Price-Action Trading

1. • What: Trade decisions based purely on raw price movement — candles, structure, support/resistance — without relying on lagging indicators.
     
     

   • Origin / Who: No single inventor; evolved from bar/candlestick charting used by floor traders and early technical analysts over the 19th–20th centuries. Modern formalisation grew with retail tech (late 20th century).
     
     

   • Success / Usage: Extremely common among retail and many professional discretionary traders. Hard to quantify; arguably one of the most widely used approaches because it’s the simplest starting point.
     
     

2. Wyckoff Method (Wyckoff Theory)
   
   

   • What: A method identifying accumulation/markup/distribution/markdown phases, price–volume relationships, and specific schematics for institutional activity.
     
     

   • Origin / Who: Developed by Richard D. Wyckoff in the early 20th century (Wyckoff lived 1873–1934). Wyckoff taught and published his method in the 1910s–1930s. ChartSchool+1
     
     

   • Success / Usage: Used by many technical traders and institutions who study orderflow/volume; popular in education courses and among discretionary traders. Exact number of “successful users” unknown — success depends on skill in reading supply/demand and risk management.
     
     

3. Trend-Following (including Donchian channels / moving-average crossovers)
   
   

   • What: Enter trades in direction of established trend and ride it until it reverses. Uses breakouts, moving averages, channel systems.
     
     

   • Origin / Who: Trend-following has ancient roots; modern systematic versions were formalised mid-20th century (Richard Donchian’s channel methods are a 1950s/60s example). The Turtle experiment (see #4) popularised a strict ruleset.
     
     

   • Success / Usage: Core strategy for many Commodity Trading Advisors (CTAs) and quant shops; historically profitable over long sample periods, though performance is regime-dependent.
     
     

4. Turtle Trading (a specified trend-following ruleset)
   
   

   • What: A clearly defined breakout trend-following system with strict position sizing and entry/exit rules.
     
     

   • Origin / Who: Taught by Richard Dennis and William Eckhardt in 1983 in the famous Turtle experiment; 14 students (the “Turtles”) were trained and many produced strong returns early on. The experiment showed that rules-based trading could be taught. Investopedia+1
     
     

   • Success / Usage: Historically notable: the Turtles reportedly made tens of millions across the program’s early years. Modern traders still implement variants.
     
     

5. Momentum Trading
   
   

   • What: Buy assets showing strong recent returns and sell/short those with poor recent returns (short-term to medium-term).
     
     

   • Origin / Who: Documented in academic literature in the 1990s (e.g., Jegadeesh & Titman), but traders used momentum instincts long before.
     
     

   • Success / Usage: Widely used by quant funds and many retail traders. Momentum is a robust anomaly in many asset classes historically.
     
     

6. Mean-Reversion / Statistical Mean-Reversion
   
   

   • What: Trade anticipating a return to an average price — includes pairs trading and overbought/oversold indicator-based systems.
     
     

   • Origin / Who: Practical roots in market-making and relative-value desks; pairs trading popularised in the 1980s–1990s by hedge funds and academic papers.
     
     

   • Success / Usage: Core to many hedge funds’ relative-value desks; success depends on cointegration testing and execution.
     
     

7. Pairs Trading (market-neutral statistical arbitrage)
   
   

   • What: Trade two historically correlated instruments: long the underperformer and short the outperformer expecting convergence.
     
     

   • Origin / Who: Emerged in institutional quant desks; widely used since the 1980s–1990s. Gatev, Goetzmann and Rouwenhorst (2006) are key academic references on pair spreads.
     
     

   • Success / Usage: Popular with statistical arbitrage funds; success depends on model quality and transaction costs.
     
     

8. Arbitrage (pure arbitrage & relative-value)
   
   

   • What: Exploit price differences for the same asset across markets or instruments (e.g., triangular forex arbitrage, convertible arbitrage).
     
     

   • Origin / Who: One of the oldest strategies in trading history — arbitrage existed since markets did. Institutionalised in modern finance centres across centuries.
     
     

   • Success / Usage: Core to prop desks, prime brokers and institutional traders — where real arbitrage exists, profits can be consistent but often small per trade.
     
     

9. Market Making
   
   

   • What: Continuously post bid and ask quotes to capture spread while managing inventory risk.
     
     

   • Origin / Who: Evolved from floor broker/dealer roles; became electronic and algorithmic with electronic markets (1990s–2000s).
     
     

   • Success / Usage: Used by banks, exchanges, designated market makers, and HFT firms. Profitable at scale with low latency and large volumes.
     
     

10. High-Frequency Trading (HFT)
    
    

    • What: Very-short-term automated strategies that exploit micro-structure, latency, rebates, and tiny price dislocations.
      
