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Financial time series analysis has focused on data related to market trading activity. Next to the modeling of the conditional variance of returns within the GARCH family of models, recent attention has been devoted to other variables: first, and foremost, volatility measured on the basis of...
Persistent link: https://www.econbiz.de/10009643126
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
The explosion of algorithmic trading has been one of the most prominent recent trends in the financial industry. Algorithmic trading consists of automated trading strategies that attempt to minimize transaction costs by optimally placing orders. The key ingredient of many of these strategies are...
Persistent link: https://www.econbiz.de/10008567867
The Multiplicative Error Model introduced by Engle (2002) for positive 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 into...
Persistent link: https://www.econbiz.de/10005731547
Realized volatility of financial time series generally shows a slow–moving average level from the early 2000s to recent times, with alternating periods of turmoil and quiet. Modeling such a pattern has been variously tackled in the literature with solutions spanning from long–memory, Markov...
Persistent link: https://www.econbiz.de/10010862522
Realized volatilities measured on several assets exhibit a common secular trend and some idiosyncratic pattern. We accommodate such an empirical regularity extending the class of Multiplicative Error Models (MEMs) to a model where the common trend is estimated nonparametrically while the...
Persistent link: https://www.econbiz.de/10010862525
Empirical evidence shows that the dynamics of high frequency–based measures of volatility exhibit persistence and occasional abrupt changes in the average level. By looking at volatility measures for major indices, we notice similar patterns (including jumps at about the same time), with...
Persistent link: https://www.econbiz.de/10010862527
This paper presents evidence, using data from Consensus Forecasts, that there is an 'attraction' to conform to the mean forecasts; in other words, views expressed by other forecasters in the previous period influence individuals' current forecast. The paper then discusses-and provides further...
Persistent link: https://www.econbiz.de/10005812863