本文選題：金融物理 + 市場(chǎng)微觀結(jié)構(gòu)��； 參考：《華東理工大學(xué)》2012年博士論文

【摘要】：自從進(jìn)入二十世紀(jì)五十年代以后,金融市場(chǎng)的理論研究得到了迅猛的發(fā)展。同時(shí),隨著計(jì)算機(jī)的發(fā)展,使得金融研究人員對(duì)金融市場(chǎng)高頻交易數(shù)據(jù)的實(shí)證研究成為現(xiàn)實(shí)。中國(guó)的金融市場(chǎng)是一個(gè)新興的市場(chǎng),同時(shí)也具有其不同于一般西方市場(chǎng)的特色,這使得對(duì)中國(guó)金融市場(chǎng)的研究成為必要。本論文以中國(guó)證券市場(chǎng)為研究對(duì)象,運(yùn)用了金融物理學(xué)、計(jì)量經(jīng)濟(jì)學(xué)等方法并結(jié)合高頻數(shù)據(jù)對(duì)市場(chǎng)的內(nèi)部微觀現(xiàn)象和結(jié)構(gòu)進(jìn)行了實(shí)證的研究。同時(shí),本論文也對(duì)當(dāng)今金融市場(chǎng)新的研究方法做了深入的研究和探討,并提出了一套基于投資效用的市場(chǎng)投資理論以及基于該理論的投資策略。 在對(duì)我國(guó)金融市場(chǎng)微觀現(xiàn)象和結(jié)構(gòu)的研究中,首先我們對(duì)我國(guó)滬深兩市的買(mǎi)賣(mài)價(jià)差進(jìn)行了研究。通過(guò)Lomb功率譜分析,我們驗(yàn)證了兩市股票價(jià)差存在以日為周期的周期模式,并且該周期呈現(xiàn)“L”型的日內(nèi)模式。同時(shí),由該日內(nèi)模式得到在每個(gè)交易日開(kāi)盤(pán)后的一個(gè)小時(shí)內(nèi),兩市的買(mǎi)賣(mài)價(jià)差都呈現(xiàn)冪率遞減的現(xiàn)象,且其冪指數(shù)分別為βSHSE=0.20±0.067和βSZSE=0.19±0.069。而在對(duì)個(gè)股的日內(nèi)模式的研究中也發(fā)現(xiàn)了同樣的性質(zhì),且其冪指數(shù)大致服從正態(tài)分布。這說(shuō)明了由累積的信息導(dǎo)致市場(chǎng)的價(jià)差增大是一個(gè)內(nèi)生的動(dòng)力學(xué)過(guò)程。 第二,我們使用深圳證券交易所的超高頻交易數(shù)據(jù),對(duì)深證市場(chǎng)上交易者的撤單行為進(jìn)行了研究。研究中我們將撤單的時(shí)間間隔作為研究的對(duì)象,并分別考慮了三種不同撤單的交易者的行為,即買(mǎi)撤單、賣(mài)撤單以及所有撤單。我們發(fā)現(xiàn)每支股票撤單間隔的分布密度都可以由韋伯分布函數(shù)來(lái)描述,且市場(chǎng)的撤單間隔表現(xiàn)出一個(gè)非常好的標(biāo)度率的性質(zhì)。在對(duì)其撤單間隔長(zhǎng)度的分類(lèi)討論中撤單間隔表現(xiàn)出一個(gè)較強(qiáng)的記憶相關(guān)性。此外,我們?cè)诔穯伍g隔的數(shù)據(jù)中同樣也發(fā)現(xiàn)了一個(gè)呈“八”字型的日內(nèi)模式。通過(guò)降趨脈動(dòng)分析法和多重分形降趨脈動(dòng)分析發(fā)現(xiàn),撤單間隔之間存在長(zhǎng)程相關(guān)性和多重分形的性質(zhì),而撤單的日內(nèi)模式對(duì)此并沒(méi)有產(chǎn)生任何的影響。這些結(jié)果都說(shuō)明了市場(chǎng)交易者撤單的行為并不是一個(gè)泊松過(guò)程,這在我們對(duì)指令驅(qū)動(dòng)市場(chǎng)的建模中具有重要的參考作用。而在第二部分對(duì)基于事件時(shí)間的交易者的撤單行為的研究中,我們卻得到了與連續(xù)時(shí)間下撤單行為不同的結(jié)論。首先,撤單的分布不再具有標(biāo)度性,同時(shí),交易者撤單的分布很好的服從了一個(gè)截尾的泊松分布,這些結(jié)論給基于事件研究的模型提供了較好的實(shí)證基礎(chǔ)。 第三,我們對(duì)市場(chǎng)交易者的交易積極性進(jìn)行了研究。