Estimating Portfolio and Consumption Choice: A Conditional Euler Equations Approach

This paper develops a nonparametric approach to examine how portfolio and consumption choice depends on variables that forecast time-varying investment opportunities. I estimate single-period and multiperiod portfolio and consumption rules of an investor with constant relative risk aversion and a one-month to 20-year horizon. The investor allocates wealth to the NYSE index and a 30-day Treasury bill. I find that the portfolio choice varies significantly with the dividend yield, default premium, term premium, and lagged excess return. Furthermore, the optimal decisions depend on the investor's horizon and rebalancing frequency.     

The Empirical Average Cost of Capital: A New Approach to Estimating the Cost of Corporate Funds

The authors develop a new way to measure the cost of capital, called the empirical average cost of capital (or “EACC”), which is consistent with existing methods of calculating the weighted average cost of capital, but uses information from the firm's financial statements and requires fewer and less subjective inputs. The authors’ model relies on the concept of economic profit while using data from the period 1990‐2012 on net operating profits and total capital to estimate the EACC at both the individual company and industry‐wide levels. Estimates of the EACC and rolling quarterly forecasts of future net operating profits for a single company, McDonald's, for its related industry, and for 57 other U.S. industries are compared to five conventional “textbook” estimates of the weighted average cost of capital published by Ibbotson Associates. The authors find that the EACC yields forecasts of future net operating profit after taxes that compare favorably to those of the five published measures of the weighted average cost of capital, as well as the average and median of these measures.     

A Factor Allocation Approach to Optimal Bond Portfolio

This paper proposes a new method to a bond portfolio problem in a multi-period setting. In particular, we apply a factor allocation approach to constructing the optimal bond portfolio in a class of multi-factor Gaussian yield curve models. In other words, we consider a bond portfolio problem in terms of a factors’ allocation problem. Thus, we can obtain clear interpretation about the relation between the change in the shape of a yield curve and dynamic optimal strategy, which is usually hard to be obtained due to high correlations among individual bonds. We first present a closed form solution of the optimal bond portfolio in a class of the multi-factor Gaussian term structure model. Then, we investigate the effects of various changes in the term structure on the optimal portfolio strategy through series of comparative statics.     

Portfolio Capital Flows in Thailand: A Bayesian Model Averaging Approach

We study the gross and net terms of portfolio capital flows by examining their determinants. Through the application of the Bayesian model averaging method, the determinants are evaluated by a set of models instead of a single specification. Our findings show that the magnitude of both gross equity and gross debt flows are large, relative to their net terms. Equity inflows and outflows are quite symmetric with similar determinants; debt inflows and outflows are less symmetric. The paper provides partial evidence to support the importance of both internal and external factors as determinants of capital flows.     

Portfolio Analysis Using Single Index,Multi-Index,and Constant Correlation Models: A Unified Treatment

In this study a simple common algorithm which is applicable to seven models is proposed for optimal portfolio selection disallowing short sales of risky securities. The models considered in the analysis consist of a single index model, four multi-index models, and two constant correlation models. Unlike the previous approach, the proposed algorithm does not require explicit ranking of securities. Therefore, it is particularly useful for two multi-index models with orthogonal indices which do not provide any ranking criterion. Also, because of its algorithmic efficiency as demonstrated in a simulation study on models with multiple groups, the approach here can enhance their usefulness in portfolio analysis.     

A Benchmark Approach to Portfolio Optimization under Partial Information

This paper proposes a filtering methodology for portfolio optimization when some factors of the underlying model are only partially observed. The level of information is given by the observed quantities that are here supposed to be the primary securities and empirical log-price covariations. For a given level of information we determine the growth optimal portfolio, identify locally optimal portfolios that are located on a corresponding Markowitz efficient frontier and present an approach for expected utility maximization. We also present an expected utility indifference pricing approach under partial information for the pricing of nonreplicable contracts. This results in a real world pricing formula under partial information that turns out to be independent of the subjective utility of the investor and for which an equivalent risk neutral probability measure need not exist.      

Applications of the Integrated Approach to International Portfolio Optimization

In a recent paper, we used a stock-bond integrated model to construct aninternationally diversified portfolio using historical data of stocksand bonds of Japan and the U.S. The result of computational experiments using this integrated approach showed that it can serve as a morereliable and lessexpensive method than the traditional asset allocation strategy. In this paper, we present the results of subsequent experiments using the dataof more than 700 stocks and bonds of six countries: U.S., U.K., Germany, France, Hong Kong, and Japan. In these experiments, we compared the direct historical data method and the betapricing method in order to estimate the expected rate of return of assets. Anotherimportant feature is the use of a new strategy for hedging the exchange raterisk by using historical data to calculate the hedge rate on currencies. Computational experiments show a remarkable improvement over the resultspresented in [9]. Also, the result of the simulation shows that the beta pricing model leads to a better and more stable performance than the direct historical data method.     

Portfolio Optimization under Solvency Constraints: A Dynamical Approach

We develop portfolio optimization problems for a nonlife insurance company seeking to find the minimum capital required that simultaneously satisfies solvency and portfolio performance constraints. Motivated by standard insurance regulations, we consider solvency capital requirements based on three criteria: ruin probability, conditional Value-at-Risk, and expected policyholder deficit ratio. We propose a novel semiparametric formulation for each problem and explore the advantages of implementing this methodology over other potential approaches. When liabilities follow a Lognormal distribution, we provide sufficient conditions for convexity for each problem. Using different expected return on capital target levels, we construct efficient frontiers when portfolio assets are modeled with a special class of multivariate GARCH models. We find that the correlation between asset returns plays an important role in the behavior of the optimal capital required and the portfolio structure. The stability and out-of-sample performance of our optimal solutions are empirically tested with respect to both the solvency requirement and portfolio performance, through a double rolling window estimation exercise.     

