His primary areas of investigation include Econometrics, Financial economics, Volatility, Vector autoregression and Autoregressive model. Specifically, his work in Econometrics is concerned with the study of Quantile. He combines subjects such as Oil price, Equity, Predictability and Stock market with his study of Financial economics.
Rangan Gupta interconnects Nonparametric statistics and Monetary economics in the investigation of issues within Volatility. His work in Vector autoregression addresses subjects such as House price, which are connected to disciplines such as Shock. In Autoregressive model, Rangan Gupta works on issues like Recession, which are connected to Business cycle.
Rangan Gupta mainly investigates Econometrics, Volatility, Monetary economics, Monetary policy and Autoregressive model. The Econometrics study combines topics in areas such as Bayesian probability, Inflation and Predictability. His studies deal with areas such as Vector autoregression and Dynamic stochastic general equilibrium as well as Bayesian probability.
His research in Volatility intersects with topics in Nonparametric statistics, Conditional probability distribution and Stock market. The concepts of his Monetary economics study are interwoven with issues in Equity, Financial market, Endogenous growth theory, Emerging markets and Financial crisis. His Monetary policy study combines topics from a wide range of disciplines, such as Shock and Interest rate.
His primary areas of study are Econometrics, Volatility, Monetary economics, Predictability and Monetary policy. His work in Econometrics tackles topics such as Stock market which are related to areas like Dummy variable and Financial economics. His work deals with themes such as Nonparametric statistics, Financial crisis and Gold as an investment, which intersect with Volatility.
His Monetary economics research incorporates elements of Equity, Financial market, Emerging markets, Bond and Consumption. His study looks at the relationship between Predictability and topics such as Granger causality, which overlap with Linear model. His Monetary policy research integrates issues from Inflation and Interest rate.
Rangan Gupta mostly deals with Econometrics, Volatility, Monetary economics, Predictability and Monetary policy. His Econometrics course of study focuses on Consumption and Demand shock. His study on Volatility also encompasses disciplines like
His Monetary economics study combines topics in areas such as Spillover effect, Equity, Financial market, Volatility spillover and Bond. The study incorporates disciplines such as Index, Economic inequality, Hedge and Risk aversion in addition to Predictability. His Monetary policy research includes themes of Financial crisis, Inflation, Interest rate and Shock.
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Can volume predict Bitcoin returns and volatility? A quantiles-based approach
Mehmet Balcilar;Elie Bouri;Rangan Gupta;David Roubaud.
Economic Modelling (2017)
Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions
Elie Bouri;Rangan Gupta;Aviral Kumar Tiwari;David Roubaud.
Finance Research Letters (2017)
The nexus of electricity consumption, economic growth and CO2 emissions in the BRICS countries
Wendy N. Cowan;Tsangyao Chang;Roula Inglesi-Lotz;Rangan Gupta.
Energy Policy (2014)
Has oil price predicted stock returns for over a century
Paresh Kumar Narayan;Rangan Gupta.
Energy Economics (2015)
Herding behaviour in cryptocurrencies
Elie Bouri;Rangan Gupta;David Roubaud.
Finance Research Letters (2019)
The role of news-based uncertainty indices in predicting oil markets: a hybrid nonparametric quantile causality method
Mehmet Balcilar;Stelios Bekiros;Rangan Gupta.
Empirical Economics (2017)
Oil prices and financial stress: A volatility spillover analysis
Saban Nazlioglu;Ugur Soytas;Rangan Gupta.
Energy Policy (2015)
Regime switching model of US crude oil and stock market prices : 1859 to 2013
Mehmet Balcilar;Mehmet Balcilar;Rangan Gupta;Stephen M. Miller.
Energy Economics (2015)
The Causal Relationship Between Economic Policy Uncertainty and Stock Returns in China and India: Evidence from a Bootstrap Rolling Window Approach
Xiao-lin Li;Mehmet Balcilar;Rangan Gupta;Tsangyao Chang.
Emerging Markets Finance and Trade (2016)
The effect of monetary policy on real house price growth in South Africa : a factor augmented vector autoregression (FAVAR) approach
Rangan Gupta;Marius Jurgilas;Alain Kabundi.
Economic Modelling (2010)
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