An examination of HMM‐based investment strategies for asset allocation

We develop and analyse investment strategies relying on hidden Markov model approaches. In particular, we use filtering techniques to aid an investor in his decision to allocate all of his investment fund to either growth or value stocks at a given time. As this allows the investor to switch between growth and value stocks, we call this first strategy a switching investment strategy. This switching strategy is compared with the strategies of purely investing in growth or value stocks by tracking the quarterly terminal wealth of a hypothetical portfolio for each strategy. Using the data sets on Russell 3000 growth index and Russell 3000 value index compiled by Russell Investment Services for the period 1995–2008, we find that the overall risk‐adjusted performance of the switching strategy is better than that of solely investing in either one of the indices. We also consider a second strategy referred to as a mixed investment strategy which enables the investor to allocate an optimal proportion of his investment between growth and value stocks given a level of risk aversion. Numerical demonstrations are provided using the same data sets on Russell 3000 growth and value indices. The switching investment strategy yields the best or second best Sharpe ratio as compared with those obtained from the pure index strategies and mixed strategy in 14 intervals. The performance of the mixed investment strategy under the HMM setting is also compared with that of the classical mean–variance approach. To make the comparison valid, we choose the same level of risk aversion for each set‐up. Our findings show that the mixed investment strategy within the HMM framework gives higher Sharpe ratios in 5 intervals of the time series than that given by the standard mean–variance approach. The calculated weights through time from the strategy incorporating the HMM set‐up are more stable. A simulation analysis further shows a higher performance stability of the HMM strategies compared with the pure strategies and the mean–variance strategy. Copyright © 2009 John Wiley & Sons, Ltd.     

考虑完整交易费用的组合证券投资求解

针对中国证券市场现存的各种交易费用,建立一个更加符合实际的组合证券投资模型.该模型不仅继承了股票不可拆分、不能卖空等特点,而且完全反映了交易费用的核算情况;最后给出一个遗传算法结合动态罚函数求解的投资实例,计算结果证明了该模型及其求解方法的有效性和可操作性.     

Inducing Stock Screening Rules for Portfolio Construction

This study describes a technique originated from the emerging field of machine learning and demonstrates its effectiveness in stock screening. We have derived screening rules by applying a rule induction method, constructed portfolios using the rules, and evaluated the portfolios' performance using the Sharpe, Treynor and Jensen indexes. Results indicate that regularities among stocks can be identified, and portfolios so constructed outperformed the NYSE Composite index and the S&P 500 over the same period.     

Contrarian investment strategy with data envelopment analysis concept

One of the typical issues in financial literature is that the market tends to be overly pessimistic about value stocks, many of which are past losers. Therefore, over-reactions might capture by measuring earnings surprise vary with past return levels. In this paper, we propose a new index for an effective investment strategy to capture the return-reversal effect using both Data Envelopment Analysis (DEA) and Inverted DEA in order to consider the above characteristics of the market. Our investment strategy using the new index exhibits better performance than the naive return-reversal strategy that only uses past returns or earnings surprise. In addition, the correlations between our new index and commonly used value indices are insignificant, and the value indices cannot represent the over-valued (under-valued) situations perfectly. Hence, considering both proposed and value indices like book-to-price one, we could select value stocks more effectively than by using only one of these indices.     

影响收益的公司指标在最优投资组合选择中的应用

如何从数目巨大的市场股票集中选取一组特定的股票作为最优投资组合选择模型的输入,以确保最终的投资方案具有优异而稳定的表现一直是投资理论界和实务界关注的重点.为此,本文基于作者新近结合中国股市特性并采用新方法所确定影响中国股票收益的多个公司基本特性指标,设计了一个恰当的股票预选策略,并由此导出了新型而稳健的投资组合选择两阶段法.实证结果表明新方法能使投资者便捷地找到更稳健的投资策略.     

