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 focussing 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”.
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.
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.
Financial markets can experience sudden and extreme downward movements. Investors are highly concerned about the performance of their assets in such scenarios. Some assets perform badly in a downturn in the market; others have milder reactions.
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.