Accurate forecasting of changes in stock market indices can provide financial managers and
individual investors with strategically valuable information. However, predicting the closing …

This study measures the volatility of cryptocurrency by utilizing the symmetric (GARCH 1, 1)
and asymmetric (EGARCH, TGARCH, PGARCH) model of GARCH family using a daily …

In this paper, we explore the use of different machine learning models on predicting
currency exchange rates among BRICS economies (Brazil, Russia, India, China and South …

To improve the RMB exchange rate prediction and risk measurement, the RMB exchange
rate prediction model is constructed based on deep learning approaches. Value at risk …

In this paper, we employ the generalized autoregressive conditional heteroscedasticity-
mixed data sampling (GARCH-MIDAS) framework to forecast the daily volatility of 19 dollar …

Because the exchange rate is essentially a dynamic and nonlinear system, exchange rate
forecasting has been one of the most challenging topics in the financial field. This paper …

Accurately predicting the exchange rate prices helps investors to obtain maximum profit from
their exchange rate investments as well as to help firms conducting business with exchange …

The aim of this paper is to examine exchange rate volatility using GARCH models with a
new innovation distribution, the Normal Tempered Stable. We estimated daily exchange rate …

Volatility is the degree of variation in the stock price over time. The stock price is volatile due
to many factors, such as demand, supply, economic policy, and company earnings. Investing …

Using transaction-level tick-by-tick data of same-and next-day settlement of the Russian
Ruble versus the US Dollar exchange rate (RUB/USD) traded on the Moscow Exchange …