We summarize the general combination approach by Billio et al. [2010]. In the combination model the weights follow logistic auto-regressive processes, change over time and their dynamics are possible driven by the past forecasting performances of the predictive densities. For illustrative...

We summarize the general combination approach by Billio et al. [2010]. In the combination model the weights follow logistic autoregressive processes, change over time and their dynamics are possible driven by the past forecasting performances of the predictive densities. For illustrative...

In this research paper ARCH-type models and option implied volatilities (IV) are applied in order to estimate the Value-at-Risk (VaR) of a stock index futures portfolio for several time horizons. The relevance of the asymmetries in the estimated volatility estimation is considered. The empirical...

In assessing drivers of commodity prices and volatility at this stage of the current super-cycle in commodities (year 12 of a projected 25), it is vital to understand that production cost is a fundamental. Moreover, marginal production costs are among the most powerful drivers of commodity...

This working paper presents the general theory of the higher order "skew lognormal cascade distribution" as a mathematical extension of the previously proposed skew lognormal cascade distribution. In particular, the second order distribution is studied in details, which incorporates the fat...

Overdependence on oil revenue has exposed the economy to shocks from oil price variations. In this paper, we investigated the relationship between oil price on the stock prices of oil and gas firms quoted in the Nigerian Stock Exchange market. In doing so, the ARDL and NARDL approach is applied...

This paper investigates how investor sentiment affects stock market returns and evaluates the predictability power of sentiment indices on U.S. and EU stock market returns. As regards the American example, evidence shows that investor sentiment indices have an economic and statistical...

Existing methods of partitioning the market index into bull and bear regimes do not identify market corrections or bear market rallies. In contrast, our probabilistic model of the return distribution allows for rich and heterogeneous intra-regime dynamics. We focus on the characteristics and...

Financial time series often exhibit properties that depart from the usual assumptions of serial independence and normality. These include volatility clustering, heavy-tailedness and serial dependence. A voluminous literature on different approaches for modeling these empirical regularities has...

We extract contextualized representations of news text to predict returns using the state-of-the-art large language models in natural language processing. Unlike the traditional bag-of-words approach, the contextualized representation captures both the syntax and semantics of text, thus...