Northern Lights Fund Trust III - Counterpoint Quantitative Equity ETF CPAI 34.41 Northern Lights Fund Trust III - Counterpoint Quantitative Equity ETF

Home
  /  
Stock List  /  Northern Lights Fund Trust III - Counterpoint Quantitative Equity ETF
Range:25.137-34.469Vol Avg:5895Last Div:0.02Changes:0.3
Beta:1.23Cap:0.04BCurrency:USDExchange:AMEX
Sector:Financial ServicesIPO:Wed Nov 29 2023Empoloyees:
CUSIP:CIK:ISIN:US66538R5404Country:US
CPAI employs a quantitative, model-driven strategy that integrates quantitative analysis and machine learning insights to navigate diverse market conditions. The portfolio consists of at least 50 US-listed companies of any capitalization or ADRs. The selection process relies on advanced quantitative models leveraging machine learning technology, considering over 30 variables related to value, long-term reversal, momentum, profitability, investor sentiment, and stock price stability. Additionally, the Adviser backtests variable combinations considered to be supported by economic reasoning or investor behavioral biases. The models continually learn and adapt relationships between input variables and realized historic returns, updating during quarterly portfolio rebalances. Moreover, rebalancing ensures the portfolio aligns with the models' rankings, with adjustments made to limit sector exposure to 35% or less.

Stock Details

The content provided on this site is for informational purposes only and does not constitute financial, investment, or professional advice. We are not registered investment advisors or financial planners, and we do not provide recommendations or advice on buying, selling, or holding any particular stocks or securities. Any investment decisions should be made based on your own research and consultation with a qualified financial professional. We are not responsible for any financial loss or damages incurred from reliance on the information provided on this site. Please invest responsibly and seek professional advice when needed.
DMCA.com Protection StatusPowered by StackThrow