Interval portfolio selection models within the framework of uncertainty theory

The expected returns for securities are traditionally estimated as crisp values. Since the improper values may bring on an unsuccessful investment decision, portfolio experts generally prefer offering interval estimations for expected returns rather than crisp ones. The portfolio selection problem with interval expected returns is widely studied recently. In this paper, by considering the security returns with interval expected returns as uncertain variables, a mean-semiabsolute deviation model is proposed within the framework of uncertainty theory, which is a crisp nonlinear programming model and can be well solved by the classical optimization algorithms. In order to illustrate the method, some numerical experiments are given and solved.     

Multi-period portfolio optimization under possibility measures

A single-period portfolio selection theory provides optimal tradeoff between the mean and the variance of the portfolio return for a future period. However, in a real investment process, the investment horizon is usually multi-period and the investor needs to rebalance his position from time to time. Hence it is natural to extend the single-period fuzzy portfolio selection to the multi-period case based on the possibility theory. In this paper, we propose the possibilistic expected value and variance for the terminal wealth with fuzzy forms after T periods by using the central value operator. Classes of multi-period possibilistic mean-variance models are formulated originally under the assumption that the proceeds of risky assets are fuzzy variables. Besides, we apply a particle swarm optimization algorithm to solve the proposed multi-period fuzzy portfolio selection models. A numerical example is given to illustrate the performance of the proposed models and algorithm.     

Risk index based models for portfolio adjusting problem with returns subject to experts' evaluations

This paper discusses a portfolio adjusting problem with additional risk assets and a riskless asset in the situation where security returns are given by experts' evaluations rather than historical data. Uncertain variables are employed to describe the security returns. Using expected value and risk index as measurements of portfolio return and risk respectively, we propose two portfolio optimization models for an existing portfolio in two cases, taking minimum transaction lot, transaction cost, and lower and upper bound constraints into account. In one case the riskless asset can be both borrowed and lent freely, and in another case the riskless asset can only be lent and the borrowing of riskless asset is not allowed. The adjusting models are converted into their crisp equivalents, enabling the users to solve them with currently available programming solvers. For the sake of illustration, numerical examples in two cases are also provided. The results show that under the same predetermined maximum tolerable risk level the expected return of the optimal portfolio is smaller when the riskless asset can only be lent than when the riskless asset can be both borrowed and lent freely.     

Optimal diversification and risk-taking: a theoretical and empirical analysis

Among the justifications for capital property income received by private households is that it is a ‘return to risk-taking’. However, portfolio diversification provides an obvious means toward the reduction of risk. Moreover, it is widely believed that the wealthier the household, the more diversification it practices: the larger tends to be the proportion of its total portfolio allocated to publicly traded stock, and the larger tends to be the number of individual stock issues included in its portfolio. Using a simple ‘homogeneous securities’ model, explicit functional forms are obtained for both the optimal proportion of the portfolio allocated to stocks, and the optimal number of individual stock issues in the portfolio. Empirical evaluation of these theoretical results, using a dataset derived from the 2004 Survey of Consumer Finances (SCF), lends substantial support to the model. Applying these empirical results, it is found that as household capital wealth increases, expected capital income increases while simultaneously a reasonable risk indicator (the probability of incurring a negative return on the capital portfolio) decreases owing to the higher level of portfolio diversification. This indication casts significant doubt on the ‘return to risk-taking’ justification for capital property income received by wealthy private households.     

多维认知偏差投资风险能量密度模型探究

金融全球化下,金融活动的参与主体逐步多样化,投资者的认知偏差加剧了证券投资活动中风险度量的难度。现有的金融证券投资的理论研究与实践应用基本都是围绕着如何处理风险与收益的关系而展开的。但是,传统的理论方法与标准的金融风险度量方法在一定程度上忽略了人的心理认知行为等因素的影响,使得对现有的风险度量工具和方法的借鉴与应用增加了投资者额外的决策风险。鉴于此,本文引入心理行为因素的时间变量,在理论研究与投资者认知行为研究的基础上,借助物理学中能量密度相关理论与思想方法构建多认知偏差的时间风险度量模型,度量金融投资活动中基于多种偏差的投资组合风险,克服了传统风险度量方法在完全理性人条件下主要依赖于历史数据推导的缺陷,从而使得证券组合的风险度量更接近于实际的证券投资组合状况。最后文章根据模型分析提出相关政策建议。     

