Events

Mathieu Rosenbaum, École Polytechnique: Rough Heston model: Pricing, hedging and microstructural foundations

It has been recently shown that rough volatility models, where the volatility is driven by a fractional Brownian motion with small Hurst parameter, provide very relevant dynamics in order to reproduce the behavior of both historical and implied volatilities. However, due to the non-Markovian nature of the fractional Brownian motion, they raise new issues when it comes to the risk management of derivatives. Using an original link between nearly unstable Hawkes processes and rough volatility models, we explain in this talk how to price and hedge options in the rough version of the Heston...

Alexander N D'amour, UC Berkeley: Advances in Basketball Analytics Using Player Tracking Data

In the 2013-2014 season, the National Basketball League, in conjunction with STATS LLC, implemented a league-wide program to collect player-tracking data for all NBA games. The data feed now provides 25-FPS records of all players' XY coordinates on the court, as well as XYZ coordinates for the ball. This data source has opened up new lines in inquiry into the quantitative analysis of basketball that have previously been hamstrung by a reliance on spatially naive box-score and play-by-play statistics. In this talk I will discuss several projects undertaken by myself and the...

David Bailey, UC Davis: Backtest overfitting, stock fund design and forecast performance

Backtest overfitting means the usage of backtests (historical market data) to construct an investment strategy, fund or portfolio, when the number of variations explored exceeds limits of statistical reliability. We show that backtest overfitting is inevitable when computer programs are employed to explore millions or even billions of parameter variations (as is typical) to select an optimal variant. We illustrate this by showing that while it is a simple matter to design a stock fund, based only on a weighted collection of S&P500 stocks, that achieves any desired performance profile,...

Nick Gunther, UC Berkeley: The Futures Financing Rate

We estimate the financing rate implicit in equity index futures (“FIR”) by comparing the prices of the near and next contracts and adjusting for expected dividends and convexity. We provide a direct estimate ...

Jeremy Evnine, Evnine & Associates: Social Finance and the Postmodern Portfolio: Theory and Practice

We formulate the portfolio construction problem as a mean/variance problem which includes a linear term representing an investor’s preference for expected “social return”, in addition to her expected “financial return” of the classical theory. By making various assumptions, we are able to exploit the heterogeneous expectations version of the CAPM to derive an equilibrium model which is an extension of the standard Capital Asset Pricing Model. Among other things, the model implies that, in equilibrium, assets with higher expected social return that is valued by investors will have, ceteris...

Ben Gum, AXA Rosenberg: Machine Learning and Alternative Data in Fundamental-based Quantitative Equity

We begin with a survey of machine learning techniques and applications outside of finance. Then we discuss our use of Machine Learning techniques at Rosenberg. Finally, we explore some alternative data sources.

Start date: 2017-09-26 11:00:00 End date: 2017-09-26 12:30:00 Venue: 639 Evans Hall at UC Berkeley Address: 639 Evans Hall, Berkeley, CA, 94720

Michael Ohlrogge, Stanford: Bank Capital and Risk Taking: A Loan Level Analysis

I examine whether whether low capital levels incentivize banks to systematically originate and hold riskier loans. I construct a novel data set consisting of 1.8 million small business and home mortgage loans, matched to the specific banks that originated them and the capital levels of those banks at the time of origination, and verified to be held on bank portfolios, rather than sold. A one point increase in capital ratios (e.g. from 12% to 13%) is associated with a 4% decrease in the default risk of mortgage loans held on portfolio (from a net foreclosure rate of 2.5% to 2.4%). Bank...

Bob Anderson, UC Berkeley: Sparse Low Rank Dictionary Learning

Sparse Dictionary Learning (SDL) can be used to extract narrow factors driving stock returns from a stock returns matrix, provided the returns are generated by sparse factors alone. We describe progress on a variant called Sparse Low Rank Dictionary Learning (SLRDL), designed to simultaneously extract broad and narrow factors for the returns matrix, when the returns are generated by both types of factors.

Start date: 2017-09-05 11:00:00 End date: 2017-09-05 12:30:00 Venue: 639 Evans Hall at UC Berkeley Address: 639 Evans Hall, Berkeley, CA, 94720

Lionel Martellini (EDHEC-Risk Institute), Mass Customisation versus Mass Production in Retirement Investment Management: Addressing a “Tough Engineering Problem”

The seminar will be held at 1011 Evans Hall, UC Berkeley. Abstract: Triggered by the introduction of ever stricter accounting and prudential pension fund regulations, a massive shift from defined-benefit to defined-contribution pension schemes is taking place across the world. As a result of this massive shift of retirement risks on individuals, the investment management industry is facing an increasing responsibility in terms of the need to provide households with suitable retirement solutions. Existing retirement products such as target date funds, annuities and variable annuities suffer...

Alexander Shkolnik, CRMR Postdoctoral Scholar, to give contributed session at the International Conference on Monte Carlo Methods and Applications

Alexander Shkolnik, CRMR Postdoctoral Scholar, to give contributed session at the MCM 2017 International Conference on Monte Carlo Methods and Applications Session title: Compactness Approaches for Importance Sampling From the conference website: "Nine invited plenary speakers will give one-hour talks, with discussion. All other talks will last 30 minutes including questions and discussion. They will be split into sessions of 3 or 4 talks. Some special...