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All Publications

ZORA Publication List

Publications

Journal Article
- 2025
  - Paolella, M. S., Polak, P., & Walker, P. S. (2025). Risk parity portfolio optimization under heavy‐tailed returns and dynamic correlations Journal of Time Series Analysis, 46, 353–377. https://doi.org/10.1111/jtsa.12792
- 2023
  - Broda, S. A., & Paolella, M. (2023). ARCHModels.jl: Estimating ARCH Models in Julia Journal of Statistical Software, 107, 1–25. https://doi.org/10.18637/jss.v107.i05
  - Hediger, S., Näf, J., Paolella, M. S., & Polak, P. (2023). Heterogeneous Tail Generalized Common Factor Modeling Digital Finance, 5, 389–420. https://doi.org/10.1007/s42521-023-00083-z
  - Paolella, M. S., & Polak, P. (2023). Density and Risk Prediction with Non-Gaussian COMFORT Models Annals of Financial Economics, 18, 2250033. https://doi.org/10.1142/s2010495222500336
- 2021
  - Paolella, M. S., Polak, P., & Walker, P. S. (2021). A non-elliptical orthogonal GARCH model for portfolio selection under transaction costs Journal of Banking and Finance, 125, 106046. https://doi.org/10.1016/j.jbankfin.2021.106046
- 2019
  - Paolella, M. S., Polak, P., & Walker, P. S. (2019). Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns Journal of Econometrics, 213, 493–515. https://doi.org/10.1016/j.jeconom.2019.07.002
  - Näf, J., Paolella, M. S., & Polak, P. (2019). Heterogeneous tail generalized COMFORT modeling via Cholesky decomposition Journal of Multivariate Analysis, 172, 84–106. https://doi.org/10.1016/j.jmva.2019.02.004
- 2018
  - Broda, S. A., Krause, J., & Paolella, M. S. (2018). Approximating expected shortfall for heavy-tailed distributions Econometrics and Statistics, 8, 184–203. https://doi.org/10.1016/j.ecosta.2017.07.003
- 2017
  - Butler, R. W., & Paolella, M. S. (2017). Autoregressive Lag-Order Selection Using Conditional Saddlepoint Approximations Econometrics, 5, 43–43. https://doi.org/10.3390/econometrics5030043
  - Paolella, M. S. (2017). The Univariate Collapsing Method for Portfolio Optimization Econometrics, 5, 18–18. https://doi.org/10.3390/econometrics5020018
  - Gambacciani, M., & Paolella, M. S. (2017). Robust normal mixtures for financial portfolio allocation Econometrics and Statistics, 3, 91–111. https://doi.org/10.1016/j.ecosta.2017.02.003
  - Paolella, M. S. (2017). Asymmetric stable Paretian distribution testing Econometrics and Statistics, 1, 19–39. https://doi.org/10.1016/j.ecosta.2016.05.002
- 2016
  - Paolella, M. S. (2016). Stable-GARCH Models for Financial Returns: Fast Estimation and Tests for Stability Econometrics, 4, 25–25. https://doi.org/10.3390/econometrics4020025
- 2015
  - Paolella, M. S. (2015). Multivariate asset return prediction with mixture models The European Journal of Finance, 21, 1214–1252. https://doi.org/10.1080/1351847X.2012.760167
  - Paolella, M. S., & Polak, P. (2015). COMFORT: A common market factor non-Gaussian returns model Journal of Econometrics, 187, 593–605. https://doi.org/10.1016/j.jeconom.2015.02.041
  - Paolella, M. S., & Polak, P. (2015). ALRIGHT: Asymmetric LaRge-Scale (I)GARCH with Hetero-Tails International Review of Economics and Finance, 40, 282–297. https://doi.org/10.1016/j.iref.2015.02.025
  - Paolella, M. S. (2015). New graphical methods and test statistics for testing composite normality Econometrics, 3, 532–560. https://doi.org/10.3390/econometrics3030532
- 2014
