Portfolio Selection with Quadratic Utility Revisited

Considering a simple portfolio selection problem by agents with quadratic utility, an apparently counterintuitive outcome results. When such a choice is over two assets that can be ordered in terms of riskiness, an agent that is more risk averse may optimally invest a larger portion of wealth in the riskier asset. It is shown that such an outcome is not counterintuitive, since for the portfolios from which agents optimally choose, a larger proportion of investment in the riskier asset leads to a less risky portfolio.     

The Post‐Cost Profitability of Momentum Trading Strategies: Further Evidence from the UK

This paper examines the post‐cost profitability of momentum trading strategies in the UK over the period 1988–2003 and provides direct evidence on stock concentration, turnover and trading cost associated with the strategy. We find that after factoring out transaction costs the profitability of the momentum strategy disappears for shorter horizons but remains for longer horizons. Indeed, for ranking and holding periods up to 6‐months, profitable momentum returns would not be available to most average investors as the cost of implementation outweighs the possible returns. However, we find post‐cost profitability for ranking and/or holding periods beyond 6 months as portfolio turnover and its associated cost reduces. We find similar results for a sub‐sample of relatively large and liquid stocks.     

Investment Horizon Effects

Abstract:   Boudry and Gray (2003) have documented that the optimal buy‐and‐hold demand for Australian stocks is not necessarily increasing in the investment horizon when returns are predictable. Such finding is in contrast with Barberis (2000) who shows that positive monotonic horizon effects predominate for US stocks. Using a closed‐form approximation to the asset allocation problem, this paper relates the return dynamics to the investor's portfolio choice for different investment horizons. In the special case of a single risky asset, it is shown that return predictability under stationarity may induce both positive and negative horizon effects in the optimal allocation to the risky asset. The paper extends previous empirical results by solving for the optimal portfolio when two risky assets with predictable returns are available for investment.     

Active investment manager portfolios and preferences for stock characteristics

The present study investigates the stock characteristic preferences of institutional Australian equity managers. In aggregate we find that active managers exhibit preferences for stocks exhibiting high‐price variance, large market capitalization, low transaction costs, value‐oriented characteristics, greater levels of analyst coverage and lower variability in analyst earnings forecasts. We observe stronger preferences for higher volatility, value stocks and wider analyst coverage among smaller stocks. We also find that smaller investment managers prefer securities with higher market capitalization and analyst coverage (including low variation in the forecasts of these analysts). We also document that industry effects play an important role in portfolio construction.     

Portfolio Selection under Maximum Minimum Criterion

In this paper, we studied the problem of risky portfolio selection under uncertainty. Different from risk-return analytical methodology, we formulated a model under maximum minimal criterion of uncertain decision-making theory. If the investor had no any distribution information of the returns and (s)he knew the variation scopes of the returns by his/her knowledge of the market information or experts’ evaluations of the alternative risky assets, then we showed that the optimal portfolio strategy of the model under maximal minimal criterion could be obtained by solving linear programming. If the returns were known to be normal distributed, the investor’s optimal portfolio strategy could be obtained by solving a nonlinear programming. The paper also provided an algorithm to solve this programming. At last, the paper compared this model with Markowitz’s mean-varience (M-V) model and Young’s minmax model, and pointed out the distinctions and similarities between our model and the other two. Supported in part by Program for NCET, in part by the Key Project of Chinese Ministry of Education 104053.     

资本跨国双向流动:理论与现实

近年来,在国际资本流动领域中出现了一个较为特殊的现象:发展中国家的资本流向发达国家,而发达国家的资本投向发展中国家,传统的国际投资理论难以对此做出有力的解释.文章对近期国外关于资本跨国双向流动的理论进行回顾,比较典型的有资产组合理论、超国民待遇理论和财富效应理论,在介绍这些理论的基础上,考察这些理论在中国的适用性,从而探索中国当前的资本跨国双向流动的理论成因.     

浅谈风险投资的管理咨询力度与投资组合规模

为企业提供咨询。虽然能快速帮助企业成长起来。但同时也是一项消耗资源的的活动，需要为企业提供专业的人才和时间，这就产生了运行成本。如何在这个成本与收益之间形成均衡，是最重要的工作。而本文认为，以风险投资公司的管理咨询力度来确定其所投资的风险企业的数量比反过来的确定方式更为合理。     

MONOTONICITY PROPERTIES OF OPTIMAL INVESTMENT STRATEGIES FOR LOG-BROWNIAN ASSET PRICES

Consider the geometric Brownian motion market model and an investor who strives to maximize expected utility from terminal wealth. If the investor's relative risk aversion is an increasing function of wealth, the main result in this paper proves that the optimal demand in terms of the total wealth invested in a given risky portfolio at any date is decreasing in absolute value with wealth. The proof depends on the functional form of the Brunn–Minkowski inequality due to Prékopa.     

A new approach to assessing model risk in high dimensions

A central problem for regulators and risk managers concerns the risk assessment of an aggregate portfolio defined as the sum of d individual dependent risks $X_i$. This problem is mainly a numerical issue once the joint distribution of $\left(X_1\text{,}{X}_2\text{,}\dots \text{,}{X}_d\right)$ is fully specified. Unfortunately, while the marginal distributions of the risks $X_i$ are often known, their interaction (dependence) is usually either unknown or only partially known, implying that any risk assessment of the portfolio is subject to model uncertainty.Previous academic research has focused on the maximum and minimum possible values of a given risk measure of the portfolio when only the marginal distributions are known. This approach leads to wide bounds, as all information on the dependence is ignored. In this paper, we integrate, in a natural way, available information on the multivariate dependence. We make use of the Rearrangement Algorithm (RA) of Embrechts et al. (2013) to provide bounds for the risk measure at hand. We observe that incorporating the information of a well-fitted multivariate model may, or may not, lead to much tighter bounds, a feature that also depends on the risk measure used. In particular, the risk of underestimating the Value-at-Risk at a very high confidence level (as used in Basel II) is typically significant, even if one knows the multivariate distribution almost completely.Our results make it possible to determine which risk measures can benefit from adding dependence information (i.e., leading to narrower bounds when used to assess portfolio risk) and, hence, to identify those situations for which it would be meaningful to develop accurate multivariate models.     

Skewed distributions in finance and actuarial science: a review

That the returns on financial assets and insurance claims are not well described by the multivariate normal distribution is generally acknowledged in the literature. This paper presents a review of the use of the skew-normal distribution and its extensions in finance and actuarial science, highlighting known results as well as potential directions for future research. When skewness and kurtosis are present in asset returns, the skew-normal and skew-Student distributions are natural candidates in both theoretical and empirical work. Their parameterization is parsimonious and they are mathematically tractable. In finance, the distributions are interpretable in terms of the efficient markets hypothesis. Furthermore, they lead to theoretical results that are useful for portfolio selection and asset pricing. In actuarial science, the presence of skewness and kurtosis in insurance claims data is the main motivation for using the skew-normal distribution and its extensions. The skew-normal has been used in studies on risk measurement and capital allocation, which are two important research fields in actuarial science. Empirical studies consider the skew-normal distribution because of its flexibility, interpretability, and tractability. This paper comprises four main sections: an overview of skew-normal distributions; a review of skewness in finance, including asset pricing, portfolio selection, time series modeling, and a review of its applications in insurance, in which the use of alternative distribution functions is widespread. The final section summarizes some of the challenges associated with the use of skew-elliptical distributions and points out some directions for future research.