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    <title>Forecasting and Simulation</title>
    <link>http://repub.eur.nl/res/concept/jel-E47/</link>
    <description>Recent publications classified by JEL Code E47</description>
    <language>en</language>
    <image>
      <url>http://repub.eur.nl/static-eur/img/logo.png</url>
      <title>RePub, Erasmus University Rotterdam</title>
      <link>http://repub.eur.nl</link>
    </image>
    <item>
      <title>Prediction Bias Correction
for Dynamic Term Structure Models (Research Paper)</title>
      <link>http://repub.eur.nl/res/pub/39191/</link>
      <pubDate>2013-03-07T00:00:00Z</pubDate>
      <description>
        
        
      </description>
      <author>Raviv, E.</author>
    </item> <item>
      <title>Predicting the Term Structure of Interest Rates: Incorporating parameter uncertainty, model uncertainty and macroeconomic information (Research Paper)</title>
      <link>http://repub.eur.nl/res/pub/9148/</link>
      <pubDate>2007-03-03T00:00:00Z</pubDate>
      <description>
        
        We forecast the term structure of U.S. Treasury zero-coupon bond yields by analyzing a range of models that have been used in the literature. We assess the relevance of parameter uncertainty by examining the added value of using Bayesian inference compared to frequentist estimation techniques, and model uncertainty by combining forecasts from individual models. Following current literature we also investigate the benefits of incorporating macroeconomic information in yield curve models. Our results show that adding macroeconomic factors is very beneficial for improving the out-of-sample forecasting performance of individual models. Despite this, the predictive accuracy of models varies over time considerably, irrespective of using the Bayesian or frequentist approach. We show that mitigating model uncertainty by combining forecasts leads to substantial gains in forecasting performance, especially when applying Bayesian model averaging.
      </description>
      <author>Pooter, M.D. de</author> <author>Ravazzolo, F.</author> <author>Dijk, D.J.C. van</author>
    </item> <item>
      <title>Essays on the Dynamic Portfolio Choice (Doctoral Thesis)</title>
      <link>http://repub.eur.nl/res/pub/7994/</link>
      <pubDate>2006-10-06T00:00:00Z</pubDate>
      <description>
        
        Anna Gutkowska obtained Masters Degrees in Quantitative Methods and in Finance and Banking at the Warsaw School of Economics, Poland. In October 1998 she joined the Econometric Institute at the Warsaw School of Economics. In 2001 she started the Ph.D. programme at the Erasmus Research Institute of Management (ERIM). Since February 2005 she has been working as an Assistant Professor in the Econometric Institute at the Warsaw School of Economics.
      </description>
      <author>Gutkowska, A.B.</author>
    </item> <item>
      <title>Pricing Models for Bermudan-Style Interest Rate Derivatives (Doctoral Thesis)</title>
      <link>http://repub.eur.nl/res/pub/7122/</link>
      <pubDate>2005-12-08T00:00:00Z</pubDate>
      <description>
        
        Bermuda-stijl rente derivaten vormen een belangrijke klasse van opties. Veel bancaire en verzekeringsproducten, zoals hypotheken, vervroegd aflosbare obligaties, en levensverzekeringen, bevatten Bermuda rente opties, die een gevolg zijn van de mogelijkheid tot vervroegde terugbetaling of stopzetting van het contract. Het veel voorkomen van deze opties maakt duidelijk dat het belangrijk is, voor banken en verzekeraars, om de waarde en risico van deze producten op de juiste manier in te schatten. Het juist inschatten van het risico maakt het mogelijk om markt risico af te dekken met onderliggende en regelmatig verhandelde waardes en opties. Waarderingsmodellen moeten arbitrage-vrij zijn, en dienen gekalibreerd te zijn aan prijzen van actief verhandelde onderliggende opties. De dynamica van de modellen moet overeen komen met de geobserveerde dynamica van de rente-termijnstructuur, zoals bijvoorbeeld correlatie tussen rentestanden. Bovendien moeten waarderingsalgoritmes efficiënt zijn: Financiële beslissingen gebaseerd op derivaten waarderingsberekeningen worden veeleer binnen enkele seconden genomen, dan binnen uren of dagen. In recente jaren is een succesvolle klasse van modellen naar voren gekomen, genaamd markt modellen. Dit proefschrift breidt de theorie van markt modellen uit, door: (i) een nieuwe, efficiënte en meer nauwkeurige benaderende waarderingstechniek te introduceren, (ii) twee nieuwe en snelle algoritmes voor correlatie-kalibratie te presenteren, (iii) nieuwe modellen te ontwikkelen die een efficiënte kalibratie toestaan voor een hele nieuwe klasse van derivaten, zoals vaste-looptijd Bermuda rente opties, en (iv) nieuwe empirische vergelijkingen te presenteren van bestaande kalibratie technieken en modellen, in termen van reductie van risico.
      </description>
      <author>Pietersz, R.</author>
    </item> <item>
      <title>Inflation, Forecast Intervals and Long Memory Regression Models (Research Paper)</title>
      <link>http://repub.eur.nl/res/pub/6874/</link>
      <pubDate>2001-02-23T00:00:00Z</pubDate>
      <description>
        
