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  本文選題：雙層遺傳算法　切入點：投資組合　出處：《河北工業(yè)大學》2014年碩士論文　論文類型：學位論文

【摘要】：證券投資具有市場變化快、影響因素復雜、風險不確定性等特點。為了分散風險，，需按照不同的比例選擇多個不同的證券進行投資，即采用投資組合的方式。投資組合問題屬于復雜的優(yōu)化問題，常規(guī)的算法難以在短時間內(nèi)找到全局最優(yōu)解，而遺傳算法的普適性強、對目標函數(shù)的性質(zhì)幾乎沒要求等特點，為投資組合問題的求解找到了可行的方法。本文主要探討了如何建立投資組合模型，研究了如何根據(jù)具體問題設計模型求解的算法。 本文綜合經(jīng)濟學理論中的效用論和理性人假設以及統(tǒng)計學理論中的組合方差公式，依據(jù)CAPM模型和夏普比率中衡量風險的方法，提出了一個全新的證券投資組合模型：基于單位系統(tǒng)性風險的超額收益模型。該模型以組合標準差衡量風險，以單位系統(tǒng)性風險下的超額收益最大化為目標函數(shù)，根據(jù)單位風險收益來比較不同投資組合的優(yōu)劣。建立在單位風險基礎上的收益最大化模型，相對于單純追求收益最大化的模型綜合考慮了風險的因素，更符合現(xiàn)實中的投資需求。文章在詳細給出了模型的推導過程之后，為模型設計了遺傳算法求解。 本文獨創(chuàng)性的設計了雙層遺傳算法來解決證券投資組合問題。第一層遺傳算法使用財務比率編碼，持有期收益率作為適應函數(shù)，其運算結(jié)果篩選出了供模型使用的樣本范圍。第二層遺傳算法針對模型詳細設計了權(quán)重編碼，直接使用模型的目標函數(shù)作為適應函數(shù)，對投資組合模型進行求解，使最終結(jié)果能夠確定出一個組合各證券的投資比例。 本文最后以滬深A股市場為例，運用實證分析實現(xiàn)了算法，驗證了使用該模型進行投資可以有效的分散風險，選出的證券按比例進行投資其持有期收益率高于市場平均水平，模型和算法取得了較好的結(jié)果。
[Abstract]:Securities investment has the characteristics of fast market change, complex influencing factors and uncertainty of risk. In order to disperse risk, it is necessary to select multiple different securities to invest according to different proportions. That is to say, the portfolio problem is a complex optimization problem, and the conventional algorithm is difficult to find the global optimal solution in a short time. However, the genetic algorithm has the characteristics of strong universality and little requirement for the properties of the objective function. This paper mainly discusses how to establish the portfolio model and how to design the algorithm of solving the model according to the specific problem. This paper synthesizes the utility theory and rational man hypothesis in economic theory and the combination variance formula in statistical theory, according to the CAPM model and the method of measuring risk in Sharp ratio. This paper presents a new portfolio model: excess return model based on unit systemic risk, which measures the risk based on the standard deviation of the portfolio, and takes the maximization of the excess return under the unit systemic risk as the objective function. This paper compares the advantages and disadvantages of different investment portfolios according to the unit risk return. The profit maximization model based on the unit risk considers the risk factors compared with the model which simply pursues the income maximization. After giving the derivation process of the model in detail, a genetic algorithm is designed for solving the model. In this paper, a two-layer genetic algorithm is designed to solve the portfolio problem. The second layer genetic algorithm designs the weight coding for the model in detail, and directly uses the objective function of the model as the fitness function to solve the portfolio model. Enables the final result to determine the investment ratio of a portfolio of securities. Finally, taking the Shanghai and Shenzhen A share market as an example, we use the empirical analysis to realize the algorithm, and verify that using this model to invest can effectively spread the risk, and select the securities to invest in a proportionate rate of return higher than the market average. The model and algorithm obtained good results.
【學位授予單位】：河北工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP18;F830.91;F224

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相關期刊論文 前1條

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本文編號：1565996