Fasanara Open Quant portfolio is composed of several investment algorithms both built in-house and in partnership with start-ups around the world. From genetic algorithms to neural network and complexity theory, we combine the best of our research team and our global network of Quants to build innovative strategies.
Our development process is systems-based with the goal of generating robust sets of uncorrelated trading strategies across multiple asset classes. Our team continuously analyses trends to identify market regimes and employ best performing strategies for both micro and macro specific environments.
We invest in the next generation of portfolio managers by selecting the best risk-adjusted performers to enhance our portfolio. We seek to emulate the emerging managers premium, i.e. the observation that the average Sharpe Ratio in the fledgling years of a fund is better than the long-term return.
In partnership with crowdsourced platforms, we track the returns of over thousands independent traders around the world. We identify and allocate capital to exceptional trading talent, that have proven they can deliver consistent returns, with controlled risk, in different market conditions.
We engage in rigorous oversight of our quant traders and dynamically allocate our capital in a rules-based fashion across both internal and external strategies.
Fasanara's unique investment approach combines several trading models divided into three main groups:
Futures and FX Algos
Models that use machine learning to identify non-linear relationships and apply a confidence based allocation on global futures markets and FX, with limited risk exposure.
Models that seek market-neutrality by trading volatility-based instruments such as VIX futures and equity options, to reduce the risk of the portfolio (hedging), and also to generate alpha in moments of high volatility.
Equity Arb Algos
A set of econometrical strategies applied to stocks and digital assets. These strategies take advantage of statistical concepts using several trading techniques to identify intraday and short-term patterns.
We have a proactive risk management tool, built as a Complexity Based Systemic Risk Alert, which spots small-scale market drops. Using this model, we are able to automatically reduce our risk exposure when a higher probability of a relevant market drawdown is indicated by our models.
All our trading models are subject to defined downside loss constraint targets and risk limits. The investment algorithms in the portfolio are monitored for a variety of risk factors including position limits, absolute loss thresholds, correlation, volatility, risk-return, etc.
Our sourcing and selection process is designed to find high caliber under-the-radar portfolio managers with unique investment strategies. We believe exceptional returns are found In early-stage managers, start-ups and independent traders.
If you'd like to join our quant network, please send an email to firstname.lastname@example.org with your research and results. Your strategy must trade only liquid instruments and demonstrate a successful live track record, in different market regimes.
Please get in touch for further info about our funds and how to invest.