【摘要】：連續(xù)時(shí)間隨機(jī)波動(dòng)率模型是目前研究期權(quán)定價(jià)的主流,波動(dòng)率作為反應(yīng)標(biāo)的資產(chǎn)投資回報(bào)率的變化程度的指標(biāo),受到多方面的影響,其隨機(jī)特性是基于大量研究得出的,隨機(jī)波動(dòng)率不僅解釋了微笑模式的基本形狀,也同樣適用于隱含波動(dòng)率的“期限結(jié)構(gòu)”。因此連續(xù)時(shí)間隨機(jī)波動(dòng)率的設(shè)定能使得模型更好的模擬出基礎(chǔ)資產(chǎn)價(jià)格運(yùn)動(dòng)的過程,從而為進(jìn)一步的期權(quán)定價(jià)問題打好基礎(chǔ)。 本文基于DELL公司2010年11月5日至2011年11月5日一年內(nèi)共計(jì)253個(gè)交易日股票數(shù)據(jù)作為基礎(chǔ)資產(chǎn)的觀測(cè)數(shù)據(jù)研究連續(xù)時(shí)間隨機(jī)波動(dòng)率模型研究期權(quán)的非參數(shù)定價(jià)問題,主要做了以下工作： 在第一部分總結(jié)了有關(guān)模型選擇以及隨機(jī)波動(dòng)率模型非參數(shù)定價(jià)方面的研究現(xiàn)狀。第二部分介紹并總結(jié)了相關(guān)預(yù)備知識(shí),包括期權(quán)定價(jià)的影響因素,幾類典型的連續(xù)時(shí)間隨機(jī)波動(dòng)率模型,以及非參數(shù)估計(jì)方法；在第三部分說明了基礎(chǔ)資產(chǎn)價(jià)格過程的模型以及各項(xiàng)參數(shù)的估計(jì)方法,主要運(yùn)用非參數(shù)方法估計(jì)出波動(dòng)率函數(shù)形式,再在波動(dòng)率的基礎(chǔ)上估計(jì)其他各項(xiàng)參數(shù)；第四部分是模擬分析,判斷模型設(shè)定以及方法的選擇是否合理：第五部分是實(shí)證研究,根據(jù)以上方法代入數(shù)據(jù)得到最終的估計(jì)結(jié)果。結(jié)果表明非參數(shù)定價(jià)方法能夠很好的擬合期權(quán)定價(jià)過程,
[Abstract]:Continuous time stochastic volatility model is the mainstream of option pricing at present. Volatility, as an indicator of the degree of change of return on investment of underlying assets, is affected by many aspects, and its stochastic characteristics are based on a large number of studies. Random volatility not only explains the basic shape of smile mode, but also applies to the term structure of implicit volatility. Therefore, the continuous time stochastic volatility can make the model better simulate the process of the underlying asset price movement, thus laying a good foundation for the further option pricing problem. Based on the observation data of 253trading days stock data from November 5, 2010 to November 5, 2011, this paper studies the nonparametric pricing problem of option based on continuous time stochastic volatility model. The main work is as follows: in the first part, the research status of model selection and non-parametric pricing of stochastic volatility model is summarized. The second part introduces and summarizes the relevant preparatory knowledge, including the influence factors of option pricing, several typical continuous-time stochastic volatility models, as well as non-parametric estimation methods. In the third part, the model of the basic asset price process and the estimation method of each parameter are explained. The non-parametric method is mainly used to estimate the volatility function form, and then the other parameters are estimated on the basis of volatility. The fourth part is the simulation analysis to judge whether the model setting and the method choice is reasonable. The fifth part is the empirical research, according to the above method substitute the data to obtain the final estimate result. The results show that the non-parametric pricing method can fit the process of option pricing well.
【學(xué)位授予單位】：南京理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：F830.9;F224

【參考文獻(xiàn)】

相關(guān)博士學(xué)位論文 前1條

1 陳萍;隨機(jī)波動(dòng)率模型的統(tǒng)計(jì)推斷及其衍生證券的定價(jià)[D];南京理工大學(xué);2004年

，

本文編號(hào)：2314455