Principles of Financial Regulation: A Dynamic Portfolio Approach

Economists seeking explanations for the global financial crisisof 1997–99 are reaching consensus that a major factorwas weak financial institutions, which resulted in part frominadequate government regulations. At the same time many developingcountries are struggling with an overregulated financial system—onethat stifles innovation and the flow of credit to new entrepreneursand that can stunt the growth of well-established firms. Inparticular, too many countries are relying excessively on capitaladequacy standards, which are inefficient and sometimes counterproductive.The author argues that financial systems can be reformed successfullyusing a "dynamic portfolio approach" aimed at managing the incentivesand constraints that affect not only financial institutions'exposure to risk but also their ability to cope with it. Thearticle sets out general principles of financial regulationand shows how the dynamic portfolio approach can help countriesdeal with the special problems that arise during the transitionto a more liberalized economy as well as those that arise indealing with a financial crisis similar to the 1997 crisis inEast Asia.      

A Simulation Approach to Dynamic Portfolio Choice with an Application to Learning About Return Predictability

We present a simulation-based method for solving discrete-timeportfolio choice problems involving non-standard preferences,a large number of assets with arbitrary return distribution,and, most importantly, a large number of state variables withpotentially path-dependent or non-stationary dynamics. The methodis flexible enough to accommodate intermediate consumption,portfolio constraints, parameter and model uncertainty, andlearning. We first establish the properties of the method forthe portfolio choice between a stock index and cash when thestock returns are either iid or predictable by the dividendyield. We then explore the problem of an investor who takesinto account the predictability of returns but is uncertainabout the parameters of the data generating process. The investorchooses the portfolio anticipating that future data realizationswill contain useful information to learn about the true parametervalues.     

A General Equilibrium Model of International Portfolio Choice

We investigate, in a two-country general equilibrium model, whether a bias in consumption towards domestic goods will necessarily lead to a preference for domestic securities. We develop a model where investors are constrained to consume only from their domestic capital stock and where it is costly to transfer capital across countries. In this model, investors less risk averse than an investor with log utility bias their portfolios towards domestic assets. Investors more risk averse than log, however, prefer foreign assets. Thus, this model suggests that it is unlikely that the portfolios observed empirically can be explained by the high proportion of domestic goods in total consumption.     

Markowitz投资组合模型的最小二乘算法

本文从一个新的视角来研究Markowitz均值—方差模型。通过将Markowitz均值—方差模型表述为约束最小二乘问题,继而使用约束最小二乘问题的算法研究了协方差矩阵正定和半正定时模型的求解问题,我们给出了计算投资组合有效前沿及最小方差组合的新算法。实证分析表明：最小二乘算法在计算稳定和计算速度方面优于传统算法。     

A Note on Option Pricing for the Constant Elasticity of Variance Model

We study the arbitrage free optionpricing problem for the constant elasticity of variance (CEV) model. To treatthestochastic aspect of the CEV model, we direct attention to the relationship between the CEV modeland squared Bessel processes. Then we show the existence of a unique equivalentmartingale measure and derive the Cox's arbitrage free option pricing formulathrough the properties of squared Bessel processes. Finally we show that the CEVmodel admits arbitrage opportunities when it is conditioned to be strictlypositive.     

An Extension of Spatial Dependence Models for Estimating Short-Term Temperature Portfolio Risk

Temperature risk is any adverse financial outcome caused by temperature outcomes. The Chicago Mercantile Exchange lists a series of financial products that link payments to temperature outcomes, and these products can help buyers manage temperature risk. Financial institutions can also hold a portfolio of these products as counterparty to the buyers facing temperature risk. Here we take an actuarial perspective to measuring the risk by modeling the daily temperatures directly. These models are then used to simulate distributions of future temperature outcomes. The model for daily temperature is a spatial ARMA-EGARCH statistical model that incorporates dependence in both time and space, in addition to modeling the volatility. Simulations from this model are used to build up distributions of temperature outcomes, and we demonstrate how actuarial risk measures of the portfolio can then be estimated from these distributions.     

Z-score模型最优分割点的确定方法比较——基于违约风险预测能力的分析

Z-score模型在对企业进行财务困境和违约风险判别方面具有重要的应用价值,最优分割点的确定方法对于提高模型的违约风险判别能力至关重要.本文以医药生物行业上市公司为样本,运用Fisher逐步判别法从15类财务比率中筛选出判别能力较强的7个指标构建了Z-score模型,并尝试采用加权平均法和考虑先验概率及误判成本的ZETAc模型法分别确定最优分割点.研究发现,ZETAc模型法预测企业违约风险的能力明显优于加权平均法.     

A Shrinkage Approach to Model Uncertainty and Asset Allocation

This article takes a shrinkage approach to examine the empiricalimplications of aversion to model uncertainty. The shrinkageapproach explicitly shows how predictive distributions incorporatedata and prior beliefs. It enables us to solve the optimal portfoliosfor uncertainty-averse investors. Aversion to uncertainty aboutthe capital asset pricing model leads investors to hold a portfoliothat is not mean-variance efficient for any predictive distribution.However, mean-variance efficient portfolios corresponding toextremely strong beliefs in the Fama–French model areapproximately optimal for uncertainty-averse investors. Theempirical Bayes approach does not result in optimal portfoliosfor investors who are averse to model uncertainty.