【摘要】：建模金融資產(chǎn)收益和回報(bào)并進(jìn)行預(yù)測(cè)對(duì)于資本市場(chǎng)的決策者和參與者追求利潤(rùn)最大化的目標(biāo)和做出精準(zhǔn)判決是至關(guān)重要的。盡管在相關(guān)的文獻(xiàn)中已經(jīng)出現(xiàn)了對(duì)金融資產(chǎn)收益率動(dòng)態(tài)波動(dòng)的相關(guān)的學(xué)術(shù)文章,但是建模和預(yù)測(cè)金融資產(chǎn)收益的動(dòng)態(tài)波動(dòng)性在金融數(shù)學(xué),金融計(jì)量經(jīng)濟(jì)學(xué),金融經(jīng)濟(jì)學(xué),應(yīng)用統(tǒng)計(jì)與經(jīng)濟(jì)增長(zhǎng)中所能夠起到的關(guān)鍵作用時(shí)至至今,仍然是一個(gè)懸而未決的問(wèn)題。因此,本論文詳細(xì)闡述并探討了關(guān)于標(biāo)準(zhǔn)普爾500股指日收益率和塞拉利昂月匯率收益的動(dòng)態(tài)波動(dòng)模型的建模和預(yù)測(cè),這其中包括自回歸滑動(dòng)平均模型,廣義自回歸條件異方差模型(GARCH), Taylor,Schwert廣義自回歸條件異方差模型(GARCH), Glosten, Jagannathan, Runkle GARCH模型及條件正態(tài)分布,t分布的非對(duì)稱(chēng)ARCH模型。于此同時(shí),此篇文章也詳細(xì)論述了由Dickey-Fuller, Phillip-Perron提出的單位根檢驗(yàn),誤差糾正模型。同時(shí)證明了在簡(jiǎn)單序約束條件下,平穩(wěn)APARCH(p)模型的一致收斂性,強(qiáng)相合性和漸進(jìn)正態(tài)性。同時(shí)也推導(dǎo)了APARCH模型解析得分表達(dá)式。結(jié)合極大似然估計(jì)推導(dǎo)了GARCH模型的相關(guān)性質(zhì)。將2002年1月1日至2012年至12月31日期間的日標(biāo)準(zhǔn)普爾500指數(shù)回報(bào)數(shù)據(jù),1991年1月1日至2013年12月31日,塞拉利昂月匯率收益數(shù)據(jù)對(duì)上述提及的模型進(jìn)行擬合,結(jié)果表明使用重尾t分布的APARCH模型是最有效和最成功預(yù)測(cè)模型,能夠成功預(yù)測(cè)日股指回報(bào)序列。在重尾t分布下的GJR-GARCH模型能夠最有效的預(yù)測(cè)塞拉利昂月匯率收益率序。誤差修正的結(jié)果顯示,如果長(zhǎng)期的均衡出現(xiàn)偏離,則可通過(guò)對(duì)日股票指數(shù)和月度匯率的不平衡性的調(diào)整,來(lái)達(dá)到恢復(fù)平衡的效果。最后,研究表明,文中給出的模型能夠成功建模日500股票指數(shù)和塞拉利昂月匯率波動(dòng)。同時(shí)由于杠桿效應(yīng)的存在,導(dǎo)致了非對(duì)稱(chēng)GARCH模型顯示出了非對(duì)稱(chēng)的收益率序列。在非常態(tài)分布下,非對(duì)稱(chēng)(GARCH)和GARCH模型能夠更好的擬合并提升整體的對(duì)條件方差的估計(jì)。鑒于股指和匯率波動(dòng)的實(shí)際含義,此研究將對(duì)資本市場(chǎng)的決策者,投資人及行業(yè)從業(yè)研究人員在經(jīng)濟(jì)行業(yè)實(shí)踐中,所涌現(xiàn)出的風(fēng)險(xiǎn)管控和外匯市場(chǎng)波動(dòng)等領(lǐng)域起到至關(guān)重要的作用。
[Abstract]:Modeling and forecasting the returns and returns of financial assets is essential for capital market decision makers and participants to pursue the goal of maximizing profits and making accurate decisions. Although there have been relevant academic articles on the dynamic volatility of financial asset returns in the relevant literature, modeling and predicting the dynamic volatility of financial asset returns in financial mathematics, financial econometrics, financial economics, Application of statistics and economic growth can play a key role until now, is still an outstanding issue. Therefore, this paper discusses the modeling and forecasting of the dynamic volatility model of the daily yield of the S & P 500 stock index and the Sierra Leone monthly exchange rate return, which includes the autoregressive moving average model. Generalized autoregressive conditional heteroscedasticity model (GARCH), Taylor,Schwert generalized autoregressive conditional heteroscedasticity model (GARCH), Glosten, Jagannathan, Runkle GARCH model and asymmetric ARCH model with conditional normal distribution and t distribution. At the same time, this paper also discusses the unit root test and error correction model proposed by Dickey-Fuller, Phillip-Perron in detail. At the same time, the uniform convergence, strong consistency and asymptotic normality of stationary APARCH (p) model are proved under the condition of simple order constraint. At the same time, the analytic score expression of APARCH model is derived. The related properties of GARCH model are derived by using maximum likelihood estimation. Using the daily S & P 500 return data for the period from 1 January 2002 to 31 December 2012 and the Sierra Leone monthly exchange rate gains data from 1 January 1991 to 31 December 2013 to fit the model mentioned above, The results show that the APARCH model with heavy-tailed t distribution is the most effective and successful prediction model and can successfully predict the daily stock index return series. The GJR-GARCH model under the heavy-tailed t distribution can best predict the monthly exchange rate return order in Sierra Leone. The result of error correction shows that if the long-term equilibrium deviates, the effect of restoring equilibrium can be achieved by adjusting the imbalance between the Japanese stock index and the monthly exchange rate. Finally, it is shown that the proposed model can successfully model the daily 500 stock index and the Sierra Leone monthly exchange rate fluctuation. At the same time, because of the existence of leverage effect, the asymmetric GARCH model shows an asymmetric return sequence. Under the abnormal distribution, asymmetric (GARCH) and GARCH models can better estimate the conditional variance of the whole quasi combined lifting system. In view of the actual implications of stock index and exchange rate fluctuations, the study will apply to capital market decision makers, investors and industry researchers in the practice of the economic industry. Emerging risk management and foreign exchange market volatility and other areas play a vital role.
【學(xué)位授予單位】：大連理工大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：F830;F224

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