Sell Side Coverage Matrix
The Sell Side Coverage Matrix is a dataset that enhances traditional sector and industry classifications by defining peer groups based on overlapping sell-side analyst coverage. The dataset consists of all pairs of stocks which have overlapping coverage, along with their degree of overlap.
This approach provides more nuanced stock groupings, improving signal generation for predictive models.
It helps investors identify peers through dynamic business model similarities and investor perspectives, giving a competitive edge in portfolio management.
Key Features:
- Dynamic Peer Grouping
- Improved Signal Performance
- Peer Surprise and Peer Momentum signals
- Peer-Relative Factors:
- Momentum
- Reversal
- Value
- Global coverage
Peer-based benchmarks drive better risk-adjusted returns and lower turnover, making this approach ideal for signal refinement and portfolio optimization.
Applications:
- Enhances momentum models and earnings surprise prediction models such as ExtractAlpha’s TrueBeats by using cross-stock spillover effects
- Strengthens momentum and reversal strategies using peer-relative rankings
- Optimizes value-based investing through peer comparisons
For example: Apple’s closest peers, according to the sell side analysts who cover the stock, are NVIDIA and Google. But according to GICS and other industry classifications, Apple is a hardward company; NVIDIA a semiconductor company; and Google is an internet company. Traditional static, one-size-fits-all industry classifications do not reflect the reality that today the Mag7 are economically linked and move together. By using broker coverage to determine peer stocks, the Sell Side Coverage Matrix provides a more accurate metric for stock groupings for these and over 10,000 other names globally.
The Sell Side Coverage Matrix gives institutional investors a powerful tool to refine stock rankings, improve signal performance, and enhance risk management strategies through dynamic peer groups.
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