Trading Strategies: The Main Families
Most retail strategies, whatever their branding, belong to a handful of families. Knowing the family tells you what a method needs to work, when it will bleed, and what its statistics should look like — which is more useful than any single setup.
Trend following
Enter in the direction of an established move, exit when it bends. Low win rates (often 30–45%) with large winners; the cost is many small losses and deep patience during choppy markets. Its statistics only make sense over big samples, which is why trend followers live and die by expectancy, not win rate.
Mean reversion
Fade stretched moves back toward an average or a range midpoint. High win rates with small winners and occasionally ugly losers — the profile is the mirror of trend following, and its danger is the same trade that works forty times becoming the one that trends against you. Hard stops are non-negotiable here.
Breakout and momentum
Buy strength through a defined level, expecting continuation. The whole method lives on the quality of the level and the handling of false breaks; the common fixes — waiting for a retest, requiring a session or volatility filter — all trade fewer entries for cleaner ones.
News and event trading
Trade the volatility around scheduled releases — CPI, central-bank decisions, payrolls. The moves are fast, spreads widen, and fills slip; it is a specialist's game where practice on historical events matters more than opinions about the number. It also intersects every other family: the same breakout is a different trade during a release.
What makes any of them tradeable
- Exact rules: entry trigger, invalidation, and management written so a stranger could execute them.
- A known cost of doing business: the historical losing streak and drawdown, so a normal bad run does not read as failure.
- Fit to the trader: a method needing eight screen hours cannot be traded around a job; a 35% win rate cannot be traded by someone who cannot tolerate losing often.
- Evidence: a tested sample first, then a live journalled sample at small size.
One strategy, deeply
The consistent pattern among traders who make it is depth over breadth: one or two setups, known cold, executed for years — with a record proving which conditions they pay in. Strategy-hopping resets the sample every time and guarantees permanent inexperience in everything.
CLIMB tags every entry with its setup and reads performance per setup from your record — win rate, expectancy and R by playbook — so "which of my strategies actually pays" stops being a feeling.