While, other predictors have an inverse relation with stock crash probability. The results are consistent while using FGLS technique however, GMM estimates exhibit corporate tax avoidance as a significant predictor. Overall, the outcomes support H2 and H3, while H1 is rejected ...
stock market crash over the next 6 months.Lochstoer and Muir (2022)find that investors' subjective stock market risk perceptions seems to be slowly moving, with initial underreaction to volatility shocks and subsequent delayed overreaction. They show that these dynamics in forecast errors provide a ...
The random walk model of stock prices states that stock market returns are independent of the returns in other periods; for example, whether the stock market does well or poorly in the coming month does not depend on whether it has done well or poorly during the past month, the past 12 ...
Causality is a key part of many fields and facets of life, from finding the relationship between diet and disease to discovering the reason for a particular stock market crash. Despite centuries of work in philosophy and decades of computational research, automated inference and explanation remains ...
such as the protection of property rights and the enforcement of contracts that are critical determinants of sustainable economic growth and investment opportunities. his methods allowed him to successfully predict the crash of the chinese, russian, brazilian stock markets along with the price of oil....
from risk neutral and physical probabili- ties, estimated via S&P 500 options and stock returns, respectively.3 While he finds risk aversion to be positive and decreasing in wealth prior to the 1987 stock market crash, risk aversion is partially negative and increasing in the post-crash era. ...
[31] to describe the stock market at the Paris stock exchange. He gets the credit for having been the first to write down an equation that was later named after Paul Langevin (Sect. 3.4). For a recent and detailed monograph on Brownian motion and the mathematics of normal diffusion, ...
comcrashtothehousingbubbleandtheGreatRecession.Foralmostthatentiretime,he'ssuccessfullyusedchartsandtechnicalanalysisasthebasisforhisinvestingdecisions.Now,withHigh-ProbabilityTradeSetups,heshowsyouhowtodothesame.Dividedintothreecomprehensiveparts,thisreliableresourceopenswithaninformativeoverviewofchartsetupsandoffers...
applied PIN to study the effect of informed trading in a broad range of areas in finance, including stock price informativeness, corporate governance and investment decisions, stock market volatility, and insider trading, just to name a few. However, the traditional PIN measure has some well known...
Overall, this paper applies a predicting model to estimate the probabilities of the future extreme returns, and figures out the significant influence and possible sources of the crash and jackpot probabilities in China. Portfolios based on extreme return probabilities can be profitable and steady ...