This paper discusses the effects of introducing nonlinear interactions and noise-filtering to the covariance matrix used in Markowitz’s portfolio allocation model, evaluating the technique’s performances for daily data from seven financial markets between January 2000 and August 2018. We estimated the covariance matrix by applying Kernel functions, and applied filtering following the theoretical distribution of the eigenvalues based on the Random Matrix Theory. The results were compared with the traditional linear Pearson estimator and robust estimation methods for covariance matrices. The results showed that noise-filtering yielded portfolios with significantly larger risk-adjusted profitability than its non-filtered counterpart for almost half of the tested cases. Moreover, we analyzed the improvements and setbacks of the nonlinear approaches over linear ones, discussing in which circumstances the additional complexity of nonlinear features seemed to predominantly add more noise or predictive performance.

A negative leader propagates in a stepping fashion where the leader halts in between forward jumps. In between the forward jumps the corona at the leader tip gradually charges up until the corona explodes forward in a corona burst, emitting strong very high frequency (VHF) pulses. A corona is a region of very weakly conducting plasma around a leader, generally thought to consist of many streamers where a streamer is a self-propagating structure which develops inside a charged region (Dwyer & Uman, 2014). It is thought that VHF (30-300 MHz) radio emission from lightning is dominated by streamer activity (

A negative leader propagates in a stepping fashion where the leader halts in between forward jumps. In between the forward jumps the corona at the leader tip gradually charges up until the corona explodes forward in a corona burst, emitting strong very high frequency (VHF) pulses. A corona is a region of very weakly conducting plasma around a leader, generally thought to consist of many streamers where a streamer is a self-propagating structure which develops inside a charged region (Dwyer & Uman, 2014). It is thought that VHF (30-300 MHz) radio emission from lightning is dominated by streamer activity (