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MALCOLM (MAximum Likelihood COintegration analysis of Linear Models): The Theory and Practice of Cointegration Analysis in RATS, Cafoscarina, Venezia
No full textPreliminary evidence based on ultra high frequency data on the relationship among stock prices, traded quantities and order book quotes in the Italian stock market
No full textThis paper is one of the few attempts to analyze ultra high frequency data from an order driven market. We develop some new indicators for bid-ask spread and the sign of traded quantities (buy or sell). Instead of using ACD-like models, we transform the data, wich are originally irregularly spaced over time, into regularly spaced (5 of 45 seconds). We perform non causality analysis on such data, finding some preliminary but interesting results
Stock Prices and Traded Quantities: Evidence from Ultra High Frequency Data
No full textThis paper provides some empirical evidence on the role of demand and supply mechanisms in the stock market, using ultra high frequency data on trades and the limit order book for two stocks traded on Borsa Italiana in February 2005. We conclude with some suggestion for modelling
Identification of Cointegrating Relations in I(2) Vector Autoregressive Models
No full textThis paper discusses identification within a new parametrization for I(2) systems, where the integral and proportional control cointegrating relations are not necessarily orthogonal. The new parametrization, while equivalent to previously proposed ones, gives more flexibility in choosing the variables to include in first differences in the integral and proportional control term. We discuss the joint identification of the cointegrating relations, providing rank and order conditions. We discuss likelihood estimation, and propose a simple alternating algorithm for likelihood-maximization, under the cases of under- exact- and over-identification. An illustration on US consumption is also presented
Inizialization of Maximum Likelihood algorithms for cointegrated I(1) and I(2) VAR models
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