The traditional models to optimize portfolios based on mean-variance
analysis aim to determine the portfolio weights that minimize the variance
for a certain return level. The covariance matrices used to optimize are
difficult to estimate and ad hoc methods often need to be applied to limit
or smooth the mean-variance efficient allocations recommended by the model.
Although the method is efficient, the tracking error isn’t certainly
stationary, so the portfolio can get distant from the benchmark, requiring
frequent re-balancements. This work uses cointegration methodology to devise
two quantitative strategies: index tracking and long-short market neutral.
We aim to design optimal portfolios acquiring the asset prices’
co-movements. The results show that the devise of index tracking portfolios
using cointegration generates goods results, replicating the benchmark’s
return and volatility. The long-short strategy generated stable returns
under several market circumstances, presenting low volatility.
Inflation Tracking Portfolios