综合收益最优的贷款组合鲁棒优化模型

商业银行信贷经营的基本目标是资金来源与运用在效益性、安全性和流动性上的“三性”平衡,而贷款组合优化配置是商业银行维持或达到资金“三性”平衡的有效方式,也是商业银行信贷经营管理中的重要内容.而贷款的预期收益具有不确定性,如果简单地假设其预期收益率往往会出现与实际脱节的情况,因此需要考虑贷款期间可能出现的变化.针对这一特征,考虑构建风险调整后资本收益率(RAROC)最优的贷款组合鲁棒优化模型.根据某商业银行实际经营数据进行数值分析,结果表明该模型具有鲁棒性,不仅能够兼顾贷款组合综合收益以及未来收益的不确定性因素,同时还可以在贷款组合风险约束范围内获得最大收益,为商业银行贷款优化配置管理提供有效可行的决策依据.     

基于截集的加权可能性均值-方差模型

本文以模糊数的截集为切入点,给出随机变量取值为模糊数时基于截集的加权可能性均值、加权可能性方差和加权可能性协方差的定义,研究了基于截集的加权可能性均值、加权可能性方差和加权可能性协方差的性质,给出三角模糊数的基于截集的加权可能性均值、加权可能性方差和加权可能性协方差的具体形式.并以基于截集的加权可能性均值作为证券组合投资收益率为模糊数时投资未来收益的度量,以基于截集的加权可能性方差作为证券组合投资收益率为模糊数时投资风险的度量,以基于截集的加权可能性协方差作为不同资产之间相关程度的度量,以不同的权重表示不同投资者的对投资收益的风险偏好程度,构建基于模糊数截集的加权可能性均值-方差组合投资模型,给出模型的求解方法.最后将基于截集的加权可能性均值-方差模型与传统的均值-方差模型进行了比较分析,并结合我国证券交易市场的具体实例说明该模型的应用价值.     

Empirical tests on the asset pricing model with liquidity risk: An unobserved components approach

The aim of this paper is to test empirically the conditional liquidity-adjusted capital asset pricing model (L-CAPM) developed by Acharya and Pedersen (2005). Accordingly, we propose to estimate the L-CAPM using unobserved components methodology, which allows us to take into account the main stylized facts characterizing liquidity. Based on a sample of firms listed on the NASDAQ, our empirical analysis reveals several findings. Firstly, we show that liquidity is time-varying and exhibits strong seasonality. Secondly, we highlight the impact of the liquidity level premium on asset prices. Thirdly, we show that the most important liquidity risk is related to the covariance between portfolio illiquidity and market returns. Fourthly, we observe a negative relationship between portfolio returns and market illiquidity. Fifthly, we find that liquidity risk and illiquidity level are not always positively correlated.     

艺术品的金融属性：投资收益与资产配置*

本文基于2000—2014年中国艺术品拍卖市场近现代国画的微观数据,在资产配置中引入市场交易机制中的佣金变量,加入艺术品市场规模约束,采用重复交易法实证计量嵌入艺术品市场的投资收益特征并量化其资产配置效应,以测度其市场功能。优质的艺术精品具备金融资产风险和收益的基本特征,本文对艺术品资产与资本资产定价模型的适应性进行讨论。研究表明：在样本期内,剔除通胀和佣金成本因素后收益率更加贴近现实,中国艺术品投资的实际收益率水平为1308%,表现出高于欧美市场的投资溢价;艺术品投资与传统的股票、债券等金融资产之间表现出相对独立性,并能有效改善投资者资产组合的风险边界,可以成为资产配置优化和多样化的重要选择。中国艺术品市场的长期稳健发展将为投资者提供更多的资产优化产品和工具。     

