Stock market volatility is the systematic risk faced by investors who hold a market portfolio (e.g., a stock market index fund). Schwert (1989b) has undertaken an extensive study of stock market volatility, using historical data back to the 19th century. Some of his major findings are illustrated in Figure 1, which plots quarterly stock market volatility for the post-World War II period.1 The f...

Maximum Relative Drawdown measures the largest percentage drop of the price process on a given time interval. Recently, Maximum Relative Drawdown has become more popular as an alternative measure of risk. In contrast to the Value at Risk measure, it captures the path property of the price process. In this article, we propose a partial differential equation approach to determine the theoretical ...

Crude oil exerts a strong influence on national economy. Changes of international crude oil price have an important effect on Chinese economy because of China’s high dependence on the import of the crude oil. Thus, Chinese stock market can be shocked by the fluctuation of oil price. Reversely, changes in crude oil imports of China have some effect on demands and price of the crude oil. This art...

Stock market volatility is the systematic risk faced by investors who hold a market portfolio (e.g., a stock market index fund). Schwert (1989b) has undertaken an extensive study of stock market volatility, using historical data back to the 19th century. Some of his major findings are illustrated in Figure 1, which plots quarterly stock market volatility for the post-World War II period.1 The f...

• The 2020 U.S. stock market crash stems from its own systemic instability. COVID-19 merely served as the spark of crash. Bubble for stocks with different cap levels have distinct temporal profiles. Stock sectors middle and small suffer greater losses. We employed log-periodic power law singularity (LPPLS) methodology to systematically investigate in equities total capitalizations through four ...

In this study business operations and liquidity and credit risk on price fluctuations on the stock exchange since 2010 to 2013 has been Tehran distance. The sample consisted of 76 company The systematic elimination method is selected. The company had a total of 304 years, in this study, the hypothesis of linear regression and correlation to analyse the data and test hypotheses Eviews software i...

W investigate the association between information contained in the American Customer Satisfaction Index (ACSI) metric and future stock market performance. Some past research has provided results suggesting that the financial markets misprice customer satisfaction; i.e., firms advantaged in customer satisfaction are posited to earn positive future-period abnormal stock returns. We reexamine this...

The use of price–earnings ratios and dividend-price ratios as forecasting variables for the stock market is examined using aggregate annual US data 1871 to 2000 and aggregate quarterly data for twelve countries since 1970. Various simple efficient-markets models of financial markets imply that these ratios should be useful in forecasting future dividend growth, future earnings growth, or future...

It is a common wisdom that individual stocks’ returns are difficult to predict, though in many situations it is important to have such estimates at our disposal. In particular, they are needed to determine the cost of capital. Market equilibrium models posit that expected returns are proportional to the sensitivities to systematic risk factors. Fama and French (1993) three-factor model explains...

Stock market plays a vital role in a country’s economy and it is an important consideration in all the fields due to its potential financial gain. Using Data mining future stock price, whether stock price go high or low can be predicted. There are two types of stock market predictions, fundamental analysis based on unstructured data and technical analysis based on structured data. In this paper...