Search Results - "Baruník, Jozef"

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  1. 1

    Volatility Spillovers Across Petroleum Markets by Barunk, Jozef, Kočenda, Evzen, Váchaa, Lukáš

    Published in The Energy journal (Cambridge, Mass.) (01-07-2015)
    “…By using our newly defined measure, we detect and quantify asymmetries in the volatility spillovers of petroleum commodities: crude oil, gasoline, and heating…”
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    Quantile coherency: A general measure for dependence between cyclical economic variables by Baruník, Jozef, Kley, Tobias

    Published in The econometrics journal (01-05-2019)
    “…Summary In this paper, we introduce quantile coherency to measure general dependence structures emerging in the joint distribution in the frequency domain and…”
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  5. 5

    Asymmetric volatility connectedness on the forex market by Baruník, Jozef, Kočenda, Evžen, Vácha, Lukáš

    Published in Journal of international money and finance (01-10-2017)
    “…•The forex market exhibits asymmetric volatility connectedness.•We use high-frequency data of the most actively traded currencies over 2007–2015.•We document…”
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  6. 6

    Asymmetric connectedness on the U.S. stock market: Bad and good volatility spillovers by Baruník, Jozef, Kočenda, Evžen, Vácha, Lukáš

    “…In this paper, we examine how to quantify asymmetries in volatility spillovers that emerge due to bad and good volatility. Using data covering most liquid U.S…”
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  7. 7

    Cyclical properties of supply-side and demand-side shocks in oil-based commodity markets by Křehlík, Tomáš, Baruník, Jozef

    Published in Energy economics (01-06-2017)
    “…Oil markets profoundly influence world economies through determination of prices of energy and transports. Using novel methodology devised in frequency domain,…”
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  8. 8

    Forecasting the term structure of crude oil futures prices with neural networks by Baruník, Jozef, Malinská, Barbora

    Published in Applied energy (15-02-2016)
    “…•We analyse term structure of crude oil markets.•New model for forecasting based on neural networks is proposed.•We show that even basic architecture of neural…”
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  9. 9

    Total, Asymmetric and Frequency Connectedness between Oil and Forex Markets by Barunik, Jozef, Kocenda, Evzen

    Published in The Energy journal (Cambridge, Mass.) (15-03-2019)
    “…We analyze total, asymmetric and frequency connectedness between oil and forex markets using high-frequency, intra-day data over the period 2007–2017. By…”
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  10. 10

    Risks of heterogeneously persistent higher moments by Baruník, Jozef, Kurka, Josef

    Published in International review of financial analysis (01-11-2024)
    “…Using intraday data for the cross-section of individual stocks, we show that both transitory and persistent fluctuations in realized market and average…”
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  11. 11

    Are benefits from oil–stocks diversification gone? New evidence from a dynamic copula and high frequency data by Avdulaj, Krenar, Barunik, Jozef

    Published in Energy economics (01-09-2015)
    “…Oil is perceived as a good diversification tool for stock markets. To fully understand this potential, we propose a new empirical methodology that combines…”
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  12. 12

    Dynamic industry uncertainty networks and the business cycle by Baruník, Jozef, Bevilacqua, Mattia, Faff, Robert

    Published in Journal of economic dynamics & control (01-02-2024)
    “…This paper identifies smoothly varying industry uncertainty networks from option prices that contain valuable information about business cycles, especially in…”
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  13. 13

    Good volatility, bad volatility: What drives the asymmetric connectedness of Australian electricity markets? by Apergis, Nicholas, Baruník, Jozef, Lau, Marco Chi Keung

    Published in Energy economics (01-08-2017)
    “…Efficient delivery of network services and the electricity infrastructure to meet the long-term consumer's interests are the main objectives and the strategies…”
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  14. 14

    Predicting the volatility of major energy commodity prices: The dynamic persistence model by Baruník, Jozef, Vácha, Lukáš

    Published in Energy economics (01-12-2024)
    “…Time variation and persistence are crucial properties of volatility that are often studied separately in energy volatility forecasting models. Here, we propose…”
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  15. 15

    Quantile Spectral Beta: A Tale of Tail Risks, Investment Horizons, and Asset Prices by Baruník, Jozef, Nevrla, Matěj

    Published in Journal of financial econometrics (15-11-2023)
    “…Abstract This article investigates how two important sources of risk—market tail risk (TR) and extreme market volatility risk—are priced into the cross-section…”
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  16. 16

    Forecasting dynamic return distributions based on ordered binary choice by Anatolyev, Stanislav, Baruník, Jozef

    Published in International journal of forecasting (01-07-2019)
    “…We present a simple approach to the forecasting of conditional probability distributions of asset returns. We work with a parsimonious specification of ordered…”
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  17. 17

    Combining high frequency data with non-linear models for forecasting energy market volatility by Barunik, Jozef, Krehlika, Tomas

    Published in Expert systems with applications (15-08-2016)
    “…•High-frequency data are coupled with nonlinear models to predict volatility.•Comprehensive evaluation of multiple-step ahead volatility forecasts is…”
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    Measurement of common risks in tails: A panel quantile regression model for financial returns by Baruník, Jozef, Čech, František

    “…We investigate how to measure common risks in the tails of return distributions using the recently proposed panel quantile regression model for financial…”
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  19. 19

    Gold, oil, and stocks: Dynamic correlations by Baruník, Jozef, Kocenda, Evzen, Vácha, Luká

    “…We employ a wavelet approach and conduct a time-frequency analysis of dynamic correlations between pairs of key traded assets (gold, oil, and stocks) covering…”
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  20. 20

    Taming Data‐Driven Probability Distributions by Baruník, Jozef, Hanus, Luboš

    Published in Journal of forecasting (19-11-2024)
    “…ABSTRACT We propose a deep learning approach to probabilistic forecasting of macroeconomic and financial time series. By allowing complex time series patterns…”
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