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⚠️ 风险提示
交易 involves substantial risk of loss. Most traders lose money. Past performance does not guarantee future results. This content is for educational purposes only and does not constitute investment advice.
You should never trade with money you can't afford to lose, always use proper position sizing and risk management, and thoroughly backtest any strategy before risking capital. The authors are not responsible for trading losses.
📚 Start Here: The 基础
Read these 4 articles IN ORDER before attempting any trading strategy. They cover:
- Why 90% of traders fail (with statistics)
- How markets actually work (structure and mechanics)
- Position sizing and risk management (the most important skill)
- 交易 psychology and behavioral biases
If you skip these foundations, you WILL lose money. No strategy will save you without proper risk management and psychological discipline.
第 1 级：基础 (Start Here)
Evidence-based education on trading realities, market structure, risk management, and psychology. Read in order.
1. 残酷的真相 About 交易
Why 90% of traders lose money, the mathematics of edge, and why you should probably just buy index funds instead.
2. 市场结构 & Mechanics
How markets actually work: payment for order flow, HFT advantages, dark pools, and why "free" trading costs you.
3. 风险管理大师课
Position sizing, Kelly Criterion, risk of ruin, portfolio heat, and why this matters more than your strategy.
4. 交易心理 & Behavioral Finance
Cognitive biases that kill traders, emotional discipline, and why smart people make dumb trading decisions.
第 2 级：深度解析 Loading...
Evidence-based strategies with full backtests, Python implementations, and honest performance expectations.
✅ Momentum & Mean Reversion
Complete coverage: Four institutional-quality strategy guides with complete Python code, multi-decade backtests, and proper methodology.
- 双动量: 13.8% CAGR, 0.91 Sharpe, crushes buy-and-hold
- Pairs 交易: Market-neutral, 1.42 Sharpe, 69.6% win rate
- 趋势跟随: 12.8% CAGR despite 35-45% win rate
- Backtesting: Avoid the 7 deadly sins that kill strategies
✅ Options Mastery
Complete coverage: Everything you need to trade options safely—from blow-ups to Greeks to volatility selling with proper risk management.
- Why Sellers Blow Up: Victor Niederhoffer, James Cordier, LJM—how to avoid their fate
- Covered Calls Done Right: 8-15% annual income, when to use, 0.3 delta rule
- Volatility 卖出： 10-18% returns with credit spreads, iron condors, regime-based sizing
- The Greeks: Delta, gamma, theta, vega in actual trading (not textbooks)
✅ 技术分析 That Works
Complete coverage: Statistical validation of what actually works in technical analysis—ditching the noise, keeping the edge.
- 价格行为 交易: Volume-weighted POC levels (67% hold rate), VWAP mean reversion, order flow
- 蜡烛图形态: Only 5 patterns work (62-71% win rates), rest are worthless
- 真正有用的指标: RSI divergences (71%), Bollinger Bands, ATR—99.78% of indicators fail
- 图表形态: Bull flags (68%), Cup & handle (72%), Head & shoulders overrated (52%)
✅ 高阶 风险管理 & Alternative Assets 🆕
Complete coverage: Professional-grade risk management, options strategies for retirement, and alternative asset allocation frameworks.
- Options for Income/Protection: Covered calls (8-15% income), protective puts, PMCC, when NOT to use
- Position Sizing & Risk: Kelly Criterion simplified, portfolio heat, correlation risk, stop-loss when to avoid
- Alternative Assets: REITs vs rentals, gold allocation (5-10%), crypto limits (1-3%), I Bonds/TIPS
1. 双动量 Strategy
Gary Antonacci's GEM methodology. 13.8% CAGR (50+ years), 0.91 Sharpe, -24.7% max DD. Beats S&P 500 with lower drawdowns. Full Python code.
2. Pairs 交易 & Statistical Arbitrage
Market-neutral strategy (0.12 correlation to SPY). Cointegration testing, real PEP/KO example. 1.42 Sharpe, 69.6% win rate. Complete Python implementation.
3. 趋势跟随 Systems
How to profit losing 60% of the time. Moving averages, Donchian breakouts, ATR trailing stops. 12.8% CAGR, 38% win rate, 4.2:1 win/loss ratio. Full Python code.
4. Backtesting Methodology
The 7 deadly sins of backtesting: look-ahead bias, survivorship bias, data snooping, curve-fitting. Walk-forward analysis, Monte Carlo, proper testing framework.
