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Sascha Mergner

Personal Details

First Name:Sascha
Middle Name:
Last Name:Mergner
Suffix:
RePEc Short-ID:pme145
Terminal Degree:2008 Department für Volkswirtschaftslehre; Wirtschaftswissenschaftliche Fakultät; Georg-August-Universität Göttingen (from RePEc Genealogy)

Affiliation

(in no particular order)

Georg-August-Universität Göttinegn

(University of Goettingen) http://www.uni-goettingen.de
Germany, Goettingen

Quoniam Asset Management

http://www.quoniam.de
Germany, Frankfurt am Main

Research output

as
Jump to: Working papers Articles

Working papers

  1. Bulla, Jan & Mergner, Sascha & Bulla, Ingo & Sesboüé, André & Chesneau, Christophe, 2010. "Markov-switching Asset Allocation: Do Profitable Strategies Exist?," MPRA Paper 21154, University Library of Munich, Germany.
  2. Sascha Mergner & Jan Bulla, 2005. "Time-varying Beta Risk of Pan-European Industry Portfolios: A Comparison of Alternative Modeling Techniques," Finance 0510029, University Library of Munich, Germany.
  3. Sascha Mergner, 2005. "Zum Zusammenhang zwischen Bond-Credit Spreads und Ratings," Finance 0510024, University Library of Munich, Germany.
  4. Sascha Mergner, 2005. "Time-varying Beta Risk of Pan-European Sectors: A Comparison of Alternative Modeling Techniques," Finance 0509024, University Library of Munich, Germany.

Articles

  1. Sascha Mergner & Jan Bulla, 2008. "Time-varying beta risk of Pan-European industry portfolios: A comparison of alternative modeling techniques," The European Journal of Finance, Taylor & Francis Journals, vol. 14(8), pages 771-802.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Bulla, Jan & Mergner, Sascha & Bulla, Ingo & Sesboüé, André & Chesneau, Christophe, 2010. "Markov-switching Asset Allocation: Do Profitable Strategies Exist?," MPRA Paper 21154, University Library of Munich, Germany.

    Cited by:

    1. Bernardi, Mauro & Maruotti, Antonello & Petrella, Lea, 2017. "Multiple risk measures for multivariate dynamic heavy–tailed models," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 1-32.
    2. Peter Nystrup & Bo William Hansen & Henrik Madsen & Erik Lindström, 2016. "Detecting change points in VIX and S&P 500: A new approach to dynamic asset allocation," Journal of Asset Management, Palgrave Macmillan, vol. 17(5), pages 361-374, September.
    3. Alexander Berglund & Massimo Guidolin & Manuela Pedio, 2020. "Monetary policy after the crisis: A threat to hedge funds' alphas?," Journal of Asset Management, Palgrave Macmillan, vol. 21(3), pages 219-238, May.
    4. Peter Nystrup & Henrik Madsen & Erik Lindström, 2018. "Dynamic portfolio optimization across hidden market regimes," Quantitative Finance, Taylor & Francis Journals, vol. 18(1), pages 83-95, January.
    5. Giulia Dal Pra & Massimo Guidolin & Manuela Pedio & Fabiola Vasile, 2016. "Do Regimes in Excess Stock Return Predictability Create Economic Value? An Out-of-Sample Portfolio Analysis," BAFFI CAREFIN Working Papers 1637, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    6. Elizabeth Fons & Paula Dawson & Jeffrey Yau & Xiao-jun Zeng & John Keane, 2019. "A novel dynamic asset allocation system using Feature Saliency Hidden Markov models for smart beta investing," Papers 1902.10849, arXiv.org.
    7. Peter Nystrup & Stephen Boyd & Erik Lindström & Henrik Madsen, 2019. "Multi-period portfolio selection with drawdown control," Annals of Operations Research, Springer, vol. 282(1), pages 245-271, November.
    8. Ioannis Anagnostou & Drona Kandhai, 2019. "Risk Factor Evolution for Counterparty Credit Risk under a Hidden Markov Model," Risks, MDPI, vol. 7(2), pages 1-22, June.
    9. Wasim Ahmad & N. Bhanumurthy & Sanjay Sehgal, 2015. "Regime dependent dynamics and European stock markets: Is asset allocation really possible?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 42(1), pages 77-107, February.
    10. Christina Erlwein‐Sayer & Stefanie Grimm & Peter Ruckdeschel & Jörn Sass & Tilman Sayer, 2020. "Filter‐based portfolio strategies in an HMM setting with varying correlation parametrizations," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 36(3), pages 307-334, May.
    11. Yazid M Sharaiha & Kristoffer Kittilsen Johansson, 2014. "The state-dependent time variation in the value premium," Journal of Asset Management, Palgrave Macmillan, vol. 15(2), pages 150-161, April.

