Abstract Behavioural finance has challenged many claims of efficient market hypothesis (EMH). Unfortunately many of these challenges are in the form of anecdotal evidence and lack quantification. This article uses market data together with some simple statistics to show that in practice certain...

This note explores machine learning based modelling approach over classical quantitative methods with a focus on modelling realized volatility of asset price over time. Initially, a few modelling assumptions of classical quantitative finance are examined using recent market data. Daily stock...

We study volatility spillovers among commodity and equity markets by employing a recently developed approach based on realized measures and forecast error variance decomposition invariant to the variable ordering from vector-autoregressions. This enables us to measure total, directional and net...

We detect and quantify asymmetries in the volatility spillovers of petroleum commodities: crude oil, gasoline, and heating oil. The increase in volatility spillovers after 2001 correlates with the progressive financialization of the commodities. Further, increasing spillovers from volatility...

Given the emerging consensus from previous studies that crude oil and refined product (as well as crack spread) prices are cointegrated, this study examines the link between the crude oil spot and crack spread derivatives markets. Specifically, the usefulness of the two crack spread derivatives...

I provide conditions under which the trimmed FDQML estimator, advanced by McCloskey (2010) in the context of fully parametric short-memory models, can be used to estimate the long-memory stochastic volatility model parameters in the presence of additive low-frequency contamination in log-squared...

Asymmetries in volatility spillovers are highly relevant to risk valuation and portfolio diversification strategies in financial markets. Yet, the large literature studying information transmission mechanisms ignores the fact that bad and good volatility may spill over at different magnitudes....

This paper suggests how to quantify asymmetries in volatility spillovers that emerge due to bad and good volatility. Using data covering most liquid U.S. stocks in seven sectors, we provide ample evidence of the asymmetric connectedness of stocks at the disaggregate level. Moreover, the...

In this work we focus on the application of wavelet-based methods in volatility modeling. We introduce a new, wavelet-based estimator (wavelet Whittle estimator) of a FIEGARCH model, ARCH-family model capturing long-memory and asymmetry in volatility, and study its properties. Based on an...

We introduce a methodology for dynamic modelling and forecasting of realized covariance matrices based on generalization of the heterogeneous autoregressive model (HAR) for realized volatility. Multivariate extensions of popular HAR framework leave substantial information unmodeled in residuals....