5. Why Option Sellers Blow Up
Victor Niederhoffer, James Cordier, LJM—all blown to zero. Naked options, no hedging, bad sizing. Learn how to sell volatility safely with defined risk and tail hedges.
6. Covered Calls Done Right
Generate 8-15% annual income on stocks you own. When to use (concentrated positions, sideways markets), optimal strike selection (0.3 delta), tax optimization, when they hurt returns.
7. Volatility Selling with 风险管理
Credit spreads, iron condors, cash-secured puts. 10-18% annual returns with proper position sizing, VIX regime-based sizing, and tail hedging. Python calculator included.
8. The Greeks in Actual 交易
Delta, gamma, theta, vega, rho—what textbooks don't tell you. Gamma kills short sellers near expiration, theta decay is non-linear, vega spikes wipe accounts. Real examples.
9. 价格行为 交易
Volume-weighted levels that matter: POC (67% hold rate), VWAP bands, auction theory, order flow. Random S/R lines = 48%. Statistical validation required.
10. 蜡烛图形态 (Statistical 分析方式)
10,000+ patterns tested: only 5 work (62-71% with context). Doji worthless (49.7%), hammer at support (67%), engulfing traps. Context is everything.
11. 真正有用的指标
99.78% of indicators fail statistical tests. RSI divergences work (71% at key levels), MACD overrated, Bollinger Bands for ranges only. ATR for position sizing.
12. 图表形态 with Real Edge
8,400+ patterns tested: Bull flags (68%), Cup & handle (72%), head & shoulders overrated (52%). Volume confirmation mandatory. Continuation > reversal.
13. Options for Income & Protection 🆕
Generate 8-15% annual income with covered calls. Protect portfolios with puts. Poor man's covered call strategy. When NOT to use options (most critical section).
14. Position Sizing & 风险管理 🆕
Kelly Criterion simplified for retail traders. Portfolio heat management (max 6%). Correlation & concentration risk. Stop-loss strategies: when to use, when to avoid.
15. Alternative Assets in Retirement Portfolios 🆕
REITs vs. rental properties (liquidity matters). Gold allocation (5-10% inflation hedge). Crypto limits (1-3% max). I Bonds and TIPS. Private equity for HNW ($5M+).
16. 均值回归交易系统 🆕
如何用 RSI、布林带和统计 Z 分数来反向操作极端超伸的行情。 Best for ranging markets.
17. 波动率突破策略 🆕
Capitalizing on volatility expansion. 交易 breakouts from tight consolidation zones and ATR squeezes.
18. 日历价差与对角价差 🆕
利用期权市场的期限结构和非线性 theta 衰减。 高阶 Greek management.
📊 What's Different About These 策略类型
- ✅ 100+ years of academic evidence (not YouTube nonsense)
- ✅ Real backtests with transaction costs included
- ✅ Shows underperformance periods (brutal honesty)
- ✅ Full Python code (actually works, not snippets)
- ✅ Risk management integrated (position sizing for each strategy)
第 3 级：专家洞察 Loading...
Institutional-quality quantitative strategies adapted for retail traders.
✅ Alpha Generation Masters 🆕🔥
NEWEST: Reverse-engineer the world's most successful quant funds. Learn how Citadel, Renaissance, Two Sigma, Bridgewater, and Jane Street actually generate alpha.
- Citadel Multi-Strategy: Combine uncorrelated streams (stat arb + vol arb + quality L/S) → 14.2% CAGR, 1.78 Sharpe
- Renaissance Signal Discovery: 1000+ weak predictors → ensemble models → 11.8% CAGR, 1.52 Sharpe (retail-adapted)
- Two Sigma ML Alpha: Alternative data + machine learning pipeline + regime detection → 12.3% CAGR, 1.41 Sharpe
- Bridgewater Pure Alpha: All-Weather + systematic trend + tail hedges (2008: +6%, 2020: +11%) → 10.8% CAGR, 1.32 Sharpe
- Jane Street 做市： ETF arbitrage + options spread capture + delta hedging → 9.7% CAGR, 1.28 Sharpe
✅ Institutional Prop 交易 策略类型
Complete coverage: 策略类型 used by Goldman Sachs, Citadel, Bridgewater, and Jane Street. Institutional approaches adapted for retail.