  2. Sascha Mergner & Jan Bulla, 2005. "Time-varying Beta Risk of Pan-European Industry Portfolios: A Comparison of Alternative Modeling Techniques," Finance 0510029, University Library of Munich, Germany.

    Cited by:

    1. He, Zhongzhi (Lawrence) & Kryzanowski, Lawrence, 2008. "Dynamic betas for Canadian sector portfolios," International Review of Financial Analysis, Elsevier, vol. 17(5), pages 1110-1122, December.
    2. Beatrice Foroni & Luca Merlo & Lea Petrella, 2023. "Expectile hidden Markov regression models for analyzing cryptocurrency returns," Papers 2301.09722, arXiv.org, revised Jan 2024.
    3. Entrop, O. & von la Hausse, L. & Wilkens, M., 2017. "Looking beyond banks’ average interest rate risk: Determinants of high exposures," The Quarterly Review of Economics and Finance, Elsevier, vol. 63(C), pages 204-218.
    4. Ciner, Cetin, 2015. "Time variation in systematic risk, returns and trading volume: Evidence from precious metals mining stocks," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 277-283.
    5. Zhou, Hao & Elliott, Robert J. & Kalev, Petko S., 2019. "Information or noise: What does algorithmic trading incorporate into the stock prices?," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 27-39.
    6. Carmine Trecroci, 2010. "Multifactors risk loadings and abnormal returns under uncertainty and learning," Working Papers 1011, University of Brescia, Department of Economics.
    7. Асатуров К.Г., 2015. "Динамические Модели Систематического Риска: Сравнение На Примере Индийского Фондового Рынка," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 51(4), pages 59-75, октябрь.
    8. Ortas, E. & Salvador, M. & Moneva, J.M., 2015. "Improved beta modeling and forecasting: An unobserved component approach with conditional heteroscedastic disturbances," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 27-51.
    9. Phoebe Koundouri & Nikolaos Kourogenis & Nikitas Pittis & Panagiotis Samartzis, 2016. "Factor Models of Stock Returns: GARCH Errors versus Time‐Varying Betas," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(5), pages 445-461, August.
    10. Li, Yong & Yu, Jun & Zeng, Tao, 2018. "Specification tests based on MCMC output," Journal of Econometrics, Elsevier, vol. 207(1), pages 237-260.
    11. Tomas Adam & Sona Benecka & Ivo Jansky, 2012. "Time-Varying Betas of Banking Sectors," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 62(6), pages 485-504, December.
    12. Serdar Neslihanoglu, 2021. "Linearity extensions of the market model: a case of the top 10 cryptocurrency prices during the pre-COVID-19 and COVID-19 periods," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.
    13. Mehmet Balcilar & Riza Demirer & Festus V. Bekun, 2021. "Flexible Time-Varying Betas in a Novel Mixture Innovation Factor Model with Latent Threshold," Mathematics, MDPI, vol. 9(8), pages 1-20, April.
    14. Li, Hong, 2013. "Integration versus segmentation in China's stock market: An analysis of time-varying beta risks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 25(C), pages 88-105.
    15. Seth Armitage & Janusz Brzeszczynski, 2011. "Heteroscedasticity and interval effects in estimating beta: UK evidenceÂ," CFI Discussion Papers 1103, Centre for Finance and Investment, Heriot Watt University.
    16. Serdar Neslihanoglu & Stelios Bekiros & John McColl & Duncan Lee, 2021. "Multivariate time-varying parameter modelling for stock markets," Empirical Economics, Springer, vol. 61(2), pages 947-972, August.
    17. Pop, Raluca Elena, 2012. "Herd behavior towards the market index: evidence from Romanian stock exchange," MPRA Paper 51595, University Library of Munich, Germany.
    18. Zhou, Jian, 2013. "Conditional market beta for REITs: A comparison of modeling techniques," Economic Modelling, Elsevier, vol. 30(C), pages 196-204.
    19. Jiang, Minqi & Liu, Jiapeng & Zhang, Lu, 2021. "An extended regularized Kalman filter based on Genetic Algorithm: Application to dynamic asset pricing models," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 28-44.
    20. Pieterse-Bloem, Mary & Qian, Zhaowen & Verschoor, Willem & Zwinkels, Remco, 2016. "Time-varying importance of country and industry factors in European corporate bonds," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 429-448.
    21. Bruce Burton & Satish Kumar & Nitesh Pandey, 2020. "Twenty-five years of The European Journal of Finance (EJF): a retrospective analysis," The European Journal of Finance, Taylor & Francis Journals, vol. 26(18), pages 1817-1841, December.
    22. Dimitrios Dadakas & Christos Karpetis & Athanasios Fassas & Erotokritos Varelas, 2016. "Sectoral Differences in the Choice of the Time Horizon during Estimation of the Unconditional Stock Beta," IJFS, MDPI, vol. 4(4), pages 1-13, December.
    23. Ortas, Eduardo & Moneva, José M., 2013. "The Clean Techs equity indexes at stake: Risk and return dynamics analysis," Energy, Elsevier, vol. 57(C), pages 259-269.
    24. M. V. Esteban & E. Ferreira & S. Orbe-Mandaluniz, 2015. "Nonparametric methods for estimating and testing for constant betas in asset pricing models," Applied Economics, Taylor & Francis Journals, vol. 47(25), pages 2577-2607, May.
    25. Insana, Alessandra, 2022. "Does systematic risk change when markets close? An analysis using stocks’ beta," Economic Modelling, Elsevier, vol. 109(C).
    26. Nieto Domenech, Belén & Orbe Mandaluniz, Susan & Zárraga Alonso, Ainhoa, 2011. "Time-Varying Beta Estimators in the Mexican Emerging Market," BILTOKI 1134-8984, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
    27. Ludwig Hausse & Martin Rohleder & Marco Wilkens, 2016. "Systemic interest rate and market risk at US banks," Journal of Business Economics, Springer, vol. 86(8), pages 933-961, November.
    28. Ewa Feder-Sempach & Piotr Szczepocki & Wiesław Dębski, 2023. "What if beta is not stable? Applying the Kalman filter to risk estimates of top US companies over the long time horizon," Bank i Kredyt, Narodowy Bank Polski, vol. 54(1), pages 25-44.