      

    • Origin / Who: Grew with electronic markets and co-location in the 1990s–2000s; many proprietary firms pursued it.
      
      

    • Success / Usage: Successful firms (e.g., historically Virtu, Citadel-Securities) made consistent profits until competition compressed returns; highly specialised.
      
      

11. Scalping
    
    

    • What: Take many very-short-term trades for a few ticks/pips per trade, often using market making or micro-momentum.
      
      

    • Origin / Who: Floor traders and forex/CFD scalpers have used it for decades; a retail favorite.
      
      

    • Success / Usage: Popular with active retail intraday traders; success depends on costs, discipline, and execution speed.
      
      

12. Day Trading (intraday strategies)
    
    

    • What: Enter and exit positions within same trading day; includes breakout, fade, and news-driven intraday plays.
      
      

    • Origin / Who: Naturally arises with intraday markets and electronic access (20th century onward).
      
      

    • Success / Usage: Very widespread among retail traders; many lose money due to costs and psychology, but disciplined professionals and prop-traders can be consistently profitable.
      
      

13. Swing Trading
    
    

    • What: Trade holding positions for days to weeks, capturing intermediate moves within a trend or range.
      
      

    • Origin / Who: Longstanding trading style; popularised among retail traders with charting tools.
      
      

    • Success / Usage: Common with retail and discretionary pros who prefer lower time commitment than day trading.
      
      

14. Position Trading (long-term trend / investment style)
    
    

    • What: Hold positions weeks to years based on macro/trend/fundamental views.
      
      

    • Origin / Who: Classical investment style — overlaps with investing (value/growth).
      
      

    • Success / Usage: Used by trend funds, long-only managers, and many private investors.
      
      

15. Quantitative / Algorithmic Trading
    
    

    • What: Systematic rules encoded into algorithms — can be trend, mean-reversion, statistical-arb, machine learning, etc.
      
      

    • Origin / Who: Gained prominence from 1970s–present with computing power growth. Institutional quant shops and hedge funds drove early adoption.
      
      

    • Success / Usage: Very broad — from small retail algos to multi-billion institutional funds.
      
      

16. Statistical Arbitrage (StatArb)
    
    

    • What: Use statistical models across many securities to find exploitable patterns (mean reversion, factor exposures).
      
      

    • Origin / Who: Rose to prominence in the 1980s–1990s at quant hedge funds.
      
      

    • Success / Usage: Backbone of many quant funds; success is data- and transaction-cost dependent.
      
      

17. Risk-Parity / Volatility-Targeting
    
    

    • What: Allocate capital so assets contribute equally to portfolio risk (or target a fixed portfolio volatility).
      
      

    • Origin / Who: Academic/portfolio innovations from late 20th / early 21st century; popularised by institutional allocators.
      
      

    • Success / Usage: Widely used in institutional asset allocation and some retail ETFs.
      
      

18. Carry Trade (FX & rates)
    
    

    • What: Borrow in a low-interest currency and invest in a higher-yielding one, profiting from the interest differential (plus potential appreciation).
      
      

    • Origin / Who: Classic macro strategy used by banks and FX speculators for decades; became particularly popular in the 2000s.
      
      

    • Success / Usage: Profitable in stable risk environments; large drawdowns in crises.
      
      

19. Event-Driven (including Merger Arbitrage)
    
    

    • What: Trade around corporate events — M&A, earnings, restructurings, spinoffs. Merger arbitrage = long target / short acquirer to capture spread.
      
      

    • Origin / Who: Institutional strategy used by hedge funds since at least mid-20th century.
      
      

    • Success / Usage: Many specialized funds; success depends on deal flow and deal completion risk.
      
      

20. News Trading / Event Trading
    
    

    • What: Trade immediately on news releases — economic data, earnings, central bank statements.
      
      

    • Origin / Who: Traders on floor and screens have done this for as long as news affected markets; algorithmic news-reading has grown since 2000s.
      
      

    • Success / Usage: High risk/reward; used by prop desks and algo shops with fast information feeds.
      
      

21. Options Strategies (covered call, straddle, strangle, iron condor, butterflies, calendar spreads, delta-hedged strategies)
    
    

    • What: Use option combinations to express directional, volatility or income views while tailoring risk.
      
      

    • Origin / Who: Options strategies evolved as option markets matured; formal pricing came with Black-Scholes (1973) and binomial models (1979). Black & Scholes’ work (1973) was foundational to modern options markets. Computer Science Department Princeton+1
      
      

    • Success / Usage: Widely used by retail and institutional options traders, market makers, and hedgers. Some strategies (e.g., selling premium) are very common; success depends on option selection and risk control.
      
      

22. Volatility Trading (VIX, variance swaps, volatility arbitrage)
    
    

    • What: Trade implied vs realized volatility (time decay, term structure) using options and derivatives.
      
