I am an assistant professor of finance at Reykjavik University. My research interests focus on empirical asset pricing and, particularly, topics on the intersection between asset pricing and corporate finance for stocks and corporate bonds. 

I also co-author Tidy Finance together with Christoph Scheuch, Stefan Voigt, and Christoph Frey:

Reykjavik University

Menntavegur 1
Reykjavik, 102

E-Mail: patrickw@ru.is

Socials: LinkedIn, Twitter

Research: SSRN, Google Scholar

Code: Github

Phone: +354 820 6247

My curriculum vitae.


Paper: Updated version of our paper on Methodological Uncertainty in Portfolio Sorts out now.

Paper: The crowd-sourced paper on Reproducibility in Management Science (contributed as a member of the Management Science Reproducibility Collaboration) is now forthcoming in Management Science.

Book: Christoph Scheuch, Stefan Voigt, Christoph Frey, and I signed a contract with Chapman & Hall/CRC to publish Tidy Finance with Python in June 2024.

Next Events

I will join the SFS Cavalcade in Atlanta from May 19 - 22, 2024.

The print version of Tidy Finance with Python (joint work with Christoph Frey, Christoph Scheuch, and Stefan Voigt) will be released in June 2024.


Working Papers

Greenness Demand For US Corporate Bonds

joint work with Rainer Jankowitsch (VGSF & WU), Alexander Pasler (WU), and Josef Zechner (VGSF& WU).  Draft coming soon.

Abstract: We characterize the demand for green securities based on institutional holdings of US corporate bonds. The generally positive demand for greenness shows significant time variation, with the highest average levels around the Paris Agreement in 2016 and a sharp decline during the Trump administration. The demand and its variation following exogenous events significantly affect prices and investors' wealth. Additionally, we uncover greenness-related real effects at the firm level. In particular, we find an association between heightened greenness demand and firms' motivation to enhance their environmental performance, as well as more frequent bond issuances with higher notional amounts by greener firms.


This graph shows the evolution of institutional investors' greenness demand over time. The line shows the average greenness demand for each quarter from 2012 until the end of 2022. A 95% confidence band is drawn around the average. Greenness demand fluctatues from roughly 0 to 0.15.

joint work with Dominik Walter (VGSF) and Rüdiger Weber (WU).  December 2023.

Abstract: Systematically studying methodological variation in portfolio sorts reveals four key insights. (1) The average monthly non-standard error is 0.19% and exceeds standard errors. Despite this considerable variation, estimated premia are robust regarding their sign, statistical significance, and monotonicity. This alleviates concerns about replicability. (2) Decisions such as excluding firms with negative earnings or the information lag have an impact comparable to size-related choices. (3) Methodological choices induce not just orthogonal noise but add predictably non-zero returns of unclear origin. (4) To address methodological uncertainty, we propose a two-step protocol adaptable to economic motivations, for which we provide an open-source tool. 

Internet Appendix, open-source code on Github with full replication and all-in-one script. Formerly circulated as "Non-standard errors in portfolio sorts".

Presentations: Australasian 2022, AWG 2022,  DGF 2023, EFA 2023*, EFMA 2023*, PFMC 2022*, University of Vienna


joint work with Lukas Handler (WU) and Rainer Jankowitsch (VGSF & WU).  February 2023.

Abstract: In this paper, we analyze the key drivers of bond covenant prices by employing a novel measurement approach based on secondary market data. We find that covenant prices vary significantly over time and are associated with market-wide credit risk, volatility, and macroeconomic variables. Apart from the time-series dynamics, there is also significant variation across bond and firm characteristics. In particular, covenant prices increase with the riskiness of bonds and are higher for firms that have more growth options, more tangible assets, and are smaller. Furthermore, we document a positive correlation between the prices of covenants and their subsequent inclusion rates.

Presentations: Australasian 2021, AWG 2021, EFMA 2022, DGF 2022, Reykjavik University, SFA 2022*, VGSF Conference 2019

Refereed Journal Publications

Published in The Journal of Financial Economics.

Joint work with Maria Chaderina (UOregon) and Josef Zechner (VGSF & WU).  2022.

Abstract: We show that firms with longer debt maturities earn risk premia not explained by unconditional factors. Embedding dynamic capital structure choices in an asset-pricing framework where the market price of risk evolves with the business cycle, we find that firms with long-term debt exhibit more countercyclical leverage. The induced covariance between betas and the market price of risk generates a maturity premium similar in size to our empirical estimate of 0.21% per month. We also provide direct evidence for the model mechanism and confirm that the maturity premium is consistent with observed leverage dynamics of long- and short-maturity firms. 

Internet Appendix

Published online in The Journal of Finance. Joint work as part of the FINCAP team. 2024.

Abstract: In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants. 

Published in Management Science. Contributed as a member of the Management Science Reproducibility Collaboration. 2024.

Abstract: With the help of more than 700 reviewers, we assess the reproducibility of nearly 500 articles published in the journal Management Science before and after the introduction of a new Data and Code Disclosure policy in 2019. When considering only articles for which data accessibility and hardware and software requirements were not an obstacle for reviewers, the results of more than 95% of articles under the new disclosure policy could be fully or largely computationally reproduced. However, for 29% of articles, at least part of the data set was not accessible to the reviewer. Considering all articles in our sample reduces the share of reproduced articles to 68%. These figures represent a significant increase compared with the period before the introduction of the disclosure policy, where only 12% of articles voluntarily provided replication materials, of which 55% could be (largely) reproduced. Substantial heterogeneity in reproducibility rates across different fields is mainly driven by differences in data set accessibility. Other reasons for unsuccessful reproduction attempts include missing code, unresolvable code errors, weak or missing documentation, and software and hardware requirements and code complexity. Our findings highlight the importance of journal code and data disclosure policies and suggest potential avenues for enhancing their effectiveness.

(* presentation by coauthor; ° scheduled)