Erhan Uluceviz's research while affiliated with Gebze Technical University and other places
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Publications (16)
We analyze the connectedness between the real and the financial sectors of the U.S. economy. Using the weekly ADS index of the Philadelphia Fed (the widely used business conditions indicator) to represent the real side, we find that during times of financial distress and business cycle turning points, the direction of connectedness runs from the re...
Abstract We study macro-financial linkages and their importance within the Swiss economy from a network perspective. First, we investigate the real-financial connectedness in the Swiss economy, using the KOF economic barometer, obtained from real and financial variables, and, the real activity index (RAI), we distilled from a small set of real vari...
Analyzing networks of asset markets on the basis of daily return-to-volatility and volatility-to-volatility spillovers between markets and in terms of propagation values is a well-established methodology. The present study uses notions from information theory, in particular the Kolmogorov-Sinai entropy, to analyze the flow of information in a netwo...
This paper investigates the relative importance of stock markets in a network consisting of the four BRIC (Brazil, Russia, India, China) markets, plus the USA. Each of these markets is represented by a stock index: Bovespa (Brazil), RTS (Russia), BSE Sentex (India), Shanghai Stock Index Composite (China), and Dow-Jones Industrial Average (USA), con...
BRICS, the acronym for an association of the states Brazil, Russia, India, China and South Africa, is an invented concept. Nevertheless, the member states have institutionalized, to some extent, their economic and political cooperation and thus gained more influence worldwide as an entity. The main purpose of the present paper is to investigate how...
This paper investigates the relative importance of stock markets in a network consisting of the four BRIC (Brazil, Russia, India, China) markets, plus the USA. Each of these markets is represented by a stock index: Bovespa (Brazil), RTS (Russia), BSE Sentex (India), Shanghai Stock Index Composite (China), and Dow-Jones Industrial Average (USA), con...
Cycles in the behavior of stock markets have been widely documented. There is an increasing body of literature on whether stock markets anticipate business cycles or its turning points. Several recent studies assert that financial integration impacts positively on business cycle comovements of economies.
We consider three western equity markets, re...
The goal of the this paper is to investigate the shock spillover characteristics of the Russian stock market during different rounds of sanctions imposed as a reaction to Russia’s alleged role in the Ukrainian crisis. We consider six stock markets, represented by their respective stock indices, namely the US (DJIA), the UK (FTSE), the euro area (Eu...
We consider three equity markets, represented by stock indices DJIA (USA), FTSE 100 (UK), and EURO STOXX 50 (euro area). Connecting these three markets together via vector autoregressive processes in index returns (or volatilities), we construct “propagation values” to measure, on a daily basis, the relative importance of a market as a volatility c...
The dating of cyclical phenomena in economies, such as business cycles, is at the core
of economic policy research. Moreover, policy decisions which are due to affect interacting
economies should take into account the economies’ connectedness and synchronicity. The
cross-country analysis of business cycles is conceptually close to the study of “con...
The degree of connectedness of equity markets on a given day can be assessed by decomposing the forecast error variance resulting from a vector autoregressive model, applied to daily returns on stock indices. This well-known procedure leads, for each day, to a spillover matrix which can be readily interpreted as a network structure and summarized i...
Measures of spillovers between international equity markets can be derived building on the well-established forecast error variance decomposition in a vector autoregression VAR) framework. Typically, a day-by-day monitoring of these measures leads to non-stationary time series, the patterns giving rise to speculations about the existence of cyclica...
Publicly traded corporations can be seen as a directed graph or network with nodes as corporations and edges with weights quantifying return spillovers in terms of forecast error variance decompositions (fevds) of daily returns on their stock prices. Information-theoretic measures can then be used to analyze the flow of information (for example, th...
The overall degree of international equity market connectedness has gradually increased
over the past two decades. Reflecting the shift in global economic power, it has been recently suggested to pay more attention to the BRICT (Brazil, Russia, India, China, and Turkey) countries. Building on, and methodologically adding to, an established approach...
