Profitable quant trading for actively managed funds

Machine-learning algorithms generate frequent alpha opportunities

Quant Alpha

Intensity has developed quantitative machinery that produces reliable, alpha-generating trading signals

for the U.S. equity markets.  Our machinery provides equity selection, trade timing, position size, duration of entry, and duration of exit.

This allows hedge funds to:

  • Add quant trading to their strategy
  • Generate superior risk-adjusted returns
  • Raise overall fund performance
  • Reduce in-house quant risk and expense

  • Intensity Forecasting Note #1 (Types of Forecasts)

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Trading Algorithms

Quant alpha algorithms

Intensity algorithms are built to perform on future data that have never been seen,

resulting in a higher number of potentially profitable outcomes each market day.

Our methods ingest a substantial breadth of data, select impactful predictors, evaluate numerous modeling techniques, apply advanced simulation engines, and employ robust scientific testing and validation methodologies that enable continual evolution and rapid response to changing market conditions.   Benefits include:

  • Built to predict in all market conditions
  • Out-of-sample forecast performance​
  • Non-correlated to market movements
  • Continuous improvement in accuracy and reliability

  • Intensity Forecasting Note #2 (Evaluating Point Forecasts)

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  • Intensity Forecasting Note #3 (Interval and Probability Forecasts)

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Risk Management

Intensity optimizes risk-to-performance using advanced mathematics and

multi-dimensional modeling.  Combining the best of human and machine intelligence, the resulting computed trading signals are unbiased, unemotional, and removed from human judgement.

Our data scientists focused on:

  • Extensive out-of-sample performance testing
  • Rigorous simulation and validation
  • Minimizing draw downs

  • Intensity Executives are Featured in Financial Sense’s Article "AI Predicts Next US Recession to Start in 2019"

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Portfolio Optimization

Portfolio Optimization

Many funds are struggling to beat the market. Having

frequent, profitable quant trading signals can optimize a fund’s return while throttling risk.

More specifically, the alpha quant engine was built for:

  • Portfolio reweighting
  • Determining optimal mix of signals to trade on
  • Decreasing performance risk
  • Hundreds of trades annually for improved profits

  • Intensity 2017 February Recession Outlook:

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  • Dr. Ryan Sullivan is Featured in Datanami’s Article "Don't be a data snooper"

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