Showing 1 - 10 of 22
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
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
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
Persistent link: https://www.econbiz.de/10001346270
The literature on Markov switching models is increasing and producing interesting results both at theoretical and applied levels. Most often the number of regimes, i.e., of data generating processes, is considered known; this strong hypothesis is adopted to somewhat bypass the nuisance parameter...
Persistent link: https://www.econbiz.de/10005075732
In this paper we evaluate the impact that stock returns recorded between market closing and opening the next business day have on intra-daily volatility. A simple test shows that the estimated volatility clustering of the intra-daily returns may be affected by a market opening surprise bias. An...
Persistent link: https://www.econbiz.de/10005687786
In this paper we suggest ways to characterize the transmission mechanisms of volatility between markets by making use of a new Markov Switching bivariate model where the state of one variable feeds into the transition probability of the state of the other. The comparison between this model and...
Persistent link: https://www.econbiz.de/10005687787