通過(guò)對(duì)深證指令簿訂單數(shù)據(jù)的研究,我們發(fā)現(xiàn)：(1)交易指令簿的深度(包括已方指令簿的深度和對(duì)手方指令簿的深度)對(duì)交易雙方的積極性都產(chǎn)生積極的影響,即當(dāng)市場(chǎng)指令簿深度增加時(shí),市場(chǎng)交易的積極性就會(huì)增加。但是由該因素所產(chǎn)生的影響非常有限,在模型中其影響幾乎可以忽略不計(jì)；(2)大的買(mǎi)賣(mài)價(jià)差能夠有效的降低市場(chǎng)交易者的下單積極性,這說(shuō)明深市的交易者大多是成本厭惡型的投資者,當(dāng)面臨較大的交易成本時(shí),他們更多的是選擇承擔(dān)風(fēng)險(xiǎn)；(3)指令簿中高頻率的買(mǎi)單委托指令能夠有效的激發(fā)買(mǎi)方交易者提交積極的買(mǎi)單指令,而低頻率的賣(mài)單委托則能迫使賣(mài)方交易者提交積極的賣(mài)單指令；(4)不穩(wěn)定的價(jià)格波動(dòng)使得更多的交易者在更利于自己的價(jià)位上等待自己的交易時(shí)機(jī),這說(shuō)明了深市的交易者多為成熟的交易者,在出現(xiàn)股價(jià)劇烈波動(dòng)的時(shí)候不輕易追漲殺跌。 而在對(duì)當(dāng)今金融市場(chǎng)新的研究方法的探討中,我們首先引入了可視圖的研究方法。通過(guò)產(chǎn)生分形布朗運(yùn)動(dòng)和多重分形隨機(jī)游走的模擬實(shí)驗(yàn),我們發(fā)現(xiàn)其對(duì)應(yīng)的可視圖的度分布呈現(xiàn)出冪率下降的行為,同時(shí)該冪函數(shù)的的冪指數(shù)和原序列的Hurst指數(shù)之間呈現(xiàn)出一個(gè)較好的線性關(guān)系。而在多重分形的性質(zhì)并沒(méi)有對(duì)結(jié)果產(chǎn)生太大的影響。在對(duì)中國(guó)滬深兩市和香港股市的實(shí)證研究中,我們?cè)僖淮悟?yàn)證了該關(guān)系。 第二,我們?cè)趯?duì)金融市場(chǎng)資產(chǎn)收益的估值上引入了Levy-Roll的估值方法。對(duì)于他們的理論,我們相應(yīng)提出了一套更為完善和細(xì)致的對(duì)該方法的魯棒性的檢驗(yàn)方法。在該方法通過(guò)我們的監(jiān)測(cè)后,我們則使用該方法對(duì)整個(gè)市場(chǎng)的進(jìn)行了實(shí)證檢驗(yàn),而該方法表現(xiàn)出了較之傳統(tǒng)估計(jì)更為穩(wěn)定性的收益率；最后,在對(duì)一組資產(chǎn)組合的實(shí)際應(yīng)用中,該方法再一次展現(xiàn)了相比于使用樣本參數(shù)等常規(guī)方法的優(yōu)越性。從而我們認(rèn)為,使用Levy-Roll的收益估值方法能夠獲得的資產(chǎn)的內(nèi)在投資價(jià)值,同時(shí)在如今對(duì)CAPM一片的質(zhì)疑聲中,我們?cè)僖淮慰隙薈APM在現(xiàn)代金融學(xué)中的核心地位。 最后,我們提出了一套基于投資效用的慣序投資理論。在該模型下,我們指出在證券市場(chǎng)中,交易者的交易效用由市場(chǎng)的上升趨勢(shì)β和投資者所使用的交易策略的準(zhǔn)確率α所共同決定,且僅當(dāng)兩參數(shù)的總和大于1時(shí),交易者才能在市場(chǎng)上獲得正的預(yù)期投資收益效用。此外,我們還指出了在該模型下,當(dāng)投資者對(duì)兩個(gè)以上的資產(chǎn)進(jìn)行慣序分析投資時(shí),他能夠得到大于對(duì)單個(gè)資產(chǎn)進(jìn)行分析投資而帶來(lái)的預(yù)期投資效用,且該效用隨著投入資產(chǎn)數(shù)量的增加而增加,但其上限為兩倍于對(duì)單支資產(chǎn)分析投資時(shí)所獲得的投資效用。隨后,我們?cè)谠摻灰桌碚摰幕A(chǔ)上提出了一個(gè)輪轉(zhuǎn)投資策略,并提出了一套用來(lái)判斷策略投資優(yōu)劣的評(píng)價(jià)體系。在對(duì)滬深兩市的實(shí)證研究中,使用輪轉(zhuǎn)策略的投資收益能夠輕松地跑贏所選用的兩支股票,并且在隨機(jī)策略的模擬測(cè)試中能夠取得較高的輪轉(zhuǎn)正確率和較低的平均懲罰收益。同時(shí),通過(guò)計(jì)算4753對(duì)股票的投資結(jié)果,我們認(rèn)為較少的輪轉(zhuǎn)的能得到較低的平均懲罰收益。
