| Financial Services Industry | Financials Sector | - CEO | LSE Exchange | 66538R540 CUSIP |
| US Country | - Employees | - Last Dividend | 15 Jan 2024 Last Split | - IPO Date |
Counterpoint Quantitative Equity ETF is an actively managed exchange-traded fund aimed at achieving long-term capital appreciation through a systematic, multifactor investment strategy. The fund predominantly focuses on a diversified selection of U.S.-listed stocks, with a requirement to maintain a minimum of 50 securities at any given time. The core investment approach employs proprietary quantitative models, integrating machine learning techniques along with over 30 empirical factors such as value, momentum, quality, long-term reversal, investor sentiment, and price stability. This allows for a dynamic ranking and selection process that identifies the most attractive stocks tailored to the current market environment.
The portfolio is designed to adapt factor exposures reflective of prevailing market conditions, with the intention of leveraging shifts in market anomalies while effectively managing downside risk. By merging fundamental and technical analysis elements, Counterpoint Quantitative Equity ETF aims to offer balanced exposure across a diverse array of sectors and market capitalizations, underscoring its broad-based equity focus. Notably, the ETF distinguishes itself through the utilization of advanced artificial intelligence and data-driven methodologies, with the goal of surpassing the broader equity market in performance while concurrently reducing volatility and exposure to downside risks. The holdings, portfolio weights, and sector allocations are dynamic and undergo regular review as fresh information is assimilated by the underlying models.
Counterpoint Quantitative Equity ETF operates as an actively managed ETF that allows investors to partake in a diversified portfolio of U.S.-listed stocks through a single investment vehicle, thus simplifying exposure to the equity market.
The fund employs a systematic multifactor strategy that integrates quantitative models and empirical factors. This method enables the identification and selection of stocks based on data-driven analyses, aimed at optimizing returns in response to the current market dynamics.
With an emphasis on active management, the ETF dynamically adjusts its portfolio based on evolving market conditions. This proactive strategy is designed to capitalize on market anomalies while effectively navigating downturns.
The fund maintains a broad-based equity focus that spans various sectors and market capitalizations, ensuring comprehensive market representation while providing balanced risk exposure.
Counterpoint Quantitative Equity ETF leverages advanced machine learning techniques within its investment process, allowing for enhanced data analysis and decision-making that contributes to superior stock selection and portfolio management.
The fund incorporates robust risk management strategies to mitigate volatility and minimize downside exposure, safeguarding investor capital while pursuing capital appreciation.
The ETF’s holdings, weights, and sector distributions are subject to continuous review. This systematic reassessment ensures that the portfolio remains aligned with the latest market insights and quantitative analyses, adapting swiftly to new information.