---
title: "Trading and Investing — Active Trading & How Financial Markets Work (Family Root)"
description: "The front door for active trading and how financial markets actually work for a US retail participant. This skill does two jobs:"
---

# Trading & Investing (foundation + hub)

The front door for **active trading and how financial markets actually work** for a US retail participant. This skill does two jobs:

1. **Foundation** — it carries the shared overview every trading sub-topic builds on: the asset classes, the market participants, primary vs secondary markets, how an order travels from your broker to the market, market sessions and hours, the core investing-vs-trading distinction, and the risk/regulatory backbone. Deep treatments live in `references/` (loaded on demand).
2. **Hub / router** — it routes specific questions down to the family's spokes (see the routing table for the original 17-spoke plan, and the Foundation references table below for all 44 reference files as built). The spokes are the *intended* family; as each is built it owns its depth and this hub just points to it.

> **Educational information only — NOT financial, investment, tax, or legal advice, and NOT a recommendation to buy, sell, or hold anything.** All securities and trading carry **risk of loss**; you can lose money, and with leverage you can lose **more than you put in**. Past performance does not guarantee future results. **The large majority of active retail/day traders underperform a simple index or lose money** (see `references/investing-vs-trading.md`). Rules, products, tax treatment, and the vendor landscape change — every volatile claim here is stamped **as of 2026**; verify current facts with the primary regulator (SEC/Investor.gov, FINRA, CFTC, SIPC) before acting. For a personal decision, consult a licensed professional.

## Sibling skill — the passive/retirement seam (read this first if unsure)

This family is the **active** side: markets, instruments, execution, trading styles, and the risks of trading. Its sibling **`investing-and-retirement`** (in the consumer-finance family) owns the **passive, long-term, retirement** side — low-cost index buy-and-hold, 401(k)/403(b)/IRA/Roth mechanics and contribution limits, employer match and vesting, dollar-cost averaging for retirement, Social Security claiming, target-date defaults, and choosing a robo-advisor or fee-only fiduciary.

- "How do I start investing for retirement / which account / is this fund's expense ratio good / should I do a backdoor Roth / when do I claim Social Security" → **`investing-and-retirement`**.
- "How do markets work / how do I trade X / what's a limit order / is day trading worth it / how does margin work / what is options-/futures-/forex-/crypto-trading" → **this family**.

The two overlap on shared vocabulary (diversification, asset allocation, ETFs vs mutual funds, fees). When the *intent* is long-term passive wealth-building, defer to `investing-and-retirement`; when the intent is understanding markets or actively trading, stay here. `portfolio-theory-and-asset-allocation` (a spoke here) covers the *theory* (MPT, efficient frontier, factor models, rebalancing math); `investing-and-retirement` covers the *consumer how-to*.

## Routing table — the 17 planned spokes

> Spokes are the **intended family**. **Built** = reference file exists in `references/` and is listed in the Foundation references table below. **Unbuilt** = hub answers from this foundation until the spoke is built; check the available-skills list for a standalone installed skill of that slug first.

