Search Results for author:
Found 11 papers, 3 papers with code
Automatic Outlier Rectification via Optimal Transport
In this paper, we propose a novel conceptual framework to detect outliers using optimal transport with a concave cost function.
Target PCA: Transfer Learning Large Dimensional Panel Data
This paper develops a novel method to estimate a latent factor model for a large target panel with missing observations by optimally using the information from auxiliary panel data sets.
A Simple Method for Predicting Covariance Matrices of Financial Returns
We also test covariance predictors on downstream applications such as portfolio optimization methods that depend on the covariance matrix.
Inference for Large Panel Data with Many Covariates
This paper proposes a novel testing procedure for selecting a sparse set of covariates that explains a large dimensional panel.
Deep Learning Statistical Arbitrage
Statistical arbitrage exploits temporal price differences between similar assets.
Time-Series Imputation with Wasserstein Interpolation for Optimal Look-Ahead-Bias and Variance Tradeoff
Imputation methods in time-series data often are applied to the full panel data with the purpose of training a model for a downstream out-of-sample task.
TextGNN: Improving Text Encoder via Graph Neural Network in Sponsored Search
Text encoders based on C-DSSM or transformers have demonstrated strong performance in many Natural Language Processing (NLP) tasks.
Large Dimensional Latent Factor Modeling with Missing Observations and Applications to Causal Inference
We derive the asymptotic distribution for the estimated factors, loadings and the imputed values under an approximate factor model and general missing patterns.
Deep Learning in Asset Pricing
We use deep neural networks to estimate an asset pricing model for individual stock returns that takes advantage of the vast amount of conditioning information, while keeping a fully flexible form and accounting for time-variation.
Change-Point Testing for Risk Measures in Time Series
We propose novel methods for change-point testing for nonparametric estimators of expected shortfall and related risk measures in weakly dependent time series.
On the existence of sure profits via flash strategies
We introduce and study the notion of sure profit via flash strategy, consisting of a high-frequency limit of buy-and-hold trading strategies.
