Events

Algorithms for Modern Massive Data Sets (MMDS 2016) Workshop

Early Registration deadline: Sunday, May 1, 2016. Download the full pdf program here (PDF file)(link is external). This four-day series of academic workshops addresses algorithmic and statistical challenges in modern large-scale data analysis. The goals of this series of workshops are to explore novel techniques for modeling and analyzing massive, high-dimensional, and non-linearly structured scientific and internet data sets and to bring together computer scientists, statisticians, mathematicians, and data...

Alex Shkolnik, UC Berkeley: Dynamic Importance Sampling for Compound Point Processes

We develop efficient importance sampling estimators of certain rare event probabilities involving compound point processes. Our approach is based on the state-dependent techniques developed in (Dupuis & Wang 2004) and subsequent work. The design of the estimators departs from past literature to accommodate the point process setting. Namely, the state-dependent change of measure is updated not at event arrivals but over a deterministic time grid. Several common criteria for the optimality of the estimators are analyzed. Numerical results illustrate the advantages of the proposed...

Roger Craine, UC Berkeley: Safe Capital Ratios for Bank Holding Companies

This paper gives three quantitative answers to Fischer’s question “at what level should capital ratios be set?” based on (1) the FED Stress Tests 2015 (2) VLab’s Systemic Risk measures and (3) our (Craine- Martin) estimates. This paper compares Safe Capital Ratios for 18 Bank Holding Companies. The Craine-Martin (CM) implied safe capital ratios are the highest averaging 22%, followed by VLab’s averaging 16%, and the FED Stress tests the lowest at 11%. We (CM) find higher implied safe capital ratios than VLab because our specification allows losses at one bank holding company to effect the...

Jeff Bohn, State Street Global Exchange: Simplicity and complexity in risk modeling: When is a risk model too simple? 

Most financial risk modelers (like most scientific modelers) attempt to develop models that are as simple as possible while still remaining useful. This said, models can become too simple thereby losing their signalling power. This circumstance can leave a risk manager without guidance as to what material risks a financial institution may be exposed. As financial markets, financial securities and regulations have proliferated, trading off simplicity and complexity becomes a particularly difficult challenge for financial risk modelers. This presentation introduces some thoughts and raises...

Nathan Tidd, Tidd Labs: Predicting Equity Returns with Valuation Factor Models 

This presentation summarizes the motivation, methodology, and initial test results of Equity Valuation Factor Models, an adaptation of popular multi-factor modeling techniques that seeks to explain the price and payoff of business ownership as a precursor to explaining equity returns. A departure from traditional returns-based models, the approach produces new information such as current factor prices that inform both risk & returns expectations, with a number of potential applications for real-world investment decisions.

Start date: 2016-02-09 11:00:00 End date: 2016-02-09 12:30:...

Yaniv Konchitchki, UC Berkeley (Haas): Accounting and the Macroeconomy: The Housing Market

This study introduces a new approach for financial statement analysis—the geographic analysis of firms’ financial statements. Start date: 2016-02-23 11:00:00 End date: 2016-02-23 12:30:00 Venue: 639 Evans Hall at UC Berkeley Address: 639 Evans Hall, Berkeley, CA, 94720

Roger Stein, MIT: A simple hedge for longevity risk and reimbursement risk using research-backed obligations 

Longevity risk is the risk that the promised recipient of lifetime cashflows ends up living much longer than originally anticipated, thus causing a shortfall in funding. A related risk, reimbursement risk is the risk that providers of health insurance face when new and expensive drugs are introduced and the insurer must cover their costs. Longevity and reimbursement risks are particularly acute in domains in which scientific breakthroughs can increase the speed of new drug development. An emerging asset class, research-backed obligations or RBOs (cf., Fernandez et al., 2012), provides a...

Ezra Nahum, Goldman Sachs: The Life of a Quant 1995-2015

In this lecture, I will review different practical risk management and modeling challenges that I encountered during the course of my career (inclusive of my Ph.D years). My review will highlight how the landscape has changed. For instance, while modeling exotic derivatives was the main activity for quants in the late 90s, capital optimization is the most important consideration today.

Start date: 2016-02-16 11:00:00 End date: 2016-02-16 12:30:00 Venue: 639 Evans Hall at UC Berkeley Address: 639 Evans Hall, Berkeley, CA, 94720

Johan Walden, UC Berkeley (Haas): Trading, Profits, and Volatility in a Dynamic Information Network Model

We introduce a dynamic noisy rational expectations model, in which information diffuses through a general network of agents. In equilibrium, agents’ trading behavior and profits are determined by their position in the network. Agents who are more closely connected have more similar periodby-period trades, and an agent’s profitability is determined by a centrality measure that is closely related to eigenvector centrality. In line with the Mixture of Distributions Hypothesis, the market’s network structure influences aggregate trading volume and price volatility. Volatility after an...

Keith Sollers, UC Davis: Recent Developments in Optimal Placement of Trades

Optimal placement of trades has received more attention recently, particularly in the high-frequency trading venue. We define a formulation of the optimal placement problem and present a closed-form solution to this problem in the discrete-time case. We then discuss the continuous-time case, where optimal solutions exist but no closed-form solution is known. After tuning the models using high-frequency market data, we present numerical solutions in continuous-time and exact solutions in discrete-time.

Start date: 2016-03-29 11:00:00 End date: 2016-03-29 12:30:00 Venue: 639 Evans Hall...