【摘要】：證券投資者(含機(jī)構(gòu)及眾多散戶)一直在尋找更好的選股策略與算法,以獲得收益最大化。但由于證券市場(chǎng)受眾多因素影響,包括公司經(jīng)營(yíng)狀況、政策、經(jīng)濟(jì)環(huán)境、戰(zhàn)爭(zhēng)和自然災(zāi)害等,導(dǎo)致股票的走勢(shì)難于預(yù)測(cè),沒有人能保證一定盈利。 本文的研究涉及選股和優(yōu)化策略兩個(gè)方面：①在大盤及單支股票無(wú)法預(yù)測(cè)、股票相對(duì)來回波動(dòng)前提下,研究如何利用股票的相對(duì)波動(dòng)獲得超過大盤收益的一種模型；②為控制風(fēng)險(xiǎn),對(duì)選股階段的投資組合,研究如何科學(xué)地配置投資比例,使用戶在利益最大化與風(fēng)險(xiǎn)最小化之間獲得一個(gè)平衡。 本文主要的研究工作概述如下： 1、在對(duì)證券市場(chǎng)進(jìn)行基本面分析和技術(shù)分析的基礎(chǔ)上,本文基于套利這一思想出發(fā),挖掘一種新的組合投資盈利模型：利用股票相對(duì)波動(dòng),在股票之間來回交換實(shí)現(xiàn)盈利。并對(duì)該模型進(jìn)行了選股算法的研究,針對(duì)選股算法需要兩兩配對(duì)計(jì)算股票波動(dòng)性、算法復(fù)雜度為o(n2)這樣一個(gè)事實(shí),提出該算法的并行與群集計(jì)算方案,達(dá)到減少計(jì)算時(shí)間的目的。通過歷史數(shù)據(jù)進(jìn)行模擬測(cè)試,證實(shí)了算法的可用性和有效性。 2、給出一種關(guān)于股票行業(yè)的優(yōu)化配置算法。選股階段的投資組合分屬于不同的行業(yè),需要投資者根據(jù)行業(yè)的成長(zhǎng)性和相關(guān)經(jīng)濟(jì)指標(biāo)等,從宏觀上把握每個(gè)行業(yè)的投資資金比例。本文首先對(duì)行業(yè)進(jìn)行量化分析,為行業(yè)優(yōu)化配置算法提供數(shù)據(jù)支持和參考。 3、給出投資組合中投資個(gè)體的優(yōu)化配置算法。該算法模型的建立依賴眾多約束條件的設(shè)置,包括行業(yè)投資比例約束、beta約束、alpha約束和預(yù)期收益約束等方面,再利用二次規(guī)劃求解,以此指導(dǎo)投資者對(duì)個(gè)股的配置比例。對(duì)于得到的配置結(jié)果,從不同維度進(jìn)行了風(fēng)險(xiǎn)評(píng)估的考察,并計(jì)算出投資組合的系統(tǒng)風(fēng)險(xiǎn)與非系統(tǒng)風(fēng)險(xiǎn)提示用戶,以使得用戶能在收益與風(fēng)險(xiǎn)之間取得一個(gè)折中平衡。 4、設(shè)計(jì)和實(shí)現(xiàn)了一個(gè)原型系統(tǒng)。根據(jù)股票投資盈利模型和上述研究成果,本文通過計(jì)算機(jī)軟件構(gòu)架、算法、網(wǎng)絡(luò)通信、數(shù)學(xué)、金融學(xué)和運(yùn)籌學(xué)等相關(guān)知識(shí),設(shè)計(jì)和實(shí)現(xiàn)了一個(gè)原型系統(tǒng)。 實(shí)踐和實(shí)驗(yàn)證明,本文的研究工作及其相關(guān)成果能夠?yàn)樽C券投資者在組合選股和投資比例優(yōu)化配置方面提供很好的參考,具有可借鑒性。實(shí)現(xiàn)了一個(gè)可用的原型系統(tǒng),對(duì)選股算法的有效性、配置方法的實(shí)用性進(jìn)行了驗(yàn)證。
[Abstract]:Securities investors (including institutions and many retail investors) have been looking for better stock selection strategies and algorithms to maximize returns. However, the stock market is affected by many factors, including company management, policy, economic environment, war and natural disasters, which makes the trend of stocks difficult to predict, and no one can guarantee a certain profit. The research of this paper involves two aspects: stock selection and optimization strategy. Under the premise that stock market and single stock can not be predicted and stocks fluctuate back and forth, this paper studies how to use the relative volatility of stock to obtain a model that exceeds the return of large market. 2 in order to control the risk, the paper studies how to scientifically allocate the investment proportion in the stock selection stage, so that the user can get a balance between the profit maximization and the risk minimization. The main research work of this paper is summarized as follows: 1. Based on the fundamental analysis and technical analysis of the stock market, this paper based on the arbitrage idea, A new profit-making model for portfolio investment is developed: using relative volatility of stocks to achieve profit by swapping stocks back and forth. Based on the fact that the stock selection algorithm needs pairing to calculate the stock volatility and the complexity of the algorithm is o (N2), the parallel and cluster computing scheme of the algorithm is proposed. The purpose of reducing the calculation time is achieved. The availability and validity of the algorithm are verified by the simulation test of historical data. 2. An optimal configuration algorithm for the stock industry is presented. The portfolio of stock selection stage belongs to different industries, which requires investors to grasp the proportion of investment funds in each industry macroscopically according to the growth of the industry and related economic indicators. In this paper, the quantitative analysis of the industry is carried out to provide data support and reference for the industry optimization allocation algorithm. 3. The optimal allocation algorithm for the individual in the investment portfolio is given. The establishment of the algorithm model depends on the setting of many constraint conditions, including industry investment ratio constraint, beta constraint, alpha constraint and expected income constraint, etc. The quadratic programming is used to solve the problem so as to guide investors to allocate the proportion of individual stocks. For the obtained configuration results, the risk assessment is conducted from different dimensions, and the system risk and non-system risk of the portfolio are calculated to prompt the user. A prototype system is designed and implemented to enable the user to achieve a compromise between profit and risk. According to the stock investment profit model and the above research results, this paper designs and implements a prototype system through computer software architecture, algorithm, network communication, mathematics, finance and operational research. Practice and experiment prove that the research work and its related achievements can provide a good reference for securities investors in portfolio selection and optimal allocation of investment ratio, and it can be used for reference. An available prototype system is implemented to verify the validity of the stock selection algorithm and the practicability of the configuration method.
【學(xué)位授予單位】：東華大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：F224;F830.91

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