Tuesday, November 14th @ 11:00-12:30 PM (639 Evans Hall)
Investor Behavior and Market Dynamics
John Arabadjis, State Street
The Market is a consensual hallucination that commands attention by wielding its Invisible Hand. In this talk, we will examine the ways that Adam Smith’s 250-year-old appendage makes itself felt – positioning, trading, and hurting herding – and their implications for the investment process.
Tuesday, September 19th @ 11:00-12:30 PM (639 Evans Hall)
Change-point detection for stochastic processes
Sveinn Olafsson, UC Santa Barbara
Since the work of Page in the 1950s, the problem of detecting an abrupt change in the distribution of stochastic processes has received a great deal of attention. There are two main formulations of such problems: A Bayesian approach where the change-point is assumed to be random, and a min-max approach under which the change-point is assumed to be...
Tuesday, October 3rd @ 11:00-12:30 PM (639 Evans Hall)
Nonparametric Risk Attribution for Factor Models of Portfolios
Kellie Ottoboni, UC Berkeley
Factor models are used to predict the future returns of a portfolio with known positions in many assets. These simulations yield a distribution of future returns and various measures of the risk of the portfolio. Clients would often like to identify sources of risk in their portfolios, but this is difficult when factors influence the...
Factor models are used to predict the future returns of a portfolio with known positions in many assets. These simulations yield a distribution of future returns and various measures of the risk of the portfolio. Clients would often like to identify sources of risk in their portfolios, but this is difficult when factors influence the portfolio in nonlinear ways, such as when returns are measured on a log scale and when the portfolio contains nonlinear instruments. We develop a two-step method to partition risk among factors in a portfolio which accounts for these nonlinearities: first,...
Since the work of Page in the 1950s, the problem of detecting an abrupt change in the distribution of stochastic processes has received a great deal of attention. There are two main formulations of such problems: A Bayesian approach where the change-point is assumed to be random, and a min-max approach under which the change-point is assumed to be fixed but unknown. In both cases, a deep connection has been established to variations of the widely used CUSUM procedure, but results for processes with jumps are still scarce, while the practical importance of such processes has escalated. In...
The Market is a consensual hallucination that commands attention by wielding its Invisible Hand. In this talk we will examine the ways that Adam Smith’s 250-year-old appendage makes itself felt – positioning, trading, and hurting herding – and their implications for the investment process.
Start date: 2017-11-14 11:00:00 End date: 2017-11-14 12:30:00 Venue: 639 Evans Hall at UC Berkeley Address: 639 Evans Hall, Berkeley, CA, 94720
We analyze the optimal allocation of trades to portfolios when the cost associated with an allocation is proportional to each portfolio's risk. Our investigation is motivated by changes in the over-the-counter derivatives markets, under which some contracts may be traded bilaterally or through central counterparties, splitting a set of trades into two or more portfolios. A derivatives dealer faces risk-based collateral and capital costs for each portfolio, and it seeks to minimize total margin requirements through its allocation of trades to portfolios. When margin requirements are...
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...
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,...
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...