It is well-know that estimation by reduced rank regression is given by the solution to a generalized eigenvalue problem. This paper presents a new proof to establish this result and provides additional insight into the structure of the estimation problem. The proof is a direct algebraic proof that some might find more intuitive than existing proofs. JEL Classification: C3, C32

A Bayesian Analysis of a Variance Decomposition for Stock Returns We apply Bayesian methods to study a common VAR-based approach for decomposing the variance of excess stock returns into components reflecting news about future excess stock returns, future real interest rates, and future dividends. We develop a new prior elicitation strategy which involves expressing beliefs about the components...

in this research, potential effects of oil and monetary policy shocks on economic growth of iran are examined and share of each of them on economic growth are calculated during 1974-2006 period and potential mutual effects of those shocks by using the vector auto regressive (var) model are analysed. results of this research show that oil shocks significantly affected the economic growth in iran...

Structural vector autoregressive (SVAR) models have emerged as a dominant research strategy in empirical macroeconomics, but suffer from the large number of parameters employed and the resulting estimation uncertainty associated with their impulse responses. In this paper we propose general-to-specific model selection procedures to overcome these limitations. After showing that single-equation ...

Article history: Received 11 January 2006 Received in revised form 31 July 2008 Accepted 1 August 2008 Available online 6 August 2008 This paper considers the problem of model uncertainty in the case of multi-asset volatility models and discusses the use of model averaging techniques as away of dealing with the risk of inadvertently using false models in portfolio management. Evaluation of vola...

This paper provides new empirical evidence that bears on the efficacy of unconventional monetary policies when main policy rate is negative. When a negative interest (NIRP) deployed in concert with forward guidance (FG) and quantitative easing (QE), identification impacts these instruments challenging. We propose novel approach seeks to overcome this challenge by combining dense, controlled eve...

ARCH and GARCH models are widely used to model financial market volatilities in risk management applications. Considering a GARCH model with heavy-tailed innovations, we characterize the limiting distribution of an estimator of the conditional Value-at-Risk (VaR), which corresponds to the extremal quantile of the conditional distribution of the GARCH process. We propose two methods, the normal ...

This paper proposes differentiability properties for positively homogeneous risk measures which ensure that the gradient can be applied for reasonable risk capital allocation on non-trivial portfolios. It is shown that these properties are fulfilled for a wide class of coherent risk measures based on the mean and the one-sided moments of a risky payoff. In contrast to quantile-based risk measur...

In this paper we propose a method to estimate the value-at-risk (VaR) of a portfolio based on a combination of time series, extreme value theory and copula fitting. Given multivariate financial data, we use a univariate ARMA-GARCH model for each return series. We then fit a generalized Pareto distribution to the tails of the residuals to model the distributions of marginal residuals, followed b...

abstract this paper attempts to re-investigate the catching-up (stochastic convergence) hypothesis among the selected 16 oecd countries applying the time series approach of convergence hypothesis with annual data over one century. to reach this aim, we propose a model which specifies a trend function, incorporating both types of structural breaks – that is, sharp breaks and smooth shifts using ...