Fall 2018

Risk Seminar Fall 2018 pic

SEM217: Montserrat Guillen, University of Barcelona: Is motor insurance ratemaking going to change with telematics and semi-autonomous vehicles?

Tuesday, August 28th @ 11:00-12:30 PM

Many automobile insurance companies offer the possibility to monitor driving habits and distance driven by means of telematics devices installed in the vehicles. This provides a novel source of data that can be analysed to calculate personalised tariffs. 

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SEM217: Dangxing Chen, UC Berkeley: Predicting Portfolio Return Volatility at Median Horizons

Tuesday, October 2nd @ 11:00-12:30 PM

Commercially available factor models provide good predictions of short-horizon (e.g. one day or one week) portfolio volatility, based on estimated portfolio factor loadings and responsive estimates of factor volatility. 

Risk Seminar Fall 2018 pic

SEM217: Ben Gum, AXA Rosenberg: A Deep Learning Investigation of One-Month Momentum

Tuesday, September 25th @ 11:00-12:30 PM

The one-month return reversal in equity prices was first documented by Jedadeesh (1990), who found that there was a highly significant negative serial correlation in the monthly return series of stocks. This is in contrast to the positive serial correlation of the annual stock returns. 

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SEM217: Xiang Zhang, SWUFE: Proliferation of Anomalies and Zoo of Factors – What does the Hansen–Jagannathan Distance Tell Us?

Tuesday, October 23rd @ 11:00-12:30 PM

Recent research finds that prominent asset pricing models have mixed success in evaluating the cross-section of anomalies, which highlights proliferation of anomalies and zoo of factors. In this paper, I investigate that how is the relative pricing performance of these models to explain anomalies, when comparing their misspecification errors– the Hansen–Jagannathan (HJ) distance measure.

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SEM217: Chi Zhang, Kamyar Kaviani, Nikita Vemuri, and Simon Walter (UC Berkeley) - Putting the 'I' in IPO

Tuesday, November 13th @ 11:00-12:30 PM

As an alternative to traditional loans, young people could issue securities that pay dividends that depend on their future financial success in life. This type of a personal IPO is especially desirable for young people, who for example may need money for a college education, because it allows them to shift the risk of repayment to investors who bet on their future success, unlike in a traditional loan setting. 

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SEM217: Saad Mouti, UC Berkeley: On Optimal Options Book Execution Strategies with Market Impact

Tuesday, September 4th @ 11:00-12:30 PM

We consider the optimal execution of a book of options when market impact is a driver of the option price. We aim at minimizing the mean-variance risk criterion for a given market impact function. First, we develop a framework to justify the choice of our market impact function.

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SEM217: Michael Ohlrogge, Stanford University: Bankruptcy Claim Dischargeability and Public Externalities: Evidence from a Natural Experiment

Tuesday, November 27th @ 11:00-12:30 PM

In 2009, the Seventh Circuit ruled in U.S. v. Apex Oil that certain types of injunctions requiring firms to clean up previously released toxic chemicals were not dischargeable in bankruptcy. 

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SEM217: Tingyue Gan, UC Berkeley: Asymptotic Spectral Analysis of Markov Chains with Rare Transitions: A Graph-Algorithmic Approach

Tuesday, October 16th @ 11:00-12:30 PM

Parameter-dependent Markov chains with exponentially small transition rates arise in modeling complex systems in physics, chemistry, and biology. Such processes often manifest metastability, and the spectral properties of the generators largely govern their long-term dynamics.

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SEM217: Haosui (Kevin) Duanmu, UC Berkeley: Nonstandard Analysis and its Application to Markov Processes

Tuesday, September 18th @ 11:00-12:30 PM 

Nonstandard analysis, a powerful machinery derived from mathematical logic, has had many applications in probability theory as well as stochastic processes. Nonstandard analysis allows construction of a single object - a hyperfinite probability space - which satisfies all the first order logical properties of a finite probability space, but which can be simultaneously viewed as a measure-theoretical probability space via the Loeb construction. 

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SEM217: Tamas Batyi, UC Berkeley: Capacity constraints in earning, and asset prices before earnings announcements

Tuesday, September 11th @ 11:00-12:30 PM

This paper proposes an asset pricing model with endogenous allocation of constrained learning capacity, that provides an explanation for abnormal returns before the scheduled release of information about firms, such as quarterly earnings announcements. 

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SEM217: Jacob Steinhardt, Stanford: Robust Learning: Information Theory and Algorithms

Tuesday, October 9th @ 11:00-12:30 PM

This talk will provide an overview of recent results in high-dimensional robust estimation. The key question is the following: given a dataset, some fraction of which consists of arbitrary outliers, what can be learned about the non-outlying points?