Jupiter Merian Global Equity

A very well-established, quant-driven equity fund which invests across hundreds of different companies. Stocks are selected on a fundamental basis by clever systematic models which are constantly being updated and tweaked by the investment team. It is a core fund which is well diversified by style and sector and has fairly tight risk controls relative to a benchmark of global stocks.

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Our Opinion

A unique quant-driven fund, managed by a highly experienced and stable team, which has worked together for many years. We like the fund’s excellent consistency and the team’s constant efforts to update and incrementally improve the process. Long-term performance has been excellent and the fund has rarely had periods of bad underperformance thanks to its tight risk controls. This fund is a great building block for any portfolio.

Fund Manager

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Fund Manager

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Amadeo Alentorn, Fund manager Dr. Amadeo Altentorn joined Merian Global Investors in 2005 (it was acquired by Jupiter in 2020). He is one of the original architects of this strategy and has been working on it for 20 years now. Amadeo holds a BSC in Robotics, an MSC in computer science, and a PHD in computational finance from the University of Essex. Prior to working on this fund, Amadeo worked at the Bank of England, developing simulation models for systemic risk and liquidity. Amadeo is the head of systematic equities. He is also a CFA charterholder.

Amadeo Alentorn, Fund manager Dr. Amadeo Altentorn joined Merian Global Investors in 2005 (it was acquired by Jupiter in 2020). He is one of the original architects of this strategy and has been working on it for 20 years now. Amadeo holds a BSC in Robotics, an MSC in computer science, and a PHD in computational finance from the University of Essex. Prior to working on this fund, Amadeo worked at the Bank of England, developing simulation models for systemic risk and liquidity. Amadeo is the head of systematic equities. He is also a CFA charterholder.

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Investment process

The fund’s philosophy is that markets are not fully efficient due to a number of investor behavioural and psychological biases. Following a purely quant-based systematic approach can exploit these errors and lead to outperformance over time.

The team also believe that investment styles are cyclical and seek to profit by forecasting which styles are most likely to perform in a particular market environment.

The team has a very large opportunity set of 6,000 global stocks. Although they remove illiquid stocks from their investment universe, the strategy does invest across the market-cap spectrum - although most exposure is to developed market large-caps.

Every stock in the universe is analysed across five stock selection criteria.

These are:

- dynamic valuations: measuring a stock’s quality versus its valuation
- sustainable growth: distinguishing between companies with sustainable growth versus one-hit wonders
- analyst sentiment: taking advantage of under or over-reaction from markets to an analysts’ forecast
- company management: how have they performed historically?
- price action: this covers several components at stock and sector level.

Once the stocks have been analysed across the five selection criteria, the next step is to understand which criteria are likely to outperform in the current market conditions. It is important to understand the market sentiment and uncertainty in different regions. Once the current position has been established, the model can look at history to give expectations for future risk and return.

The portfolio is then built from the stocks which maximise alpha within the funds set risk limits and controls.

The team are constantly tweaking and adding new ideas and data to improve their models. One thing which sets this fund apart is its relationship to academia. The team sponsor PHDs and work with academics to explore blue sky ideas.

The final portfolio is well diversified with 450-600 positions.

Risk

The process has been designed to allow for quick rotation and turnover. The strategy is always trading and moving towards an optimal portfolio every day. Transaction cost models are used to optimise the portfolio and to avoid trading just for the sake of it.

The fund has fairly tight risk controls. Beta is targeted at 1 and tracking error is set in a 3-4% range. An initial maximum stock allocation relative to the benchmark plus or minus is just 0.5%. Sector size is limited to +/-5% relative to the benchmark and country size is limited to just +/-2%. Stock turnover is limited to a maximum of 1% a day. The fund has the ability to use index futures for efficient portfolio management purposes.

ESG

ESG factors are fully integrated into the investment process. This is now an Article 8 fund. The team use MSCI data to analyse the level and improvement in E, S and G. The portfolio’s carbon intensity is targeted to be below the benchmark level. The fund excludes companies which derive over 25% of their revenues from coal extraction and power generation. The fund has no positions in tobacco or controversial weapons.

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