0000000000160831

AUTHOR

Francisco Jareño

0000-0001-9778-7345

Does Shariah compliance make interest rate sensitivity of Islamic equities lower? An industry level analysis under different market states

This paper examines the sensitivity of the Dow Jones Islamic market index and its corresponding industry equity indices to changes in the level, slope and curvature of the U.S. term structure of in...

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Interest Rate Sensitivity of Spanish Industries: A Quantile Regression Approach

This paper examines the degree of interest rate exposure of Spanish industries for the period 1993–2012 using the quantile regression methodology. The empirical results show that the Spanish stock market exhibits a significant level of interest rate sensitivity, although there are notable differences across industries and over time. In addition, the impact of changes in interest rates on industry equity returns tends to be more pronounced in extreme market conditions, i.e. during crises or bubbles in stock markets, than in normal periods. This finding may be related to herding behavior of stock investors during periods of market stress.

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Main driving factors of the interest rate-stock market Granger causality

Abstract This paper investigates the causal relationship between changes in the 10-year Treasury bond yield and the S&P 500 stock return in the United Sates with emphasis on time variation, stress factors and smooth regime transition. First, the time-varying Granger causality test proposed by Lu et al. (2014) is applied. Then a two-regime multifactor smooth transition regression model with a single transition variable representing a wide range of macroeconomic and financial variables is estimated in order to identify the key explanatory factors governing the causal relationship. The results show a significant bidirectional causal relationship over most of the study period, mainly due to the…

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Time-varying causality between crude oil and stock markets: What can we learn from a multiscale perspective?

This paper investigates the presence of time-varying causal linkages in mean and variance between oil price changes and stock returns for six major oil-importing countries (France, Germany, Italy, Spain, the UK and the US) in a multiscale framework that combines wavelet analysis and a modified version of the dynamic causality test of Lu, Hong, Wang, Lai, and Liu (2014). The results show significant bidirectional causal relations between oil and stock markets at the different time horizons for all countries. The causal links tend to be stronger at coarser scales and in periods of financial turmoil, mainly during the recent global financial and European sovereign debt crises. This evidence pr…

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Time and frequency dynamics of connectedness between renewable energy stocks and crude oil prices

Abstract This paper examines the time and frequency dynamics of connectedness among stock prices of U.S. clean energy companies, crude oil prices and a number of key financial variables using the methodology developed by Barunik and Krehlik (2018). This approach allows measuring the dynamics of return and volatility connectedness over time and across frequencies simultaneously. The empirical results show that most of return and volatility connectedness is generated in the very short-term, i.e. movements up to five days, while the long-term plays a minor role. Our analysis further reveals a greater degree of interconnectedness across crude oil and financial markets since the onset of the U.S…

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US stock market sensitivity to interest and inflation rates: a quantile regression approach

ABSTRACTThis article studies the sensitivity of the US stock market to nominal and real interest rates and inflation during the 2003–2013 period using quantile regression (QR). The empirical results show that the stock market has a significant sensitivity to changes in interest rates and inflation and finds differences across sectors and over time. Moreover, the effect of changes in both interest rates and inflation tends to be more pronounced during extreme market conditions, thus distinguishing expansion periods from recession periods.

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