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Sayar Karmakar

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University of Florida

United States

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Grant: Close

ATD: New Algorithms for Inference and Predictions on Large Geospatial Datasets

Open Date: 2021-09-01

Close Date: 2024-08-31

Articles (14)

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2026

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2023

Collaborators (7)

Theodore Papamarkou

The University of Manchester

UNITED KINGDOM

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Matteo Foglia

Assistant Professor

University of Bari Aldo Moro

ITALY

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Anirbit Mukherjee

Lecturer (Assistant Professor)

The University of Manchester

UNITED KINGDOM

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Xin Sheng

Anglia Ruskin University

UNITED KINGDOM

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Kejin Wu

Assistant Professor

Loyola University Chicago

UNITED STATES

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Lavinia Rognone

Lecturer in Sustainable Finance

University of Edinburgh Business School

UNITED KINGDOM

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Vasilios Plakandaras

Associate professor

Democritus University of Thrace

GREECE

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Sayar Karmakar

Research Interests

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Recent Grants

Articles (14)

Return‐Volatility Nexus in the Digital Asset Class: A Dynamic Multilayer Connectedness Analysis

Stock market bubbles and the forecastability of gold returns and volatility

Supply bottlenecks and machine learning forecasting of international stock market volatility

GARCHX-NoVaS: A Bootstrap-Based Approach of Forecasting for GARCHX Models

Shortages and machine-learning forecasting of oil returns volatility: 1900–2024

Extreme weather shocks and state-level inflation of the United States

Climate risks and predictability of the trading volume of gold: Evidence from an INGARCH model

Depth-2 neural networks under a data-poisoning attack

A model-free approach to do long-term volatility forecasting and its variants

A novel spatio-temporal clustering algorithm with applications on COVID-19 data from the United States

An NLP-assisted Bayesian time-series analysis for prevalence of Twitter cyberbullying during the COVID-19 pandemic

Are real interest rates a monetary phenomenon? Evidence from 700 years of data

On a class of PCA with size-3 neighborhood and their applications in percolation games

Safe Havens, Machine Learning, and the Sources of Geopolitical Risk: A Forecasting Analysis Using Over a Century of Data

Collaborators (7)

Theodore Papamarkou

Matteo Foglia

Anirbit Mukherjee

Xin Sheng

Kejin Wu

Lavinia Rognone

Vasilios Plakandaras

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