with general cointegration rank. Our hedge is optimal in the sense of minimum variance portfolio. We consider a model that … correlation and cointegration parameters. For short holding periods the correlation impact is predominant. For long horizons, the … hedge ratio should overweight the cointegration parameters rather then short-run correlation information. In the innite …

with general cointegration rank. Our hedge is optimal in the sense of minimum variance portfolio. We consider a model that … correlation and cointegration parameters. For short holding periods the correlation impact is predominant. For long horizons, the … hedge ratio should overweight the cointegration parameters rather then short-run correlation information. In the innite …

(CVAR) with general cointegration rank. Our hedge is optimal in the sense of minimum variance portfolio. We consider a model … correlation and cointegration parameters. For short holding periods the correlation impact is predominant. For long horizons, the … hedge ratio should overweight the cointegration parameters rather then short-run correlation information. In the infinite …

(CVAR) with general cointegration rank. Our hedge is optimal in the sense of minimum variance portfolio. We consider a model … correlation and cointegration parameters. For short holding periods the correlation impact is predominant. For long horizons, the … hedge ratio should overweight the cointegration parameters rather then short-run correlation information. In the infinite …

with general cointegration rank. Our hedge is optimal in the sense of minimum variance portfolio. We consider a model that … correlation and cointegration parameters. For short holding periods the correlation impact is predominant. For long horizons, the … hedge ratio should overweight the cointegration parameters rather then short-run correlation information. In the innite …

The purpose of this paper is to give a systematic account of the maximum likelihood inference concerning cointegration … vectors in non-stationary vector value autoregressive time series with Gaussian errors. The hypothesis of r cointegration … vectors is given a simple parametric formulation in terms of cointegration vectors and their weights. We then estimate and …

This paper gives a systematic application of maximum likelihood inference concerning cointegration vectors in non … dummies. The hypothesis of cointegration is given a simple parametric form in terms of cointegration vectors and their weights … related to the weights. Tests for the presence of cointegration vectors, both with and without a linear trend in the non …