本文選題：股票市場系統(tǒng)性風(fēng)險(xiǎn)　切入點(diǎn)：新的K線數(shù)據(jù)　出處：《天津工業(yè)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：股票市場的系統(tǒng)性風(fēng)險(xiǎn)作為金融系統(tǒng)的主要風(fēng)險(xiǎn)之一,長期受到人們的關(guān)注和研究,而目前我國的股票市場風(fēng)險(xiǎn)狀況仍然不容樂觀,影響股票市場的系統(tǒng)性風(fēng)險(xiǎn)依然存在。本文針對股票市場系統(tǒng)性風(fēng)險(xiǎn)做了三方面的工作。首先通過標(biāo)準(zhǔn)化原始數(shù)據(jù)、在計(jì)算出價(jià)格上升期間所需成交量后,對所需成交量以及價(jià)格進(jìn)行擬合,得到系統(tǒng)性風(fēng)險(xiǎn)發(fā)生前交易量和價(jià)格的關(guān)系;其次,將標(biāo)準(zhǔn)化的數(shù)據(jù)以周、月為單位進(jìn)行合并創(chuàng)造出新的具有統(tǒng)計(jì)意義的K線數(shù)據(jù)K1,并對K線數(shù)據(jù)K1進(jìn)行擬合,得到早于原始數(shù)據(jù)價(jià)格見頂?shù)腒線數(shù)據(jù)K2;第三,本文又進(jìn)一步根據(jù)K線數(shù)據(jù)K1和K2創(chuàng)造出12個(gè)特征,并使用SVR和Liner Regression方法對特征數(shù)據(jù)進(jìn)行擬合,獲得可以預(yù)測未來一年價(jià)格增長率的線性擬合函數(shù)。通過真實(shí)的股票數(shù)據(jù)驗(yàn)證表明,這三方面的工作都是有效的,且有助于幫助廣大投資者了解股票市場的變化情況,本文的工作對于預(yù)測和防范股票市場的系統(tǒng)性風(fēng)險(xiǎn)也提供了一種可行的方法。
[Abstract]:As one of the main risks in the financial system, the systemic risk of stock market has been paid attention to and studied by people for a long time. However, the situation of stock market risk in our country is still not optimistic. The systemic risk that affects the stock market still exists. This paper has done three works on the systemic risk of the stock market. Firstly, through the standardized raw data, after calculating the transaction volume required during the period of price rise, The required volume and price are fitted to obtain the relationship between transaction volume and price before systemic risk occurs. Secondly, the standardized data are weekly. Month as the unit to create a new statistical significance of K line data K1, and K line data K1 fitting, before the original data price peaked K-line data K2; third, In this paper, we further create 12 features according to K line data K1 and K2, and use SVR and Liner Regression methods to fit the feature data. To obtain a linear fitting function that can predict the rate of price growth in the coming year. Real stock data verify that these three aspects of the work are effective and help investors understand the changes in the stock market. The work of this paper also provides a feasible method to predict and prevent the systematic risk of stock market.
【學(xué)位授予單位】：天津工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F832.51;TP181

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本文編號：1558745