本文選題：VaR模型 + 股指期貨��； 參考：《上海師范大學》2013年碩士論文

【摘要】：近二十多年來，世界經(jīng)濟的快速發(fā)展，全球一體化特別是經(jīng)濟全球一體化的趨勢越來越明顯，伴隨著世界經(jīng)濟的快速發(fā)展，特別是以布雷頓森林體系的崩潰為標志，全球金融市場的穩(wěn)定性，變得越來越脆弱，金融市場風險一天都不曾消失，如同“達摩克利斯之劍”一樣懸在上空。金融風險將影響作為一個整體的世界經(jīng)濟格局，而不是一個單一的金融機構(gòu)，它的影響，就可能會影響世界經(jīng)濟的穩(wěn)定發(fā)展。金融風險度量已成為一個非常重要的課題，研究它具有十分重要的理論和現(xiàn)實意義。風險測度理論在風險管理實踐過程中不斷發(fā)展，VaR風險度量方法使金融風險的定量研究得到進一步的發(fā)展。 我國金融市場目前尚不成熟，套期保值工具品種還較為缺乏，伴隨著金融市場的快速發(fā)展，其所承擔的風險也越來越大。股指期貨作為基礎(chǔ)性風險管理工具，具有價格發(fā)現(xiàn)、套期保值的功能，滬深300股指期貨合約正式上市，標志著我國股指期貨的誕生，它的推出填補了我國股市缺乏針對系統(tǒng)性風險的管理手段這一空白，將改變股票市場缺乏規(guī)避系統(tǒng)性風險工具的現(xiàn)狀，本文用極值分布VaR模型對股指期貨的數(shù)據(jù)進行了實證研究，分析VaR值對股指期貨風險評價研究具有重要意義。 VaR值的準確度量不僅與資產(chǎn)收益率的分布有關(guān)，還與資產(chǎn)收益率的波動性有關(guān)，，準確估計資產(chǎn)的波動率對于VaR的度量顯得十分必要。本文對VaR模型進行了深入研究，包括極值波動下的VaR風險度量及其高頻數(shù)據(jù)波動的VaR風險估計。介紹了極值分布中閾值和特征參數(shù)的估算方法，同時用兩種方法，即分為廣義極值模型和廣義Pareto模型，對風險價值VaR作了實證研究，由于正態(tài)分布與金融時間序列的分布不符，其收益率具有“尖峰厚尾”的特性，從分布來看，五分鐘損失序列的分布顯然偏離正態(tài)分布，它表現(xiàn)出一個粗大的尾巴，帶有負偏態(tài)和相對較大的峰度，并呈現(xiàn)波動集聚性。其次，廣義帕累托分布是最有用和最實用的極值理論模型的研究成果，在分析金融市場風險時，由于樣本數(shù)據(jù)具有厚尾分布,厚尾分布具有顯著的優(yōu)勢。實證研究結(jié)果表明，極值理論可以準確度量尾部分布的極端事件的風險價值。
[Abstract]:In the past twenty years, with the rapid development of the world economy, the trend of global integration, especially the global economic integration, has become more and more obvious, accompanied by the rapid development of the world economy, especially marked by the collapse of the Bretton Woods system. The stability of global financial markets has become increasingly fragile, and financial market risks have not disappeared for a day, hanging like the sword of Damocles. Financial risk will affect the world economic pattern as a whole, not a single financial institution. Its influence may affect the stable development of the world economy. The measurement of financial risk has become a very important subject, and it has very important theoretical and practical significance to study it. In the process of risk management practice, the theory of risk measurement develops VaR risk measurement method, which makes the quantitative study of financial risk further developed. The financial market of our country is not mature at present, the variety of hedging tools is still lack, with the rapid development of the financial market, the risk it bears is becoming more and more big. As a basic risk management tool, stock index futures have the functions of price discovery and hedging. The Shanghai and Shenzhen 300 stock index futures contracts are officially listed, which marks the birth of stock index futures in China. Its introduction fills the blank of the lack of systematic risk management means in China's stock market, and will change the present situation of stock market lacking tools to avoid systemic risk. This paper makes an empirical study on the data of stock index futures by using the VaR model of extreme value distribution, and analyzes the importance of VaR value to the risk evaluation of stock index futures. The accuracy of VaR value is not only related to the distribution of return rate of assets, but also to the risk evaluation of stock index futures. It is also related to the volatility of the return on assets. It is necessary to estimate the volatility of assets accurately for the measurement of VaR. In this paper, the VaR model is deeply studied, including the VaR risk measurement under extreme fluctuation and the VaR risk estimation of high frequency data fluctuation. This paper introduces the estimation methods of threshold and characteristic parameters in the extreme value distribution, and uses two methods, namely, the generalized extreme value model and the generalized Pareto model, to make an empirical study on VaR of risk value, because the normal distribution does not agree with the distribution of financial time series. From the distribution, the distribution of the five-minute loss series deviates from the normal distribution obviously. It shows a coarse tail with negative skewness and relatively large kurtosis, and shows a fluctuating agglomeration. Secondly, the generalized Pareto distribution is the most useful and practical research result of extreme value theory model. In the analysis of financial market risk, because of the thick tail distribution in the sample data, the thick tail distribution has a significant advantage. The empirical results show that the extreme value theory can accurately measure the risk value of extreme events with tail distribution.
【學位授予單位】：上海師范大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：F832.51;F224

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