- Cross-Asset RV: Equity/Credit arbitrage, Gold vs Real Rates (10.2% CAGR, 1.05 Sharpe, 0.15 SPY correlation)
- Dispersion 交易: Long index vol, short component vol (15.3% CAGR, Citadel's March 2020 +40% trade)
- 3 More Coming: Carry with tail hedges, Factor timing, Structured products replication
✅ Quantitative 策略类型
Complete coverage: 高阶 strategies used by hedge funds and prop firms—stat arb, vol trading, event-driven opportunities.
- Statistical 套利： Basket trading, factor neutralization, 1.3-2.0 Sharpe ratios
- Volatility 套利： VIX futures, Volmageddon case study, tail-hedged vol selling
- Index 再平衡: Russell reconstitution (+8.1% avg), S&P 500 additions (Tesla +70%)
- Merger 套利： M&A deal trading, regulatory risk, using options for leverage
1. Citadel's Multi-Strategy Alpha Engine 🆕
How the world's most profitable hedge fund combines uncorrelated strategies (stat arb + vol arb + quality L/S). 14.2% CAGR, 1.78 Sharpe, risk parity allocation. Full Python multi-strategy framework.
Balyasny: Multi-Asset Arbitrage
Cross-asset relative value, convertible arb, and vol surface arbitrage engine.
Elliott Management: Activist Arbitrage
Forcing value realization through aggressive activist campaigns and distressed debt arbitrage.
Soros: Reflexivity & Global Macro
The Theory of Reflexivity and massive asymmetric bets in currency and bond markets.
2. Renaissance Signal Discovery 🆕
Reverse-engineer Medallion's approach: 1000+ weak predictors, ensemble modeling, transaction cost modeling. 11.8% CAGR (retail-adapted). Complete feature engineering framework with 38 signals.
3. Two Sigma's Machine Learning Alpha Factory 🆕
Alternative data + NLP sentiment (FinBERT) + regime detection (HMMs) + production ML pipeline. 12.3% CAGR, 1.41 Sharpe. Free/cheap data sources for retail.
4. Bridgewater's Pure Alpha Strategy 🆕
All-Weather risk parity + systematic trend following + tail hedges. Crisis-proof: 2008 (+6%), 2020 (+11%), 2022 (-5%). 10.8% CAGR, 1.32 Sharpe, -14% max DD.
5. Jane Street's Market Making Edge 🆕
ETF arbitrage (NAV deviations) + options market making (spread capture) + delta hedging. Retail adaptation using covered calls and cash-secured puts. 9.7% CAGR, 1.28 Sharpe.
13. Cross-Asset Relative Value 交易
Equity/Credit arbitrage, Real rates vs Gold, ADR/cross-border. Goldman Sachs & Bridgewater approach. 10.2% CAGR, 1.05 Sharpe, 0.15 SPY correlation. Full Python backtests.
14. Dispersion 交易 🆕
Long index vol, short component vol. Citadel's March 2020 +40% trade. Calendar dispersion, correlation collapse strategies. 15.3% CAGR, 1.24 Sharpe. Python implementation.
15. Statistical Arbitrage Methodologies
Beyond pairs trading: basket stat arb, factor neutralization, hedge fund approaches. 12.8% CAGR, 2.06 Sharpe, 0.04 correlation to SPY. Full Python implementation.
16. Volatility Arbitrage & Term Structure
VIX futures contango/backwardation, Volmageddon (XIV -100%), tail-hedged vol selling. 10-15% returns with proper risk management. Calendar spreads & VIX term structure tools.
17. Index 再平衡 Arbitrage
Russell reconstitution (+8.1% avg, 80% win rate), S&P 500 additions (Tesla +70%), ETF rebalancing. Front-run $200B+ in forced flows. Real 2023 examples.
18. Merger Arbitrage for Retail Traders
Trade M&A deals like hedge funds. MSFT/ATVI case study (+20.8%), deal break analysis (Qualcomm/NXP -23%), using options for capped risk. 6-10% annual returns.
🎯 What You'll Master
- ✅ Institutional strategies adapted for retail traders
- ✅ Real case studies with names, dates, dollar amounts
- ✅ Python tools for VIX analysis and stat arb
- ✅ Honest failure analysis (Volmageddon, deal breaks)
- ✅ Risk management for tail events
✅ Market Microstructure
Complete coverage: See what professional traders see—volume profile, order flow, dark pools, and execution algorithms.
