Credit risk models should reflect the observation that the relevant value of collateral is generally not the average value of the asset over all possible states of nature. In most cases, the relevant value of collateral for the lender is its secondary market value in bad states of nature, where...

See the article in <I>The North American Journal of Economics and Finance</I> (2013). Volume 26(C), pages 217-226.<P> Research papers in empirical finance and financial econometrics are among the most widely cited, downloaded and viewed articles in the discipline of Finance. The special issue presents...</p></i>

Accurate prediction of risk measures such as Value at Risk (VaR) and Expected Shortfall (ES) requires precise estimation of the tail of the predictive distribution. Two novel concepts are introduced that offer a specific focus on this part of the predictive density: the censored posterior, a...

We analyze earnings forecasts retrieved from the I/B/E/S database concerning 596 firms for the sample 1995 to 2011, with a specific focus on whether these earnings forecasts can be predicted from available data. Our main result is that earnings forecasts can be predicted quite accurately using...

See the publication in <I>Econometrics</I> (2013). Volume 1(1), pages 115-126.<P> The purpose of the paper is to discuss ten things potential users should know about the limits of the Dynamic Conditional Correlation (DCC) representation for estimating and forecasting time-varying conditional correlations....</p></i>

When the yield curve is modelled using an affine factor model, residuals may still contain relevant information and do not adhere to the familiar white noise assumption.This paper proposes a pragmatic way to improve out of sample performance for yield curve forecasting. The proposed adjustment...

See also the publication J.G. de Gooijer, C.G.H. Diks & L.T. Gatarek, 2012, 'Information flows around the globe: predicting opening gaps from overnight foreign stock price patterns', <I>Central European Journal of Economic Modelling and Econometrics</I>, 4(1), 23-44.<P> This paper describes a forecasting...</p></i>

An analysis of about 300000 earnings forecasts, created by 18000 individual forecasters for earnings of over 300 S&P listed firms, shows that these forecasts are predictable to a large extent using a statistical model that includes publicly available information. When we focus on the...

The purpose of the paper is to discuss ten things potential users should know about the limits of the Dynamic Conditional Correlation (DCC) representation for estimating and forecasting time-varying conditional correlations. The reasons given for caution about the use of DCC include the...

We propose a modeling framework which allows for creating probability predictions on a future market crash in the medium term, like sometime in the next five days. Our framework draws upon noticeable similarities between stock returns around a financial market crash and seismic activity around...