本文選題：財(cái)務(wù)指標(biāo)　切入點(diǎn)：量化選股　出處：《浙江工商大學(xué)》2017年碩士論文

【摘要】：Alpha策略以其風(fēng)險(xiǎn)敞口小、不受市場(chǎng)所處經(jīng)濟(jì)周期的影響等優(yōu)勢(shì)在量化投資領(lǐng)域占有不朽的一席之地。尋找有效的alpha因子成為能否獲取正的alpha收益的關(guān)鍵,而資本市場(chǎng)中公開(kāi)披露的財(cái)務(wù)信息與alpha收益是否存在緊密相關(guān)性,能否利用財(cái)務(wù)信息構(gòu)建alpha因子,都成為量化策略投資特別關(guān)注的問(wèn)題。本文從alpha收益與財(cái)務(wù)指標(biāo)的相關(guān)性分析出發(fā),探討基于財(cái)務(wù)指標(biāo)構(gòu)建alpha因子的可行性。首先,本文根據(jù)alpha收益構(gòu)建的基本原理,通過(guò)剔除Fama-French的三因子和五因子模型中財(cái)務(wù)指標(biāo),提出了兩因子模型,即只考慮了市場(chǎng)系統(tǒng)風(fēng)險(xiǎn)和市值風(fēng)險(xiǎn)因子的資本資產(chǎn)定價(jià)模型,從而使得實(shí)證過(guò)程中alpha收益包含了不確定的公司財(cái)務(wù)指標(biāo)的影響,以此研究alpha收益與財(cái)務(wù)指標(biāo)的相關(guān)性。在樣本時(shí)間區(qū)間內(nèi)依據(jù)財(cái)務(wù)指標(biāo)大小對(duì)股票進(jìn)行排序,得到財(cái)務(wù)指標(biāo)排名前20%的股票的平均α收益α1時(shí)間序列和財(cái)務(wù)指標(biāo)排名后20%的股票的平均α收益α2時(shí)間序列,對(duì)兩組時(shí)間序列做t檢驗(yàn)來(lái)判斷兩者之間是否有顯著差異,并由此判斷財(cái)務(wù)指標(biāo)與股票alpha收益之間的相關(guān)性。其次,通過(guò)滾動(dòng)回歸計(jì)算所需alpha,并依據(jù)財(cái)務(wù)報(bào)表披露日期對(duì)財(cái)務(wù)數(shù)據(jù)做滯后處理。由于在一段時(shí)間內(nèi)財(cái)務(wù)指標(biāo)數(shù)值是不變的,alpha是時(shí)變的,這就使得兩者之間的spearman相關(guān)系數(shù)是時(shí)變的。最后,基于樣本內(nèi)分析所得有效財(cái)務(wù)因子構(gòu)建alpha策略,并通過(guò)樣本外數(shù)據(jù)檢驗(yàn)是否可獲取正alpha收益。本文共做了三次樣本外投資組合的構(gòu)建,對(duì)所有可能涉及到的持倉(cāng)區(qū)間均進(jìn)行了實(shí)證檢驗(yàn)。通過(guò)對(duì)樣本內(nèi)32個(gè)財(cái)務(wù)指標(biāo)與股票alpha收益之間的相關(guān)性分析得到如下結(jié)論:若持倉(cāng)期為半年,則在10%顯著性水平下,不存在與股票alpha收益相關(guān)性較為顯著的財(cái)務(wù)指標(biāo)。若持倉(cāng)期為四個(gè)月,則在5%顯著性水平下,每股收益同比增長(zhǎng)與alpha收益正相關(guān),資本固定化比率與股票alpha收益負(fù)相關(guān)。在10%顯著性水平下,流動(dòng)比率、扣除非經(jīng)常性損益后歸屬于母公司凈利潤(rùn)、流動(dòng)資產(chǎn)總資產(chǎn)占比、流動(dòng)負(fù)債總負(fù)債占比與股票alpha收益正相關(guān)。若持倉(cāng)期為兩個(gè)月,則在5%顯著性水平下,流動(dòng)比率、應(yīng)收賬款周轉(zhuǎn)天數(shù)與股票alpha收益正相關(guān),資本固定化比率與股票alpha收益負(fù)相關(guān)。在10%顯著性水平下,現(xiàn)金比率、現(xiàn)金循環(huán)周期、流動(dòng)負(fù)債總負(fù)債占比與股票alpha收益正相關(guān),資產(chǎn)負(fù)債率與股票alpha收益負(fù)相關(guān)。反映了相同財(cái)務(wù)指標(biāo)在不同的時(shí)間區(qū)間與股票alpha收益之間的相關(guān)性是有所不同的。三組樣本外的實(shí)證結(jié)果表明,即便是在熊市,alpha策略仍然可以使投資者獲取正的收益。且與滬深300指數(shù)和投資組合每日的漲跌幅相比,投資組合alpha收益的波動(dòng)率更為平穩(wěn),尤其是在市場(chǎng)震動(dòng)較為劇烈的時(shí)候,此優(yōu)勢(shì)更為突出。
[Abstract]:The Alpha strategy has an immortal place in the quantitative investment field because of its small exposure and its advantages such as being free from the impact of the business cycle in which the market is located.Finding effective alpha factor becomes the key to obtain positive alpha income. However, whether there is close correlation between the publicly disclosed financial information and the return of alpha in the capital market, and whether to use financial information to construct the alpha factor, can be used to construct the alpha factor.All become the question that quantification strategy investment pays special attention to.Based on the analysis of the correlation between alpha income and financial index, this paper discusses the feasibility of constructing alpha factor based on financial index.Firstly, according to the basic principle of alpha income construction, this paper proposes a capital asset pricing model which only takes market system risk and market value risk factor into account by excluding the financial indexes of Fama-French 's three-factor and five-factor models.Thus, the empirical process of alpha earnings includes the impact of uncertain corporate financial indicators, so as to study the correlation between alpha returns and financial indicators.In the sample time interval, the stock is sorted according to the size of financial index, and the average 偽 return 偽 1 time series of the top 20% stock and the average 偽 return 偽 2 time series of 20% stock after the financial index rank are obtained.T test is made on the two groups of time series to judge whether there is a significant difference between the two groups, and the correlation between the financial indexes and the stock alpha returns is judged.Secondly, the alphaa is calculated by rolling regression, and the financial data is delayed according to the date of financial statement disclosure.The spearman correlation coefficient between the two is time-varying because the value of the financial index is invariant for a period of time.Finally, the alpha strategy is constructed based on the effective financial factors obtained from the in-sample analysis, and the positive alpha income can be obtained by the out-of-sample data.In this paper, we construct the portfolio outside the sample three times, and make an empirical test on all possible positions.By analyzing the correlation between 32 financial indexes and stock alpha returns in the sample, the following conclusions are drawn: if the holding period is half a year, there is no significant correlation between the financial indicators and the stock alpha returns at the level of 10% significance.If the holding period is four months, the growth of earnings per share is positively correlated with alpha earnings at a significant level of 5%, and the capital fixation ratio is negatively correlated with stock alpha earnings.At the significant level of 10%, the current ratio, after deducting the non-recurrent profit and loss, belongs to the net profit of the parent company, the proportion of the total assets of the current assets and the proportion of the total current liabilities are positively related to the alpha return of the stock.If the holding period is two months, at the level of 5% significance, the ratio of current and the days of turnover of accounts receivable are positively correlated with the return of stock alpha, while the ratio of capital immobilization is negatively correlated with the return of stock alpha.At the significant level of 10%, the cash ratio, the cash cycle, the ratio of current liabilities to total liabilities are positively correlated with the stock alpha returns, while the asset-liability ratio is negatively correlated with the stock alpha returns.It reflects that the correlation between the same financial index and the stock alpha return is different in different time range.Empirical results out of three groups of samples show that even in the bear market alpha strategy can still enable investors to achieve positive returns.Compared with the daily rise and fall of Shanghai and Shenzhen 300 index and portfolio, the volatility of portfolio alpha returns is more stable, especially when the market trembles more intensely, this advantage is more prominent.
【學(xué)位授予單位】：浙江工商大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F275;F832.51

