A novel LASSO – TLBO – SVR hybrid model for an efficient portfolio construction

In this study a LASSO – TLBO – SVR hybrid model is used for portfolio construction. Relevant economic parameters are determined and used for stock selection. Along with stock selection, weights for the stocks are obtained by solving a portfolio optimization problem using three methods: GRG Nonlinear, Evolutionary method based on Genetic Algorithm, and Equal weight method. The portfolio return in the proposed model is compared with the return of the Indian market portfolio (NSE and BSE). It is observed that the proposed model outperforms the market portfolio.     

考虑投资组合收益率完全分布信息的投资组合优化研究

前四阶矩并不能完全决定收益率服从何种分布,因而对于偏好某种特定分布的投资者而言,以往的高阶投资组合优化方法并不适用,应当进行考虑投资组合收益率完全分布信息的投资组合优化。本文提出了一种考虑投资组合收益率完全分布信息的投资组合优化方法,通过Gram-Charlier渐进展开来近似投资组合收益率的概率密度函数,以KL散度来度量投资组合收益率的概率密度函数与目标概率密度函数的距离,从而构建了投资组合优化模型,并给出了具体算例。     

A Transaction Cost Perspective of Alliance Portfolio Diversity

Alliance portfolio diversity (APD) helps firms access diverse capabilities and knowledge. APD can also increase transaction costs, but it is unknown whether and how transaction cost theory’s (TCT’s) insights about hierarchical integration operate at the portfolio level. We adapt TCT to the portfolio level to suggest that the transaction costs from APD encourage integration into alliance partners’ industries, and we introduce the concept of shared-specific investments to pinpoint one source of transaction costs within portfolios and predict which industries will be integrated. Using data from 1996–2013 on S&P 500 firms, we find evidence in support of our theorising. Juxtaposing results with other theoretical perspectives suggests that TCT offers complementary insights about which activities to perform in the firm versus the alliance portfolio.     

Numeraire portfolios and utility-based price systems under proportional transaction costs

In a discrete-time incomplete financial market with proportional transaction costs and with independent and bounded returns, we prove the existence of a consistent price system that can be written as the expectation of the discounted claim under the real-world probability measure P and not just under a martingale measure. In fact, the claim is then discounted by some specific dynamic portfolio called the numeraire portfolio as in the classical case of markets without transaction costs. For that specific numeraire, P will be a martingale measure. Naturally, the concept of a numeraire portfolio has here to be adapted to the concept of consistent price systems for markets with transaction costs. Moreover, again as in the classical case, the numeraire portfolio can be chosen as log-optimal portfolio. The same analysis works for power utility functions. However, then a change of measure is necessary. This paper applies methods from stochastic dynamic programming to finance.     

Price functionals with bid–ask spreads: an axiomatic approach

In Jouini and Kallal [Jouini, E., Kallal, H., 1995. Martinagles and arbitrage in securities markets with transaction costs. Journal of Economic Theory 66 (1) 178-197], the authors characterized the absence of arbitrage opportunities for contingent claims with cash delivery in the presence of bid–ask spreads. Other authors obtained similar results for a more general definition of the contingent claims but assuming some specific price processes and transaction costs rather than bid–ask spreads in general (see for instance, Cvitanic and Karatzas [Cvitanic, J., Karatzas, I., 1996. Hedging and portfolio optimization under transaction costs: a martinangle approach. Mathematical Finance 6, 133-166]). The main difference consists of the fact that the bid–ask ratio is constant in this last reference. This assumption does not permit to encompass situations where the prices are determined by the buying and selling limit orders or by a (resp. competitive) specialist (resp. market-makers). We derive in this paper some implications from the no-arbitrage assumption on the price functionals that generalizes all the previous results in a very general setting. Indeed, under some minimal assumptions on the price functional, we prove that the prices of the contingent claims are necessarily in some minimal interval. This result opens the way to many empirical analyses.     

存在交易成本的权证避险策略实证研究

权证发行人在存在交易成本时对冲风险,若按照B—S理论进行动态连续避险操作,将造成巨大的交易成本,致使B-S动态连续避险不可行。因此存在交易成本时,对避险的操作都采用间断性避险。本文在统一均值方差框架下,系统全面的比较了存在交易成本的五种避险策略。在比例交易成本情形下,Whalley—Wilmott避险策略优于其他所有策略,当避险误差的标准差相同时该策略的交易成本最小;其次分别是delta固定避险带避险策略,基于标的资产价格变化的避险策略,Leland避险模型和间断的B—S避险策略。随着波动率σ上升,无风险利率γ下降,基于变动的避险策略相对于基于时间的策略优势更大。     

