Fall 2020

SEM217: Hubeyb Gurdogan, Florida State University: Multi-Anchor Point Shrinkage for Better Betas

Tuesday, December 1 @ 11:00 - 12:30 PM (ONLINE)

Multi-Anchor Point Shrinkage for Better Betas

Hubeyb Gurdogan, Florida State University

ABSTRACT: The GPS (Goldberg, Papanicolaou, Shkolnik) method shrinks the leading eigenvector of the sample covariance matrix towards the vector of all 1’s by a data driven amount in the low sample-high dimension regime. That creates an estimate of betas that has lower l_2 error and significantly reduces the impact of the...

SEM217: Othmane Mounjid, École Polytechnique: Improving reinforcement learning algorithms using an optimal learning rate policy

Tuesday, October 20 @ 11:00 - 12:30 PM (ONLINE)

Improving reinforcement learning algorithms using an optimal learning rate policy

Othmane Mounjid, École Polytechnique

ABSTRACT: We investigate to what extent one can improve reinforcement learning algorithms. For this, we first show that the classical asymptotic convergence rate O(1/√N) is pessimistic and can be replaced by O((log(N)/N)^Beta) with Beta in [0.5,1] and N the number of iterations....

SEM217: Zhipu Zhou, UC Santa Barbara: Endogenous Representation of Asset Returns

Tuesday, October 27 @ 11:00 - 12:30 PM (ONLINE)

Endogenous Representation of Asset Returns

Zhipu Zhou, UCSB

ABSTRACT: Factor modeling of asset returns has been a dominant practice in investment science since the introduction of the Capital Asset Pricing Model (CAPM) and the Arbitrage Pricing Theory (APT). The factors, which account for the systematic risk, are either specified or interpreted to be exogenous. They explain a significant portion of the risk in...

SEM217: Ola Mahmoud, University of Basel: The Anatomy of Sustainability

Tuesday, September 29 @ 11:00 - 12:30 PM (ONLINE)

The Anatomy of Sustainability

Ola Mahmoud, University of Basel

ABSTRACT: We present evidence that sustainability is inextricably linked with market-implied uncertainty. We derive an econometric decomposition of sustainability ratings yielding three orthogonal components capturing uncertainty, investor sentiment, and an idiosyncratic sustainability factor. Examining the shock of the COVID-19 pandemic to the US stock market in light of...

SEM217: Marco Avellaneda, NYU: Hierarchical PCA and modeling asset correlations

Tuesday, September 22 @ 11:00 - 12:30 PM (ONLINE)

Hierarchical PCA and modeling asset correlations

Marco Avellaneda, NYU

ABSTRACT: Modeling return correlations between thousands of stocks poses great challenges, as empirical estimators tend to perform poorly when assets don’t share common risk factors, such as country or industry sector. In this paper, we show the advantages of using Hierarchical Principal Component Analysis (HPCA) for modeling correlations, as opposed to the classic...

SEM217: Samim Ghamami, Financial Services Forum: The Impact of Collateral and Stays on Financial Stability

Tuesday, October 6 @ 11:00 - 12:30 PM (ONLINE)

The Impact of Collateral and Stays on Financial Stability

Samim Ghamami, Financial Services Forum

ABSTRACT: We study the spread of losses and defaults in financial networks with two features: collateral requirements and resolution and bankruptcy stay rules. When collateral is committed to a firm’s counterparties, a solvent firm may default if it lacks sufficient liquid assets to meet its payment obligations. Collateral requirements can...

SEM217: Jeff Bohn, Swiss Re

Tuesday, November 17 @ 11:00 - 12:30 PM (ONLINE)

Boosting prediction performance for economic and market indicators

Jeffrey R. Bohn, Swiss Re Institute

ABSTRACT: As risk, trading, strategy, and decision-support systems have become more deeply integrated into financial services firms’ workflows, predicting a collection of economic and market indicators becomes even more critical to support these systems than in the past. At the same time, the...

SEM217: Tingyue Gan, UC Berkeley: Machine-Assisted Mini-Scene Writing

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

Machine-Assisted Mini-Scene Writing

Tingyue Gan, UC Berkeley

Please see this brief for a preview of the seminar.

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SEM217: Ruoxuan Xiong, Stanford: Large Dimensional Latent Factor Modeling with Missing Observations and Applications to Causal Inference

Tuesday, September 1 @ 11:00 - 12:30 PM (ONLINE)

Large Dimensional Latent Factor Modeling with Missing Observations and Applications to Causal Inference

Ruoxuan Xiong, Stanford

ABSTRACT: This paper develops the inferential theory for latent factor models estimated from large dimensional panel data with missing observations. We estimate a latent factor model by applying principal component analysis to an adjusted covariance...

SEM217: Xiaowu Dai & Saad Mouti, UC Berkeley: A resampling approach for causal inference on two-point time-series with application to identify risk factors for type-2 diabetes and cardiovascular disease

Tuesday, October 13 @ 11:00 - 12:30 PM (ONLINE)

A resampling approach for causal inference on two-point time-series with application to identify risk factors for type-2 diabetes and cardiovascular disease

Xiaowu Dai & Saad Mouti, UC Berkeley

ABSTRACT: Two-point time-series data, characterized by baseline and follow-up observations, are frequently encountered in health research. In analyzing such time-series data, the two-point pattern must be adequately accounted to balance the...