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, the quality of forecasts should improve. Yet, there is no consensus about a "true" or "best" measure of volatility. In …. The estimation results show significant interactions between the indicators. We also show that one-month-ahead forecasts …
Persistent link: https://www.econbiz.de/10005812865
Knowledge of the characteristics of the short-term evolution of consumer prices for each country and for their average is important for better monitoring and forecasting of inflation in the euro area. In this paper we seek to verify to what extent the short-term variability of the HICPs can be...
Persistent link: https://www.econbiz.de/10005113568
We analyze several measures of volatility (realized variance, bipower variation and squared daily returns) as estimators of integrated variance of a continuous time stochastic process for an asset price. We use a Multiplicative Error Model to describe the evolution of each measure as the product...
Persistent link: https://www.econbiz.de/10005812866
Persistent link: https://www.econbiz.de/10008509948
methodology can significantly outperform the unconstrained ML forecasts of rich flexible specifications. …
Persistent link: https://www.econbiz.de/10005075728
In this paper we address the issue of forecasting Value–at–Risk (VaR) using different volatility measures: realized volatility, bipower realized volatility, two scales realized volatility, realized kernel as well as the daily range. We propose a dynamic model with a flexible trend...
Persistent link: https://www.econbiz.de/10005075734
The frequency of crashes and the magnitude of crises in international financial markets are growing more severe over time. Recent financial crises are not singular events portrayed in recent accounts, rather, they erupt in circumstances that are very similar to the economic and financial...
Persistent link: https://www.econbiz.de/10005687785
Multiplicative Error Models (MEM) can be used to trace the dynamics of non–negative valued processes. Interactions between several such processes are accommodated by the vector MEM and estimated by maximum likelihood (Gamma marginals with copula functions) or by Generalized Method of Moments....
Persistent link: https://www.econbiz.de/10005731539
In financial time series analysis we encounter several instances of non–negative valued processes (volumes, trades, durations, realized volatility, daily range, and so on) which exhibit clustering and can be modeled as the product of a vector of conditionally autoregressive scale factors and a...
Persistent link: https://www.econbiz.de/10005731543
The Multiplicative Error Model introduced by Engle (2002) for non-negative valued processes is specified as the product of a (conditionally autoregressive) scale factor and an innovation process with positive support. In this paper we propose a multivariate extension of such a model, by taking...
Persistent link: https://www.econbiz.de/10005731544