Zobrazeno 1 - 10
of 878
pro vyhledávání: '"Rangan Gupta"'
Publikováno v:
Financial Innovation, Vol 10, Iss 1, Pp 1-17 (2024)
Abstract This paper analyzes the degree of dynamic connectedness between energy and metal commodity prices in the pre and post-COVID-19 era, using the time-varying parameter vector autoregressive connectedness approach of Antonakakis et al. (J Risk F
Externí odkaz:
https://doaj.org/article/b29c9cd391c44d0a860101fa91d718fd
Publikováno v:
Quantitative Finance and Economics, Vol 7, Iss 3, Pp 475-490 (2023)
We examine the potential of gold and other precious metals as safe havens during negative market shocks caused by the Global Financial Cycle (GFCy). We analyze a vast global vector autoregressive (GVAR) model that includes developing and emerging mar
Externí odkaz:
https://doaj.org/article/9a0a31b5a74e4f7b88886634fb080dfc
Publikováno v:
Climate, Vol 12, Iss 5, p 68 (2024)
Because climate change broadcasts a large aggregate risk to the overall macroeconomy and the global financial system, we investigate how a temperature anomaly and/or its volatility affect the accuracy of forecasts of stock return volatility. To this
Externí odkaz:
https://doaj.org/article/6e6caccdc5454368b7161aef8e2a47b4
Publikováno v:
Financial Innovation, Vol 9, Iss 1, Pp 1-23 (2023)
Abstract Forecasting returns for the Artificial Intelligence and Robotics Index is of great significance for financial market stability, and the development of the artificial intelligence industry. To provide investors with a more reliable reference
Externí odkaz:
https://doaj.org/article/93d2b3c7c8a740c9826b6cc6efb34ce9
Publikováno v:
Financial Innovation, Vol 9, Iss 1, Pp 1-22 (2023)
Abstract This paper is motivated by Bitcoin’s rapid ascension into mainstream finance and recent evidence of a strong relationship between Bitcoin and US stock markets. It is also motivated by a lack of empirical studies on whether Bitcoin prices c
Externí odkaz:
https://doaj.org/article/1846be9eede2450e9b6fb43f731b3e85
Autor:
Rangan Gupta, Christian Pierdzioch
Publikováno v:
Financial Innovation, Vol 9, Iss 1, Pp 1-22 (2023)
Abstract Because the U.S. is a major player in the international oil market, it is interesting to study whether aggregate and state-level economic conditions can predict the subsequent realized volatility of oil price returns. To address this researc
Externí odkaz:
https://doaj.org/article/4e85b32529904ac084736e28649ff472
Publikováno v:
Risks, Vol 11, Iss 11, p 186 (2023)
We examine the impact of the global economic activity, oil supply, oil-specific consumption demand, and oil inventory demand shocks on the expected aggregate skewness of the United States (US) economy, obtained based on a data-rich environment involv
Externí odkaz:
https://doaj.org/article/fa38d7dc22bc4f8facc35a1f82bcb32e
Publikováno v:
Mathematics, Vol 11, Iss 13, p 2964 (2023)
Studying the question of whether macroeconomic predictors play a role in forecasting stock-market volatility has a long and significant tradition in the empirical finance literature. We went beyond the earlier literature in that we studied whether th
Externí odkaz:
https://doaj.org/article/5d33ff34d8224e8786bd8a2e8f17d416
Publikováno v:
Mathematics, Vol 11, Iss 9, p 2077 (2023)
In this study, we contribute to the rapidly growing climate-finance literature by shedding light on the question of whether climate risks have predictive value for stock market returns. We measure climate risks in terms of both the change in the nort
Externí odkaz:
https://doaj.org/article/ca53d10e78854642a9a97507c6b328bb
Publikováno v:
Mathematics, Vol 11, Iss 6, p 1371 (2023)
We use a quantile machine learning (random forests) approach to analyse the predictive ability of newspapers-based macroeconomic attention indexes (MAIs) on eight major fundamentals of the United States on the realized volatility of a major commodity
Externí odkaz:
https://doaj.org/article/f767a3e275f141eaa7c6569eda9ed0e2