Pricing-to-market using EGARCH-error correction model

In this paper, the authors use an exponential generalized autoregressive conditional heteroscedastic (EGARCH) error-correction model (ECM), that is, EGARCH-ECM, to estimate the pass-through effects of foreign exchange (FX) rates and producers’ prices for 20 U.K. export sectors. The long-run adjustment of export prices to FX rates and producers’ prices is within the range of -1.02% (for the Textiles sector) and -17.22% (for the Meat sector). The contemporaneous pricing-to-market (PTM) coefficient is within the range of -72.84% (for the Fuels sector) and -8.05% (for the Textiles sector). Short-run FX rate pass-through is not complete even after several months. Rolling EGARCH-ECMs show that the short and long-run effects of FX rate and producers’ prices fluctuate substantially as are asymmetry and volatility estimates before equilibrium is achieved.

Previsão da volatilidade no mercado interbancário de câmbio

O artigo apresenta um estudo comparativo da capacidade preditiva dos modelos EWMA, GARCH (1,1), EGARCH (1,1) e TARCH (1,1), quando utilizados para prever a volatilidade das taxas de câmbio praticadas no mercado interbancário brasileiro. A amostra é composta pelas cotações diárias de fechamento da taxa de câmbio real/dólar estadunidense observadas no período de 20 de agosto de 2001 a 30 de setembro de 2003. Os resultados demonstraram que o modelo TARCH (1,1) apresentou o melhor desempenho preditivo para o período, acompanhado de perto pelo modelo EGARCH (1,1), seguindo-se o modelo GARCH (1,1) e, por último, o modelo EWMA. Constatou-se também que todos os modelos revelaram uma propensão a superestimar a volatilidade futura, e que a Clearing de Câmbio da BM&F atua de forma excessivamente conservadora e subjetiva na definição dos índices de variação da taxa de câmbio contratualmente garantidos e, conseqüentemente, na exigência de garantias.

The problem of estimating the volatility of zero coupon bond interest rate

Financial literature and financial industry use often zero coupon yield curves as input for testing hypotheses, pricing assets or managing risk. They assume this provided data as accurate. We analyse implications of the methodology and of the sample selection criteria used to estimate the zero coupon bond yield term structure on the resulting volatility of spot rates with different maturities. We obtain the volatility term structure using historical volatilities and Egarch volatilities. As input for these volatilities we consider our own spot rates estimation from GovPX bond data and three popular interest rates data sets: from the Federal Reserve Board, from the US Department of the Treasury (H15), and from Bloomberg. We find strong evidence that the resulting zero coupon bond yield volatility estimates as well as the correlation coefficients among spot and forward rates depend significantly on the data set. We observe relevant differences in economic terms when volatilities are used to price derivatives.

Assimetria na volatilidade dos mercados de acções

Mestrado em Controlo e Gestão dos Negócios

Assimetria na volatilidade dos principais índices bolsistas de Portugal, Irlanda, Itália, Grécia e Espanha : um estudo comparativo

Mestrado em Controlo de Gestão e dos Negócios

A proposal for a new specification for a conditionally heteroskedastic variance model: the Quadratic Moving-Average Conditional Heteroskedasticity and an application to the D. Mark-U.S. dollar Exchange Rate

Ever since the appearance of the ARCH model [Engle(1982a)], an impressive array of variance specifications belonging to the same class of models has emerged [i.e. Bollerslev's (1986) GARCH; Nelson's (1990) EGARCH]. This recent domain has achieved very successful developments. Nevertheless, several empirical studies seem to show that the performance of such models is not always appropriate [Boulier(1992)]. In this paper we propose a new specification: the Quadratic Moving Average Conditional heteroskedasticity model. Its statistical properties, such as the kurtosis and the symmetry, as well as two estimators (Method of Moments and Maximum Likelihood) are studied. Two statistical tests are presented, the first one tests for homoskedasticity and the second one, discriminates between ARCH and QMACH specification. A Monte Carlo study is presented in order to illustrate some of the theoretical results. An empirical study is undertaken for the DM-US exchange rate.

