top of page

Research Interest

ESG and Sustainable Finance

Vine Copula  Modeling and Risk Analysis

Network Analysis and Graphical Models

Statistics and Financial Econometrics

Working Papers

A generalized precision matrix for t-Student distributions in portfolio optimization.

With Taufer, Emanuele & Paterlini, Sandra (2022)

Status: Currently under review

Available at SSRN 4063255​

The Markowitz model is still the cornerstone of modern portfolio theory. In particular, when focusing on the minimum-variance portfolio, the covariance matrix or better its inverse, the so-called precision matrix, is the only input required. Technically, the precision matrix can be used to understand the conditional dependence structure of random vectors. However, the inverse of the covariance matrix might not necessarily result in a reliable and accurate picture of reality when non-Gaussian settings are analyzed. In this paper, exploiting the local dependence function, different definitions of the generalized precision matrix, which holds for a general class of distributions, are provided. In particular, we focus on the multivariate t-Student distribution and point out that the interaction in random vectors does not depend only on the inverse of the covariance matrix, but also on additional elements. We test the performance using a minimum-variance portfolio approach by considering S\&P 100 and Fama and French industry data. We show that portfolios using the generalized precision matrix often generate statistically significantly lower out-of-sample variances than state-of-art methods.

Vine Copula based portfolio level conditional risk measure forecasting

With Sommer, Emanuel and Czado, Claudia (2022)

Status: Currently under review

Available on ArXiv 2208.09156

Accurate estimation of different risk measures for financial portfolios is of utmost importance equally for financial institutions as well as regulators, however, many existing models fail to incorporate any high dimensional dependence structures adequately. To overcome this problem and capture complex cross-dependence structures, we use the flexible class of vine copulas and introduce a conditional estimation approach focusing on a stress factor. Furthermore, we compute conditional portfolio level risk measure estimates by simulating portfolio level forecasts conditionally on a stress factor. We then introduce a quantile-based approach to observe the behavior of the risk measures given a particular state of the conditioning asset or assets. In particular, this can generate valuable insights in stress testing situations. In a case study on Spanish stocks, we show, using different stress factors, that the portfolio is quite robust against strong market downtrends in the American market. At the same time, we find no evidence of this behavior with respect to the European market. The novel algorithms presented are combined in the R package portvine , which is publically available on CRAN.

Which ESG dimension matters most to private investors?

An experimental study on financial decisions

With Benuzzi, Matteo and Klaser, Klaudijo

Status: Working Paper

Available at SSRN 4262763

The UN list of Sustainable Development Goals (SDGs) has made it widely recognized that sustainability is not exclusively an environmental concept but it rather has multiple dimensions. In the same vein, different non financial information and actions, specifically environmental, social, and governance (ESG), have been provided and undertaken by companies. However, since their introduction, many scholars have questioned whether these three ESG dimensions are equally important under different perspectives. For example, especially since the process of climate change is rapidly evolving, recently, the environmental dimension (E-Pillar) has received more attention than other sustainability factors. In this paper, we focus on the investment decision-making process of retail investors when ESG information is provided. Moreover, in addition to considering the E, S, and G dimensions, we introduce an F-dimension, which encompasses actions that aim to directly impact future generations. In order to explore the mentioned relationship, we follow an experimental approach that allows us to disentangle how these four dimensions (E, S, G, and F) interact with different risk-return configurations and, therefore, with investors' preferences. Preliminary analyses indicate that investors trade-off financial returns with pro-social objectives, i.e. they invest in sustainable companies in which they would not have invested if they had considered only the personal financial consequences. Furthermore, our results show that the subjects attribute different weightings to the ESGF dimensions: when adopting a purely sustainable perspective, the E-Pillar ranks first, while when adopting a financial perspective, the S-Pillar is the most relevant. Finally, the F-pillar does not seem to play a significant role in the decision, because it is perceived as a factor complementary to the other three.


Published Papers

Bax, K., Sahin, Ö., Czado, C. & Paterlini, S. (2023). ESG, Risk, and (Tail) Dependence. International Review of Financial Analysis. 87(May 2023).

DOI: 10.1016/j.irfa.2023.102513

Bax, K. (2023). Do diverse and inclusive workplaces benefit investors?  An Empirical Analysis on Europe and the United States. Finance Research Letters 53(March 2023).

DOI: 10.1016/

Bax, K., Bonaccolto, G., & Paterlini, S. (2022). Do Lower ESG Rated Companies Have Higher Systemic Impact? Empirical Evidence from Europe and the United States. Corporate Social Responsibility and Environmental Management.

DOI: 10.1002/csr.2427

Czado, C., Bax, K., Sahin, Ö., Nagler, T., Min, A., & Paterlini, S. (2022). Vine copula based dependence modeling in sustainable finance. Journal of Finance and Data Science (JFDS) 8(November 2022).

DOI: 10.1016/j.jfds.2022.11.003

Sahin, Ö, Bax, K.,  Paterlini, S., & Czado, C. (2022). The pitfalls of (non-definitive) Environmental, Social, and Governance scoring methodology. Global Finance Journal.

DOI: 10.1016/j.gfj.2022.100780

Sahin, Ö, Bax, K.,  Paterlini, S., & Czado, C. (2022). ESGM: ESG scores and the Missing pillar - Why does missing information matter?. Corporate Social Responsibility and Environmental Management 29(5), p. 1782-1798.

DOI: 10.1002/csr.2326

Bax, K. & Paterlini, S. (2022). Environmental Social Governance Information and Disclosure from a Company Perspective: a Structured Literature Review. International Journal of Business Performance Management, 23(3), p. 304–322. DOI: 10.1504/IJBPM.2022.123824

bottom of page