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 張靖;;構(gòu)建多因子模型 發(fā)掘細(xì)微投資機(jī)會(huì)[J];股市動(dòng)態(tài)分析;2013年38期

2 王力弘;;淺議量化投資發(fā)展趨勢(shì)及其對(duì)中國(guó)的啟示[J];中國(guó)投資;2013年S2期

3 吳威成;;GARP選股策略研究[J];時(shí)代金融;2012年36期

4 方浩文;;量化投資發(fā)展趨勢(shì)及其對(duì)中國(guó)的啟示[J];管理現(xiàn)代化;2012年05期

5 王冰;李想;;淺議量化投資在國(guó)內(nèi)市場(chǎng)的發(fā)展[J];經(jīng)濟(jì)視角(下);2011年03期

6 潘莉;徐建國(guó);;A股個(gè)股回報(bào)率的慣性與反轉(zhuǎn)[J];金融研究;2011年01期

7 游家興;;誰(shuí)反應(yīng)過(guò)度，，誰(shuí)反應(yīng)不足——投資者異質(zhì)性與收益時(shí)間可預(yù)測(cè)性分析[J];金融研究;2008年04期

8 魯臻;鄒恒甫;;中國(guó)股市的慣性與反轉(zhuǎn)效應(yīng)研究[J];經(jīng)濟(jì)研究;2007年09期

9 王程;;中國(guó)股市價(jià)值策略實(shí)證研究[J];世界經(jīng)濟(jì)文匯;2005年06期

10 林斗志;價(jià)值投資在我國(guó)股市表現(xiàn)的實(shí)證分析[J];財(cái)經(jīng)科學(xué);2004年S1期

相關(guān)博士學(xué)位論文 前1條

1 溫琪;金融市場(chǎng)資產(chǎn)選擇與配置策略研究[D];中國(guó)科學(xué)技術(shù)大學(xué);2011年

相關(guān)碩士學(xué)位論文 前9條

1 朱世清;多因子選股模型的構(gòu)建與應(yīng)用[D];山東財(cái)經(jīng)大學(xué);2015年

2 鄒春陽(yáng);股票超額收益歸因研究[D];吉林財(cái)經(jīng)大學(xué);2015年

3 張利平;基于多因子模型的量化選股[D];河北經(jīng)貿(mào)大學(xué);2014年

4 開(kāi)翔;上市公司財(cái)務(wù)狀況與股票收益關(guān)聯(lián)性分析[D];首都經(jīng)濟(jì)貿(mào)易大學(xué);2014年

5 鄒運(yùn);基于遺傳算法的風(fēng)格選股模型研究[D];東北財(cái)經(jīng)大學(xué);2012年

6 劉毅;因子選股模型在中國(guó)市場(chǎng)的實(shí)證研究[D];復(fù)旦大學(xué);2012年

7 錢(qián)致昕;我國(guó)分行業(yè)上市公司股票投資價(jià)值研究[D];南京師范大學(xué);2007年

8 王小龍;多因子定價(jià)模型理論及在中國(guó)股票市場(chǎng)的檢驗(yàn)[D];武漢大學(xué);2005年

9 李成海;我國(guó)股票市場(chǎng)價(jià)值投資策略理論的實(shí)證研究[D];湖南大學(xué);2005年

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