      

    • Origin / Who: Grew with liquid options markets and volatility products in the 1990s–2000s.
      
      

    • Success / Usage: Specialist hedge funds and prop desks run volatility arbitrage strategies.
      
      

23. Delta-Neutral / Market-Neutral Strategies
    
    

    • What: Construct positions hedged to remove directional market exposure and capture alpha from other sources (volatility, relative value).
      
      

    • Origin / Who: Institutional desks developed these via options and hedged equity strategies over decades.
      
      

    • Success / Usage: Common approach for hedge funds seeking uncorrelated returns.
      
      

24. Value Investing / Fundamental Investing
    
    

    • What: Select undervalued securities based on fundamentals (financials, discounts to intrinsic value); often long-term.
      
      

    • Origin / Who: Benjamin Graham and David Dodd formalised value investing in the 1930s; Warren Buffett popularised successful application from the 1960s onward.
      
      

    • Success / Usage: Many successful institutional and retail investors; long track record but requires deep fundamental research.
      
      

25. Growth Investing
    
    

    • What: Focus on companies with above-average growth prospects; valuation often secondary to growth.
      
      

    • Origin / Who: Evolved as investing styles matured; prominent managers like Philip Fisher (mid-20th century) influenced the approach.
      
      

    • Success / Usage: Widely used in long-only funds and retail investing.
      
      

26. Gann Techniques (angles, time/price geometry)
    
    

    • What: Geometric/time-based methods for predicting price/time turning points (W.D. Gann, early 20th century).
      
      

    • Origin / Who: W.D. Gann, early 1900s.
      
      

    • Success / Usage: Niche; some traders swear by Gann’s methods, others call them subjective.
      
      

27. Elliott Wave Theory
    
    

    • What: Markets move in fractal wave patterns (5 impulse waves followed by 3 corrective waves), used for timing and structure.
      
      

    • Origin / Who: Developed by R. N. Elliott in the 1930s (published The Wave Principle in 1938). Wikipedia+1
      
      

    • Success / Usage: Popular in some technical communities; criticized for subjectivity in wave counts.
      
      

28. Ichimoku Kinko Hyo (Ichimoku Cloud)
    
    

    • What: A composite indicator that displays support/resistance, trend and momentum in one view (clouds).
      
      

    • Origin / Who: Developed by Goichi Hosoda in the late 1930s and publicly released in the 1960s. Wikipedia+1
      
      

    • Success / Usage: Popular in FX and equity trading, especially among traders who like a single-system view.
      
      

29. Fibonacci Retracement / Extensions
    
    

    • What: Use Fibonacci ratios to predict likely retracement/extension levels after moves.
      
      

    • Origin / Who: Derived from Fibonacci number applications in markets; widely adopted by technicians in the 20th century.
      
      

    • Success / Usage: Very common among technical traders; viewed by many as a self-fulfilling tool where many participants watch the same levels.
      
      

30. Order-Flow / Tape-Reading / DOM Strategies
    
    

    • What: Read real-time orders, liquidity and executions to infer short-term directional pressure and execute against it.
      
      

    • Origin / Who: Tape reading is as old as trading floors; modern electronic DOM and level-2 tools enabled electronic order-flow trading (1990s–present).
      
      

    • Success / Usage: Used by professional futures/FX traders and some retails who use advanced platforms; effective for short-term microstructure plays.
      
      

31. VWAP / TWAP Execution Strategies (algorithmic execution)
    
    

    • What: Algorithms to execute large orders over time to minimize market impact (Volume Weighted Average Price, Time Weighted Average Price).
      
      

    • Origin / Who: Institutional execution algorithms developed since electronic trading matured (1990s onward).
      
      

    • Success / Usage: Standard institutional execution tools.
      
      

32. Seasonal & Calendar Strategies
    
    

    • What: Trade known seasonal patterns (e.g., “sell in May and go away,” end-of-month flows, harvest cycles in commodities).
      
      

    • Origin / Who: Observed empirically by market participants over centuries.
      
      

    • Success / Usage: Used by commodity and equity traders; provides edge if combined properly.
      
      

33. Machine-Learning / AI-Driven Strategies
    
    

    • What: Use ML models (supervised, reinforcement learning, deep learning) to predict returns or optimal execution.
      
      

    • Origin / Who: Grown with compute and data availability in 2000s–2020s; many quant shops and hedge funds use ML in research/alpha generation.
      
      

    • Success / Usage: Mixed; some firms leverage ML successfully, but overfitting and data-snooping are real risks.
      
      

34. Market-Sentiment / Social-Media Trading
    
    

    • What: Use sentiment analysis from Twitter, Reddit, newsfeeds to trade (momentum or contrarian).
      
