Stocks are one of the best-known forms investment and still used today. In stock investment, it is necessary to know movement risk loss that may be obtained from so investors can consider possibility profit. One way calculating use Expected Shortfall (ES). Because in form a time series, model formed predict which then for ES calculations using series analysis. The purpose study was determine ex...

It has been observed that most of the agricultural time series data in general and price particular are non-linear, non-stationary, non-normal heteroscedastic nature. Therefore, application usual linear nonlinear parametric models like Autoregressive integrated moving average (ARIMA), Generalized autoregressive conditional (GARCH) their component fail to capture variability present series. is a...

The globalization emerging in the post-World War II increases integration of microeconomic economic players into international trade and financial system. Hence, exchange rates gain importance for decision-making. dismissal Bretton Woods agreement 1973 caused governments to implement flexible rate regime. Therefore, reliable forecasting has developing countries having structural problems underd...

Cryptocurrencies are currently traded worldwide, with hundreds of different currencies in existence and even more on the way. This study implements some statistical machine learning approaches for cryptocurrency investments. First, we implement GJR-GARCH over GARCH model to estimate volatility ten popular cryptocurrencies based market capitalization: Bitcoin, Bitcoin Cash, SV, Chainlink, EOS, E...