Introductory Quantitative Stock Models and Trend-Following Rules
Summary
This beginner overview surveys several approaches to quantitative stock selection: multi-factor scoring or regression, style rotation, money-flow signals, momentum and reversal, analyst consensus, ownership concentration, and trend following. For style rotation it mentions relative valuation, scenario analysis, logistic prediction, and macro or volatility inputs. The trend section gives more operational detail: identify higher lows and price breaks, add a time-based drift threshold to reduce premature signals, trail a stop after a strong rise, and require price to recover above a long moving average before entry in a weak downtrend.
The article offers conceptual rationales, not empirical evidence. It does not specify a complete dataset, parameter calibration, trading costs, or comparative backtests. Several ideas, including inferring future price direction from money flows or concentrated holdings, are presented as hypotheses rather than demonstrated effects. The drift and stop parameters require estimation, and the article acknowledges that trend duration and magnitude are important design questions.
Key ideas
- Multi-factor selection combines several signals through scoring or regression.
- Style rotation attempts to forecast changing preferences for value, growth, or market capitalization.
- Momentum and reversal strategies depend on how long past strength or weakness persists.
- Trend rules can use swing highs and lows, drift-adjusted breakouts, trailing stops, and a long moving-average filter.
- The overview supplies hypotheses and rule sketches rather than backtest evidence.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.