- Volume Profile & Order Flow: POC, value area, auction theory, tape reading (68% win rate at support)
- Market Maker Behavior: Delta hedging, gamma squeezes (GME 24x), pin risk, max pain theory
- Dark Pool Flow: Block trade detection (72% win rate at support), institutional positioning
- Execution Algorithms: TWAP, VWAP, implementation shortfall, minimize slippage (save 0.02-0.10%)
19. Volume Profile & Order Flow 分析方式
POC, value area, HVN/LVN, auction market theory, tape reading. Institutional flow detection (absorption, exhaustion, blocks). 68% win rate at key levels.
20. Market Maker Behavior & Hedging
Delta hedging mechanics, gamma squeezes (GME case study), pin risk at expiration, max pain theory (63% accuracy). When MMs get caught.
21. Dark Pool Flow Interpretation
Block trade detection (10K+ shares), institutional positioning, dark pool index, context-based signals. 68-72% win rate when used correctly.
22. Execution Algorithms & Slippage
TWAP, VWAP, implementation shortfall, limit order strategies. Minimize trading costs (0.02-0.10% slippage reduction). Full Python implementation.
📈 Key Skills You'll Develop
- ✅ Professional-level market microstructure analysis
- ✅ Volume profile and order flow tools
- ✅ Dark pool tracking and interpretation
- ✅ Institutional execution techniques
- ✅ Real examples: GME gamma squeeze, dark pool trades
✅ Macro & Intermarket 分析方式
Complete coverage: Professional macro trading framework—business cycles, intermarket relationships, event-driven catalysts, regime-based positioning.
- The Macro Framework: Business cycle stages, Fed policy impact (QE vs QT), yield curve (85% recession prediction)
- Intermarket Relationships: Stocks/bonds correlation (2022 breakdown), dollar effects, gold signals, credit spreads
- Event-Driven 交易: Earnings IV crush (65-72% win rate), FOMC drift (+0.4% avg), NFP reversals, binary events
- Global Macro 策略： 4-regime framework, sector rotation, risk-on/off indicators, complete positioning playbook
21. The Macro Framework
Business cycle positioning (4 stages), Fed policy (QE +25%, QT -15%), yield curve inversions (85% recession accuracy, 6-24 month lead), inflation regimes, global liquidity.
22. Intermarket Relationships
Stocks/bonds correlation (2022: +0.7 breakdown, 60/40 -17.8%), dollar impacts (DXY +10% = EM -12%), gold real yield signals, credit spreads > 600bps = crash warning.
23. Event-Driven 交易
Earnings IV crush (65-72% win rate), post-earnings drift (+4.2% avg), FOMC pre-drift (+0.4%), NFP reversals (65% fade first hour), binary events (FDA, M&A).
24. Global Macro Strategy
4-regime framework (early/mid/late/recession), sector rotation (+12-18% early cyclicals), risk-on/off indicators, commodity cycles, currency carry trades, complete allocation tables.
📚 高阶 交易 Education
- ✅ Institutional-grade strategies: quant, microstructure, macro, Tier-1 alpha
- ✅ Professional frameworks: business cycles, regime positioning
- ✅ Real examples with dates, names, performance data
- ✅ Complete toolkits: allocation tables, indicator dashboards
- ✅ 42 comprehensive articles (~470,000 words)
🏆 NEW: Batch 2 - Global Macro & Structural Alphas
8 文章 Launching: Master the strategies that won in 2024-2025. These articles focus on global macro trends, emerging market arbitrage, and crisis-alpha protection during the 'Great Reversal'.
- Tudor Investment Corp: Systematic global macro, the 'Great Reversal' framework (+10% in 2024)
- Brevan Howard: Emerging markets relative value & carry-to-risk arbitrage (+15.4% in 2025)
- Man Group (AHL): Adaptive trend following & ML-based regime switching
- Capula Investment: Tail risk hedging & structural volatility alpha (+4.1% in 2025)
- Hudson River 交易: Microstructure mean reversion & order flow for retail
- Voleon Group: Deep learning (LSTMs/Transformers) for non-stationary markets
- Schonfeld Advisors: Multi-manager quant pod architectures 2.0
- Batch 2 小结: Building a crisis-proof alpha portfolio for 2026+
🧠 NEW: GPT Alpha
5 new articles: LLM-native alpha generation for readers who already understand quant basics. This is not chatbot stock-picking. It is systematic extraction of narrative, guidance, entity links, and event structure from unstructured text.
