Spring 2020

SEM217: Moritz Voss, UCSB: A two-player price impact game

Tuesday, January 28th @ 11:00-12:30 PM (1011 Evans Hall)

A two-player price impact game

Moritz Voss, UCSB

ABSTRACT: We study the competition of two strategic agents for liquidity in the benchmark portfolio tracking setup of Bank, Soner, Voss (2017), both facing common aggregated temporary and permanent price impact à la Almgren and Chriss (2001). The resulting stochastic linear quadratic differential game with terminal state constraints allows for an explicitly available open-loop...

SEM217: Amanda Glazer, UC Berkeley: Hot or Not? A Nonparametric Formulation of the Hot Hand in Baseball

Tuesday, February 11th @ 11:00-12:30 PM (1011 Evans Hall)

Hot or Not? A Nonparametric Formulation of the Hot Hand in Baseball

Amanda Glazer, UC Berkeley

ABSTRACT: "I never blame myself when I’m not hitting. I just blame the bat and if it keeps up, I change bats. After all, if I know it isn’t my fault that I’m not hitting, how can I get mad at myself?" - Yogi Berra

We have all perceived streaks of hits and misses when watching sports. Often people will blame...

SEM217: Saad Mouti, UC Berkeley: Rough volatility: Evidence from range-based and implied volatility

Tuesday, February 4th @ 11:00-12:30 PM (1011 Evans Hall)

Rough volatility: Evidence from range-based and implied volatility

Saad Mouti, UC Berkeley

ABSTRACT: In Gatheral et al. 2014, it has been shown that volatility exhibits a fractional behavior with a Hurst exponent $H < 0.5$, changing the typical perception of volatility. In their study, Gatheral and his co-authors used the realized volatility. In this analysis we explore the finding using two other...

SEM217: Alex Bernstein, UCSB: A Closed-Form Solution to the Markowitz Portfolio Problem

Tuesday, March 3rd @ 11:00-12:30 PM (70 Evans Hall)

A Closed-Form Solution to the Markowitz Portfolio Problem

Alex Bernstein, UCSB

ABSTRACT: In 1952, Harry Markowitz transformed finance by framing the portfolio construction problem as a tradeoff between the mean and the variance of return. This application of quadratic optimization is at the basis of breakthroughs such as the Capital Asset Pricing Model (CAPM) and Arbitrage Pricing Theory (APT). The classical Markowitz problem may be...

SEM217: Dangxing Chen, UC Berkeley: Nonparametric prediction of portfolio return volatility and its extension to the longer horizon

Tuesday, February 18th @ 11:00-12:30 PM (1011 Evans Hall)

Nonparametric prediction of portfolio return volatility and its extension to the longer horizon

Dangxing Chen, UC Berkeley

ABSTRACT: Medium-horizon portfolio volatility predictions are of significant value to long-term investors, such as Defined Benefit pension plans, insurance companies, sovereign wealth funds, endowments, and individual owners of Defined Contribution pension plans. In this paper, we...

SEM217: Hanlin Yang, University of Zurich: Decomposing Factor Momentum

Tuesday, February 25th @ 11:00-12:30 PM (1011 Evans Hall)

Decomposing Factor Momentum

Hanlin Yang, University of Zurich

ABSTRACT: The factor momentum portfolio is decomposed into a factor timing portfolio and a buy-and-hold portfolio, where the former collects the return from time-series predictability and the latter collects the return due to the cross-sectional dispersion of factor returns. Based on a large set of stock return factors, I document rich evidence that factor return...

SEM217: Laurent El Ghaoui, UC Berkeley: Implicit Deep Learning

Tuesday, March 10th @ 11:00-12:30 PM (ONLINE)

Implicit Deep Learning

Laurent El Ghaoui, UC Berkeley

ABSTRACT: We define a new class of "implicit'' deep learning prediction rules that generalize the recursive rules of feedforward neural networks. These models are based on the solution of a fixed-point equation involving a single vector of hidden features, which is thus only implicitly defined. The new framework greatly simplifies the...

Special Seminar: Xiaowu Dai, UC Berkeley: Multi-Layer Kernel Machines: A Fast and Accurate Approach for Large-Scale Supervised Learning (Biostat Seminar Series)

Monday, February 10th @ 9:00-10:00 AM (Berkeley Way West, RM 5400)

Multi-Layer Kernel Machines: A Fast and Accurate Approach for Large-Scale Supervised Learning (Biostat Seminar Series)

Xiaowu Dai, UC Berkeley

ABSTRACT: We propose an approximation of kernel ridge regression (KRR) based on random features and a multi-layer structure. KRR is popular in statistics and machine learning for nonparametric regressions over reproducing kernel Hilbert spaces. We study the minimum number of...

SEM217: Saad Mouti and Xiaowu Dai, UC Berkeley, Identifying Risk Factors for Cardiovascular Disease

Tuesday, April 14th @ 11:00-12:00 PM (ONLINE)

Identifying Risk Factors for Cardiovascular Disease

Saad Mouti and Xiaowu Dai, UC Berkeley

ABSTRACT: Cardiovascular disease (CVD) is the most common non-communicable disease occurring globally. Early diagnosis of CVD and identification of CVD related risk factors has become a health priority. In this work, we evaluate the causal effects of risk factors for CVD using matching methods and subsampling. In particular, we find that...

Xiaowu Dai, UC Berkeley: Multi-Layer Kernel Machines: A Fast and Accurate Approach for Large-Scale Supervised Learning (Biostat Seminar Series)

ABSTRACT: We propose an approximation of kernel ridge regression (KRR) based on random features and a multi-layer structure. KRR is popular in statistics and machine learning for nonparametric regressions over reproducing kernel Hilbert spaces. We study the minimum number of random features and the size of layers can be chosen for preserving minimax optimality of the approximate KRR estimate. We show that the multi-layer kernel machines only require O(n^1.5 log(n)) time and O(n log(n)) memory, which is significantly better compared to O(n^3) time and O(n^2) memory in computing KRR. For...