Almost Stochastic Dominance and stocks for the long run

The geometric-mean argument and the recently developed Almost Stochastic Dominance criterion have been employed to make the case for “stocks for the long run”. We show that Almost Stochastic Dominance and the geometric-mean argument do not necessarily support long-run investment in equities. In fact, for standard preferences bonds may be preferred to stocks for the long run while stocks are preferred for shorter horizons.     

International portfolio choice and political instability risk: A multi-objective approach

The benefits derived from international portfolio diversification into foreign nations (including the less developed countries) are well documented, yet this practice is discouraged due to market imperfections such as political instability. In practice, nations may be differentiated further by many aspects, such as border controls or political and social trends, which constrain private transactions and financial decisions. This paper attempts to examine (1) whether the home asset bias in a portfolio holding is associated with higher political instability risk, and (2) to what extent international diversification among stocks, in the presence of such risk, outperforms domestic stock portfolios. Using alternative instability risk proxies in the context of a discrete-time version of mean–variance framework, we corroborate the impact of this type of risk on international portfolio investment decisions.     

Maximin investment problems for discounted and total wealth

Email: nikolaidokuchaev{at}trentu.ca Received on 27 March 2006. Accepted on 14 September 2007. We study an optimal investment problem for a continuous-timeincomplete market model such that the risk-free rate, the appreciationrates and the volatility of the stocks are all random; theyare not necessarily adapted to the driving Brownian motion,and their distributions are unknown, but they are supposed tobe currently observable. The optimal investment problem is statedin ‘maximin’ setting which leads to maximizationof the minimum of expected utility over all distributions ofparameters. We found that the presence of the non-discountedwealth in the performance criterion (in addition to the discountedwealth) implies an additional condition for the saddle pointof the maximin problem: the saddle point must include the minimumof the possible risk-free return. This is different from thecase when the utility depends on the discounted wealth only.Using this result, the maximin problem is reduced to a linearparabolic equation and minimization over two scalar parameters.It is an important development of the results obtained in Dokuchaev(2002, Dynamic Portfolio Strategies: Quantitative Methods andEmpirical Rules for Incomplete Information. Boston: Kluwer;2006, IMA J. Manage. Math., 17, 257–276).     

博彩型股票与投资者的博彩性偏好——基于中国股票市场数据的实证研究

在新兴资本市场中,股票价格容易受到投资者投资偏好的影响。其中,投资者的博彩性投资偏好是本文研究的重点。本文基于中国股票市场实际情况,借鉴并改进了过往文献对于博彩型股票的分类方法,将高个体偏度、高个体波动率、低价格和高超额换手率的股票定义为博彩型股票,并发现个人投资者过度配置了博彩型股票,存在明显的博彩性投资偏好。本文验证了在中国股票市场中博彩型股票未来收益表现较差的结论,说明投资者偏好博彩型股票的投资行为存在非理性偏误。同时,相对于主板市场而言,在投机性相对较强的中小板和创业板市场中的博彩型股票未来收益表现更差;无论市场在上升或下降环境中,博彩型股票的未来负超额收益一直稳定存在。因此,本文认为应在中国股票市场中加强投资者教育,以降低个人投资者的非理性行为偏差,维护股票市场的健康稳定发展。     

Incorporating environmental and social considerations into the portfolio optimization process

Over the last years, more and more companies face increased pressure by the public to provide information on how they perform on environmental, social and governance (ESG) issues. However, so far a very small number of studies have investigated optimal ways to construct socially responsible portfolios, either in the sense of the screening criteria used to narrow the investment universe, or the optimization process employed to determine the asset proportions. This study covers this gap by introducing an algorithm that first performs a screening to eliminate stocks from the investment universe that do not respect the imposed ESG constraint and then on the ESG compliant universe the portfolio optimization is performed. The novelty of the proposed approach lies in the fact that all underlying functionality of the algorithm, including the screening procedure and the imposed constraints, is facilitated seamlessly through a novel solution representation. Three multiobjective evolutionary algorithms have been adapted to work well with the proposed solution representation and the imposed constraints. The study by utilizing data from the FTSE-100 corporate social responsibility index finds that investors that are concerned about the environmental and social impact of their investments that must be ready to sacrifice a part of their welfare by selecting combinations of assets that provide subordinate return and risk combinations, compared to the available investment opportunities.