      

    • Origin / Who: Increased since social platforms gained traction (2010s onward); notable retail episodes (e.g., GameStop 2021).
      
      

    • Success / Usage: Can produce outsized short-term moves; risky and noisy.
      
      

35. Liquidity-Provision & Passive Income Strategies (e.g., lending, staking, liquidity pools)
    
    

    • What: Provide liquidity or lend assets (crypto and some derivatives markets) to earn fees/yield.
      
      

    • Origin / Who: Market microstructure plus DeFi innovations (2010s–2020s).
      
      

    • Success / Usage: Popular in crypto and institutional repo markets; risk includes impermanent loss and counterparty risk.
      
      

36. Martingale / Anti-Martingale Position-Sizing (betting systems)
    
    

    • What: Martingale doubles position after losses vs anti-martingale increases size after wins.
      
      

    • Origin / Who: Gambling roots; applied by some traders.
      
      

    • Success / Usage: Martingale is widely warned against — it can wipe accounts; anti-martingale (trend sizing) is used cautiously in some systems.
      
      

37. Carry & Term-Structure Trades (commodities, rates)
    
    

    • What: Trade the futures curve (roll yield), calendar spreads (e.g., calendar spread in commodities).
      
      

    • Origin / Who: Traditional commodity desks and fixed-income traders.
      
      

    • Success / Usage: Institutional staple; requires deep understanding of storage, seasonality, and financing costs.
      
      

38. Dividend Capture / Covered Call Income
    
    

    • What: Buy before ex-dividend and sell after, or sell covered calls to generate income.
      
      

    • Origin / Who: Common income strategies in equities markets for decades.
      
      

    • Success / Usage: Used by retail and institutional income funds; tax and transaction nuances matter.
      
      

39. Macro / Global Macro Trading
    
    

    • What: Big-picture bets on rates, FX, commodities, equities based on macroeconomic views.
      
      

    • Origin / Who: Classic hedge fund strategy since the 1960s–1980s (notable macro traders: George Soros, Paul Tudor Jones).
      
      

    • Success / Usage: High-profile successes and failures — requires research and risk control.
      
      

40. Proprietary / Hybrid & Fund-Specific Strategies
    
    

    • What: Firms combine elements above into proprietary systems that are rarely fully public.
      
      

    • Origin / Who: Hedge funds and proprietary trading firms continuously innovate.
      
      

    • Success / Usage: Many large firms succeed with proprietary blends; impossible to enumerate.
      
      

 Smart Money Concepts (SMC)
What: A methodology of reading markets through liquidity, market structure, order blocks, and supply-demand zones. Focuses on how larger players accumulate and distribute positions, leaving “footprints” in price action.

Origin / Who: Emerged in the late 20th and early 21st century as a modern interpretation of Wyckoff theory combined with institutional trading principles. The term “SMC” itself became widely adopted by trading communities around the 2010s, especially among retail traders.

Success / Usage: Rapidly popular in the last decade. Thousands of traders worldwide now apply it, particularly in FX, indices, and crypto. Its success rate varies widely, as it requires deep skill in reading price action and strong risk management.

Inner Circle Trader (ICT)

What:
A trading education framework created by Michael J. Huddleston. It focuses on concepts like liquidity pools, fair value gaps (FVGs), market structure shifts (MSS), optimal trade entry (OTE), and the idea that markets are engineered to “take liquidity.” ICT blends Smart Money Concepts with Huddleston’s own terminology and models.

Origin / Who:
Founded and popularized by Michael J. Huddleston (alias: The Inner Circle Trader). He began teaching as early as the mid-2000s through mentorships and became widely known around 2010–2015 when his free and paid teachings started circulating on forums and later on YouTube.

Success / Usage:
ICT has one of the largest retail trader followings in the world today. His concepts directly inspired the SMC boom in the 2010s–2020s, though many traders now separate ICT from “general SMC.” Thousands of traders use his models daily across Forex, indices, and crypto. Some have achieved significant success, but others criticize the steep learning curve and over-complication of his models.

On “who started it” and “how many successful people use it”

• For some strategies—Wyckoff, Elliott Wave, Ichimoku, Black-Scholes, Turtle Trading—we have named founders and dates (see citations above). Investopedia+7ChartSchool+7Investopedia+7
  
  

• For many strategies there is no single inventor (price action, trend following broadly, many quant methods) — they evolved from practice, academic research, and institutional needs.
  
  

• Counting “successful people” who use a strategy is generally impossible to measure reliably:
  
  

  • “Success” is subjective and time-dependent (a strategy can work in one regime and fail in another).
    
    

  • Many strategies are proprietary; firms don’t disclose specifics or user counts.
    
    

  • Where historical examples exist (e.g., the original Turtles’ early profits), those are cited above. Investopedia