As an equity quantitative analyst, you have recurring positioning analysis tasks. Your most effective approach is to model your object of study (usually stocks, portfolios or indexes) and decompose its behavior into common risk factors. You can leverage the FF-5 equity factor model, which we will reproduce here, to use in real time!
As a quantitative researcher, your main goal is to find new financial edges. In this article, we will show an overview of the pipeline for designing alpha-generating investment strategies, with associated python code as usual.
You want to hedge a stock portfolio with a very liquid option contract. However, your fund has a high tracking error relative to the underlying option index. You can divide your portfolio to reduce your basis risk.
In portfolio management, the combination of SAA and TAA portfolios is key to build robust funds.
The SAA reflects the long term view of the management team on the different assets, while the TAA allows to implement short-term views and adds a tilt to SAA, hopefully adding some alpha to the fund.
In this article we look into the incorporation of TAA and its sizing along an existing SAA portfolio.
Rebalancing portfolios is an important event in the life of the portfolio manager, as transaction fees have non negligible impact on performance. We will focus on mitigating portfolio turnover via Tracking-error minimization under a QP framework.
Studying market structure through the use of correlation matrices is well spread. Here we will share a methodology to enhance visual clustering analysis, the Minimum Spanning Tree.
