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97 229 (0,204s)

Result

Modeling and forecasting exchange rate volatility in time-frequency domain

This paper proposes an enhanced approach to modeling and forecasting volatility using high frequency data. Using a forecasting model based on Realized GARCH of different timescales on volatility forecasts....

AH - Ekonomie

  • 2016
  • Jx
  • Link
Result

Combining high frequency data with non-linear models for forecasting energy market volatility

is to comprehensively evaluate multiple-step-ahead volatility forecasts of energy markets using the complex patterns hidden in linear models commonly used to forecast realized volatility, and natural gas ...

AH - Ekonomie

  • 2016
  • Jx
  • Link
Result

Modeling realized volatility of the EUR/USD exchange rate: Does implied volatility really matter?

of the models with implied volatility up to 17.3% for one-day-ahead, 42.1% for one-week-ahead, and 22.8% for one-month-ahead forecasts. Additionally, the superior set not only for individual forecast<...

Finance

  • 2021
  • Jimp
  • Link
Result

Direct versus iterated multi-step forecasting of glycaemia in type 1 diabetics using autoregressive models

The paper compares two approaches to multi-step ahead glycaemia forecasting. While the direct approach uses a different model for each number of steps ahead, the iterative approach applies one one-step ahead

Endocrinology and metabolism (including diabetes, hormones)

  • 2020
  • D
  • Link
Result

Forecasting day-ahead expected shortfall on the EUR/USD exchange rate: The (I)relevance of implied volatility

option contracts. The day-ahead forecasts are obtained from several classes volatility for managing risky assets, while evidence for expected shortfall predictions is almost nonexistent. Given its forward-looking nature, i...

Finance

  • 2024
  • Jimp
  • Link
Result

Value at Risk forecasting with the ARMA-GARCH family of models in times of increased volatility

The paper evaluates several hundred one-day-ahead VaR forecasting models in the time period between the years 2004 and 2009 on data from six world stock indices and their forecasting accuracy is evaluated on the ou...

AH - Ekonomie

  • 2011
  • O
Result

Improving stock market volatility forecasts with complete subset linear and quantile HAR models

Volatility forecasting plays an integral role in risk management, investments autoregressive (HAR) volatility model: the complete subset linear/quantile regression HAR models, HAR-CSLR and HAR-CSQR. Predictions of 1-to 22-d...

Finance

  • 2021
  • Jimp
  • Link
Result

The Effects of US Volatility on Smaller Markets

In this paper, alternative models are proposed which take account of volatility in the US market. One obvious modification is to use GARCH forecasts of volatility from the USA in explaining volatility in smaller ma...

AH - Ekonomie

  • 2003
  • D
Result

Exploiting dependence: Day-ahead volatility forecasting for crude oil and natural gas exchange-traded funds

This paper investigates volatility forecasting for crude oil and natural gas does not improve volatility forecasts, whether we consider a multivariate model, or various univariate models that include this informati...

Finance

  • 2018
  • Jimp
  • Link
Result

Trading and non-trading period realized market volatility: Does it matter for forecasting the volatility of US stocks?

volatilities to model and forecast the stock volatility over the next one to 22 days. We, matters significantly for improving the model fit and volatility forecasting accuracy of up to five trading days, ...

Finance

  • 2020
  • Jimp
  • Link
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