| Report Date | |
| Manager | |
| Fund Name | |
| Strategy | |
| Latest Return Date | |
| Latest Return | |
| Latest 6 Months | |
| Latest 12 Months | |
| Latest 24 Months (pa) | |
| Annualised Since Inception | |
| Inception Date | |
| FUM (millions) | |
| Fund Overview | The investment objective of the Fund is to achieve long-term capital appreciation with low correlation to global equity markets through investment in the Underlying Fund. Fund One is a global macro fund that utilises quantitative research including machine learning techniques and fully automated trading algorithms which will aim to generate positive uncorrelated returns relative to any significant equity benchmark. The traded instruments are either major FX pairs or the most liquid exchange traded stock index, bond, and commodity futures across North America, Europe and Asia Pacific. The algorithm backtests over 10 years of tick data and in order to do so effectively requires machine learning to filter noise and identify meaningful signals, which results in statistically significant prediction of price movements. In production this processing is done in real time and the portfolio reacts to asset movements by rebalancing automatically to the desired risk exposure through the market impact optimised execution logic. Risk management layers built into the algorithm have been developed using the experience the team has gained from their decades in highly liquid fast-moving markets in the proprietary High Frequency Trading world. This allows the system to trade autonomously but safely to all trading opportunities and potential system issues, and to alert the team to any behaviour outside of strictly controlled bounds. The Fund is a 'feeder fund' which indirectly gains exposure to the underlying assets by investing all or substantially all of its assets in the Underlying Fund. The Fund may retain a certain amount of cash from the investment in the Fund for the purpose of payment of costs, fees, hedging and expenses. |
| Manager Comments | The best performance assets for the month were: Hang Seng Index (+3.13% of NAV), E-mini S&P 500 (+2.13% of NAV) and Euro Stoxx 50 (+2.06% of NAV). The worst performing assets were: Nikkei 225 (-1.06% of NAV), E-mini Russell (-2.30% of NAV) and Hang Seng China Ent. Index (-3.98% of NAV). |
| More Information |