The determination of EONIA rate: The impact of the financial crisis and the effects of the changes in the monetary policy implementation framework

EONIA is a market based overnight interest rate, whose role as the starting point of the yield curve makes it critical from the perspective of the implementation of European Central Bank´s common monetary policy in the euro area. The financial crisis that started in 2007 had a large impact on the determination mechanism of this interest rate, which is considered as the central bank´s operational target. This thesis examines the monetary policy implementation framework of the European Central Bank and changes made to it. Furthermore, we discuss the development of the recent turmoil in the money market. EONIA rate is modelled by means of a regression equation using variables related to liquidity conditions, refinancing need, auction results and calendar effects. Conditional volatility is captured by an EGARCH model, and autocorrelation is taken into account by employing an autoregressive structure. The results highlight how the tensions in the initial stage of the market turmoil were successfully countered by ECB´s liquidity policy. The subsequent response of EONIA to liquidity conditions under the full allotment liquidity provision procedure adopted after the demise of Lehman Brothers is also established. A clear distinction in the behavior of the interest rate between the sub-periods was evident. In the light of the results obtained, some of the challenges posed by the exit-strategy implementation will be addressed.

The Impact of European Macroeconomic News Announcements on CIVETS Stock Markets

The purpose of this research is to investigate how CIVETS (Colombia, Indonesia, Vietnam, Egypt, Turkey and South Africa) stock markets are integrated with Europe as measured by the impact of euro area (EA) scheduled macroeconomic news announcements, which are related to macroeconomic indicators that are commonly used to indicate the direction of the economy. Macroeconomic announcements used in this study can be divided into four categories; (1) prices, (2) real economy, (3) money supply and (4) business climate and consumer confidence. The data set consists of daily market data from CIVETS and scheduled macroeconomic announcements from the EA for the years 2007-2012. The econometric model used in this research is Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH). Empirical results show diverse impacts of macroeconomic news releases and surprises for different categories of news supporting the perception of heterogeneity among CIVETS. The analyses revealed that in general EA macroeconomic news releases and surprises affect stock market volatility in CIVETS and only in some cases asset pricing. In conclusion, all CIVETS stock markets reacted to the incoming EA macroeconomic news suggesting market integration to some extent. Thus, EA should be considered as a possible risk factor when investing in CIVETS.

Idiosyncratic volatility around information release date

Several papers document idiosyncratic volatility is time-varying and many attempts have been made to reveal whether idiosyncratic risk is priced. This research studies behavior of idiosyncratic volatility around information release dates and also its relation with return after public announcement. The results indicate that when a company discloses specific information to the market, firm’s specific volatility level shifts and short-horizon event-induced volatility vary significantly however, the category to which the announcement belongs is not important in magnitude of change. This event-induced volatility is not small in size and should not be downplayed in event studies. Moreover, this study shows stocks with higher contemporaneous realized idiosyncratic volatility earn lower return after public announcement consistent with “divergence of opinion hypothesis”. While no significant relation is found between EGARCH estimated idiosyncratic volatility and return and also between one-month lagged idiosyncratic volatility and return presumably due to significant jump around public announcement both may provide some signals regarding future idiosyncratic volatility through their correlations with contemporaneous realized idiosyncratic volatility. Finally, the study show that positive relation between return and idiosyncratic volatility based on under-diversification is inadequate to explain all different scenarios and this negative relation after public announcement may provide a useful trading rule.

Alhaisen volatiliteetin sekä korkean idiosynkraattisen riskin anomaliat Suomen osakemarkkinoilla institutionaalisen sijoittajan näkökulmasta