Portfolio management with robustness in both prediction and decision: A mixture model based learning approach

We develop in this paper a novel portfolio selection framework with a feature of double robustness in both return distribution modeling and portfolio optimization. While predicting the future return distributions always represents the most compelling challenge in investment, any underlying distribution can be always well approximated by utilizing a mixture distribution, if we are able to ensure that the component list of a mixture distribution includes all possible distributions corresponding to the scenario analysis of potential market modes. Adopting a mixture distribution enables us to (1) reduce the problem of distribution prediction to a parameter estimation problem in which the mixture weights of a mixture distribution are estimated under a Bayesian learning scheme and the corresponding credible regions of the mixture weights are obtained as well and (2) harmonize information from different channels, such as historical data, market implied information and investors׳ subjective views. We further formulate a robust mean-CVaR portfolio selection problem to deal with the inherent uncertainty in predicting the future return distributions. By employing the duality theory, we show that the robust portfolio selection problem via learning with a mixture model can be reformulated as a linear program or a second-order cone program, which can be effectively solved in polynomial time. We present the results of simulation analyses and primary empirical tests to illustrate a significance of the proposed approach and demonstrate its pros and cons.     

基于投资组合理论的企业多项目投资管理研究

投资行为所具有的风险和收益密切相关的特点,使投资者必须努力寻求低风险和高收益的投资策略。而投资组合则能够为企业进行分散风险和扩张经营提供强有力的保证。本文使用现代投资组合理论,为企业的多项目投资组合建立优化模型,从定量的角度说明在企业多项目投资管理中运用投资组合的合理性和有效性。     

On portfolio optimization: How and when do we benefit from high‐frequency data?

We examine how the use of high‐frequency data impacts the portfolio optimization decision. Prior research has documented that an estimate of realized volatility is more precise when based upon intraday returns rather than daily returns. Using the framework of a professional investment manager who wishes to track the S&P 500 with the 30 Dow Jones Industrial Average stocks, we find that the benefits of using high‐frequency data depend upon the rebalancing frequency and estimation horizon. If the portfolio is rebalanced monthly and the manager has access to at least the previous 12 months of data, daily data have the potential to perform as well as high‐frequency data. However, substantial improvements in the portfolio optimization decision from high‐frequency data are realized if the manager rebalances daily or has less than a 6‐month estimation window. These findings are robust to transaction costs. Copyright © 2009 John Wiley & Sons, Ltd.     

Causes of cross-autocorrelation in security returns: Transaction costs versus information quality

We examine empirically the role of transaction costs and information quality as causes of cross-autocorrelations in security returns. Nonsynchronous trading influences are addressed by forming weekly returns based on averages of closing inside bid and ask quotations for NMS securities. Stock return volatility scaled by the bid-ask spread is employed as a proxy for transaction costs and trading volume is used as a measure of information quality. We find evidence that both transaction costs and information quality may contribute to cross-autocorrelations, but that information quality dominates transaction costs in explaining cross-autocorrelations after controlling for autocorrelation influences.     

城市规划管理中的交易费用

当代经济学研究注重交易费用在经济发展与社会制度设计中所起的作用.而作为社会制度的一部分,城市规划管理对城市开发有重要的影响,科学的城市规划管理应当注重经济学理论的指导作用.在介绍交易费用相关的基本理论基础上,结合美国城市规划管理实践,对城市规划管理中可能存在的交易费用及其影响进行分析研究,并对我国目前的规划管理实践进行思考,提出适应经济发展,尽量降低城市规划管理中的各种交易费用,以提高社会的总效用.     

A three-moment based portfolio selection model

This article studies a portfolio selection model based on Expected return, Variance and Skewness (E-V-S), under a distributional hypothesis that allows 3-funds separation. The efficient portfolio is the solution of a non-linear problem that maximizes skewness under a specified level of expected return and variance. The analysis of the efficient frontier shows that the return of any efficient portfolio is the sum of a riskless return (if available), a variance premium and a skewness discount. Furthermore, the strategy based on the maximization of skewness is equivalent to adding a definite non-zero arbitrage portfolio (with null expected return) to an efficient E-V portfolio.     

Fractal statistical measure and portfolio model optimization under power-law distribution

An effective portfolio selection model is constructed on the premise of measuring accurately the risk and return on assets. According to the reality that the tail of returns on assets obey power-law distribution, this paper firstly builds two fractal statistical measures, fractal expectation and fractal variance, to measure the asset returns and risks, inspired by the method of measuring curve length in the fractal theory. Then, by incorporating the fractal statistical measure into the return-risk criterion, a portfolio selection model based on fractal statistical measure is established, namely the fractal portfolio selection model, and the closed-form solution of the model is given. Finally, through empirical analysis we find that the fractal portfolio selection model is effective and can improve investment performance.     