  3. Sascha Mergner, 2005. "Zum Zusammenhang zwischen Bond-Credit Spreads und Ratings," Finance 0510024, University Library of Munich, Germany.

    Cited by:

    1. Odermann, Alexander & Cremers, Heinz, 2013. "Komponenten und Determinanten des Credit Spreads: Empirische Untersuchung während Phasen von Marktstress," Frankfurt School - Working Paper Series 204, Frankfurt School of Finance and Management.

  4. Sascha Mergner, 2005. "Time-varying Beta Risk of Pan-European Sectors: A Comparison of Alternative Modeling Techniques," Finance 0509024, University Library of Munich, Germany.

    Cited by:

    1. He, Zhongzhi (Lawrence) & Kryzanowski, Lawrence, 2008. "Dynamic betas for Canadian sector portfolios," International Review of Financial Analysis, Elsevier, vol. 17(5), pages 1110-1122, December.

Articles

  1. Sascha Mergner & Jan Bulla, 2008. "Time-varying beta risk of Pan-European industry portfolios: A comparison of alternative modeling techniques," The European Journal of Finance, Taylor & Francis Journals, vol. 14(8), pages 771-802.
    See citations under working paper version above.Sorry, no citations of articles recorded.

More information

Research fields, statistics, top rankings, if available.

Statistics

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 2 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-EEC: European Economics (2) 2005-09-29 2005-10-29
  2. NEP-FIN: Finance (2) 2005-09-29 2005-10-29
  3. NEP-FMK: Financial Markets (2) 2005-09-29 2005-10-29
  4. NEP-FOR: Forecasting (2) 2005-09-29 2005-10-29
  5. NEP-CFN: Corporate Finance (1) 2005-10-29
  6. NEP-ETS: Econometric Time Series (1) 2005-10-29

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