Alternative investment that aims to be decorrelated, finding different sources of alpha and coordinating them with each other is the challenge. Applying science in the service of financial advisory.
In an increasingly globalized world, any small negative event can end up causing sharp declines in stock markets around the world; that's why data is becoming even more important in finding new sources of excess return with little correlation to the market.
Finding different sources of alpha and coordinating them with each other to build a balanced portfolio, without exposure to market beta. Looking for patterns across the noise of alternative data.
Long/Short leveraged equity strategy with ESG focus, which relies on the use of alternative data to generate market-uncorrelated returns. With options trade on top.
| Portfolio | |
|---|---|
| Total Return | 33.0 % |
| Annualized Return | 10.6 % |
| Annualized Volatility | 8.5 % |
| Annualized Sharpe | 1.2 |
Data-driven investment strategy that analyze complex data sets through quantitative methods to deliver a truly differentiated and uncorrelated investment solution.
Quantitative research process for identifying quality, ESG-integrated, companies for the long leg. While offseting risks embedded in the long book by shorting companies with no exposure to any factor premium.
Disciplined risk management algorithm that avoids over-exposure to any security, sector or factor, generating an enduring source of alpha.
The strategy provides exposure to equities without assuming all of the associated risks. The strategy seeks to exploit investment opportunities in both bull and bear markets to generate steady returns, whatever the weather.
100% systematic methodology
Quality factor bias on the long leg
No-factor exposure on the short leg
Options trades on top
We build the short book to hedge market risk and to source additional alpha.
A machine learning algorithm is applied to financial data to identify securities with high probability of underperformance in the next 5-60 days.
We filter stocks with high borrow costs that tend to have high volatility and risk, as well as stocks that potentially have high ESG ratings.
To hedge market risk, we optimize the short portfolio weights to achieve near beta-neutrality for the portfolio.
At ETS Asset Management Factory we are constantly improving our strategies by promoting innovation based on our data, algorithms, team and experience. Each of these elements serves a distinct purpose, collectively forming our company’s four main pillars.Following this philosophy, in today’s post we will be using an advanced algorithm to improve a module of the […]
When we enter the ESG world, we can fall into an abyss of terminology, extreme currents of thought, emerging regulation, and a lot of marketing.
In this post we are going to examine two alternative methods of calculating the factor contribution to the performance of an equity portfolio.