In this study, we compare the out-of-sample forecasting performance of several modern Value-at- Risk (VaR) estimators derived from extreme value theory (EVT). Specifically, in a multi-asset study covering 30 years of stock, bond, commodity and currency market data, we analyse the accuracy of the...

We propose a new method (implemented in an R-program) to simulate long-range daily stock-price data. The program reproduces various stylized facts much better than various parametric models from the extended GARCH-family. In particular, the empirically observed changes in unconditional variance...

The empirical literature of stock market predictability mainly suffers from model uncertainty and parameter instability. To meet this challenge, we propose a novel approach that combines the documented merits of diffusion indices, regime-switching models, and forecast combination to predict the...

The empirical literature of stock market predictability mainly suffers from model uncertainty and parameter instability. To meet this challenge, we propose a novel approach that combines the documented merits of diffusion indices, regime-switching models, and forecast combination to predict the...

Natural gas is likely to become increasingly important in the future. Understanding the stochastic underpinnings of natural gas prices will be critical, both to policy analysts and to market participants. To this end, we investigate the potential presence of jumps in natural gas spot prices in...

The popular scholarly exercise of evaluating exchange rate forecasting models relative to a random walk was stimulated by the well-cited Meese and Rogoff (1983) paper. Practitioners who construct quantitative models for trading exchange rates approach forecasting from a different perspective....

This paper examines price overreactions in the case of the following cryptocurrencies: BitCoin, LiteCoin, Ripple and Dash. A number of parametric (t-test, ANOVA, regression analysis with dummy variables) and non-parametric (Mann–Whitney U test) tests confirm the presence of price patterns...

This paper explores price (momentum and contrarian) effects on the days characterised by abnormal returns and the following ones in two commodity markets. Specifically, using daily Gold and Oil price data over the period 01.01.2009-31.03.2020 the following hypotheses are tested: H1) there are...

This paper investigates the impact of abnormal returns on stock prices by using daily and hourly data for some developed (US, UK, Japan) and emerging (China, India) markets over the period 01.01.2010-01.01.2020. Average analysis, t-tests, CAR and trading simulation methods are used to test the...

We propose a novel dynamic mixture vector autoregressive (VAR) model in which time-varying mixture weights are driven by the predictive likelihood score. Intuitively, the state weight of the k-th component VAR model in the subsequent period is increased if the current observation is more likely...