What is he best known for?
The fields of study he is best known for:
- Statistics
- Finance
- Macroeconomics
His primary areas of investigation include Econometrics, Volatility, Financial economics, Bivariate analysis and Monetary economics.
He has included themes like Sample, Monte Carlo method and Oil price in his Econometrics study.
His Volatility research incorporates themes from Emerging stock markets, Spillover effect and Emerging markets.
The concepts of his Financial economics study are interwoven with issues in Statistical hypothesis testing, Efficient-market hypothesis, Market liquidity, Debt and Autocorrelation.
His Bivariate analysis research incorporates elements of Precautionary demand and China.
His Monetary economics study incorporates themes from Financial risk management, Financial crisis and Credit risk.
His most cited work include:
- Stock market development and economic growth: The causal linkage (219 citations)
- Testing for contagion: a conditional correlation analysis (198 citations)
- Income and happiness across Europe: do reference values matter? (166 citations)
What are the main themes of his work throughout his whole career to date?
Econometrics, Monetary economics, Volatility, Financial economics and Stock market are his primary areas of study.
His Econometrics research includes themes of Exchange rate and Series.
As a member of one scientific family, Guglielmo Maria Caporale mostly works in the field of Monetary economics, focusing on Emerging markets and, on occasion, Latin Americans.
His work on Autoregressive conditional heteroskedasticity as part of general Volatility research is frequently linked to Macro and Estimation, bridging the gap between disciplines.
The Stock market study which covers Trading strategy that intersects with Financial market, Dummy variable and Regression analysis.
The concepts of his Cointegration study are interwoven with issues in Bivariate analysis and Unit root.
He most often published in these fields:
- Econometrics (53.67%)
- Monetary economics (30.43%)
- Volatility (16.74%)
What were the highlights of his more recent work (between 2019-2021)?
- Econometrics (53.67%)
- Long memory (13.55%)
- Monetary economics (30.43%)
In recent papers he was focusing on the following fields of study:
Guglielmo Maria Caporale spends much of his time researching Econometrics, Long memory, Monetary economics, Persistence and Volatility.
His research integrates issues of Inflation, Contrarian and Cryptocurrency in his study of Econometrics.
Guglielmo Maria Caporale interconnects Cointegration and Stock market in the investigation of issues within Long memory.
Guglielmo Maria Caporale works mostly in the field of Stock market, limiting it down to topics relating to Politics and, in certain cases, Financial economics, Markov chain and Multivariate garch, as a part of the same area of interest.
He has included themes like Financial crisis and Equity in his Monetary economics study.
His Volatility research incorporates elements of Stock exchange, Robustness and Stock market volatility.
Between 2019 and 2021, his most popular works were:
- Non-Linearities, Cyber Attacks and Cryptocurrencies (6 citations)
- The bank lending channel in the Malaysian Islamic and conventional banking system. (5 citations)
- High and low prices and the range in the European stock markets: A long-memory approach (4 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Finance
- Macroeconomics
The scientist’s investigation covers issues in Econometrics, Monetary economics, Volatility, Stock market and Cryptocurrency.
The Econometrics study combines topics in areas such as Stock market index and Contrarian.
His work on Interest rate and Exchange rate as part of general Monetary economics research is frequently linked to Financial development, thereby connecting diverse disciplines of science.
Guglielmo Maria Caporale studies Volatility, namely Autoregressive conditional heteroskedasticity.
His study looks at the relationship between Stock market and topics such as Politics, which overlap with Financial market, Financial economics and Multivariate garch.
His Mean reversion research is multidisciplinary, relying on both Bond and Unit root.
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