Quantitative Primer: Everything you wanted to know about quant…*

研报英文原文证据摘录

Quantitative Primer: Everything you wanted to know about quant…*

ng signals are increasingly picked over. Some of the Tech? Ignore long-term forecasts, just

more fruitful analyses we have conducted have involved hard-to-get data (scraping for look for the biggest quarterly revisions.

private funding rounds, analyzing guidance instead of revisions, identifying differences (5) Statistically cheap Media &

between expert vs. consensus views, using BofA proprietary data, …) and have yielded Entertainment stocks usually get

cheaper – low PE is a better short thanbetter, more surprising results in our research. See Alt. Data section.

long factor in this group.

• For Quants: What’s the crowdedWhat’s new: pick peer groups by capital allocation…

We have found benefits in tailoring frameworks to peer groups rather than a “one-size- trade?

fits-all” approach (see Section III). But a secular trend of increasing correlations within • For sector analysts: most predictive

sectors (perhaps from sector ETF trading) and shifts in sectors over time (a recent stock selection attributes within

example: R&D/buybacks replaced by capex in Tech) have rendered some signals less sectors.

effective. Investors may be better served comparing stocks across peer groups based on • For equity long-short investors:

capital allocation decisions (capex, R&D, buybacks, dividends) rather than vendor-defined Long- and short factors are not

sector classifications – and we provide a guide for stock-selection within these groups. always symmetric – it pays to tweak.

• For macro investors: market timing

…plus new tools to gauge allocation & resource efficiency models, sector rotation approaches,