
Faculty
Chair of Empirical Economics
Am Stadtgraben 9
48143
Münster
Room: 317
Phone: +49 251 83-25045
Fax: +49 251 83-25042
segnon@uni-muenster.de
Am Stadtgraben 9
48143
Münster
Segnon, M., Gupta, R., & Wilfling, B. (2024). Forecasting stock market volatility with regime-switching GARCH-MIDAS: The role of geopolitical risks. International Journal of Forecasting, 40(1), 29–43.
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Schulte-Tillmann, B., Segnon, M., & Wiedemann, T. (2023). A comparison of high-frequency realized variance measures: Duration- vs. return-based approaches. In CQE Working Papers: Vol. 105/2023. Münster: Universität Münster.
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Segnon, M., Lau, C.-K., Wilfling, B., & Gupta, R. (2022). Are multifractal processes suited to forecasting electricity price volatility?
Evidence from Australian intraday data. Studies in Nonlinear Dynamics and Econometrics, 26(1), 73–98.
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Schulte-Tillmann, B., Segnon, M., & Wilfling, B. (2022). Financial-market volatility prediction with multiplicative Markov-switching MIDAS components. In Center, f. Q. E. (. (Ed.), CQE Working Papers: Vol. 99/2022. Münster: Universität Münster.
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Segnon, M. (2022). Strict stationarity of Poisson integer-valued ARCH processes of order infinity. In Center, f. Q. E. (. (Ed.), CQE Working Papers: Vol. 102/2022. University of Muenster.
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Segnon, M., & Bekiros, S. (2020). Forecasting Volatility in Bitcoin Market. Annals of Finance, 16, 435–462.
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Segnon, M., Gupta, R., Lesame, K., & Wohar, M. E. (2020). High-Frequency Volatility Forecasting of US Housing Markets. Journal of Real Estate Finance and Economics, 2020.
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Segnon, M., Antonakakis, N., Cunado, J., & Gupta, R. (2019). Revisiting the twin deficits hypothesis: A quantile cointegration analysis over the period 1791 — 2013. Journal of Applied Economics, 22, 116–130.
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Segnon, M., & Bekiros, S. (2019). Forecasting Volatility in Cryptocurrency Markets. University of Muenster: Center for Quantitative Economics (CQE), University of Muenster.
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Segnon, M., & Stapper, M. (2019). Long Memory Conditional Heteroscedasticity in Count Data. University of Muenster: Center for Quantitative Economics (CQE), University of Muenster.
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Segnon, M., & Lux, T. (2018). Multifractal models in finance: Their origin properties and applications. In Chen, S. H., Kaboudan, M., & Du, Y. R. (Eds.), The Oxford Handbook of Computational Economic and Finance (pp. xxx).
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Segnon, M., Bekiros, S., Gupta, R., & Wohar, M. E. (2018). Forecasting US GNP Growth: The Role of Uncertainty. Journal of Forecasting, 37, 541–559.
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Segnon, M., Bekiros, S., & Wilfling, B. (2018). Forecasting inflation uncertainty in the G7 countries. Econometrics, 6(2), 1–25.
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Segnon, M., & Trede, M. (2018). Forecasting market risk of portfolios: copula-Markov switching multifractal
approach. European Journal of Finance, 24(14), 1123–1143.
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Segnon, M., Bekiros, S., & Wilfling, B. (2018). Forecasting Inflation Uncertainty in the G7 Countries. In CQE-Working-Papers: Vol. 71/2018. University of Muenster: Center for Quantitative Economics (CQE), University of Muenster.
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Segnon, M., Lux, T., & Gupta, R. (2017). Modeling and Forecasting the Volatility of carbon Dioxide emission Allowance Prices: A Review and Comparison of Modern Volatility Models. Renewable and Sustainable Energy Reviews, 69, 692–704.
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Segnon, M., Keung, L. C., Wilfling, B., & Gupta, R. (2017). Are multifractal processes suited to forecasting electricity price volatility? Evidence from Australian intraday data. In CQE-Working-Papers: Vol. 61/2017. University of Muenster: Center for Quantitative Economics (CQE), University of Muenster.
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Balcilar, M., Gupta, R., & Segnon, M. (2016). The Role of Economic Policy Uncertainty in Predicting U.S. Recessions: A Mixed-Frequency Markov switching Vector Autoregressive Approach. Economics: The Open-Access, Open-Assessment E-Journal, 10, 1–20.
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Lux, T., Segnon, M., & Gupta, R. (2016). Forecasting Crude Oil Price Volatility and Value-at-Risk: Evidence from Historical and Recent Data. Energy Economics, 56, 117–133.
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Segnon, M., Hassani, H., Ghodsi, Z., & Gupta, R. (2015). Forecasting Home Sale in the Four Census Regions and the Aggregate US Economy Using Singular Spectrum Analysis. Computational Economics, 49, 83–97.
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Segnon, M., Hassani, H., Silva, E. S., & Gupta, R. (2015). Forecasting the Price of Gold. Applied Economics, 47(39), 4141–4152.
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