        We examine recursive out-of-sample forecasting of monthly postwar U.S. core inflation and log price levels. We use the autoregressive fractionally integrated moving average model with explanatory variables (ARFIMAX). Our analysis suggests a significant explanatory power of leading indicators associated with macroeconomic activity and monetary conditions for forecasting horizons up to two years. Even after correcting for the effect of explanatory variables, there is conclusive evidence of both fractional integration and structural breaks in the mean and variance of inflation in the 1970s and 1980s and we incorporate these breaks in the forecasting model for the 1980s and 1990s. We compare the results of the fractionally integrated ARFIMA(0,d,0) model with those for ARIMA(1,d,1) models with fixed order of d=0 and d=1 for inflation. Comparing mean squared forecast errors, we find that the ARMA(1,1) model performs worse than the other models over our evaluation period 1984-1999. The ARIMA(1,1,1) model provides the best forecasts, but its multi-step forecast intervals are too large.
      </description>
      <author>Bos, C.S.</author> <author>Franses, Ph.H.B.F.</author> <author>Ooms, M.</author>
    </item> <item>
      <title>On the Variation of Hedging Decisions in Daily Currency Risk Management (Research Paper)</title>
      <link>http://repub.eur.nl/res/pub/6877/</link>
      <pubDate>2001-02-08T00:00:00Z</pubDate>
      <description>
        
        Internationally operating firrns naturally face the decision whether or not to hedge the currency risk implied by foreign investments. In a recent paper, Bos, Mahieu and van Dijk (2000) evaluate the returns from optimal and alternative currency hedging strategies, for a series of 7 models, using Bayesian inference and decision analysis. The models differ in the way time-varying means, variances or the unconditional error distributions are incorporated. In this extension, we compare the hedging decisions and financial returns and utilities as they result from the modelling assumptions and the attitudes towards risk.
      </description>
      <author>Bos, C.S.</author> <author>Mahieu, R.J.</author> <author>Dijk, H.K. van</author>
    </item> <item>
      <title>Daily Exchange Rate Behaviour and Hedging of Currency Risk (Research Paper)</title>
      <link>http://repub.eur.nl/res/pub/6878/</link>
      <pubDate>2001-02-08T00:00:00Z</pubDate>
      <description>
        
        We construct models which enable a decision-maker to analyze the implications of typical time series patterns of daily exchange rates for currency risk management. Our approach is Bayesian where extensive use is made of Markov chain Monte Carlo methods. The effects of several model characteristics (unit roots, GARCH, stochastic volatility, heavy tailed disturbance densities) are investigated in relation to the hedging strategies. Consequently, we can make a distinction between statistical relevance of model specifications, and the economic consequences from a risk management point of view. We compute payoffs and utilities from several alternative hedge strategies. The results indicate that modelling time varying features of exchange rate returns may lead to improved hedge behaviour within currency overlay management.
      </description>
      <author>Bos, C.S.</author> <author>Mahieu, R.J.</author> <author>Dijk, H.K. van</author>
    </item>
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