We start this chapter with a deeper look at how crash prediction models such as the bond–stock earnings yield differential (BSEYD) work. Next, we explore the BSEYD's ability to predict crashes through a case study of the market meltdowns in China, Iceland, and the US in the 2007–...
We start this chapter with a deeper look at how crash prediction models such as the bond–stock earnings yield differential (BSEYD) work. Next, we explore the BSEYD's ability to predict crashes through a case study of the market meltdowns in China, Iceland, and the US in the 2007–200...
Forecasting stock market crisis events using deep and statistical machine learning techniques This work contributes to this ongoing debate on the nature and the characteristics of propagation channels of crash events in international stock markets. ... SP Chatzis,V Siakoulis,A Petropoulos,... - 《E...
This statistics shows the results of a survey on which European Union countries think that major stock markets around the world will crash in 2018.
of the examples of such complex systems is financial market and crashes on the market are treated as extreme events. The crash on financial market is defined as noticeable decline of indexes or even separate stocks quotations in short period of time. The noticeable decline is interpreted as the...
will happen in the future, often but not always based on experience or knowledge. While there is much overlap between prediction and forecast, a prediction may be a statement that some outcome is expected, while a forecast is more specific, and may cover a range of ...
摘要: By combining (i) the economic theory of rational expectation bubbles, (ii) behavioral finance on imitation and herding of investors and traders and (iii)the mat关键词: Stock market crash financial bubble Chinese markets rational expectation bubble log-periodic power law ...
are studied such as the price earnings ratio. FA tries to find the true value of a stock compared to the it’s current market price. The full future value of a company can be assessed and then discounted back to its value in present time. Fund managers may rely on fundamental analysis....
hungchun-lin/Stock-price-prediction-using-GAN Star232 In this project, we will compare two algorithms for stock prediction. First, we will utilize the Long Short Term Memory(LSTM) network to do the Stock Market Prediction. LSTM is a powerful method that is capable of learning order dependence...
Recently, the spread of COVID-19 led to a decrease in stock market indices, as most industries experienced a recession. Bahrain was the most affected market in the GCC, with losses shortly increasing by 0.29, totaling 0.35 over the following two months. A traffic burst-sensitive model (TBSM...