Transaction Costs and Nonlinear Adjustment Towards Equilibrium in the US Treasury Bill Market

This paper uses nonlinear error correction models to study yield movements in the US Treasury Bill Market. Nonlinear error correction arises because portfolio adjustment is an ‘on-off’ process, which occurs only when disequilibrium in the bill market is large enough to induce investors to incur the transaction costs associated with buying/selling bills. This, together with heterogeneity of transaction costs, implies that the strength of aggregate error correction depends on both the distribution of costs and the extent of disequilibrium in the market. Smooth transition models are used to describe an aggregate adjustment process which is strong when the market is distant from equilibrium, but becomes weaker as the market approaches equilibrium. Linearity tests indicate that the types of nonlinearities that would be induced by transactions costs are statistically significant, and estimated models which incororate these nonlinearities outperform their linear counterparts, both in sample and out of sample.     

Collective rationality and functional wisdom of the crowd in far-from-rational institutional investors

The average portfolio structure of institutional investors is shown to reproduce the structure which optimally accounts for transaction costs when investment constraints are weak. Strikingly, this result emerges even though these investors are not aware of the existence of such law and despite the fact that their aims and tools are very heterogeneous. This extends the so-called wisdom of the crowd to much more complex situations in two important ways. First, wisdom of the crowd also holds for whole functions instead of a point-wise estimates. Second, this shows that in socio-economic systems, the optimal individual choice may only be found when the diversity of individual decisions is averaged out. Thus, rationality at a collective level does not need nearly rational individuals with well-aligned incentives. Finally we discuss the importance of accounting for constraints when assessing the presence of wisdom of the crowd.

     

International Portfolio Diversification and the Magnitude of the Market Timer's Penalty

Market timers without timing skill suffer a penalty relative to buy-and-hold investors in the form of higher portfolio risk. With transactions costs, timers suffer lower expected returns as well. We derive the magnitude of this penalty for a timer randomly switching funds between two or more risky assets. Assuming costless trades, a U.S.-based timer randomly switching between U.S. and Japanese national stock funds can expect to face a 26.2% higher standard deviation than a comparable buy-and-hold investor at the same level of expected return. A timer randomly switching between a globally diversified equity portfolio and U.S. T-bills faces a 50.3% higher standard deviation of return than a comparable buy-and-hold investor.     

Modeling returns to owner-occupied single-family residences

This paper expands previous models of the returns to owner-occupied single-family residences by modelling returns to a specific property of an individual homeowner instead of determining an average market return based on appraised values. Included in the model are transaction costs, degree of leverage, level of price appreciation, the implied rental cost in ownership, tax bracket, and duration of home ownership. Simulation results suggests that the level and timing of transaction costs are important to homeowners and rates of return to owner-occupied single-family residences increase to a point in time and thereafter decline.     

A Stein-type shrinkage estimator of the covariance matrix for portfolio selections

The covariance matrix plays a crucial role in portfolio optimization problems as the risk and correlation measure of asset returns. An improved estimation of the covariance matrix can enhance the performance of the portfolio. In this paper, based on the Cholesky decomposition of the covariance matrix, a Stein-type shrinkage strategy for portfolio weights is constructed under the mean-variance framework. Furthermore, according to the agent’s maximum expected utility value, a portfolio selection strategy is proposed. Finally, simulation experiments and an empirical study are used to test the feasibility of the proposed strategy. The numerical results show our portfolio strategy performs satisfactorily.     

Testing affine term structure models in case of transaction costs

We empirically analyze the impact of transaction costs on the performance of essentially affine interest rate models. We test the implied Euler restrictions and calculate the specification error bound of Hansen and Jagannathan to measure model misspecification. Using both short-maturity and long-maturity bond return data we find, under the assumption of frictionless markets, strong evidence of misspecification of affine yield models with up to three factors. Next, we incorporate transaction costs in our tests. The results show that the evidence of misspecification of essentially affine yield models disappears in case of monthly holding periods at market size transaction costs.     

Nonlinear mean reversion in the term structure of interest rates

The expectations hypothesis implies that the yield curve provides information on the future change in the short-term interest rate. However, transaction costs exist in the financial market, which prevent investors from realizing the arbitrage opportunity, when the arbitrage does not fully cover the transaction costs. The purpose of this paper is to assess the effect of transaction costs on the predictability of the term structure by using the threshold vector error correction model, which allows for the nonlinear adjustment to the long-run equilibrium relationship. A significant amount of threshold effect is found, and the adjustment coefficients are regime-dependent. The empirical result supports the nonlinear mean reversion in the term structure of interest rates.