Long memory (long-term dependence) seems to be as widespread in financial time series as in nature. Inspired by the long memory property, Multi-fractal processes have recently been introduced as a new tool for modeling the stylized facts in financial time series. In this paper, we attempt to construct a bivariate multi-fractal model, and implement its estimation via both GMM and likelihood appr...

This paper examines, for the Brazilian case, if break-even inflation rates (BEIR) extracted from fixed income securities is an unbiased estimator of consumer inflation, measured by the CPI. Our estimates suggest that BEIRs are informative about future inflation, especially for the maturity of three months. The main innovation of our work, however, is the method used for estimation, allowing us ...

In this paper we discuss sensitivity of forecasts with respect to the information set considered in prediction; a sensitivity measure called impact factor, IF, is defined. This notion is specialized to the case of VAR processes integrated of order 0, 1 and 2. For stationary VARs this measure corresponds to the sum of the impulse response coefficients. For integrated VAR systems, the IF has a di...

We study the dynamic relation between aggregate mutual fund flow and market-wide volatility. Using daily flow data and a VAR approach, we find that market volatility is negatively related to concurrent and lagged flow. A structural VAR impulse response analysis suggests that shock in flow has a negative impact on market volatility: An inflow (outflow) shock predicts a decline (an increase) in v...

The objective of this study is to compare alternative computerized model-selection strategies in the context of the vector autoregressive (VAR) modeling framework. The focus is on a comparison of subset modeling strategies with the general-to-specific reduction approach automated by PcGets. Different measures of the possible gains of model selection are considered: (i) the chances of finding th...

This paper examines the sectoral and intertemporal impacts of international emigrant remittances by using a vector auto-regression (VAR) estimation focusing on Cambodia, Lao PDR, Myanmar and Vietnam (CLMV countries). The reason for targeting the CLMV countries is that they have still depended largely on remittance-earnings from their emigrant workers in their economies, and that the macroeconom...

Recently, a significant share of the empirical analysis on the impact of public capital on regional growth has used multivariate time-series frameworks based on vector auto regressive (VAR) models. Nevertheless, not as much attention has been dedicated to the analysis of the long-run determinants of regional growth processes using multi-region panel data and applying panel integration and co-in...

This paper investigates the effect of a positive technology shock on per capita hours worked within the class of Bayesian Vector Auto-Regressive [BVAR] models. Such a framework avoids the current debate regarding the specification issue of per capita hours [level versus first-difference stationary]. Six priors are considered and for each, we examine the impulse responses of per capita hours fol...

Purpose of the paper The Basel Committee regulations require the estimation of Value-at-Risk at 99% confidence level for a 10-trading-day-ahead forecasting horizon. The paper provides a multivariate modelling framework for multi-period VaR estimates for leptokurtic and asymmetrically distributed real-estate portfolio returns. The purpose of the paper is to estimate accurate 10-day-ahead 99% VaR...

Risk managers are increasingly required by international Regulatory Institutions to adopt accurate techniques for the measurement and control of portfolios financial risks. The task requires first the identification of the different risk sources affecting the portfolio and the measurement of their impact, then after: the adoption of appropriate portfolio strategies aimed at neutralising these r...