Modeling the volatility of FTSE All Share Index Returns

We tested different GARCH models in modeling the volatility of stock returns in London Stock Exchange. The monthly returns of FTSE All Share Index during the period of February 1965 and October 2002 and GARCH, TGARCH, EGARCH, and AGARCH models have been used for the analysis.volatility modeling, GARCH, EGARCH, TGARCH, AGARCH

Econometric testing of the CAPM: A granger causality analysis on the Turkish banking industry

The CAPM suggests that stock returns are linearly dependent to the market returns. The only risk factor that an asset bears is the market risk which is captured by the asset's beta. But the CAPM equation does not say much about the causal relationship between market and asset returns. In order to test the validity of the CAPM equation, we have applied Granger causality tests. The causal relationship between the Istanbul Stock Exchange 100 index and banking sector stocks are examined through Granger tests. The data between 04.12.2007 and 04.12.2009 are used for the analysis. Overall we have found weak causal relationships between market and asset returns, therefore the CAPM is not an adequate model for the asset returns of Turkish banking stocks.CAPM; Granger causality; unit-root tests

A Vector Auto-Regressıve (VAR) Model for the Turkish Financial Markets

In this paper, we develop a vector autoregressive (VAR) model of the Turkish financial markets for the period of June 15 2006 – June 15 2010 and forecasts ISE100 index, TRY/USD exchange rate, and short-term interest rates. The out-of-sample forecast performance of the VAR model is compared with the results from the univariate models. Moreover, the dynamics of the financial markets are analyzed through Granger causality and impulse response analysis.multivariate financial time series; vector auto-regressive (VAR) model; impulse response analysis; Granger causality

Return, shock and volatility co-movements between the bond markets of Turkey and developed countries

In this study, we present a VAR-BEKK model to investigate the co-movements of long-term interest rates between Turkey and four developed (Germany, Japan, USA and UK) markets . We use weekly rates on the 5-year maturity government bonds for the period of February 10, 2006 to September 12, 2014 containing 448 observations. We empirically document that, while Turkish bond market is only correlated with Japanese and the US markets, there are strong ties between the returns and volatility of developed bond markets. Our findings indicate most of the movements in international government bond markets is a product of global risk factors rather than country specific factor

Return, shock and volatility co-movements between the bond markets of Turkey and developed countries

In this study, we present a VAR-BEKK model to investigate the co-movements of long-term interest rates between Turkey and four developed (Germany, Japan, USA and UK) markets . We use weekly rates on the 5-year maturity government bonds for the period of February 10, 2006 to September 12, 2014 containing 448 observations. We empirically document that, while Turkish bond market is only correlated with Japanese and the US markets, there are strong ties between the returns and volatility of developed bond markets. Our findings indicate most of the movements in international government bond markets is a product of global risk factors rather than country specific factor

Econometric testing of the CAPM: A granger causality analysis on the Turkish banking industry

The CAPM suggests that stock returns are linearly dependent to the market returns. The only risk factor that an asset bears is the market risk which is captured by the asset's beta. But the CAPM equation does not say much about the causal relationship between market and asset returns. In order to test the validity of the CAPM equation, we have applied Granger causality tests. The causal relationship between the Istanbul Stock Exchange 100 index and banking sector stocks are examined through Granger tests. The data between 04.12.2007 and 04.12.2009 are used for the analysis. Overall we have found weak causal relationships between market and asset returns, therefore the CAPM is not an adequate model for the asset returns of Turkish banking stocks

Modeling the volatility of FTSE All Share Index Returns

We tested different GARCH models in modeling the volatility of stock returns in London Stock Exchange. The monthly returns of FTSE All Share Index during the period of February 1965 and October 2002 and GARCH, TGARCH, EGARCH, and AGARCH models have been used for the analysis

Conditional Autoregregressive Range (CARR) Based Volatility Spillover Index For the Eurozone Markets

: We examine the volatility spillovers among major Eurozone countries employing the Diebold and Yilmaz (2012) model with time-varying conditional ranges generated from conditional autoregressive range (CARR) model of Chou (2005). The empirical findings, based on a data set covering a fifteen year period (1998-2013), suggest a total volatility spillover index in a very high degree. 74.9% of total volatility in the Eurozone markets is attributed to spillover effects from other markets. Moreover, rolling window analysis shows that volatility spillover index is relatively higher during the turmoil periods

Continuous time modeling of interest rates: An empirical study on the Turkish short rate

We proposed a continuous time ARMA known as CARMA(p,q) model for modeling the interest rate dynamics. CARMA(p,q) models have an advantage over their discrete time counterparts that they allow using Ito formulas and provide closed-form solutions for bond and bond option prices. We demonstrate the capabilities of CARMA(p,q) models by using Turkish short rate. The Turkish Republic Central Bank’s benchmark bond prices are used to calculate short-term interest rates between the period of 15.07.2006 and 15.07.2008. ARMA(1,1) model and CARMA(1,0) model are chosen as best suitable models in modeling the Turkish short rate

Conditional Autoregregressive Range (CARR) Based Volatility Spillover Index For the Eurozone Markets

: We examine the volatility spillovers among major Eurozone countries employing the Diebold and Yilmaz (2012) model with time-varying conditional ranges generated from conditional autoregressive range (CARR) model of Chou (2005). The empirical findings, based on a data set covering a fifteen year period (1998-2013), suggest a total volatility spillover index in a very high degree. 74.9% of total volatility in the Eurozone markets is attributed to spillover effects from other markets. Moreover, rolling window analysis shows that volatility spillover index is relatively higher during the turmoil periods