29TH ANNUAL MFS CONFERENCE - PAPER AWARDS

The candidate papers were sent to the members of the prize committee which nominated the best paper. Each prize was awarded to the presenting author that was attending the conference.

After the extensive review of all of the eligible papers for Best Paper Award, I’m happy to announce the following winners:

BEST PAPER AWARD ($750)

COVID-19 PUZZLES: A RESOLUTION

Tony Berrada - Universite de Geneve, Switzerland
Jerome Detemple - Boston University, USA
Marcel Rindisbacher - Boston University, USA

ABSTRACT

This paper examines the economic impact of COVID-19 in an equilibrium framework. Our model, BDRA-SSL, combines two ingredients: (i) beliefs-dependent preferences foreconomic dynamics and (ii) stochastic SEIRD model with unpredictable birth and vaccine discovery events, and mitigating policy and behavioral responses, for disease propagation. We estimate the model based on economic time series and COVID-19 data. We show it explains the behaviors and levels of the S&P 500, the index volatility, and the number of new cases during the recent outbreak, while providing a good match for 25 unconditional moments of economic time series. Beliefs-dependence emerges as a critical ingredient for this comprehensive explanation of short term dynamics during the COVID-19 outbreak and of long run statistical properties. A comparison study establishes the performance of BDRA-SSL versus alternative specifications.

BEST DOCTORAL PAPER AWARD ($500)

BUBBLES TALK: NARRATIVE AUGMENTED BUBBLE PREDICTION

Yuting Chen - University College Dublin, Ireland
Don Bredin - University College Dublin, Ireland
Valerio Poti - University College Dublin, Ireland

ABSTRACT

Financial bubble theories emphasize the importance of behavioral mechanisms centered around investor beliefs, which can be potentially gleaned from prevailing narratives, that reflect investors’ psychological states and link them to economic events. By summarizing market narratives into meaningful and economically relevant features, guided by bubble theories, we offer a novel approach to bubble prediction and inference on extant theories about bubble determination. We then test whether the variation of narratives and bubble measures are related, both on a contemporaneous and on a predictive basis, as bubble theories imply. Our findings reveal that most of our narrative features exhibit significant explanatory power, with the “correct” (i.e., consistent with theory) sign and robust additional predictive power for bubble measures, and that the narrative-augmented models outperform non-augmented benchmarks in out-of-sample tests. These results offer new insights into the understanding of bubbles and lay the foundation for using narratives to develop early warning systems (EWS) for bubble for- mation and deflation, and for investigating the causal relationship between narratives and economic events.

We would like to extend our congratulations and best wishes to everyone.

The conference Program Chairs