VI Quant Fund Series
VI Quant quantamental strategy combines the best of quantitative research and fundamental principles of investing to sharpen investment results.
The quantitative approach applies statistical machine-learning (ML) models to large datasets from financial, economic, and alternative sources, to deepen the investing research processes in areas like sentiment analysis, alternative data, factor-based analysis, and portfolio allocation analysis.
When we combine ML-based research with extensive back-testing and automate the entire stock screening, selection, and execution processes, we systematically overcome key person risks, cognitive biases, and execution errors experienced by traditional funds.
Automated Stock Selection Criteria & Portfolio Allocation
Automation to Eliminate Investing Behavioural Biases
Eliminate Risk of Permanent Capital Loss
A portfolio only compounds if the companies survive, does not default, and accurately presents its business in its financials. Aggressive accounting practices are especially prominent and 'more creative' in developing markets where regulatory enforcement may be less stringent. Our proprietary accounting risk assessment models are integrated into the stock selection process to reduce our portfolio's risk of permanent capital loss.
Filter High Quality Stocks
Quantifying financial and non-financial strengths of businesses like 'Disruptive and Innovative Businesses', 'High Operating Leverage', 'Great Company Culture' and 'Visionary Management' no longer has to be manually picked up after much reading. We convert these desirable traits into features our models can constantly identify to surface these best-in-class companies for the respective portfolio strategies.
Select Reasonably Priced Basket
Valuing a business is an art and science given the diverse inputs, assumptions, business models and investment strategies. From traditional brick & mortar to turnarounds or seemingly 'loss-making' high growth software companies, our smart valuation models are extensively back-tested over multiple decades of bull and bear markets to ensure we avoid grossly overpaying or avoid missing out on seemingly 'expensive' high-quality companies.
Automated Execution
After all the above, trades execution, position sizing and portfolio rebalancing strategies contribute most towards a successful portfolio. Be it cutting losing positions fast (no loss aversion bias), adding to strong companies despite a market correction (no herd mentality) or adding to positions despite all-time high, strategies we craft in rational emotions get automated into an emotionless rule-based execution during calm or turbulent markets.