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27 Results

Estimating Systematic Risk Under Extremely Adverse Market Conditions

Staff Working Paper 2016-22 Maarten van Oordt, Chen Zhou
This paper considers the problem of estimating a linear model between two heavy-tailed variables if the explanatory variable has an extremely low (or high) value. We propose an estimator for the model coefficient by exploiting the tail dependence between the two variables and prove its asymptotic properties.

Early Warning of Financial Stress Events: A Credit-Regime-Switching Approach

Staff Working Paper 2016-21 Fuchun Li, Hongyu Xiao
We propose an early warning model for predicting the likelihood of a financial stress event for a given future time, and examine whether credit plays an important role in the model as a non-linear propagator of shocks.

Testing for the Diffusion Matrix in a Continuous-Time Markov Process Model with Applications to the Term Structure of Interest Rates

Staff Working Paper 2015-17 Fuchun Li
The author proposes a test for the parametric specification of each component in the diffusion matrix of a d-dimensional diffusion process. Overall, d (d-1)/2 test statistics are constructed for the off-diagonal components, while d test statistics are constructed for the main diagonal components.

Bootstrap Tests of Mean-Variance Efficiency with Multiple Portfolio Groupings

Staff Working Paper 2014-51 Sermin Gungor, Richard Luger
We propose double bootstrap methods to test the mean-variance efficiency hypothesis when multiple portfolio groupings of the test assets are considered jointly rather than individually.

Predicting Financial Stress Events: A Signal Extraction Approach

Staff Working Paper 2014-37 Ian Christensen, Fuchun Li
The objective of this paper is to propose an early warning system that can predict the likelihood of the occurrence of financial stress events within a given period of time. To achieve this goal, the signal extraction approach proposed by Kaminsky, Lizondo and Reinhart (1998) is used to monitor the evolution of a number of economic indicators that tend to exhibit an unusual behaviour in the periods preceding a financial stress event.

Volatility Forecasting when the Noise Variance Is Time-Varying

Staff Working Paper 2013-48 Selma Chaker, Nour Meddahi
This paper explores the volatility forecasting implications of a model in which the friction in high-frequency prices is related to the true underlying volatility. The contribution of this paper is to propose a framework under which the realized variance may improve volatility forecasting if the noise variance is related to the true return volatility.

Volatility and Liquidity Costs

Staff Working Paper 2013-29 Selma Chaker
Observed high-frequency prices are contaminated with liquidity costs or market microstructure noise. Using such data, we derive a new asset return variance estimator inspired by the market microstructure literature to explicitly model the noise and remove it from observed returns before estimating their variance.

A Semiparametric Early Warning Model of Financial Stress Events

Staff Working Paper 2013-13 Ian Christensen, Fuchun Li
The authors use the Financial Stress Index created by the International Monetary Fund to predict the likelihood of financial stress events for five developed countries: Canada, France, Germany, the United Kingdom and the United States.
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