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Full-Text Articles in Applied Statistics
Garch Modeling Of Value At Risk And Expected Shortfall Using Bayesian Model Averaging, Ismail Kheir
Garch Modeling Of Value At Risk And Expected Shortfall Using Bayesian Model Averaging, Ismail Kheir
Theses and Dissertations
This thesis conducts Value at Risk (VaR) and Expected Shortfall (ES) estimation using GARCH modeling and Bayesian Model Averaging (BMA). BMA considers multiple models weighted by some information criterion. Through BMA, this thesis finds that VaR and ES estimates can be improved through enhanced modeling of the data generation process.
Asimmetria Del Rischio Sistematico Dei Titolo Immobiliari Americani: Nuove Evidenze Econometriche, Paola De Santis, Carlo Drago
Asimmetria Del Rischio Sistematico Dei Titolo Immobiliari Americani: Nuove Evidenze Econometriche, Paola De Santis, Carlo Drago
Carlo Drago
In questo lavoro riscontriamo un aumento del rischio sistematico dei titoli del mercato immobiliare americano nell’anno 2007 seguito da un ritorno ai valori iniziali nell’anno 2009 e si evidenzia la possibile presenza di break strutturali. Per valutare il suddetto rischio sistematico è stato scelto il modello a tre fattori di Fama e French ed è stata studiata la relazione tra l’extra rendimento dell’indice REIT, utilizzato come proxy dell’andamento dei titoli immobiliari americani, e l’extra rendimento dell’indice S&P500 rappresentativo del rendimento del portafoglio di mercato. I risultati confermano la presenza di un “Asymmetric REIT Beta Puzzle” coerentemente con alcuni precedenti studi …
Time Series, Unit Roots, And Cointegration: An Introduction, Lonnie K. Stevans
Time Series, Unit Roots, And Cointegration: An Introduction, Lonnie K. Stevans
Lonnie K. Stevans
The econometric literature on unit roots took off after the publication of the paper by Nelson and Plosser (1982) that argued that most macroeconomic series have unit roots and that this is important for the analysis of macroeconomic policy. Yule (1926) suggested that regressions based on trending time series data can be spurious. This problem of spurious correlation was further pursued by Granger and Newbold (1974) and this also led to the development of the concept of cointegration (lack of cointegration implies spurious regression). The pathbreaking paper by Granger (1981), first presented at a conference at the University of Florida …