results are robust toextensions such as predictable returns. We also confirm analyticallythat parameter uncertainty, properly incorporated, producesoptimal asset allocations, in stark contrast to conventionalwisdom. Longer investment horizons require lower, not higher,allocations to risky assets.     

Seeing the Wood for the Trees: A Critical Evaluation of Methods to Estimate the Parameters of Stochastic Differential Equations

Maximum-likelihood estimates of the parameters of stochasticdifferential equations are consistent and asymptotically efficient,but unfortunately difficult to obtain if a closed-form expressionfor the transitional probability density function of the processis not available. As a result, a large number of competing estimationprocedures have been proposed. This article provides a criticalevaluation of the various estimation techniques. Special attentionis given to the ease of implementation and comparative performanceof the procedures when estimating the parameters of the Cox–Ingersoll–Rossand Ornstein–Uhlenbeck equations respectively.     

The joint estimation of bank-level market power and efficiency

The aim of this study is to provide a methodology for the joint estimation of efficiency and market power of individual banks. The proposed method utilizes the separate implications of the new empirical industrial organization and the stochastic frontier literatures and suggests identification using the local maximum likelihood (LML) technique. Through LML, estimation of market power of individual banks becomes feasible, while a number of restrictive theoretical and empirical assumptions are relaxed. The empirical analysis is carried out on the basis of EMU bank data. Market power estimates indicate fairly competitive conduct in general; however, heterogeneity in market power estimates is substantial across banks. The latter result suggests that the practice of some banks deviates from the average fairly competitive behavior, a finding that has important policy implications. Finally, efficiency and market power present a negative relationship, which is in line with the so-called “quiet life hypothesis”.     

经典波动模型下的最优债券投资组合

文章认为,由于利率和股价兼有相同的趋势性和波动性属性,股价经典波动模型对利率建模具有研究价值。通过引入经典的波动模型,结合极大似然估计的方法,本文探讨了无风险债券的最优投资方案,并将该成果运用于全球主要国债市场进行实证模拟投资,结果表明,该模型在全球主要国债市场均能取得较好的超额收益。     

Extending a Logistic Approach to Risk Modeling through Semiparametric Mixing

The new proposal of the Basel Committee on banking regulation issued in January 2001 allows banks to use internal ratings systems to classify firms. Within this context, the main problem is to find a model that fits the data as well as possible, but one that also provides good prediction and explicative capabilities. In this paper, our aim is to compare two kinds of classification models applied to creditworthiness using weighted classification error as the performance function: the standard logistic model and a mixed logistic model, adopting, respectively, a parametric and a semiparametric approach. The main problem of the former is related to the assumption of an i.i.d. hypothesis, but it is often necessary to consider the possible presence of unobservable heterogeneity that characterizes microeconomic data. To better consider this phenomenon, we defined and applied a random effect logistic model, avoiding parametric assumptions upon the random effect distribution. This leads to a likelihood that is defined as the integral of the kernel density with respect to the mixing density, which has no analytical solution. This problem can be obviated by approximating the integral with a finite sum of kernel densities, each one characterized by a different set of model parameters. This discrete nature helps us in detecting non-overlapping clusters characterized by homogeneous values of insolvency risk, and in classifying firms to one of these clusters by means of estimated posterior probabilities of component membership.     

Estimating the Model for Seasoned Equity Offering Underpricing: Application to the Chinese Financial Market

We estimate the binomial probit model to examine the significance of important explanatory variables documented in seasoned equity offering (SEO) underpricing literature using two statistical approaches: maximum likelihood estimation and Bayesian estimation. In particular, our estimation relies on SEO-related data in the Chinese financial market, where the pricing mechanism is less transparent compared to that in the U.S. market. We find that the signs of coefficients for the explanatory variables in each model are not different, but their magnitudes appear to be different. Our finding also shows that estimation results are generally consistent with the results observed in the U.S. market.     

On the complete monotonicity of the compound geometric convolution with applications in risk theory

We prove that the complete monotonicity is preserved under mixed geometric compounding, and hence show that the ruin probability, the Laplace transform of the ruin time, and the density of the tail of the joint distribution of ruin and the deficit at ruin in the Sparre Andersen model are completely monotone if the claim size distribution has a completely monotone density.     

The Predictive Power of the French Market Volatility Index: A Multi Horizons Study

The main purpose of this paper is to examine empirically the time series properties of the French Market Volatility Index (VX1). We also examine the VX1's ability to forecast future realized market volatility and finds a strong relationship. More importantly, we show how the index can be used to generate volatility forecasts over different horizons and that these forecasts are reasonably accurate predictors of future realized volatility.     

