Sub-collections in this collection

Recent Submissions

  • Forecast combination puzzle in the HAR model 

    Clements, Adam; Vasnev, Andrey
    Published 2021
    The Heterogeneous Autoregressive (HAR) model of Corsi (2009) has become the benchmark model for predicting realized volatility given its simplicity and consistent empirical performance. Many modifications and extensions ...
    Open Access
    Working Paper
  • Two-Stage Stochastic and Robust Optimization for Non-Adaptive Group Testing 

    Ho-Nguyen, Nam
    Published 2020-10-28
    We consider the problem of detecting defective items amongst a large collection, by conducting tests of individual or groups of items. Group testing offers improvements over the naive individual testing scheme by potentially ...
    Open Access
    Working Paper
  • Too similar to combine? On negative weights in forecast combination 

    Radchenko, Peter; Vasnev, Andrey; Wang, Wendun
    Published 2020-01-01
    This paper provides the first thorough investigation of the negative weights that can emerge when combining forecasts. The usual practice in the literature is to ignore or trim negative weights, i.e., set them to zero. ...
    Open Access
    Working Paper
  • Higher Moment Constraints for Predictive Density Combinations 

    Pauwels, Laurent; Radchenko, Peter; Vasnev, Andrey
    Published 2020-05-01
    The majority of financial data exhibit asymmetry and heavy tails, which makes forecasting the entire density critically important. Recently, a forecast combination methodology has been developed to combine predictive ...
    Open Access
    Article
  • Python Language Companion to Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares 

    Leung, Jessica; Matsypura, Dmytro
    Published 2019-11-13
    This Python Language Companion is drafted as a supplement to the book Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares written by Stephen Boyd and Lieven Vandenberghe (referred to here as VMLS). ...
    Open Access
    Book

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