Risk Diversification on the Polish Capital Market

The basics of portfolio management theory and methods of efficient selection of assets and their financing have been created by Markowitz and Sharpe. They propose that risk diversification consists, generally speaking, of the increase in the number of securities in a portfolio. So, authors try to answer the question of how many securities have to be bought on a given market to assure a well-diversified portfolio, where the increase in the number of securities does not lead to a significant decrease in portfolio risk. To evaluate such a purpose on the Polish capital market, 20 companies were surveyed that are included in the WIG20 index in the period January 2–October 10, 2001. The returns were estimated on a weekly basis. The research shows that a portfolio of securities constructed, according to the Sharpe Model, has a wide application to the Polish capital market.*University of Szczecin—Poland. This paper was presented at the Fifty-Eighth InternationalAtlantic Economic Conference, October 6Y9, 2005, Chicago, U.S.A.     

Liquidity shocks and equilibrium liquidity premia

We study an equilibrium in which agents face surprise liquidity shocks and invest in liquid and illiquid riskless assets. The random holding horizon from liquidity shocks makes the return of the illiquid security risky. The equilibrium premium for such risk depends on the constraint that agents face when borrowing against future income; it is insignificant without borrowing constraint, but can be very high with borrowing constraint. Illiquidity, therefore, can have large effects on asset returns when agents face liquidity shocks and borrowing constraints. This result can help us understand why some securities have high liquidity premia, despite low turnover frequency.     

数据交易市场双边匹配模型与决策方法研究

针对平台视角下的数据交易供需双边匹配问题,基于双边匹配理论,提出了考虑模糊语言评价信息、区间数评价信息和0-1评价信息的混合型多属性匹配决策方法并定义了属性匹配满意度函数。以供需主体最大匹配满意度为目标,构建了数据交易供需双边匹配的多目标优化模型,并设计模型求解算法,将多目标化模型转化为单目标线性规划模型进行求解,以获取匹配结果。结果表明,通过对供需双方需求信息的详细分析,双边匹配结果能在最大程度上满足双方需求,同时,优化模型具有合理性及有效性。     

Liquidity risk and bank portfolio management in a financial system without deposit insurance: Empirical evidence from prewar Japan

Using data from prewar Japan, this paper investigates the impact of a liquidity shock induced by depositors' behavior on bank portfolio management during financial crises in a system lacking deposit insurance. It is found that banks reacted to the liquidity shock sensitively through an increase in their cash holdings not by liquidating bank loans but by selling securities in the financial market. Moreover, banks exposed to local financial contagion adjusted the liquidity of their portfolio mainly by actively selling and buying their securities in the financial market. Finally, there is no evidence to conclude that the existence of the lender of last resort mitigated the liquidity constraints in bank portfolio adjustments.     

Fuzzy possibilistic portfolio selection model with VaR constraint and risk-free investment

We propose a possibilistic portfolio model with VaR constraint and risk-free investment based on the possibilistic mean and variance, while assuming that the expected rate of returns is a fuzzy number. The model shows more clearly that, in the financial market affected by several non-probabilistic factors, risk-averse investors wish not only to reach the expected rate of returns in their actual investment, but also to assure that the maximum of their possible future risk is lower than an expected loss. Under the condition that the expected rate of returns is a normal distribution fuzzy variable, we proposed a theorem as the solution, and derive a crisp equivalent form of the possibilistic portfolio under constraints of VaR and risk-free investment. This model is an expansion of the fuzzy possibilistic mean–variance model by Zhang (2007). Finally, an empirical study is carried out using the data concerning some stocks of various industries listed at the Shanghai Stock Exchange. A conclusion is reached that the investors are able to choose a portfolio more suitable to them under the VaR constraint.     

The Role of Industry Effects in Simultaneous Reversal and Momentum Patterns in One-Month Stock Returns

When stocks are ranked by returns in one month, the portfolio of loser stocks tends to outperform the portfolio of winner stocks in the subsequent month. Yet industry portfolios tend to display momentum. We develop a model of information diffusion among agents with constrained information processing ability that reconciles these well-documented phenomena. We test whether this model or the overreaction hypothesis is consistent with the data. Additionally, a trading strategy based on the model outperforms strategies based on overreaction and on industry momentum. The strategy produces abnormal returns while controlling for market–risk and the size, book value, January, momentum, and liquidity effects.     

