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improvingmvportfolio

This code tests the basic idea of my Master thesis. I propose an improved estimator of the covariance matrix of asset returns, employed in the computation of the minimum-variance portfolio. The main.py script tests the out-of-sample performance of this estimator, which is shown to deliver much better results than the sample covariance matrix and the equally-weighted portfolio.

montecarlooptionpricing

portfoliostrategy

Enhanced version of the Master thesis project. The original code has been enriched with a module that automatically downloads and stores new intraday data from Yahoo Finance, to serve as a real robo-advisor for investments. The code lets you choose between U.S. and European market, represented by stocks listed in the SP500 and STOXXE600 indices.

portfoliostrategybacktestus

Master thesis project. The improved estimator of the covariance matrix of asset returns is employed to derive a new trading strategy based on a two-step procedure. First, it shrinks the asset universe via a subset selection, leaving only the most suitable assets. Then, it performs the mean-variance analysis. Back-testing is carried out in the U.S. stock market between 2018 and 2020. For comparison purposes, the code also implements also other strategies, such as the widely-used momentum strategy. The proposed technique is observed to deliver a very good and much more stable performance with respect to its competitors.

rnn-for-prediction-of-sp500

Prediction of SP500 up/down movements via Recurrent Neural Network