This paper shows how existing band-pass filtering techniques and their extension can be applied to the common current-analysis problem of estimating current trends or cycles.
An effective technique governments use to evaluate the desirability of different financing strategies involves stochastic simulation. This approach requires the postulation of the future dynamics of key macroeconomic variables and the use of those variables in the construction of a debt charge distribution for each individual financing strategy.
The exponential family, relative entropy, and distortion are methods of transforming probability distributions. We establish a link between those methods, focusing on the relation between relative entropy and distortion.
Wavelets are mathematical expansions that transform data from the time domain into different layers of frequency levels. Compared to standard Fourier analysis, they have the advantage of being localized both in time and in the frequency domain, and enable the researcher to observe and analyze data at different scales.
This paper examines asset allocation strategies in an extreme value at risk (VaR) framework in which the risk measure is the p-quantile from the extreme value distribution. The main focus is on the allocation problem faced by an extremely risk-averse institution, such as a central bank.
This paper uses a smooth transition error-correction model (STECM) to model the one-year and five-year mortgage rate changes. The model allows for a non-linear adjustment process of mortgage rates towards their long-run equilibrium.
This paper describes a new test for evaluating conditional density functions that remains valid when the data are time-dependent and that is therefore applicable to forecasting problems. We show that the test statistic is asymptotically distributed standard normal under the null hypothesis, and diverges to infinity when the null hypothesis is false.
This paper evaluates the forecasting performance of factor models for Canadian inflation. This type of model was introduced and examined by Stock and Watson (1999a), who have shown that it is quite promising for forecasting U.S. inflation.
Affine models describe the stylized time-series properties of the term structure of interest rates in a reasonable manner, they generalize relatively easily to higher dimensions, and a vast academic literature exists relating to their implementation. This combination of characteristics makes the affine class a natural introductory point for modelling interest rate dynamics.