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Essays on multivariate volatility and dependence models for financial time seriesNoureldin, Diaa January 2011 (has links)
This thesis investigates the modelling and forecasting of multivariate volatility and dependence in financial time series. The first paper proposes a new model for forecasting changes in the term structure (TS) of interest rates. Using the level, slope and curvature factors of the dynamic Nelson-Siegel model, we build a time-varying copula model for the factor dynamics allowing for departure from the normality assumption typically adopted in TS models. To induce relative immunity to structural breaks, we model and forecast the factor changes and not the factor levels. Using US Treasury yields for the period 1986:3-2010:12, our in-sample analysis indicates model stability and we show statistically significant gains due to allowing for a time-varying dependence structure which permits joint extreme factor movements. Our out-of-sample analysis indicates the model's superior ability to forecast the conditional mean in terms of root mean square error reductions and directional forecast accuracy. The forecast gains are stronger during the recent financial crisis. We also conduct out-of-sample model evaluation based on conditional density forecasts. The second paper introduces a new class of multivariate volatility models that utilizes high-frequency data. We discuss the models' dynamics and highlight their differences from multivariate GARCH models. We also discuss their covariance targeting specification and provide closed-form formulas for multi-step forecasts. Estimation and inference strategies are outlined. Empirical results suggest that the HEAVY model outperforms the multivariate GARCH model out-of-sample, with the gains being particularly significant at short forecast horizons. Forecast gains are obtained for both forecast variances and correlations. The third paper introduces a new class of multivariate volatility models which is easy to estimate using covariance targeting. The key idea is to rotate the returns and then fit them using a BEKK model for the conditional covariance with the identity matrix as the covariance target. The extension to DCC type models is given, enriching this class. We focus primarily on diagonal BEKK and DCC models, and a related parameterisation which imposes common persistence on all elements of the conditional covariance matrix. Inference for these models is computationally attractive, and the asymptotics is standard. The techniques are illustrated using recent data on the S&P 500 ETF and some DJIA stocks, including comparisons to the related orthogonal GARCH models.
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Measuring treatment effects in poverty alleviation programs : three essays using data from Turkish household surveysAran, Meltem A. January 2012 (has links)
The dissertation is a compilation of three essays on Turkey's poverty alleviation programs. The first paper focuses on the welfare impact of the global financial Crisis on Turkish households. The second paper considers the protective impact of the Green Card non-contributory health insurance program in Turkey during the Crisis in 2008-2009. The third paper uses experimental data from the field in eastern Turkey, to look at patterns of agricultural technology diffusion in a rural development program implemented in a post-conflict setting.
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Inflation expectations, labour markets and EMUCurto Millet, Fabien January 2007 (has links)
This thesis examines the measurement, applications and properties of consumer inflation expectations in the context of eight European Union countries: France, Germany, the UK, Spain, Italy, Belgium, the Netherlands and Sweden. The data proceed mainly from the European Commission's Consumer Survey and are qualitative in nature, therefore requiring quantification prior to use. This study first seeks to determine the optimal quantification methodology among a set of approaches spanning three traditions, associated with Carlson-Parkin (1975), Pesaran (1984) and Seitz (1988). The success of a quantification methodology is assessed on the basis of its ability to match quantitative expectations data and on its behaviour in an important economic application, namely the modelling of wages for our sample countries. The wage equation developed here draws on the theoretical background of the staggered contracts and the wage bargaining literature, and controls carefully for inflation expectations and institutional variables. The Carlson-Parkin variation proposed in Curto Millet (2004) was found to be the most satisfactory. This being established, the wage equations are used to test the hypothesis that the advent of EMU generated an increase in labour market flexibility, which would be reflected in structural breaks. The hypothesis is essentially rejected. Finally, the properties of inflation expectations and perceptions themselves are examined, especially in the context of EMU. Both the rational expectations and rational perceptions hypotheses are rejected. Popular expectations mechanisms, such as the "rule-of-thumb" model or Akerlof et al.'s (2000) "near-rationality hypothesis" are similarly unsupported. On the other hand, evidence is found for the transmission of expert forecasts to consumer expectations in the case of the UK, as in Carroll's (2003) model. The distribution of consumer expectations and perceptions is also considered, showing a tendency for gradual (as in Mankiw and Reis, 2002) but non-rational adjustment. Expectations formation is further shown to have important qualitative features.
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