     

基于免疫记忆克隆算法的指数化投资组合优化构建策略

本文基于克隆选择学说及基于克隆选择学说及生物免疫响应过程的相关机理,提出用于指数化投资的免疫记忆克隆算法,并将其应用于指数化投资组合优化构建模型的求解,旨在探索指数化投资的优化构建策略。文章首先提出多目标的指数化投资组合构建模型。其次,分别设计了适用于指数化投资组合构建策略的抗原、抗体、亲和度函数、克隆选择算子、免疫记忆算子和相应的进化算法。该算法有效避免了传统遗传算法所存在的计算后期解的多样性差、易早熟以及收敛速度慢等缺点。同时,提出了限制投资组合中股票数量的启发式算法。最后,使用包括上证180指数在内的6组世界主要股票市场指数及其成份股的历史数据对模型及算法进行测算,结果表明算法具有良好的求解能力和收敛速度,所建模型的合理性和有效性亦被论证,模型和算法均具有很强的实践价值;     

A heuristic for the one-dimensional cutting stock problem with usable leftover

A heuristic algorithm for the one-dimensional cutting stock problem with usable leftover (residual length) is presented. The algorithm consists of two procedures. The first is a linear programming procedure that fulfills the major portion of the item demand. The second is a sequential heuristic procedure that fulfills the remaining portion of the item demand. The algorithm can balance the cost of the consumed bars, the profit from leftovers and the profit from shorter stocks reduction. The computational results show that the algorithm performs better than a recently published algorithm.     

The informational content of insider trading disclosures: empirical results for the Polish stock market

In this paper, we try to answer the question as to whether insider trading disclosures convey valuable information to market participants, valuable in the sense of the profitability of an investment strategy that faithfully mirrors insider behaviour. Our interest in this subject is limited to the case of announcements concerning insider transactions issued over a 6 year-period on the Warsaw Stock Exchange (WSE). Initially, we use event study methodology to check whether insider trading disclosures are accompanied by a performance of stock returns as well as trading volume. Two different models generating expected returns (expected volume) are employed to verify the robustness of our results. The first of these is the regime switching model, with the results then being recalculated by using a GARCH-type model which seem to be most useful for dealing with some of the inconvenient statistical properties of stock return and trading volume data. Afterwards, a technique based on the reference return strategies is used to examine whether or not outsiders who imitate insider behaviour are able to profit from it. The major findings are as follows: firstly, announcements about the sale of stocks by insiders convey no information to market participants. Secondly, a statistically significant market response to insider disclosures of purchases of stocks in their own company can be observed in the three days prior to the announcement release for both return as well as trading volume series, and finally, outsiders who purchased stocks previously bought by insiders experience negative returns whereas outsiders disposing of stocks previously sold by insiders earned a return of 8.57% over the 6 month-period.      

Development and Evaluation of Decision-Making Model for Stock Markets

The paper introduces an intelligent decision-making model which is based on the application of artificial neural networks (ANN) and swarm intelligence technologies. The proposed model is used to generate one-step forward investment decisions for stock markets. The ANN are used to make the analysis of daily stock returns and to calculate one day forward decision for purchase of the stocks. Subsequently the Particle Swarm Optimization (PSO) algorithm is applied in order to select the “the best” ANN for the future investment decisions and to adapt the weights of other networks towards the weights of the best network. The experimental investigations were made considering different forms of decision-making model: different number of ANN, ANN inputs, sliding windows, and commission fees. The paper introduces the decision-making model, its evaluation results and discusses its application possibilities.     