- Narrative Regime Engine: map macro and earnings language into sector and factor rotation
- Earnings Guidance Delta: trade changes in management language instead of headlines
- Supply Chain Knowledge Graph: capture second-order winners and losers
- Event Linkage 套利： map policy, legal, and geopolitical shocks into tradable baskets
- Alpha Orchestrator: combine all modules with risk gates and kill-switches
GPT Alpha Series Hub 🆕
Landing page for the full GPT alpha research stack: LLM-native signal extraction, event parsing, knowledge graphs, and portfolio orchestration.
Narrative Regime Engine 🆕
Convert FOMC, CPI, and earnings language into structured macro and sector regime labels. Trade narrative delta with basket construction and risk gates.
Earnings Guidance Delta 🆕
Compare current management language to prior guidance and consensus framing. Rank post-earnings drift candidates with structured extraction.
Supply Chain Knowledge Graph 🆕
Use entity extraction and graph logic to find second-order beneficiaries and victims across suppliers, customers, distributors, and input-cost chains.
Event Linkage Arbitrage 🆕
Turn policy, regulatory, litigation, and geopolitical text into event objects, sympathy baskets, and fade candidates with explicit timing rules.
GPT Alpha Orchestrator 🆕
Combine narrative, guidance, graph, and event signals into one portfolio using confidence scoring, exposure limits, governance, and kill-switches.
34. Tudor Systematic Global Macro 🆕🔥
Paul Tudor Jones's 'Great Reversal' thesis systematized. Multi-asset trend + macro factors. 10.4% CAGR, 1.65 Sharpe. Crisis-ready 4-regime framework. Full Python implementation.
35. Brevan Howard EM Arbitrage 🆕
EM currency and interest rate arbitrage masterclass. +15.4% performance in 2025. Institutional Carry-to-Risk frameworks adapted for retail.
36. Man Group AHL Adaptive Trend 🆕
Solving the 2024-2025 trend crisis. ML-based regime switching and non-linear trend models. Why CTAs failed and how to fix them.
37. Capula Tail Risk Alpha 🆕
Structural volatility and tail protection masterclass. +4.1% in 2025. Convexity trading and crisis-alpha hedging for retail portfolios.
38. Hudson River 交易: Microstructure 🆕
HFT microstructure mean reversion adapted for retail. Order flow, book imbalance, and volume profile POC transitions.
39. Voleon Group Deep Learning 🆕
Deep learning (LSTMs/Transformers) for non-stationary markets. How to trade when linear models and traditional ML fail.
40. Schonfeld Multi-Manager 2.0 🆕
Dynamic capital allocation across uncorrelated macro quants. Building a mini-Schonfeld pod structure for retail traders.
41. Batch 2 小结: Crisis-Proof Alpha 🆕
Building a crisis-proof alpha portfolio for 2026+. Multi-strategy integration and risk-regime orchestration.
🔥 NEW: Tier-1 Alpha 策略类型 (Batch 1)
9 文章 Complete: Reverse-engineer the world's most successful hedge funds. Full Python code, real performance data, institutional strategies adapted for retail traders.
- Point72 Cubist: ML pipeline, XGBoost ensembles, SHAP interpretability (19% returns, 2.0+ Sharpe)
- Winton Capital: Statistical arbitrage, cointegration, Kalman filters (13.4% returns, 1.5+ Sharpe)
- Millennium: Pod structure, 330+ independent strategies (14% CAGR since 1989, 2.5 Sharpe)
- AQR Capital: Factor momentum, dynamic rotation (11.4% CAGR)
- D.E. Shaw: Macro volatility, HMM regime detection (36.1% in 2024)
- Goldman Sachs: Alternative data, NLP sentiment (14.2% CAGR)
- JP Morgan: Macrosynergy, correlation trading (10.4% returns, 1.74 Sharpe)
- Balyasny: Multi-asset arbitrage (16.7% returns, $33B AUM)
25. Point72 Cubist ML Pipeline 🆕
Machine learning trading pipeline: Feature engineering (38 signals), XGBoost/LightGBM ensembles, SHAP interpretability, production deployment. 19% returns (2024), 2.0+ Sharpe.
26. Winton Statistical Arbitrage 🆕
Pairs trading at scale: Cointegration testing (Engle-Granger, Johansen), Kalman filters, mean reversion models. +13.4% returns (2024), 1.5+ Sharpe. Full Python implementation.
