Quant BuffetRelax, Not Over Thinking

Lesson 7 · 22 min

Classic strategies in the library

Momentum, trend, mean reversion, risk parity — the patterns behind 1,700+ Quant Buffet strategies.

MomentumMean reversionTemplates

Most published quant ideas fall into a small set of families. Quant Buffet encodes them as `backtest.templates` and as custom code in the strategy library. Recognizing the family helps you read any article faster.

Momentum

Winners keep winning over 3–12 month horizons. Library favorite: dual_momentum (623 strategies).

Quant Buffet templates: abs_momentumdual_momentummomentum_rotation

Watch out: Crash risk when trends reverse sharply (2009, 2020).

Template cheat sheet

TemplateEconomic storyLibrary share
dual_momentumPick best asset, but go to cash if trend weak~35% of catalog
abs_momentumOwn recent winners equally~19%
momentum_rotationRotate into top-N performers monthly~14%
sma_trendOnly hold assets above long average~13%
equal_weightDiversify naively, rebalance~11%
mean_reversionBuy oversold z-scores~6%
vol_target / risk_parityScale or balance by volatilityRare but important

Your first hands-on path

  1. Finish Lesson 1–6 checklists.
  2. Open API docs → Examples and paste the minimal SMA strategy into the lab.
  3. Browse Strategy Library filtered by momentum or mean reversion.
  4. Change ASSETS to a MULTI_ASSET book and re-run — watch Sharpe vs drawdown.
  5. Read the academic paper linked on the strategy page — compare proxy to original.
from backtest.templates import make_dual_momentum

ASSETS = ["SPY", "EFA", "EEM", "TLT", "GLD", "BIL"]

def make_on_day(prices):
    return make_dual_momentum(prices, ASSETS, {"lookback": 252, "top_n": 1})

Course complete — you can now

  • Explain how daily data flows into `make_on_day`.
  • Name major asset classes and pick ETF proxies from universes.
  • Describe broker / venue / platform layers and cost models.
  • Contrast order types with Quant Buffet's weight-based execution.
  • Interpret Sharpe & drawdown and fix common lab errors.
  • Identify momentum, trend, mean reversion, and risk templates in the library.