In this study, we examine the volatility connectedness among eight major cryptocurrencies by the virtue of market capitalization by employing the frequency connectedness approach over the period July 26, 2017, and October 28, 2020. To this end, we compute short-, medium-, and long-cycle overall spillover indexes on different frequency bands, All indexes properly capture well-known events such as the 2018 cryptocurrency market crash and COVID-19 pandemic, and markedly surge around these incidents. Furthermore, owing to notably increased volatilities after the official announcement of the COVID-19 pandemic, we concentrate on network connectedness of volatility spillovers for two distinct periods, July 26, 2017-March 10, 2020, and March 11, 2020-October 28, 2020, respectively. In line with the related studies, major cryptocurrencies stand at the epicenter of the connectedness network, and directional volatility spillovers dramatically intensify based on the network analysis.
In this study, we examine the energy commodities connectedness between the period June 2006 and April 2020 by implementing the Diebold�Yilmaz and the frequency connectedness approaches. We estimate dynamic connectedness between WTI crude oil, the Henry Hub natural gas, ULS diesel and the gasoline prices over the analysed period. Overall spillover indexes estimated by both methodologies properly respond to prominent geopolitical events over the sample period. Additionally, we plot network graphs for directional spillovers reflecting two distinct periods, 2007:3�2019:12 and 2020:1�2020:4. Network analysis verifies that the directional spillovers between energy commodities have prominently surged due to the COVID-19 outbreak. The findings of the study underline the importance of an effective regulatory framework for monitoring commodity price developments to avoid adverse effects of commodity price shocks. Additionally, the authorities should enact policy actions to counteract the detrimental effects of the COVID-19 pandemic on the commodity markets.
The goal of the portfolio optimization problem is to minimise risk for an expected portfolio return by determining the proportions of included assets. As the pool of assets increases and additional constraints are considered, the problem becomes NP-hard. Thus, metaheuristics are commonly employed for solving large instances of rich versions. However, metaheuristics fail to account for stochastic returns and covariances, rendering them unrealistic in the presence of heightened uncertainty in financial markets. This paper aims at closing this gap by proposing a simulation-optimization approach, specifically a simheuristic algorithm that integrates a variable neighbourhood search metaheuristic with Monte Carlo simulation, to deal with returns and covariances modelled as random variables. Computational experiments performed on a well-established benchmark instance illustrate the use of our methodology and analyse how the solutions change in response to varying the degree of randomness, minimum required return, and probability of obtaining at least the specified return.
Bu �alisma Subat 1990 ve Kasim 2019 d�neminde petrol fiyat soklarinin k�resel finansal aktiviteye olan zaman-degisimli etkilerini Zamana G�re Degisen Parametreli VAR (TVP-VAR) modeli uygulayarak incelemektedir. Bu baglamda aylik spot WTI ham petrol fiyatlari, d�nya ham petrol �retimi ve Kansas Sehri Finansal Stres Endeksi (KCFSI) verileri ampirik analizde kullanilmistir. �alismanin ampirik sonu�lari petrol fiyatlarindaki kalici bir artisin finansal kosullari olumsuz olarak etkiledigini g�stermektedir. Bununla birlikte, pozitif bir petrol arz soku petrol fiyatlarinda d�s�se neden olmaktadir. �alismanin bulgulari literat�rde elde edilen sonu�larla uyumludur ve TVP-VAR modelinin yapisal petrol fiyat soklarinin zaman-degisimli yapisini yakalamadaki tutarliligini g�stermektedir.
We use a Bayesian time-varying parameter vector autoregression (TVP-VAR) model to examine the time-varying transmission mechanisms between structural oil price shocks and Borsa Istanbul Stock Exchange, Turkey's stock market (BIST). Our data span the period February 1988 to December 2018, and include monthly West Texas Intermediate (WTI) spot crude oil prices, world crude oil production data, a measure of global real economic activity (the Kilian Index), and BIST data. Accordingly, we contribute to the literature by using a novel approach to estimate the time-varying propagations between oil-specific shocks and financial activity in Turkey. Our results are in line with those of related studies, thus verifying the consistency of the TVP-VAR model in capturing the time-varying nature of oil price shocks.
In this study, we analyze the quality of governance in Turkey by using worldwide governance indicators (WGIs), namely, voice and accountability (VA), political stability and absence of violence (PV), government effectiveness (GE), regulatory quality (RQ), rule of law (RL), and control of corruption (CC) which aggregate 6 dimensions of governance. In that regard, we employ principal component analysis (PCA) to construct a composite governance index (CGI) for Turkey over the 2002-2017 period. We find that the CGI creates proper signals to both economic and political disequlibriums observed in the post-2001 financial crisis era. Our findings underline an effective regulatory framework for monitoring the quality of governance and accordingly suggests the CGI as a policy tool.
