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.     

A Stochastic Correlation Model with Mean Reversion for Pricing Multi-Asset Options

We set up a new kind of model to price the multi-asset options. A square root process fluctuating around its mean value is introduced to describe the random evolution of correlation between two assets. In this stochastic correlation model with mean reversion term, the correlation is a random walk within the region from −1 to 1, and it is centered around its equilibrium value. The trading strategy to hedge the correlation risk is discussed. Since a solution of high-dimensional partial differential equation may be impossible, the Quasi-Monte Carlo and Monte Carlo methods are introduced to compute the multi-asset option price as well. Taking a better-of two asset rainbow as an example, we compare our results with the price obtained by the Black–Scholes model with constant correlation.     

Asymmetric Mean Reversion in European Interest Rates: A Two-factor Model

Abstract

This paper tests for asymmetric mean reversion in European short-term interest rates using a combination of the interest rate models introduced by Longstaff and Schwartz (Longstaff, F.A., Schwarts, E.S. (1992) Interest rate volatility and the ferm structure: A two factor general equilibrium model, Journal of Finance, 48, pp. 1259–1282.) and Bali (Bali, T. (2000) Testing the empirical performance of stochastic volatility models of the short-term interest rates, Journal of Financial and Quantitative Analysis, 35, pp. 191–215.). Using weekly rates for France, Germany and the United Kingdom, it is found that short-term rates follow in all instances asymmetric mean reverting processes. Specifically, interest rates exhibit non-stationary behavior following rate increases, but they are strongly mean reverting following rate decreases. The mean reverting component is statistically and economically stronger thus offsetting non-stationarity. Volatility depends on past innovations past volatility and the level of interest rates. With respect to past innovations volatility is asymmetric rising more in response to positive innovations. This is exactly opposite to the asymmetry found in stock returns.     

The augmented Black–Litterman model: a ranking-free approach to factor-based portfolio construction and beyond

The Fama and French factor-ranking approach (1992, 1993, etc.) has been extensively applied in quantitative fund management. However, this approach suffers from hidden factor view, information inefficiency, etc. issues. Based on the Black–Litterman model (1992; as explained in Cheung 2010b Cheung, W. 2010b. The Black–Litterman model explained. J. Asset Mgmt., 11: 229–243. [Crossref] , [Google Scholar]), we develop a technique that endogenizes the ranking process and elegantly resolves these issues. This model explicitly seeks forward-looking factor views and smoothly blends them to deliver robust allocation to securities. Our numerical experiments show this is an intuitive and practical framework for factor-based portfolio construction, and beyond. This article features: (1) a new and unified framework for strategy combination, factor mimicking and security-specific bets; (2) an elegant and ranking-free approach to factor style construction; (3) worked examples based on the FTSE EUROTOP 100 universe; (4) insight into the classic issue of confidence parameter setting; and (5) implementation guidance in an appendix.     

FM遥测解调自动极性纠反功能的改进设计

针对FM遥测解调在高误码条件下出现的极性误反转问题,从传输信道不同的高低差变 频方式会导致频谱反转进而导致解调极性反转出发,引出了自动极性纠反功能的设计背景。 通过详述帧极性检测标识在搜索和校核、锁定两种不同状态下的判决逻辑,分析了原自动极 性纠反功能的设计原理,结合模拟验证试验,揭示了原判决逻辑在帧极性检测标识第二次判 1过程中不够严格,未考虑到高误码也可造成反码出现后帧极性检测标识被误判1的设计缺陷 。将帧极性检测标识第二次判1逻辑改进为异或累加结果超过帧同步码组长的一半而非滑动 相关峰值,解决了缺陷问题又兼顾了检测的快速性,通过改进后的验证试验证明了改进设计 的正确性和有效性。     

On Estimators of the Nearest Neighbour Distance Distribution Function for Stationary Point Processes

There are three approaches for the estimation of the distribution function D(r) of distance to the nearest neighbour of a stationary point process: the border method, the Hanisch method and the Kaplan-Meier approach. The corresponding estimators and some modifications are compared with respect to bias and mean squared error (mse). Simulations for Poisson, cluster and hard-core processes show that the classical border estimator has good properties; still better is the Hanisch estimator. Typically, mse depends on r, having small values for small and large r and a maximum in between. The mse is not reduced if the exact intensity λ (if known) or intensity estimators from larger windows are built in the estimators of D(r); in contrast, the intensity estimator should have the same precision as that of λ D(r). In the case of replicated estimation from more than one window the best way of pooling the subwindow estimates is averaging by weights which are proportional to squared point numbers.     

特质波动、风险溢价与学习效应

本文是一项实证研究,分析中国证券市场中股票特质波动性(Idiosyn-cratic Volatility)的风险溢价问题。我们发现较高波动性的投资组合在下一期收益率反而较低,为了解释这个看起来反常的现象,我们引入投资人逐步了解、发现上市公司盈利能力的学习过程。类似Lucas(1978)的一般均衡定价公式说明,不完全信息和学习过程会导致股票价格出现均值回归的现象(Mean Reversion),并且盈利能力不确定性越高的公司,股价向均值回归的趋势越明显,由此导致下一期收益率的反转。