  - Krause, J., & Paolella, M. S. (2014). A fast, accurate method for value-at-risk and expected shortfall Econometrics, 2, 98–122. https://doi.org/10.3390/econometrics2020098
  - Paolella, M. (2014). Fast methods for large-scale non-elliptical portfolio optimization Annals of Financial Economics, 9, 1–32. https://doi.org/10.1142/S2010495214400016
- 2013
  - Haas, M., Krause, J., Paolella, M. S., & Steude, S. C. (2013). Time-varying mixture GARCH models and asymmetric volatility North American Journal of Economics and Finance, 26, 602–623. https://doi.org/10.1016/j.najef.2013.02.024
  - Broda, S. A., Haas, M., Krause, J., Paolella, M. S., & Steude, S. C. (2013). Stable mixture GARCH models Journal of Econometrics, 172, 292–306. https://doi.org/10.1016/j.jeconom.2012.08.012
- 2009
  - Broda, S., & Paolella, M. S. (2009). Evaluating the density of ratios of noncentral quadratic forms in normal variables Computational Statistics & Data Analysis, 53, 1264–1270. https://doi.org/10.1016/j.csda.2008.10.035
  - Haas, M., Mittnik, S., & Paolella, M. S. (2009). Asymmetric multivariate normal mixture GARCH Computational Statistics & Data Analysis, 53, 2129–2154. https://doi.org/10.1016/j.csda.2007.12.018
  - Broda, S., & Paolella, M. S. (2009). CHICAGO: A fast and accurate method for portfolio risk calculation Journal of Financial Econometrics, 7, 412–436. https://doi.org/10.1093/jjfinec/nbp011
  - Broda, S., Carstensen, K., & Paolella, M. S. (2009). Assessing and improving the performance of nearly efficient unit root tests in small samples Econometric Reviews, 28, 468–494. https://doi.org/10.1080/07474930802467282
- 2008
  - Paolella, M. S., & Taschini, L. (2008). An econometric analysis of emission allowance prices Journal of Banking and Finance, 32, 2022–2032. https://doi.org/10.1016/j.jbankfin.2007.09.024
  - Paolella, M. S., & Steude, S. C. (2008). Risk Prediction: A DWARF-like Approach Journal of Risk Model Validation, 2, 25–43. http://search.ebscohost.com/login.aspx?direct=true&db=ecn&AN=0996751&loginpage=Login.asp&site=ehost-live
  - Butler, R. W., & Paolella, M. S. (2008). Uniform saddlepoint approximations for ratios of quadratic forms Bernoulli, 14, 140–154. https://doi.org/10.3150/07-BEJ6169
- 2007
  - Broda, S., Paolella, M. S., & Carstensen, K. (2007). Bias-adjusted estimation in the ARX(1) model Computational Statistics & Data Analysis, 51, 3355–3367. https://doi.org/10.1016/j.csda.2006.07.009
  - Broda, S., & Paolella, M. S. (2007). Saddlepoint approximations for the doubly noncentral t distribution Computational Statistics & Data Analysis, 51, 2907–2918. https://doi.org/10.1016/j.csda.2006.11.024
- 2006
  - Haas, M., Mittnik, S., & Paolella, M. S. (2006). Modeling and predicting market risk with Laplace-Gaussian mixture distributions Applied Financial Economics, 16, 1145–1162. https://doi.org/10.1080/09603100500438817
  - Paolella, M., Hartz, C., & Mittnik, S. (2006). Accurate value-at-risk forecasting based on the Normal-GARCH model Computational Statistics & Data Analysis, 51, 2295–2312. https://doi.org/10.1016/j.csda.2006.09.017
  - Kuester, K., Mittnik, S., & Paolella, M. S. (2006). Value-at-risk prediction: A comparison of alternative strategies Journal of Financial Econometrics, 4, 53–89. https://doi.org/10.1093/jjfinec/nbj002
- 2004
  - Paolella, M., Haas, M., & Mittnik, S. (2004). A new approach to markov-switching GARCH models Journal of Financial Econometrics, 2, 493–530. https://doi.org/10.1093/jjfinec/nbh020
