Journal Article |
File Downloads |
Abstract Views |
Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
A new look at variance estimation based on low, high and closing prices taking into account the drift |
0 |
0 |
0 |
15 |
0 |
0 |
0 |
65 |
Attention to oil prices and its impact on the oil, gold and stock markets and their covariance |
0 |
0 |
0 |
1 |
1 |
1 |
4 |
7 |
Conformable Models for GARCH Processes |
0 |
0 |
0 |
8 |
0 |
0 |
0 |
40 |
Dynamic Hedging Portfolios - Application of Bivariate GARCH Models |
0 |
0 |
0 |
10 |
0 |
0 |
0 |
37 |
Exchange Rate Covariance Modelling by Means of Minimum and Maximum Prices (Modelowanie kowariancji kursow walutowych z zastosowaniem cen minimalnych i maksymalnych) |
0 |
0 |
0 |
2 |
0 |
0 |
1 |
20 |
Forecasting Volatility of Energy Commodities: Comparison of GARCH Models with Support Vector Regression |
0 |
0 |
1 |
11 |
0 |
0 |
3 |
56 |
Forecasting volatility during the outbreak of Russian invasion of Ukraine: application to commodities, stock indices, currencies, and cryptocurrencies |
0 |
1 |
2 |
5 |
0 |
1 |
8 |
28 |
Forecasting: theory and practice |
1 |
5 |
18 |
48 |
11 |
32 |
148 |
286 |
How to Increase Accuracy of Volatility Forecasts Based on GARCH Models |
0 |
0 |
0 |
18 |
0 |
0 |
0 |
60 |
Improving forecasts with the co-range dynamic conditional correlation model |
0 |
0 |
0 |
1 |
0 |
0 |
3 |
17 |
Improving volatility forecasts: Evidence from range-based models |
1 |
3 |
8 |
8 |
1 |
5 |
17 |
18 |
Low and high prices can improve covariance forecasts: The evidence based on currency rates |
0 |
0 |
0 |
4 |
0 |
0 |
1 |
18 |
Low and high prices can improve volatility forecasts during periods of turmoil |
0 |
1 |
1 |
9 |
0 |
1 |
2 |
50 |
Minimum Variance Portfolio Selection for Large Number of Stocks – Application of Time-Varying Covariance Matrices |
0 |
0 |
0 |
44 |
0 |
0 |
1 |
140 |
Modeling and forecasting dynamic conditional correlations with opening, high, low, and closing prices |
1 |
2 |
4 |
5 |
3 |
4 |
12 |
18 |
Modelling Financial Processes with Long Memory in Mean and Variance |
0 |
0 |
0 |
12 |
0 |
0 |
1 |
61 |
Monetary policy in steering the EONIA and POLONIA rates in the Eurosystem and Poland: a comparative analysis |
0 |
0 |
0 |
7 |
0 |
1 |
3 |
48 |
Nonlinear Granger causality between grains and livestock |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
Nonparametric Verification of GARCH-Class Models for Selected Polish Exchange Rates and Stock Indices |
0 |
0 |
0 |
27 |
0 |
0 |
1 |
130 |
Pricing of Weather Options for Berlin Quoted on the Chicago Mercantile Exchange |
0 |
0 |
0 |
8 |
0 |
0 |
0 |
48 |
Range-based DCC models for covariance and value-at-risk forecasting |
0 |
0 |
2 |
11 |
0 |
0 |
6 |
47 |
Robust estimation of the range-based GARCH model: Forecasting volatility, value at risk and expected shortfall of cryptocurrencies |
0 |
0 |
0 |
0 |
2 |
2 |
2 |
2 |
Total Journal Articles |
3 |
12 |
36 |
254 |
18 |
47 |
213 |
1,197 |