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Please Note: This seminar will be given in-person.

Recalcitrant Betas: Intraday Cross-Sectional Distributions of Systematic Risk

High-frequency financial data allows for efficient estimation of assets’ exposures to systematic risk, provided these exposures do not vary significantly at high frequencies.  We develop a test for deciding whether this is the case. The test is constructed for a panel of high-frequency asset returns, with the size of the cross-section and the sampling frequency increasing simultaneously. It is based on a comparison of the empirical characteristic functions of estimates of the assets' factor loadings at different parts of the trading day, formed from local blocks of asset returns and the corresponding factor realizations. The limiting behavior of the test statistic is governed by unobservable latent factors in the asset prices. Empirical implementation of the test to stocks in the S&P 500 index and the five Fama-French factors, as well as the momentum factor, reveals different intraday behavior of the factor loadings: assets' exposure to size, market and value risks vary systematically over the trading day while the three remaining factors do not exhibit statistically significant intraday variation. Moreover, we find diverse, and for some factors large, reactions in the assets' factor loadings to major economic or firm specific news releases. Finally, we document that time-varying correlations between the observable risk factors drive a wedge between the time-of-day pattern of market betas, estimated with and without control for the other observable risk factors.

Please Note: This seminar will be given in-person.

New Developments in Economic Scenario Generator Modelling

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Dynamic Capital Allocation in General Insurance

Please Note: This seminar will be given in-person.

Optimal (re)insurance risk sharing: the effect of multiple insurers or reinsurers

Please Note: This seminar will be given in person.

Annealed sequential Monte Carlo method with non-standard applications

Please Note: This seminar will be given in person.

Transfer Learning under High-dimensional Generalized Linear Models

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Insurer Capital and Organizational Forms in Market Equilibrium

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Network Functional Varying Coefficient Model

Please Note: This seminar will be given online.

Whatever Happened to Design-Based Inference?

What exactly should we think about appropriate analyses for designed experiments and why? If conditional inference trumps marginal inference, why should we care about randomisation? Isn’t everything just modelling? The Rothamsted School held that design matters. Taking an example of applying John Nelder’s general balance approach to a notorious problem, Lord’s paradox, I shall show that there may be some lessons for two fashionable topics: causal analysis and big data. I shall conclude that if we want not only to make good estimates but estimate how good our estimates are, design does matter.

Please Note: This seminar will be given in-person.

The Gradient Allocation Principle based on the Higher Moment Risk Measure