4th Brown Bag workshop- Accounting, Finance and Actuarial Science Seminar series

Event details

Paper 1: Does Land Affect Stock Return Volatility

Presenter: Yun Liu

This paper introduces land as a novel source of stock return volatility and develops a production-based asset pricing model augmented with land. In the model, land enters household utility, and serves as firm production input and collateral in the credit constraint. The estimation and simulation generate data-size stock return volatility, which is mainly attributed to the changes in land price according to the variance decomposition exercise. Besides, the introduction of land also helps reconcile the macro-finance tradeoff and replicate equity premium. This research indicates that the dual role of land could be a non-negligible modeling choice in a general equilibrium framework.

Presenter’s short biography:

Dr. Yun Liu is a Lecturer in Accounting and Finance since August 2023. She holds a BSc in Physics from Fudan University, as well as an MSc and a PhD in Economics from the Hong Kong University of Science and Technology. Her research interest lies in the development of theoretical and quantitative models within the fields of macro-finance, supply chain finance, environmental economics, and corporate finance. Her works related to these topics have been published in Production and Operations Management (ABS 4), Journal of Comparative Economics (ABS 3), and Small Business Economics (ABS 3), among others.

Paper 2: Expect the Unexpected: Modelling Mortality in the Presence of Catastrophic Events

Presenter: Şule Şahin

Population events such as natural disasters, pandemics, extreme weather, and wars can cause abrupt changes that have an immediate impact on mortality rates. The recent COVID-19 pandemic has demonstrated that these events should not be treated as non-repetitive exogenous interventions. As such, mortality models that aim to capture pandemic-type shocks on the mortality curve are crucial. This presentation is composed of two research papers: the first is an ongoing study, and the second is published in Risks (Sahin and Ozen, 2024).
 
Part I: We introduce an extension to the Lee-Carter mortality model by making use of what we describe as “conical” distributions: Normal, Laplace, and Hyperbolic, both straight and skew. We explore whether a COVID-type pandemic was forecastable based on past mortality data. 

Part II: Mortality models incorporating jump effects are particularly important to capture adverse mortality shocks. The mortality models with jumps, which we consider in this study, differ in terms of the duration of the jumps—transitory or permanent—the frequency of the jumps, and the size of the jumps. To illustrate the effect of the jumps, we also consider benchmark mortality models without jump effects, such as the Lee-Carter model, the Renshaw and Haberman model, and the Cairns-Blake-Dowd model. We discuss the performance of all the models by analysing their ability to capture the mortality deterioration caused by COVID-19. We use data from different countries to simulate the mortality rates for the pandemic and post-pandemic years and examine their accuracy in forecasting the mortality jumps due to the pandemic. Moreover, we also examine the jump-free and jump models in terms of their impact on insurance pricing, specifically term annuity and life insurance present values calibrated for both pre- and post-COVID data.

Presenter’s short biography:

Dr. Şule Şahin is a Senior Lecturer in Actuarial Science in the School for Business and Society at the University of York. She is a member of the AFIR-ERM Lessons Learned from the COVID-19 Pandemic Crisis Management Working Party of the International Actuarial Association and the Ogden Working Party, which produces the actuarial tables for personal injury and wrongful death compensation calculations.