本文選題：股民投資決策 + 薦股信息��； 參考：《大連理工大學(xué)》2014年碩士論文

【摘要】：決策是基于信息的,信息在決策過程中能對結(jié)果產(chǎn)生影響,是投資者在投資決策過程中的核心要素。薦股信息作為股評專家發(fā)布的具有明確措辭和直接操作性的綜合性結(jié)論,是股民投資決策的重要信息參考來源。作為股民投資決策行為研究領(lǐng)域的重要分支,許多學(xué)者從心理學(xué)或者社會學(xué)的角度出發(fā)對股民投資決策的影響因素進行了深入的研究,然而鮮有研究從股民關(guān)注的薦股信息價值角度出發(fā),探究廣大股民的投資決策問題。本文在股評專家薦股信息價值驗證的基礎(chǔ)上,通過挖掘股評專家的歷史薦股行為信息,研究股票市場信息不對稱背景下的股民投資決策問題。 本文首先整理了股民投資決策與薦股信息的相關(guān)研究,然后在股評專家薦股信息價值驗證的基礎(chǔ)上,挖掘?qū)＜业乃]股信息,從股評專家群體行為分析的角度出發(fā),構(gòu)建基于專家薦股信息的股民投資決策模型,輔助股民做投資決策。具體開展了兩個研究： 研究1,專家薦股信息價值驗證研究。采用事件研究法,通過對比股評專家推薦的股票樣本與大盤樣本的收益率,探究股評專家薦股信息的價值存在。本研究結(jié)果為進一步挖掘股評專家的薦股行為信息、輔助股民投資決策提供了強有力的支撐,為本文的下一步研究奠定了基礎(chǔ)。 研究2,基于專家薦股信息的股民投資決策模型。首先,構(gòu)建“專家-股票”二部網(wǎng)絡(luò),定量化描述股票市場中股評專家與股票之間多對多的薦股關(guān)系；然后,從股評專家歷史的薦股行為出發(fā),構(gòu)建股評專家薦股檔案,定量描述每一位股評專家的薦股能力；最后,從股評專家群體的績效構(gòu)成和風(fēng)險構(gòu)成角度出發(fā),建立股票的股評專家構(gòu)成分析模型,定量化評估股票價值,并在此基礎(chǔ)上構(gòu)建投資決策模型,輔助股民進行投資決策。 最后,總結(jié)了相關(guān)研究結(jié)論,在此基礎(chǔ)上,分析了本研究的不足之處,提出了未來可能的拓展研究。
[Abstract]:Decision making is based on information, which can influence the result in the decision-making process, and is the core element of investors' investment decision-making process. As a comprehensive conclusion with clear wording and direct operation issued by stock appraisal experts, recommendation information is an important reference source for investors to make investment decisions. As an important branch of the research field of investors' investment decision-making behavior, many scholars have conducted in-depth research on the influencing factors of shareholders' investment decision-making from the perspective of psychology or sociology. However, few studies have explored the investment decision of the shareholders from the perspective of the information value of the stock recommendation. Based on the verification of the value of stock recommendation information, this paper studies the investors' investment decision under the background of asymmetric information in the stock market by digging out the historical information of the stock evaluation experts. This paper first collates the relevant research of investors' investment decision and recommendation information, and then, on the basis of verifying the value of recommendation information of stock appraisal experts, excavates the recommended stock information of experts, and sets out from the angle of group behavior analysis of stock review experts. The investment decision model based on expert recommendation information is constructed to assist investors to make investment decisions. Carried out two specific research: research 1, expert recommendation information value verification research. By comparing the stock samples recommended by stock review experts with the return rate of large market samples, this paper explores the value of stock recommendation information in stock review experts by means of event research. The results of this study provide a strong support for further excavating the information of the recommended stock behavior of the stock appraisal experts and assist the investors' investment decision, and lay a foundation for the next research of this paper. Research 2, the investment decision model based on expert recommendation information. First of all, we construct the "expert-stock" network to quantitatively describe the many-to-many relationship between the experts and the stock in the stock market, and then, starting from the history of the recommendation of the expert, we construct the stock recommendation file of the expert. Finally, from the point of view of the performance composition and risk composition of the stock appraisal expert group, a stock appraisal expert composition analysis model is established to quantitatively evaluate the stock value. On this basis, the investment decision model is constructed to assist shareholders to make investment decision. Finally, this paper summarizes the relevant research conclusions, and then analyzes the shortcomings of this study, and puts forward the possible development of the future research.
【學(xué)位授予單位】：大連理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：F832.51

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