Investment Process

A true hybrid approach, effectively combining data and research from a diverse set of studies to accomplish a common goal.

Semi-Systematic Execution

In a landscape driven by both data and disruption, we believe adopting a strategy which captures the best of both qualitative and quantitative strategies has become increasingly valuable. Following this belief, we have structured a process which combines the predictive power of systematic models along the ideas and judgement of our own discretionary insight. Quantitative tools are powerful for cutting out noise, assessing probabilities, and removing emotion, but without a forward-looking view even the most sophisticated models risk anchoring to outdated patterns. This is why we integrate the two. A clear outlook provides context, and our models bring structure. Together they form a framework capable of responding to the ever-changing dynamics of the market while staying disciplined in data and process.

Human Discretion To Guide Quantitative Use

Part of what builds our data-driven approach, we are always looking to find quantitative explanations to qualitative problems. Beginning our process with a top-down view of the economy, our fundamental insights supply critical outlooks and queries which drive our quantitative models. Following this blueprint, we strategically translate our ideas to market signals with potential predictive power, tailored to specific market conditions and the greater risks posed by wider macroeconomic forces.

Our Framework

Following a multi-layered process, we attempt to effectively blend an array of qualitative and quantitative research to generate smart, data-driven investments.

Forming the ideas which create our outlooks and drive our strategies, we strategically approach our fundamental research from macro to micro.

Macro Evaluation

With a focus on developing direction, we apply data and research from key areas to establish a nuanced perspective on macroeconomics and monetary policy. This evaluation marks the beginning of our investment process, and acts as our compass in navigating the translational effects of the macroeconomic environment on financial markets.

Key Areas Of Research:

Growth and Labor Market
Inflation and Monetary Direction
Financial Health

Consumer Data
Geopolitics

Market Assessment

Absorbing breadth and depth of research, we use this process to evaluate the behavioural and structural forces driving the markets performance. Leveraging public data and open-source models, we couple our market and macroeconomic understandings to form forward-looking views and identify the sectors best positioned to benefit.

Key areas of research:

Sentiment
Market Performance
Risks and Valuations

Capital Flows
Sector Performance

Fundamental Valuation

Focused on investing in the most promising companies in the best performing sectors, we apply deep fundamental research and financial analysis to guide portfolios towards the most compelling opportunities while minimizing broad market exposures. Using our insights and key valuation models to find intrinsic value, this area of research is critical in separating strength from weakness.

Qualitative Research:

Business model and revenue streams
Industry position and scalability
Competitive moat
Growth drivers and catalysts
Industry outlook and developments

Quantitative Research:

Financial Statement analysis
Intrinsic valuation models
Earnings and profitability
Financial ratios and valuation multiples

Leveraging advanced data science and quantitative strategies on the notion that data is a powerful tool capable of exploiting alpha opportunities.

Designed to enhance, not replace human conviction, we employ a diverse set of quantitative models & tools that contribute to our statistically grounded, hybrid approach. Given their semi-systematic role, our proprietary models serve as reinforcement tools rather than operating as autonomous decision-makers.

We take pride in our ability to think about the world systematically and quantitatively, as well as our ability to deal with uncertainty in a statistical approach. Utilizing advanced statistical and quantitative modeling techniques to build and execute strategies across key areas of the investment process, we follow a framework allowing us to run sophisticated strategies with efficiency. To ensure reliability, we subject all models to extensive back testing and threshold grading to evaluate success rates and predictive accuracy.

Machine Learning Models

Following industry standard metrics with leading architectures, we operate proprietary ML models to provide new perspectives towards investment ideas. Utilizing the latest developments in AI, we apply ML to multiple fronts which help enhance our ability in price forecasting, risk modeling, portfolio optimization, market scanning, and more.

Signal-Based Models

Leveraging rule-defined strategies, we engineer signals to identify favorable buy/sell setups by capturing discretionary market behaviour, helping spot potential investment opportunities.