Our process consists of three stages:
The investment process is driven by models that encapsulate our investment beliefs developed over many years of experience in fundamental stock analysis, macroeconomic studies, and quantitative analytics. Using models helps process large amounts of data efficiently, while consistently applying our investment philosophy.
There are over 50,000 listed equities in the world. From that list, we select stocks from global developed markets based on market capitalisation, liquidity, and data quality criteria. We end up with an Investable Universe of around 4,000 stocks, a number that can marginally fluctuate with underlying data.
We then clean up the data to ensure quality and calculate our proprietary Factor Scores for each stock. While the data we use is publicly available, our Factor Scores are proprietary and calculated in a way that best captures characteristics that work with our Macro Model’s Factor Weights.
Factors are, in essence, a stock’s basic descriptors or characteristics. For example, a stock with a low Price-to-earnings multiple (PE) is seen as a “value” stock and has a high score on value factors. A stock with a strong share price performance is described as a “momentum” stock and has a high momentum score. Ordinarily, a value investor would focus on the value score, a growth fund would focus on a mix of momentum and quality and a quantitative investor may blend momentum and value. The value, quality and size factors use key data metrics, usually based on earnings, balance sheet, consensus estimates and market data.
Most funds have a static exposure to factors that capture their investment philosophy. We, on the other hand, run a range of Macro Models to create a strategic blend of factors for the current macro environment. This is our fundamental differentiator.
Our Macro Models utilise a measure of what investors generally accept to be true.
The models gather data (such as security returns and volatility, Gross Domestic Product (GDP) growth, money supply, purchasing manager indices, interest rates) and process it (detrending, smoothing, combining) to generate an output such as our leading indicator of excess liquidity.
If there is too much money chasing too few goods and services, we expect it to benefit styles with more leverage to the cycle, such as value and small caps. Rising uncertainty may signal a turning point in the cycle and cause a rotation in the stock markets from past winners into laggards.
By taking the current macro valuation and outlook indicators, we calculate Factor Weights. Factor Weights are risk adjusted return expectations of each of the factors. Factor Weights determine how we blend Momentum, Value, Quality and Size into each individual stock’s Thymos Score.
Since our Macro Models are driven by the data captured, our blend changes with the speed and magnitude of the macro environment and enables us to focus on being at the right place at the right time.
The first two stages result in a Scored Thymos Universe. It is a list of around 4,000 stocks, each with a single Thymos Score that represents the stock’s relative expected return.
Our Portfolio Construction process selects stocks from the Thymos Universe to build a portfolio of stocks that meet the Fund’s risk / return profile. In other words, the Portfolio Construction maximises the Portfolio’s aggregate Thymos Score, while keeping within risk constraints dictated by the Fund’s risk / return parameters.
Without risk constraints, the Portfolio Construction stage would simply select the stock with the highest Thymos Score (expected return) and put all the money into that one stock. Portfolios start to take shape once risk constraints are introduced. These include:
The Funds section lists individual Funds and their investment objective that in turn dictate risk / return profile of the fund that can be found on the individual Fund’s pages.