9 citations · 9 across the 4 of their papers we have counts for
4 papers
GARCHX-NoVaS: A Model-free Approach to Incorporate Exogenous Variables
Kejin Wu, Sayar Karmakar, Rangan Gupta
In this work, we explore the forecasting ability of a recently proposed normalizing and variance-stabilizing (NoVaS) transformation with the possible inclusion of exogenous variabl…
An NLP-Assisted Bayesian Time Series Analysis for Prevalence of Twitter Cyberbullying During the COVID-19 Pandemic
Christopher Perez, Sayar Karmakar
COVID-19 has brought about many changes in social dynamics. Stay-at-home orders and disruptions in school teaching can influence bullying behavior in-person and online, both of whi…
A New Model-free Prediction Method: GA-NoVaS
Kejin Wu, Sayar Karmakar
Volatility forecasting plays an important role in the financial econometrics. Previous works in this regime are mainly based on applying various GARCH-type models. However, it is h…
Model-free time-aggregated predictions for econometric datasets
Kejin Wu, Sayar Karmakar
This article explores the existing normalizing and variance-stabilizing (NoVaS) method on predicting squared log-returns of financial data. First, we explore the robustness of the…