本文選題：股指期貨錯(cuò)誤定價(jià) + 非線性特征�。� 參考：《湖南大學(xué)》2012年碩士論文

【摘要】：滬深300股指期貨作為我國(guó)首只金融期貨品種，自推出來(lái)了在平抑市場(chǎng)波動(dòng)，增加市場(chǎng)流動(dòng)性，價(jià)格發(fā)現(xiàn)等方面取得不錯(cuò)成果。由于交易成本，市場(chǎng)微觀結(jié)構(gòu)以及投資者行為等因素的影響，股指期貨市場(chǎng)存在錯(cuò)誤定價(jià)現(xiàn)象。滬深300股指期貨的錯(cuò)誤定價(jià)表述為股指期貨的市場(chǎng)價(jià)格與其理論價(jià)格的偏差。股指期貨錯(cuò)誤定價(jià)時(shí)間序列是股指期貨錯(cuò)誤定價(jià)在時(shí)間軸上形成的一系列連續(xù)值。股指期貨錯(cuò)誤定價(jià)時(shí)間序列作為金融時(shí)間序列的一部分，它具有金融時(shí)間序列一般的非線性特征，比如說(shuō)尖峰厚尾，波動(dòng)集聚等非線性特征。目前對(duì)金融時(shí)間序列非線性特征的研究比較多，然而關(guān)于滬深300股指期貨錯(cuò)誤定價(jià)時(shí)間序列非線性特征研究的文章很少。為此，本文參照金融時(shí)間序列非線性特征的研究思路，對(duì)錯(cuò)誤定價(jià)時(shí)間序列進(jìn)行相關(guān)的非線性檢驗(yàn)，實(shí)證得到錯(cuò)誤定價(jià)時(shí)間序列存在尖峰厚尾，自相關(guān)，波動(dòng)集聚的特征之后，接著采用分形理論，運(yùn)用R/S分析法來(lái)研究錯(cuò)誤定價(jià)時(shí)間序列的長(zhǎng)期記憶和分形特征，建立ARMA-GARCH模型來(lái)擬合錯(cuò)誤定價(jià)時(shí)間序列，，并進(jìn)行模型的短期預(yù)測(cè)。
[Abstract]:As the first financial futures in China, Shanghai and Shenzhen 300 stock index futures have achieved good results in stabilizing market fluctuations, increasing market liquidity and price discovery. Because of the influence of transaction cost, market microstructure and investor behavior, the stock index futures market has mispricing phenomenon. The mispricing of Shanghai and Shenzhen 300 stock index futures is expressed as the deviation between the market price and the theoretical price of stock index futures. Stock index futures mispricing time series is a series of continuous values formed on the time axis of stock index futures mispricing. Stock index futures mispricing time series as a part of financial time series, it has the general nonlinear characteristics of financial time series, such as peak thick tail, volatility agglomeration and other nonlinear characteristics. At present, there are many researches on the nonlinear characteristics of financial time series, but there are few articles on the nonlinear characteristics of Shanghai and Shenzhen 300 stock index futures mispricing time series. Therefore, according to the research ideas of the nonlinear characteristics of financial time series, this paper makes a correlation nonlinear test on the mispricing time series. The empirical results show that the mispricing time series has the characteristics of peak and thick tail, autocorrelation and volatility agglomeration. Then we use fractal theory and R / S analysis to study the long-term memory and fractal characteristics of mispricing time series, establish ARMA-GARCH model to fit the mispricing time series, and carry out short-term prediction of the model.
【學(xué)位授予單位】：湖南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：F832.51;F224

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本文編號(hào)：1970860