[Abstract]:Since the 1950s, the theoretical research of the financial market has developed rapidly. At the same time, with the development of the computer, the empirical research on the high frequency transaction data of the financial market has become a reality with the development of the computer. The financial market in China is a new market, and it is also different from the general west. The characteristics of the market make it necessary to study the financial market in China. This paper takes the Chinese securities market as the research object, uses the financial physics, econometrics and other methods, and carries out an empirical study on the internal micro phenomena and structure of the market combined with high frequency data. At the same time, this paper also has a new research on the current financial market. The method has been thoroughly studied and discussed, and a set of market investment theory based on investment utility and investment strategy based on this theory have been put forward.
In the study of the microcosmic phenomenon and structure of China's financial market, we first studied the price difference between the two cities and Shanghai cities in China. Through the Lomb power spectrum analysis, we verified the periodic pattern of the two stock price difference in the daily cycle, and the period showed the "L" type in the day mode. In an hour after the opening of each trading day, the sale spreads of the two cities show a decline in the power rate, and the power exponents are respectively beta SHSE=0.20 + 0.067 and beta SZSE=0.19 + 0.069., respectively, and the same properties are found in the study of the intra day mode of the stock, and the power exponents are highly subordinate to the normal distribution. This shows the accumulated information. The increase of market spreads is an endogenous dynamic process.
