M
Matteo Bonato
Researcher at University of Johannesburg
Publications - 34
Citations - 663
Matteo Bonato is an academic researcher from University of Johannesburg. The author has contributed to research in topics: Realized variance & Volatility (finance). The author has an hindex of 12, co-authored 32 publications receiving 424 citations. Previous affiliations of Matteo Bonato include UBS & Credit Suisse.
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El Niño, La Niña, and Forecastability of the Realized Variance of Agricultural Commodity Prices: Evidence from a Machine Learning Approach
TL;DR: In this paper , the authors examined the predictive value of El Niño and La Niña weather episodes for the subsequent realized variance of 16 agricultural commodity prices, using high-frequency data covering the period from 2009 to 2020.
Posted Content
Geopolitical Risks and Stock Market Dynamics of the BRICS
TL;DR: In this paper, the effect of geopolitical uncertainty on return and volatility dynamics in the BRICS stock markets via nonparametric causality-in-quantiles tests was examined, finding that news regarding geopolitical tensions do not affect return dynamics in these markets in a uniform way.
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The Effect of Investor Sentiment on Gold Market Dynamics
TL;DR: This paper explored the effect of investor sentiment on the intraday dynamics in the gold market and found that extreme fear (excitement) contributes to positive (negative) volatility jumps in gold returns.
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A Forecast Based Comparison of Restricted Realized Covariance Models
TL;DR: In this paper, the forecasting performance of the parametric restrictions discussed in Bonato et al. (2009) is compared to the full model specification, a result that would support the use of restrictions when the problem cross-sectional dimension is large.
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The predictive power of industrial electricity usage revisited : evidence from non‐parametric causality tests
TL;DR: The authors showed that the predictive power of industrial electricity usage can be explained by an industry effect that is transmitted via the volatility channel, and argued that the countercyclical premium associated with industrial electric usage growth is driven by the industry components that drive stock reversals, thus resulting in the negative relationship between today's industrial electricity consumption and stock returns in the future.