Predicting the long-term stock market volatility: A GARCH-MIDAS model with variable selection

We consider a GARCH-MIDAS model with short-term and long-term volatility components, in which the long-term volatility component depends on many macroeconomic and financial variables. We select the variables that exhibit the strongest effects on the long-term stock market volatility via maximizing the penalized log-likelihood function with an Adaptive-Lasso penalty. The GARCH-MIDAS model with variable selection enables us to incorporate many variables in a single model without estimating a large number of parameters. In the empirical analysis, three variables (namely, housing starts, default spread and realized volatility) are selected from a large set of macroeconomic and financial variables. The recursive out-of-sample forecasting evaluation shows that variable selection significantly improves the predictive ability of the GARCH-MIDAS model for the long-term stock market volatility.     

The Cost Channel Reconsidered: A Comment Using an Identification‐Robust Approach

We reexamine the empirical relevance of the cost channel of monetary policy (e.g., Ravenna and Walsh 2006 ), employing recently developed moment‐conditions inference methods, including identification‐robust procedures. Using U.S. data, our results suggest that the cost channel effect is poorly identified and we are thus unable to corroborate the previous results in the literature.     

The Russian option: Finite horizon

We show that the optimal stopping boundary for the Russian option with finite horizon can be characterized as the unique solution of a nonlinear integral equation arising from the early exercise premium representation (an explicit formula for the arbitrage-free price in terms of the optimal stopping boundary having a clear economic interpretation). The results obtained stand in a complete parallel with the best known results on the American put option with finite horizon. The key argument in the proof relies upon a local time-space formula.Received: March 2004, Mathematics Subject Classification (2000): 91B28, 35R35, 45G10, 60G40, 60J60JEL Classification: G13Goran Peskir: Centre for Analytical Finance (funded by the Danish Social Science Research Council) and Network in Mathematical Physics and Stochastics (funded by the Danish National Research Foundation).The first draft of the present paper has been completed in September 2002. I am indebted to Albert Shiryaev for useful comments.     

The Asian Financial Crisis and Investors’ Risk Aversion

This paper investigates whether changes in U.S. and Japanese banks’ risk aversion, measured by changes in the relative risk aversion (RRA) coefficient, are associated with the 1997 Asian financial crisis. It finds that an increase in U.S. banks’ risk aversion is unambiguously associated with the Asian crisis, while an increase in Japanese banks’ risk aversion is only weakly associated. The results suggest that, in addition to deteriorating fundamentals of the affected countries, investors’ (banks’) increased risk aversion appears to have reinforced observed capital outflows.     

混合供给模式下巨灾保险市场的激励与约束研究

巨灾保险具有准公共物品属性,既可以由政府提供,也可以由市场提供,单纯依靠政府和私人市场提供都存在较大弊端,政府和私人部门合作,采用混合供给模式可以形成互补优势,提高效率,这已成为国际巨灾保险市场发展的一大趋势。本文以混合供给模式下的巨灾保险市场为对象,分析巨灾保险市场中的委托代理关系,并对如何构建有效的激励与约束机制进行了初步探讨。     

The deficit at ruin in the stationary renewal risk model

Properties of the distribution of the deficit at ruin in the stationary renewal risk model are studied. A mixture representation for the conditional distribution of the deficit at ruin (given that ruin occurs) is derived, as well as a stochastic decomposition involving the residual lifetime associated with the maximal aggregate loss. When the individual claims have a phase-type distribution, the deficit at ruin is also of phase-type.     

Spring Transportation in China: The Peak-Load Problem with Psychological Factors

Every year around the time of the Chinese New Year, hundreds of millions of people in China return to their hometowns, placing huge pressure on the transportation infrastructure. However, a link between the theoretical model and the Chinese context is missing. This paper provides an in-depth look at the capacity shortage of transportation during Spring Transportation in China. I use a discrete choice model to determine the travel decision mechanism for the potential traveler and extend this model from a single traveler to multiple heterogeneous travelers based on travel distances and the emotional amenity of family reunions.     

深圳车险公估市场调研报告

车险公估作为深圳公估业的重要组成部分,为深圳保险业服务经济社会发展做出了积极贡献。不仅在保险理赔、风险评估领域发挥着重要的中介作用,而且为促进公估业的经济增长注入了动力。但是进入2009年后,深圳车险公估总体呈现发展后劲不足的态势。为进一步摸清深圳车险公估市场发展现状,巩固深圳保险公估之都的地位,深圳保监局对深圳车险公估市场展开深入研究,分析目前车险公估发展现状和存在的问题,并对深圳车险公估的可持续发展问题提出相关建议。     

The proper distribution function of the deficit in the delayed renewal risk model

The main focus of this paper is to extend the analysis of ruin-related quantities to the delayed renewal risk models. First, the background for the delayed renewal risk model is introduced and a general equation that is used as a framework is derived. The equation is obtained by conditioning on the first drop below the initial surplus level. Then, we consider the deficit at ruin among many random variables associated with ruin. The properties of the distribution function (DF) of the proper deficit are examined in particular.