27. Millennium Pod Structure Strategy
Multi-strategy framework: 330+ independent pods, 5%/7.5% risk limits, dynamic capital allocation. 14% CAGR since 1989, 2.5 Sharpe ratio. Retail adaptation with 3-5 strategies.
28. AQR Factor Momentum Strategy
Combining value, momentum, quality, and low volatility with dynamic factor rotation. 11.4% CAGR, factor timing, ensemble approach. Full Python backtests.
29. D.E. Shaw Macro Volatility
Oculus fund strategy: HMM regime detection, VIX term structure arbitrage, rate transition trading, vol surface dynamics. 36.1% in 2024. Crisis-ready portfolio.
30. Goldman Sachs Alternative Data Alpha
QIS strategy: FinBERT NLP sentiment, satellite parking lot analysis, Reddit/Twitter scraping. Alternative data sources for retail. 14.2% CAGR. Full Python implementation.
31. JP Morgan Macrosynergy Strategy
Cross-asset relative value: Four-quadrant regime detection, correlation trading, dynamic risk parity, sector rotation. 10.4% returns (2024), 1.74 Sharpe. Complete framework.
32. Balyasny Multi-Asset Arbitrage
Basis trading, convertible bonds, pairs trading, cross-asset correlations. Multi-pod approach with risk management. 16.7% returns (2025), $33B AUM. Python backtests.
33. 0DTE Options Microstructure & Volatility Pinning 🆕🔥
CBOE & J.P. Morgan quantitative research on 0DTE options (>50% of SPX volume). Intraday dealer gamma exposure (GEX) flips, the 3:30 PM pin/ramp mechanics, delta-hedging equations, and Python GEX calculator. (Includes Bilingual Audio)
42. LLM Alpha & Unstructured Financial Data Mining 🆕🔥
Two Sigma Research & Point72/Cubist Systematic 策略类型: FinBERT/LLM tone extraction from 10-Q/10-K filings and earnings call Q&A vs. prepared remarks, sentiment decay half-life analysis, satellite/web-scrape alternative signals, full Python NLP pipeline. (Includes Bilingual Audio)
43. Order Flow Imbalance, Toxicity & Market Maker Internalization 🆕🔥
SEC Rule 605/606 execution data, Rama Cont's Order Flow Imbalance formula, wholesaler PFOF internalization mechanics, detecting toxic informed order flow, avoiding adverse selection, and limit vs. midpoint peg routing algorithms. (Includes Bilingual Audio)
44. Tier-1 Alpha: Complete Series 小结 📊
Compare all 9 institutional strategies side-by-side. Performance metrics, capital requirements, best combinations. Build your own multi-strategy portfolio. Strategy selection guide.
🏆 Tier-1 Alpha 策略类型
- ✅ 11 complete institutional strategy deep-dives (~370,000 words)
- ✅ Full Python implementations (production-ready code)
- ✅ Real performance data (2024 returns, Sharpe ratios, max drawdowns)
- ✅ Retail adaptations (no $100M minimum required)
- ✅ Multi-strategy portfolio construction framework
Strategy & Regime Playbook
A comprehensive summary of the core trading strategies, their pros and cons, and the market regimes where they perform best (or get destroyed).
1. 趋势跟随 (Momentum)
Mechanics: Buying assets that are going up; shorting assets going down. Using 移动平均线, Donchian Channels, and trailing stops.
Avoid In: 🔴 Choppy, sideways, low-volatility markets.
2. Mean Reversion & Statistical Arbitrage
Mechanics: Fading extreme moves based on the assumption that price/spreads revert to the historical average. Using Z-scores, RSI, Pairs 交易.
Avoid In: 🔴 Strong directional regimes or structural paradigm shifts (e.g., Tech bubble, COVID crash).
3. Volatility Selling (Short Premium)
Mechanics: Selling options (Iron Condors, Credit Spreads, Covered Calls) to harvest theta decay and implied volatility risk premium.
Avoid In: 🔴 Low IV environments transitioning into high macro uncertainty (Volmageddon).
4. Breakout & Momentum 交易
Mechanics: Buying assets as they breach key resistance levels (or shorting support) with expanding volume. Cup & Handle, Bull Flags, Volatility expansion.
Avoid In: 🔴 Choppy, low-volume, or ranging markets (summer doldrums).