Bio

Lerby Ergun is Senior Economist in the Financial Markets Department of the Bank of Canada. His primary research focusses on measuring risk in financial markets and recently started focusing on information flows in OTC markets. Before joining the Bank, Lerby worked as a Research Officer at the Systemic Risk Centre in the LSE. He received his PhD from Erasmus University Rotterdam, on the topic “Fat Tail in Financial Markets”.

Research Field(s): Asset Pricing Empirical Finance Financial Markets Information and Uncertainty Market Microstructure Risk Management

Staff working papers

Covariates Hiding in the Tails

Staff Working Paper 2021-45 Milian Bachem, Lerby Ergun, Casper G. de Vries
We characterize the bias in cross-sectional Hill estimates caused by common underlying factors and propose two simple-to-implement remedies. To test for the presence, direction and size of the bias, we use monthly US stock returns and annual US Census county population data.
Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods JEL Code(s): C, C0, C01, C1, C14, C5, C58

Strategic Uncertainty in Financial Markets: Evidence from a Consensus Pricing Service

Staff Working Paper 2020-55 Lerby Ergun, Andreas Uthemann
We look at the informational content of consensus pricing in opaque over-the-counter markets. We show that the availability of price data informs participants mainly about other participants’ valuations, rather than about the value of a financial security.
Content Type(s): Staff research, Staff working papers Topic(s): Financial institutions, Financial markets, Market structure and pricing JEL Code(s): C, C5, C58, D, D5, D53, D8, D83, G, G1, G12, G14

Tail Index Estimation: Quantile-Driven Threshold Selection

Staff Working Paper 2019-28 Jon Danielsson, Lerby Ergun, Casper G. de Vries, Laurens de Haan
The most extreme events, such as economic crises, are rare but often have a great impact. It is difficult to precisely determine the likelihood of such events because the sample is small.
Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Financial stability JEL Code(s): C, C0, C01, C1, C14, C5, C58

Challenges in Implementing Worst-Case Analysis

Staff Working Paper 2018-47 Jon Danielsson, Lerby Ergun, Casper G. de Vries
Worst-case analysis is used among financial regulators in the wake of the recent financial crisis to gauge the tail risk. We provide insight into worst-case analysis and provide guidance on how to estimate it. We derive the bias for the non-parametric heavy-tailed order statistics and contrast it with the semi-parametric extreme value theory (EVT) approach.
Content Type(s): Staff research, Staff working papers Topic(s): Financial stability JEL Code(s): C, C0, C01, C1, C14, C5, C58

See More

Journal publications

Ergun M.L. “Extreme downside risk in asset returns”. International Review of Financial Analysis, 2023;90:102840.

Ergun M.L., Stork P., Molchanov A. “Technical trading rules, loss avoidance, and the business cycle”. Pacific-Basin Finance Journal, 2023;82:102172.