In this study, the relationship between R&D tax incentives, R&D expenditures and economic growth is analyzed for the US, Australia, Belgium, Czech Republic, France, South Korea, Canada, UK, Spain, and Hungary for 2005-2015 using Panel VAR model. In this respect; B-Index, R&D expenditures and GDP series are used in the econometric analysis. Cross-sectional dependence for the variables is detected by Peseran�s (2004) CD test and stationarity of the series are tested with Peseran�s (2007) second generation cross-sectional augmented IPS (CIPS) test. The variables are found I(1), the first difference of them are used in Panel VAR analysis. The results of Panel VAR analysis support the hypothesis that proposes R&D incentives and R&D expenditures positively affect economic growth. The causality between series are examined by using Panel Granger Causality Test and one-way causality from R&D expenditures to GDP and one-way causality from R&D expenditures to B-Index are detected. The results of the study confirm the idea of R&D incentives and R&D expenditures trigger the economic growth.
Computational finance is an emerging application field of metaheuristic algorithms. In particular, these optimisation methods are becoming the solving approach alternative when dealing with realistic versions of several decision-making problems in finance, such as rich portfolio optimisation and risk management. This paper reviews the scientific literature on the use of metaheuristics for solving NPhard versions of these combinatorial optimisation problems and illustrates their capacity to provide high-quality solutions under scenarios considering realistic constraints. The paper contributes to the existing literature in three ways. Firstly, it reviews the literature on metaheuristic optimisation applications for portfolio and risk management in a systematic way. Secondly, it identifies the linkages between portfolio optimisation and risk management and presents a unified view and classi fication of both problems. Finally, it outlines the trends that have gradually become apparent in the literature and will dominate future research in order to further improve the state-of-the-art in this knowledge area.
In this study, we analyze systemic risk contagion between a set of most actively traded currencies (EURO, JPY, GBP, AUD, CAD and CHF) by application of VAR based frequency connectedness proposed by Barunik and Krehlik (2018). By using this novel approach, we gauge foreign exchange (FX) market connectedness in 200-day frequency band using spectral representation of variance decompositions of VAR and identify directional spillovers between actively traded foreign exchange rates. Dynamics of the overall spillover index reveals that the index capture well-known financial stress incidents properly. Finally, network topology of directional spillovers between currency pairs is provided for visulalization interconnectedness between them.
Measuring, analyzing and understanding systemic risk in financial system have become very important in the light of the recent global crisis. In this study, we follow Hollo, Kremer, & Lo Duca (2012) and evaluate systemic stress of financial system of Turkey with a high frequency (daily) financial stress index which consists of daily 13 financial market indicators. Dynamics of the financial stress index indicate that the index creates proper signals to the well-known financial stress events. The dynamic interaction between financial stress and real economic activity is investigated with application of structural VAR (SVAR) model. Results of the study suggest that deterioration of financial conditions impacts real economic activity significantly and adversely.
The Pigouvian taxes that are used to internalize negative externalities by policy makers in order to reduce green gas emission nowadays. These taxes are called as environmental taxes which are levied in European Union (EU) countries mostly. The efficiency of environmental taxes in reducing CO2 emission is investigated in this study. In this regard, the long run relationship between CO2 emission and environmental taxes is analyzed for 25 EU countries with application of ArellanoBover/Blundell-Bond dynamic panel model, Westerlund Panel Cointegration test and Panel DOLS model. Results of the study indicate that the series are cointegrated and there exist negative and significant long-run relationship between CO2 emission and environmental taxes.
This study examines linkages between daily oil price dynamics and financial stress. We analyze the dynamic interaction mechanism between daily WTI crude oil prices and financial stress index of the United States developed by Polat (2017) with Structural VAR model in 01/10/1993 - 11/18/2016 period. The empirical results of the study suggest that there exist a significant relationship between oil price dynamics and financial stress and the relationship is dominated by the short-run.
Thanks to the financial connectedness, contagion effects of financial instability/turmoil periods can quickly disperse. This situation indicates importance of measuring and understanding of connectedness of global financial markets. This study investigates financial connectedness of 9 countries (G-7, Norway and Turkey) using Diebold and Yilmaz (2009, 2012) methodologies. In addition, the dynamics of 200-day rolling windows of total spillover index with well-known financial stress events are given.