Second, we use the ultra high frequency transaction data of the Shenzhen stock exchange to study the behavior of the traders' withdrawal in the Shenzhen stock market. In the study, we take the time interval of the withdrawal as the object of the study, and consider the behavior of the traders with three different kinds of withdrawal, namely, the purchase of the bill, the sale of the withdrawal and all the withdrawal. The distribution density of the stock withdrawal interval can be described by the Webb distribution function, and the withdrawal interval of the market shows a very good scale rate. In the classification discussion of the length of the withdrawal interval, the withdrawal interval shows a strong memory correlation. In addition, we also find that in the data of the withdrawal interval, we also find that An intraday model with a "eight" type is found. Through the analysis of the decline in the pulsation and the multifractal degradation, it is found that there is a long range correlation and a multifractal nature between the intervals of the withdrawal, and the internal model of the withdrawal has no effect on it. These results show that the behavior of the market trader is not the behavior of the withdrawal. A Poisson process plays an important role in the modeling of the instruction driven market. In the second part of the study on the behavior of the trader based on the event time, we get the conclusion that the withdrawal behavior is different from that in the continuous time. First, the distribution of the withdrawal is no longer in scale, while the trader withdraws. The distribution of the single well obeys a censored Poisson distribution. These conclusions provide a good empirical basis for the model based on event study.
Third, we have studied the trading enthusiasm of market traders. Through the study of the order data of the Shenzhen stock order book, we found that: (1) the depth of the transaction instruction book (including the depth of the late instruction book and the depth of the opponent's instruction book) has a positive impact on the enthusiasm of both parties, that is, when the market instruction book increases in depth. In addition, the enthusiasm of market trading will increase. However, the influence produced by this factor is very limited, and its influence in the model can almost be ignored. (2) the big sale price difference can effectively reduce the initiative of the market traders, which shows that most of the traders in the deep market are cost aversion investors, when they are faced with larger ones. When trading costs, they are more likely to take risks; (3) the high frequency purchase order instruction in the instruction book can effectively motivate the buyer to submit an active purchase order, while the low frequency sell orders can force the seller to submit a positive selling order; (4) the unstable price fluctuation makes more traders. Waiting for the time to deal with its own price shows that the traders in the deep market are mostly mature traders who are not easy to chase and fall when the stock price fluctuates.
In the discussion of new research methods in the current financial market, we first introduce a view based method. Through the simulation experiments that produce fractal Brown movement and multifractal random walk, we find that the corresponding degree distribution of the corresponding view shows a line of power rate decline, and the power exponent and the original sequence of the power function. There is a good linear relationship between the Hurst index, and the nature of multifractal does not have much effect on the results. In the empirical study of China's Shanghai and Shenzhen two cities and Hongkong stock markets, we once again verified the relationship.
Second, we introduce the Levy-Roll valuation method to the valuation of financial market asset returns. For their theory, we propose a more robust and detailed test method for the robustness of the method. After our monitoring, we use this method to empirically examine the whole market. The method shows a more stable yield than the traditional estimate; finally, in the actual application of a group of portfolios, the method once again shows the superiority of the conventional methods, such as the use of the sample parameters, so we believe that the intrinsic investment of the assets that can be obtained by using the Levy-Roll's income valuation method is considered. Value, at the same time, in today's questioning of CAPM, we once again affirmed the core position of CAPM in modern finance.
Finally, we propose a set of inertial sequencing investment theory based on investment utility. Under this model, we point out that in the stock market, the trading utility of traders is determined by the rising trend beta of the market and the accuracy of the trading strategy used by investors, and only when the sum of two references is more than 1 can the trader get the market. In addition, we also point out that under this model, when investors invest in more than two assets, he can get the expected investment effectiveness greater than the investment in the analysis of individual assets, and the utility increases with the increase in the number of invested assets, but the upper limit is two. Then, we put forward a rotation investment strategy on the basis of the transaction theory, and put forward a set of evaluation system to judge the advantages and disadvantages of the strategy investment. In the empirical study on the two cities and Shanghai cities, the investment income of the rotation strategy can easily win and win the choice. The two stocks used, and in the simulation test of random strategies, can achieve higher rotation accuracy and lower average penalty returns. At the same time, by calculating the investment results of 4753 stocks, we believe that less rotation can get lower average penalty returns.

【學(xué)位授予單位】：華東理工大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2012
【分類(lèi)號(hào)】：F832.51;F224

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