考虑相对业绩的最优投资选择博弈问题研究

研究了具有相互作用的两个竞争机构投资者之间的离散时间最优投资选择博弈问题,每个机构投资者都考虑其竞争对手的相对业绩.机构投资者可以投资于相同的无风险资产和不同的具有相关关系的风险股票,以反映投资的资产专门化.机构投资者选择投资组合策略使得期望终端绝对财富和相对财富的效用最大.首先,定义了Nash均衡投资组合选择策略.然后,在机构投资者具有指数效用函数的假设下,得到了Nash均衡投资组合选择策略和值函数的显示表达式,分析了机构投资者之间的竞争对Nash均衡投资组合选择策略的影响.最后,通过数值计算给出了各种情况下Nash均衡投资组合选择策略和值函数与模型主要参数之间的关系.结果表明:机构投资者之间的竞争会影响其对风险的承担,投资机会集对机构投资者的Nash均衡投资组合选择策略和值函数与模型主要参数之间的关系会产生很大的影响.     

Enhancement of equity portfolio performance using data envelopment analysis

This paper examines the applicability of data envelopment analysis (DEA) as a basis of selection criteria for equity portfolios. It is the first DEA application for constructing a combined equity investment strategy that aims to integrate the benefits of both value investing and momentum investing. The 3-quantile portfolios are composed of a comprehensive sample of Finnish non-financial stocks based on their DEA efficiency scores that are calculated using three variants of DEA models (the constant returns-to-scale, the super-efficiency, and the cross-efficiency models). The performance of portfolios is evaluated on the basis of the average return and several risk-adjusted performance metrics throughout the 1994–2010 sample period.     

A hybrid optimization approach to index tracking

Index tracking consists in reproducing the performance of a stock-market index by investing in a subset of the stocks included in the index. A hybrid strategy that combines an evolutionary algorithm with quadratic programming is designed to solve this NP-hard problem: Given a subset of assets, quadratic programming yields the optimal tracking portfolio that invests only in the selected assets. The combinatorial problem of identifying the appropriate assets is solved by a genetic algorithm that uses the output of the quadratic optimization as fitness function. This hybrid approach allows the identification of quasi-optimal tracking portfolios at a reduced computational cost.     

我国基金博彩型股票交易是博彩偏好的结果吗？——基于信息挖掘视角

本文从信息挖掘入手,利用基金持股数据分析基金持有博彩型股票背后的原因。结果表明:基金博彩型股票持股显著提高了股价同步性,基金博彩型股票交易在整体上关注非基本面信息,仅在市场情绪低落时关注基本面信息,表明基金博彩型股票交易中存在信息交易,并不是纯粹的博彩偏好的结果。本文的研究一定程度上解释了基金持有博彩型股票的动机,并为监管当局深入了解基金择股能力和投资行为提供了参考依据。     

基于HWSME的股票最佳投资区域起端的模糊综合评判方法

寻找进入主升浪的股票对投资效益最大化意义重大.讨论并界定了股票最佳投资区域,借助于HWSME和模糊综合评判,建立了股票最佳投资区域起端的模糊综合评判方法,构建了评价指标体系和隶属函数.通过对中国股票市场部分股票进行了横向和纵向预测实验,结果证明了方法的有效性.对投资效益最大化提供了强有力的分析工具.     

三次Hermite插值方法在证券投资分析中的应用

利用三次Hermite插值公式给出了寻找曲线之间相似程度的算法,对于给定股票的任意一段曲线形状,文章利用该算法找出走势与之相似的股票,将原来只能寻找股价曲线满足特定形状(如W底)的股票的方法进行了推广,对于证券投资者来说是一个有效的工具.同时文章将相似算法应用于利用某只股票的历史走势来预测该股票价格的将来走势,具有有效的投资指导意义.实验证明,文章给出的算法是行之有效的.