Events

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...

SEM217: Philip Stark, UC Berkeley: Evidence-Based Elections

Tuesday, September 15 @ 11:00 - 1:00 PM (ONLINE)

Evidence-Based Elections

Philip Stark, UC Berkeley

ABSTRACT: Elections rely on people, hardware, and software, all of which are fallible and subject to manipulation. Well resourced nation-states continue to attack U.S. elections. Voting equipment is built by private vendors–some foreign, but all using foreign parts. Many states even outsource election results reporting to foreign firms. How can we conduct and check elections in a...

SEM217: Dangxing Chen, UC Berkeley: Modeling the dynamics of the realized variance based on high-frequency data

Tuesday, September 8 @ 11:00 - 12:30 PM (ONLINE)

Modeling the dynamics of the realized variance based on high-frequency data

Dangxing Chen, UC Berkeley

ABSTRACT: This paper studies in some detail a class of continuous-time stochastic volatility models. These models are direct models of daily asset return volatility based on realized measures constructed from high-frequency data. The models are capable of capturing the mean-reversion effect and different rates of innovations. We...

Baeho Kim, Korea University Business School: Stochastic Intensity Margin Modeling of Credit Default Swap Portfolios

Abstract: We consider the problem of initial margin (IM) modeling for portfolios of credit default swaps (CDS) from the perspective of a derivatives Central Counterparty (CCP). The CCPs' IM models in practice are based on theoretically-unfounded direct statistical modeling of CDS spreads. Using a reduced-form approach, our IM model based on stochastic default intensity prices the portfolio constituents in a theoretically meaningful way and shows that statistical IM models can underestimate CCPs' collateral requirements. In addition, our proposed Affine jump-diffusion intensity modeling...

Alex Papanicolaou: Testing Local Volatility in Short Rate Models

The first CRMR Risk Seminar of Fall 2016 features work by CDAR Postdoc Alex Papanicolaou. Abstract: We provide a simple and easy to use goodness-of-fit test for the misspecification of the volatility function in diffusion models. The test uses power variations constructed as functionals of discretely observed diffusion processes. We introduce an orthogonality condition which stabilizes the limit law in the presence of parameter estimation and avoids the necessity for a bootstrap procedure that reduces performance and leads to complications associated with the structure of the diffusion...

Bjorn Flesaker, Adjunct Professor at Courant Institute of Mathematical Sciences, NYU: Some Empirical Properties of a Bounded Interest Rate Model

We consider the two-factor version of a family of time-homogeneous interest rate models introduced by Cairns (Math Finance, 2004) in the Flesaker-Hughston positive interest framework. Specifically, we calibrate the model to cross-sectional USD swap and swaption market data, and we compare the corresponding model implied dynamics to that of the swap market rates via PCA. We investigate whether allowing a non-zero lower bound improves the model fit. The model dynamics are reformulated as a two-dimensional Ito process for the short rate and the consol rate (the par yield on a bond with no...