Global idiosyncratic risk moments

We investigate a global cross-sectional relation between idiosyncratic risk moments and expected stock returns by suggesting three global idiosyncratic volatility, skewness, and kurtosis risk factors. We also suggest two global small minus big and high minus low risk proxies for estimating return residuals of the test assets from a global asset pricing model. To perform robustness checks, we suggest other four global risk factors of momentum, leverage, bid-ask spread, and liquidity. We find a significant negative relation between stock portfolio returns and the global moments, and the cross section of stock returns reflects a significant negative price of risk for global idiosyncratic skewness (?0.13%) and idiosyncratic volatility (?1.85%) and a positive and significant price of risk for global idiosyncratic kurtosis. We find that our suggested risk factors are key drivers of risk premia in stock market and are robust to various checks. These factors also can forecast the gross domestic product growth over the sample period.     

Integrated Risk Management with a Filtered Bootstrap Approach

We present a multi-period risk model to measure portfolio risk that integrates market risk, credit risk and, in a simplified way, liquidity risk. Thus, it overcomes the major limitation currently shared by many risk models that are unable to give a complete picture of all portfolio risks according to a single, coherent framework. The model is based on the Filtered Bootstrap approach; hence, it captures conditional heteroskedasticity, serial correlation and non-normality in the risk factors, that is, most of the features of observed financial time series. Being a simulation risk model, it copes in a natural way with derivatives as it allows the full valuation of the probability density function of the contracts. In addition, it is a suitable and flexible way to generate future scenarios on medium‐term horizons, so this model is particularly appropriate for asset management companies.     

Inducing liquidity in thin financial markets through combined-value trading mechanisms

Asset pricing theory hypothesizes that investors are only interested in portfolios; individual securities are evaluated only in terms of their contribution to portfolio risk and return. Yet, standard financial market design is that of parallel, unconnected markets, whereby investors cannot submit orders in one market conditional on events in others. When markets are thin, this exposes them to substantial execution risk. Fear of ending up with unbalanced portfolios after trading may even keep investors from submitting orders, further eroding liquidity and the ability of markets to equilibrate. The suggested solution is a portfolio trading mechanism referred to as combined-value trading (CVT). Investors are allowed to submit orders for packages of securities and the system matches trades and computes prices by optimally combining portfolio orders in an open book. We study the performance of the CVT mechanism experimentally and compare it to the performance of parallel, unconnected double auctions in experiments with similar parametrization and either a similar number of subjects or substantially thicker markets. We present evidence that our portfolio trading mechanism facilitates equilibration to the extent that the thicker markets do. Inspection of order submission and trade activity reveals that subjects manage to exploit the direct linkages between markets enabled by the CVT system.     

International asset prices and portfolio choices under Bayesian learning

We calculate equilibrium asset prices and portfolio choices from a two-country OLG international asset pricing model under the assumption that investors are on a Bayesian learning path. Investors from both countries receive identical information flows, but domestic investors start off with less precise priors concerning foreign fundamentals. Learning is shown to produce first-order effects on the properties of asset prices, in the form of increased equity returns, volatility clustering, and time-varying correlations across national stock markets. Moreover, on a learning path, estimation risk generates portfolio biases similar to those observed empirically, i.e. a strong preference towards domestic securities and excessive turnover in foreign securities. These findings are robust to changes in prior beliefs, the calibration of initial information asymmetries, and the parameterization of the model. We use real GDP data for the US and Europe to calibrate the model and show that in the event of a financial liberalization during the 1970s, high excess returns, time-varying volatility, substantial home bias, and excess turnover should have been observed.     

Annuities, Bequests, and Portfolio Diversification

In this article, the diversification motives of the demand for annuities is analyzed. Using a model allowing for the uncertainty of both the human life length and the interest rate, the Decision Maker is supposed to choose an optimal portfolio to maximize a bequest. Conditions under which an increase in the risk of bond returns increase the demand for annuities are proposed and discussed. Moreover, it is shown that, contrary to previous claims, more risk adversion is associated with a lower demand for annuities.