Modelling mean reversion of asset prices towards their fundamental value

In this paper we extend the study of mean reversion behavior by modelling the fundamental value as a stochastic process. The market value of the asset is then modelled as a mean reverting Ornstein Uhlenbeck process towards the fundamental value. Solving backwards, we determine the functional form of the regression equation of changes in asset prices and returns to changes to the fundamental value. Using earnings and dividends as proxies for the fundamental value we test our model empirically. In general, other than the shortest horizon of 1-year, our model shows good explanatory power. Since our model is compatible with Campbell and Shiller (1988) framework in the earnings case and Fama and French (1988) model in the dividend case, the performance of our model has been compared with those two models. In comparison, the performance of our model is comparable to that of Campbell and Shiller and compares favorably with Fama and French.     

Boosting nonlinear predictability of macroeconomic time series

We apply the boosting estimation method in order to investigate to what extent and at what horizons macroeconomic time series have nonlinear predictability that comes from their own history. Our results indicate that the U.S. macroeconomic time series have more exploitable nonlinear predictability than previous studies have found. On average, the most favorable out-of-sample performance is obtained via a two-stage procedure, where a conventional linear prediction model is fitted first and the boosting technique is applied to build a nonlinear model for its residuals.     

Forecasting monthly riverflow time series

Mean monthly flows from thirty rivers in North and South America are used to test the short-term forecasting ability of seasonal ARIMA, deseasonalized ARMA, and periodic autoregressive models. The series were split into two sections and models were calibrated to the first portion of the data. The models were then used to generate one-step-ahead forecasts for the second portion of the data. The forecast performance is compared using various measures of accuracy. The results suggest that a periodic autoregressive model, identified by using the partial autocorrelation function, provided the most accurate forecasts     

基于评价指标聚类分析的铁路供应商选择方法

通过动态供应商选择过程的描述与特征分析,提出一种模糊C均值聚类方法,对铁路供应商选择评价指标进行聚类分析,从而确定其优选集权重指标,进而得到对供应商选择的方法。这一方面可避免多指标集权重确定过程中主观因素的影响;另一方面可提高其适应动态环境的灵活性。最后,通过实例进行验证与分析。     

Mean residual life functions of finite mixtures,order statistics and coherent systems

We study properties of the mean residual life functions of finite mixtures. Specifically, we study ordering properties, monotonicity and the limiting behaviour. We show, under some mild conditions, that the limiting behaviour is similar to that of the strongest member (in the mean residual life order) of the mixture. We also consider the case of negative mixtures (i.e., mixtures with some negative coefficients) which is applied to study the behaviour of the mean residual life of order statistics and coherent systems with possibly dependent components. Partially Supported by Ministerio de Ciencia y Tecnologí a under grant BFM2003-02947 and Fundación Séneca under grant 00698/PI/04.     

On pricing barrier control in a regime-switching regulated market

We study a pricing barrier control problem in a regime-switching regulated market. In doing so, we analyze a class of one-dimensional reflected regime-switching diffusion processes. Such diffusion models arise as the key approximating processes in a regulated financial market system with the presence of regime changes. Our main goal is to determine optimal pricing barriers as solutions of long-run average mean–variance optimization problems. More precisely, the optimal barrier, if exists, will be to maximize the long-run average expected return (i.e. steady-state mean) subject to a selected level of long-run average risk (i.e. steady-state variance).     

Capital depreciation and the underdetermination of rate of return: A unifying perspective

This paper shows that the notion of rate of return is best understood through the lens of the average-internal-rate-of-return (AIRR) model, first introduced in Magni (2010a). It is an NPV-consistent approach based on a coherent definition of rate of return and on the notion of Chisini mean, it is capable of solving the conundrums originated by the rate-of-return notion and represents a unifying theoretical paradigm under which every existing measure of wealth creation can be subsumed. We show that a rate of return is underdetermined by the project’s cash-flow stream; in particular, a unique return function (not a unique rate of return) exists for every project which maps depreciation classes into rates of return. The various shapes a rate of return can take on (internal rate of return, average accounting rate of return, modified internal rate of return, etc.) derive from the (implicit or explicit) selection of different depreciation patterns. To single out the appropriate rate of return for a project, auxiliary assumptions are needed regarding the project’s capital depreciation. This involves value judgment. On one side, this finding opens terrain for a capital valuation theory yet to be developed; on the other side, it triggers the creation of a toolkit of domain-specific and purpose-specific metrics that can be used, jointly or in isolation, for analyzing the economic profitability of a given project. We also show that the AIRR perspective has a high explanatory power that enables connecting seemingly unrelated notions and linking various disciplines such as economics, finance, and accounting. Some guidelines for practitioners are also provided.     

The Relevance and Value of Confucianism in Contemporary Business Ethics

This article examines the relevance and value of Confucian Ethics to contemporary Business Ethics by comparing their respective perspectives and approaches towards business activities within the modern capitalist framework, the principle of reciprocity and the concept of human virtues. Confucian Ethics provides interesting parallels with contemporary Western-oriented Business Ethics. At the same, it diverges from contemporary Business Ethics in some significant ways. Upon an examination of philosophical texts as well as empirical studies, it is argued that Confucian Ethics is able to provide some unique philosophical and intellectual perspectives in order to forge a richer understanding and analysis of the field of contemporary Business Ethics. Gary Kok Yew Chan is Assistant Professor of Law at Singapore Management University. Apart from Business Law, he teaches Ethics and Social Responsibility. He has obtained an LL.B (National University of Singapore) and LL.M (School of Oriental and African Studies, University of London) respectively and has published in several reputable law journals including Journal of Business Law, Cambridge Law Journal, Australian Journal of Asian Law, Hong Kong Law Journal and Singapore Journal of Legal Studies. In addition, he holds an M.A. in Southeast Asian Studies (National University of Singapore) and a B.A. in Philosophy (University of London).     

Testing for mean reversion in heteroskedastic data II: Autoregression tests based on Gibbs-sampling-augmented randomization

A decade ago Fama and French [Fama, E.G., French, K.R., 1988. Permanent and temporary components of stock prices. J. Political Econ. 96 (2) 246–273] estimated that 40% of variation in stock returns was predictable over horizons of 3–5 yr, which they attributed to a mean reverting stationary component in prices. While it has been clear that the Depression and war years exert a strong influence on these estimates, it has not been clear whether the large returns of that period contribute to the information in the data or rather are a source of noise to be discounted in estimation. This paper uses the Gibbs-sampling-augmented randomization methodology to address the problem of heteroskedasticity in estimation of multi-period return autoregressions. Extending the sample period to 1995, we find little evidence of mean reversion. Examining subsamples, only 1926–1946 provides any evidence of mean reversion, while the post war period is characterized by mean aversion. A test of structural change suggests that this difference between pre and post war periods is significant.     

Regime switching in stochastic models of commodity prices: An application to an optimal tree harvesting problem

This paper investigates whether a regime switching model of stochastic lumber prices is better for the analysis of optimal harvesting problems in forestry than a more traditional single regime model. Prices of lumber derivatives are used to calibrate a regime switching model, with each of two regimes characterized by a different mean reverting process. A single regime, mean reverting process is also calibrated. The value of a representative stand of trees and optimal harvesting prices are determined by specifying a Hamilton-Jacobi-Bellman Variational Inequality, which is solved for both pricing models using a implicit finite difference approach. The regime switching model is found to more closely match the behavior of futures prices than the single regime model. In addition, analysis of a tree harvesting problem indicates significant differences in terms of land value and optimal harvest thresholds between the regime switching and single regime models.