We suggest a robust form of conditional moment test as a constructive test for functional misspecification in multiplicative error models. The proposed test has power solely against violations of the conditional mean restriction but is not affected by any other type of model misspecification....

This paper proposes a method for comparing and combining conditional quantile forecasts based on the principle of 'encompassing'. Our test for conditional quantile forecast encompassing (CQFE) is a test of superior predictive ability, constructed as a Wald-type test on the coefficients of an...

Nowcasting methods have become a crucial tool for central banks and investors due to their timeliness and ability to make 'on the spot' predictions. However, despite their popularity, there has been little research into statistical methods for the comparison of different nowcasts across multiple...

The development of new tests and methods used in the evaluation of time series forecasts and forecasting models remains as important today as it has for the last 50 years. Paraphrasing what Sir Clive W.J. Granger (arguably the father of modern day time series forecasting) said in the 1990s at a...

This paper proposes a test to determine whether `big data' nowcasting methods, which have become an important tool to many public and private institutions, are monotonically improving as new information becomes available. The test is the first to formalise existing evaluation procedures from the...

The purpose of this paper is to investigate whether a dynamic Value at Risk model and high frequency realized volatility models can improve the accuracy of 1-day ahead VaR forecasting beyond the performance of frequently used models. As such, this paper constructs 60 conditional volatility...

It is widely known that significant in-sample evidence of predictability does not guarantee significant out-of-sample predictability. This is often interpreted as an indication that in-sample evidence is likely to be spurious and should be discounted. In this paper we question this conventional...

This paper proposes and analyzes tests that can be used to compare the accuracy of alternative conditional density forecasts of a variable. The tests are also valid in the broader context of model selection based on out-of-sample predictive ability. We restrict attention to the case of density...

We propose new scoring rules based on partial likelihood for assessing the relative out-of-sample predictive accuracy of competing density forecasts over a specific region of interest, such as the left tail in financial risk management. By construction, existing scoring rules based on weighted...

We present a hybrid model for diagnosis and critical time forecasting of real estate bubbles. The model combines two elements: 1) the Log Periodic Power Law (LPPL) model to describe endogenous price dynamics originated from positive feedback loops between economic agents; and 2) a diffusion...