The connectedness of international equity markets can be measured building on the well-established forecast error variance decomposition framework. This approach permits the assessment of the propagation of shocks (spillovers) across equity markets on a day-to-day basis. The focus of our contribution is on detecting cycles in the intensity of spill...
The degree of connectedness of equity markets on a given day can be assessed by decomposing the forecast error variance resulting from a vector autoregressive model, applied to daily returns on stock indices. This well-known procedure leads, for each day, to a spillover matrix quantifying the contribution of a shock, to which one return series
is e...
Citations
... For example, Okorie (2021c) used it to study electricity demand and cryptocurrency market connectedness. The financial system Yilmaz, 2012, 2014;Diebold and Yilmaz, 2016), business cycle (Diebold and Yilmaz, 2015b), financial and macroeconomic sectors (Diebold and Yilmaz, 2015;Cotter et al., 2017), cryptocurrency markets (Ji et al., 2019), manufacturing and industrial sector (Bilgin and Yilmaz, 2018), credit risk (Bostanci and Yilmaz, 2015), financial and real sector (Uluceviz and Yilmaz, 2018), banking sector (Demirer et al., 2018), et cetera. ...
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... In 2013, Russia's GDP was around 2.8% of global GDP; the total value of Russia's stock market in 2012 was around 1.5% of the world stock market value. 1 Russia's trading volume with the EU was approximately EUR 340 billion at that time 2 and the EU's GDP was approximately EUR 13,500 billion. 3 However, empirical studies have found evidence of strong dependence between Russia as one of the major raw-materials exporter along with its fellow BRIC (Brazil, Russia, India, China) country Brazil and the US markets, as well as a significant increase of connectedness among BRIC equity markets and with equity markets in the developed world beginning in 2005 (see Alou et al., 2011;Schmidbauer et al., 2013a). Bekiros (2014), investi- gating the spillover effects of the US financial crisis to the BRIC markets, also finds that " [...] almost all markets have become more internationally integrated after the US financial crisis and the consequent Eurozone sovereign debt crisis". ...
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... Besides, political and security considerations regarding crude oil have also affected the trade in this commodity. Later, after the crude oil crisis in the 1970s, some countries tried to use trade agreements to reduce crude oil export restrictions [4]. Dependence on oil revenues in these countries will create dangerous conditions for oil exporters for four reasons: 1. ...
... Since earlier works by Ramsey (2002), Wong et al. (2003), Crowley (2007) and Aguiar-Conraria et al. (2008), the application of wavelet-based methodologies in Economics has been widespread. Wavelets have been used to study a wide range of areas, such as equity markets (Schmidbauer et al., 2017;Verona, 2016), business cycles (Crowley & Hughes Hallett, 2015Funashima, 2016;Lo Cascio, 2013), stock markets (Aloui & Hkiri, 2014;Bogdanova & Ivanov, 2016;Fernández-Macho, 2012;Tiwari et al., 2015), energy market prices (Shahbaz et al., 2015;Sousa et al., 2014;Tiwari, 2013;Vacha & Barunik, 2012), fiscal sustainability (Lo Cascio, 2015), monetary and fiscal policy (Crowley & Hudgins, 2017, 2020Hudgins & Crowley, 2019), the synchronization of business and credit cycles (Kurowski & Rogowicz, 2018), the cohesion among euro area countries and within the US states (Rua & Lopes, 2015), the relationship between consumer and producer prices , the relationship between exchange rates and interest rates (Andrieș et al., 2014(Andrieș et al., , 2017, co-movements among macroeconomic assets (Abid & Kaffel, 2018) or the relationship between economic activity and financial stress (Ferrer et al., 2018), foreign direct investment (Ciesielska & Kołtuniak, 2017) and inequality (Chang et al., 2019). As stated by Gallegati et al. (2013), by allowing for different time scales of variation in the data, wavelets can provide a richer analysis of the relationships between variables with transient or non-stationary components, when compared to standard time-domain methods. ...
... The US stock market was a net volatility receiver in 2015 when oil prices historically plunged due to shale booming. Our findings are partially in line with Schmidbauer et al. (2016), who argue that Chinese and Russian stock markets contributed to the US stock market significantly. ...
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