Browsing by Subject "Economies"

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Embargo
Financial fusion: bridging islamic and green investments in the European stock market
(Elsevier Ltd., 2024-07) Husain, Afzol; Karim, Sitara; Şensoy, Ahmet
Given the historic decoupling nature of Islamic and green financial instruments with conventional financial markets this study investigated the interconnectedness of the European financial market with green and Islamic financial instruments amidst the unprecedented global dynamics and mounting uncertainties. Considering data from January 02, 2015, to October 03, 2023 and using TVP-VAR and Wavelet Coherence, our empirical findings challenge conventional assumptions about the behaviour of Islamic and green financial instruments in times of economic distress. While traditional financial instruments may falter, both Islamic and green financial instruments emerge as resilient options during market crises as indicated using quantile TVP-VAR as robustness measure. Both Islamic and Green bonds display remarkable potential for stability and resilience for European investors. For investors navigating the complexities of financial markets, especially during economic distress, our findings offer valuable guidance. Incorporating Islamic and green financial instruments, alongside diversified bond portfolios, emerges as a robust strategy. We strongly advocate the inclusion of both sukuk and green bonds in investment portfolios. Our result research also holds significant implications for policymakers.
Open Access
Statistical properties of genetic learning in a model of exchange rate
(Elsevier BV, 2000) Arifovic, J.; Gençay, R.
We study statistical properties of the time series of the exchange rate data generated in the environment where agents update their savings and portfolio decisions using the genetic algorithm. The genetic algorithm adaptation takes place within an overlapping generations model with two currencies and the free-trade, flexible exchange rate system. The theoretical model implies a constant exchange rate under the perfect foresight assumption. Under the genetic algorithm learning, the model's equilibrium dynamics is not constant but exhibits bounded oscillations. The time series analysis of the data indicates that the dynamics of the exchange rate returns is chaotic. Out-of-equilibrium inequality of rates of return on two currencies prompts the genetic algorithm agents to take advantage of the arbitrage opportunities by increasing the amount of the currency with higher rate of return in their portfolios. This profit seeking results in chaotic patterns of the exchange rate series. (C) 2000 Elsevier Science B.V. All rights reserved.