Since investors have diverse perspectives and limited information, their expectations can be subjective and prone to inaccuracies. Hence, price fluctuations are influenced by heterogeneous beliefs regarding future expectations, and both surveys and straightforward models can only partially...

While energy risk is increasingly recognized as a new systemic risk, there is limited comprehensive analysis of the risk propagation in regional context. In this paper, we examine oil and natural gas price changes in relation to equity market returns for 24 countries in the European Economic...

In this paper, we analyze the forecasting performance of several parametric extensions of the popular Dynamic Nelson-Siegel (DNS) model for the yield curve. Our focus is on the role of additional and time-varying decay parameters, conditional heteroscedasticity, and macroeconomic variables. We...

Prices and investors' behavior are heavily influenced by risk aversion. As it is unobservable, estimating risk aversion has been challenging for a long time. This paper proposes using a Machine Learning approach (a combination of Autoencoder and Long-Short Term Memory) to estimate the...

Volatility is a central tenet of financial markets, impacting a wide range of investors’ daily activities, including risk management, portfolio construction and option pricing. To improve their investment decisions, investors are spending considerable time and effort on finding new ways to...

We study the economic policy spillovers using framework developed by Diebold & Yilmaz (2009). Our main contribution is the analysis of the system of economic policy uncertainty spillovers at different persistence of frequency responses to shocks and to various magnitude of shocks. Mainly the...

Heavy tails and volatility clusters are both stylized facts of financial returns that destabilize markets. The former are extreme events by definition and the latter can accelerate adverse market developments. This work disentangles the two sources and examines which one does the greater damage...

In this paper, we analyzed a dataset of over 2000 crypto-assets to assess their credit risk by computing their probability of death using the daily range. Unlike conventional low-frequency volatility models that only utilize close-to-close prices, the daily range incorporates all the information...

This paper proposes an Exponential HEAVY (EHEAVY) model, which specifies the dynamics of returns and realized measures of volatility in an exponential form. The model ensures positivity of volatility and allows for asymmetric effects without restrictions on parameters, hence is more flexible. A...