  - Paolella, M. (2004). Modeling higher frequency macroeconomic data: an application to German monthly money demand Applied Economics Quarterly, 50. http://aeq.diw.de/aeq/index.jsp?n=0010&p=5&c=summary/AEQ_04_2_1
  - Paolella, M., Haas, M., & Mittnik, S. (2004). Mixed normal conditional heteroskedasticity Journal of Financial Econometrics, 2, 211–250. https://doi.org/10.1093/jjfinec/nbh009
- 2003
  - Paolella, M. S. (2003). Computing moments of ratios of quadratic forms in normal variables Computational Statistics & Data Analysis, 42, 313–331. https://doi.org/10.1016/S0167-9473(02)00213-X
- 2002
  - Butler, R. W., & Paolella, M. S. (2002). Calculating the density and distribution function for the singly and doubly noncentral F Statistics and Computing, 12, 9–16. https://doi.org/10.1023/A:1013160019893
  - Butler, R. W., & Paolella, M. S. (2002). Saddlepoint approximation and bootstrap inference for the Satterthwaite class of ratios Journal of the American Statistical Association, 97, 836–846. https://doi.org/10.1198/16214502388618636
  - Mittnik, S., Paolella, M. S., & Rachev, S. T. (2002). Stationarity of stable power-GARCH processes Journal of Econometrics, 106, 97–107. https://doi.org/10.1016/S0304-4076(01)00089-6
- 2001
  - Paolella, M. S. (2001). Testing the stable Paretian assumption Mathematical and Computer Modelling, 34, 1095–1112. https://doi.org/10.1016/S0895-7177(01)00118-2
- 2000
  - Mittnik, S., Paolella, M. S., & Rachev, S. T. (2000). Diagnosing and treating the fat tails in financial returns data Journal of Empirical Finance, 7, 389–416. https://doi.org/10.1016/S0927-5398(00)00019-0
  - Mittnik, S., & Paolella, M. S. (2000). Conditional density and value-at-risk prediciton of Asian currency exchange rates Journal of Forecasting, 19, 313–333. https://doi.org/10.1002/1099-131X(200007)19:4<313::AID-FOR776>3.0.CO;2-E
- 1999
  - Mittnik, S., & Paolella, M. S. (1999). A simple estimator for the characteristic exponent of the stable paretian distribution Mathematical and Computer Modelling, 29, 161–176. https://doi.org/10.1016/S0895-7177(99)00099-0
- 1998
  - Mittnik, S., Paolella, M. S., & Rachev, S. T. (1998). Unconditional and conditional distributional models for the Nikkei index Asia - Pacific Financial Markets, 5, 99–128. https://doi.org/10.1023/A:1010016831481
  - Paolella, M., & Butler, R. W. (1998). Approximate distributions for the various serial correlograms Bernoulli, 4, 497–518. https://doi.org/10.2307/3318663
  - Mittnik, S., Paolella, M. S., & Rachev, S. T. (1998). A tail estimator for the index of the stable paretian distribution Communications in Statistics : Theory and Methods, 27, 1239–1262. https://doi.org/10.1080/03610929808832156
Book Section
- 2018
  - Paolella, M. S., & Polak, P. (2018). COBra: Copula-Based Portfolio Optimization In V. Kreinovich, S. Sriboonchitta, & N. Chakpitak (Eds.), Predictive Econometrics and Big Data (No. 753; pp. 36–77). Springer International Publishing. https://doi.org/10.1007/978-3-319-70942-0_3
- 2012
  - Paolella, M. S., & Haas, M. (2012). Mixture and regime-switching GARCH models In L. Bauwens, C. M. Hafner, & S. Laurent (Eds.), Handbook of volatility models and their applications (No. 3; pp. 71–102). Wiley. https://doi.org/10.1002/9781118272039.ch3
  - Paolella, M. S., & Broda, S. (2012). Saddlepoint approximations: A review and some new applications In J. E. Gentle, W. K. Härdle, & Y. Mori (Eds.), Handbook of Computational Statistics : Concepts and Methods (2nd editio; pp. 953–984). Springer (Bücher). https://doi.org/10.1007/978-3-642-21551-3_32

Pagination