Alhaisen volatiliteetin anomalian mukaan sijoittajan on mahdollista saada korkeaa tuottoa alhaisella riskillä, mikä on sijoitusstrategina mielenkiintoinen, koska modernin rahoitusteorian mukaan korkeat tuotot saavutetaan vain riskiä kasvattamalla. Tässä tutkielmassa selvitettiin alhaisen volatiliteetin ja korkean idiosynkraattisen riskin anomalioiden olemassaoloa Suomen osakemarkkinoilla sekä institutionaalisen sijoittajan mahdollisuuksia hyödyntää tutkittuja anomalioita. Tutkimusaineisto large cap -osakkeilla vuosilta 2000-2013 osoittaa, että sijoittamalla alhaisen volatiliteetin osakkeisiin sijoittaja on pystynyt voittamaan absoluuttisella tuotolla mitattuna OMXH CAP-indeksin, muttei saavuttamaan riskikorjattuja ylituottoja. Alhaisen volatiliteetin osakkeiden suoriutumista on selitetty useilla tekijöillä kuten sijoittajien irrationaalisella käyttäytymisellä näiden suosiessa korkean volatiliteetin osakkeita painaen alas samalla näiden tuottopotentiaalia. Toiseksi, alhaisen volatiliteetin yrityksillä on vahvat fundamentit, joiden myötä liikevoitto sekä tulos pysyvät vahvoina, joka näkyy puolestaan hyvinä osaketuottoina. Lisäksi, institutionaaliselle sijoittajalle muodostuu esteitä sijoittaa vain alhaisen volatiliteetin osakkeisiin, mikä osaltaan estää anomalian pois pyyhkiytymisen. Idiosynkraattisen riskin anomaliaa ei voitu todentaa käytettäessä FF3-mallin residuaaleja. Anomaliaa tutkittiin historiallista sekä EGARCH-mallilla ennustettua idiosynkraattista riskiä käyttäen.

Margin requirements and volatility : evidence from Canadian stocks

Margin policy is used by regulators for the purpose of inhibiting exceSSIve volatility and stabilizing the stock market in the long run. The effect of this policy on the stock market is widely tested empirically. However, most prior studies are limited in the sense that they investigate the margin requirement for the overall stock market rather than for individual stocks, and the time periods examined are confined to the pre-1974 period as no change in the margin requirement occurred post-1974 in the U.S. This thesis intends to address the above limitations by providing a direct examination of the effect of margin requirement on return, volume, and volatility of individual companies and by using more recent data in the Canadian stock market. Using the methodologies of variance ratio test and event study with conditional volatility (EGARCH) model, we find no convincing evidence that change in margin requirement affects subsequent stock return volatility. We also find similar results for returns and trading volume. These empirical findings lead us to conclude that the use of margin policy by regulators fails to achieve the goal of inhibiting speculating activities and stabilizing volatility.

The Shape of the Risk Premium: Evidence from a Semiparametric Garch Model.

We examine the relationship between the risk premium on the S&P 500 index return and its conditional variance. We use the SMEGARCH - Semiparametric-Mean EGARCH - model in which the conditional variance process is EGARCH while the conditional mean is an arbitrary function of the conditional variance. For monthly S&P 500 excess returns, the relationship between the two moments that we uncover is nonlinear and nonmonotonic. Moreover, we find considerable persistence in the conditional variance as well as a leverage effect, as documented by others. Moreover, the shape of these relationships seems to be relatively stable over time.

Gamma stochastic volatility models

This paper presents gamma stochastic volatility models and investigates its distributional and time series properties. The parameter estimators obtained by the method of moments are shown analytically to be consistent and asymptotically normal. The simulation results indicate that the estimators behave well. The insample analysis shows that return models with gamma autoregressive stochastic volatility processes capture the leptokurtic nature of return distributions and the slowly decaying autocorrelation functions of squared stock index returns for the USA and UK. In comparison with GARCH and EGARCH models, the gamma autoregressive model picks up the persistence in volatility for the US and UK index returns but not the volatility persistence for the Canadian and Japanese index returns. The out-of-sample analysis indicates that the gamma autoregressive model has a superior volatility forecasting performance compared to GARCH and EGARCH models.

Benchmarks and the accuracy of GARCH model estimation

This paper reviews nine software packages with particular reference to their GARCH model estimation accuracy when judged against a respected benchmark. We consider the numerical consistency of GARCH and EGARCH estimation and forecasting. Our results have a number of implications for published research and future software development. Finally, we argue that the establishment of benchmarks for other standard non-linear models is long overdue.