| Spoke | Build state | Route here when the question is about… |
| --- | --- | --- |
| **stock-and-equity-trading** | Built | **Market/trader side** of equities: what a share is and where it trades, long/short mechanics, active-vs-passive evidence. The **issuer side** — valuation multiples, dividends/buybacks/splits, IPOs/SPACs/lockups — split out to `equity-fundamentals-and-corporate-actions`. |
| **options-trading-and-strategies** | Built (also standalone skill) | Listed options: calls/puts, strike/expiration, the Greeks, single-leg and multi-leg strategies (spreads, straddles, covered calls, iron condors), assignment, options pricing. |
| **derivatives-futures-and-swaps** | Unbuilt | Futures, forwards, and swaps (non-options derivatives): contract specs, margin/mark-to-market, hedging vs speculation, interest-rate/FX/commodity/credit swaps, the broader derivatives landscape. |
| **technical-analysis** | Built | Reading price/volume: chart patterns, candlesticks, trend, support/resistance, indicators (RSI, MACD, moving averages, Bollinger), Dow theory, Elliott wave. Breadth/frameworks/evidence split out to `technical-analysis-breadth-frameworks-and-evidence`. |
| **trading-strategies-and-styles** | Unbuilt | The trader's playbook by style: position/swing/day-trading/scalping mechanics, momentum/mean-reversion/breakout/trend-following systems, entries/exits, backtesting a discretionary strategy. |
| **algorithmic-and-quant-trading** | Unbuilt | Systematic/automated trading: strategy coding, backtesting frameworks, execution algos, market-making/stat-arb, signals, latency, the quant research workflow. |
| **crypto-and-digital-asset-trading** | Unbuilt | Trading crypto on centralized venues: spot vs perps/futures, exchanges and custody, stablecoins, spot crypto ETFs, order books, on-exchange mechanics (CEX). |
| **forex-and-currency-trading** | Unbuilt | The FX market: currency pairs, pips/lots, leverage, carry, sessions, majors/minors/exotics, retail spot-FX mechanics and the OTC structure. |
| **trading-risk-management** | Unbuilt | Sizing and protecting trading capital: position sizing, stop placement, risk-per-trade, R-multiples, drawdown control, Kelly, portfolio heat, margin/leverage management as a discipline. |
| **portfolio-theory-and-asset-allocation** | Unbuilt | The theory: Modern Portfolio Theory, the efficient frontier, CAPM/factor models, diversification math, correlation, rebalancing, strategic vs tactical allocation. |
| **trading-psychology-and-behavioral-finance** | Unbuilt | The mind: discipline, fear/greed, loss aversion, the disposition effect, overconfidence, prospect theory, cognitive biases, trading-journal and routine practice. |
| **fixed-income-and-bond-markets** | Unbuilt | Bonds in depth: the yield curve, duration/convexity, credit spreads, Treasuries/corporates/munis, bond pricing, rate risk, the repo/money markets. |
| **market-microstructure-and-execution** | Unbuilt | How trades really execute: order book dynamics, maker-taker, Reg NMS internals, dark pools/ATSs, latency, slippage, TWAP/VWAP, sub-penny price improvement, SIP vs direct feeds. |
| **defi-and-onchain-trading** | Built | On-chain/decentralized trading: DEXs, AMMs, liquidity pools, swaps, yield/staking, MEV, bridges — the on-chain counterpart to centralized crypto. Wallets/key-security split out to `self-custody-wallets-and-key-security`. |
| **ai-and-ml-for-trading** | Built | Machine learning applied to markets: predictive models, feature engineering on market data, sentiment/alt-data, reinforcement learning for execution. Backtesting pitfalls and production systems split out to `ml-backtesting-pitfalls-and-production-systems`. |
| **trading-regulation-compliance-and-taxes** | Unbuilt | The rulebook & the IRS: SEC/FINRA/CFTC regimes, PDT/margin rules, wash sales, trader-tax-status, capital-gains mechanics for active traders, reporting, recordkeeping. **Note:** crypto-specific tax lots and the crypto wash-sale *status* question are owned by `onchain-pnl-and-tax-accounting`; this spoke keeps general §1091 mechanics and non-crypto trader taxation. |
| **onchain-pnl-and-tax-accounting** | Built (partial) | What you actually made or lost trading on-chain: realized vs unrealized P&L, the denominator/numéraire problem (a position up in SOL terms and down in USD terms), cost-basis methods, decomposing net result into price move vs fees vs borrow/funding vs slippage vs failed-transaction waste, gross vs net, self-custody wallet reconciliation — plus **crypto** tax lots (token-to-token swaps as taxable disposals, per-wallet basis under Rev. Proc. 2024-28, crypto wash-sale status, Form 1099-DA). |

## Foundation references (load on demand)

The shared foundation is split into focused references so a spoke can cross-reference one without pulling the whole hub:

| Topic | Covers | Reference |
| --- | --- | --- |
| `asset-classes-and-instruments` | The major asset classes a retail participant can access — equities, fixed income, forex, commodities, crypto/digital assets, pooled vehicles (ETFs vs mutual vs index vs target-date), and derivatives at overview depth. What each *is* and how retail accesses it. | `references/asset-classes-and-instruments.md` |
| `market-participants-and-structure` | The cast (retail, institutions, market makers, broker-dealers, exchanges, clearinghouses/CCPs), what a clearinghouse does and why it cuts counterparty risk (DTCC/NSCC, OCC), settlement & the T+1 cycle, primary vs secondary markets, exchange vs OTC, and the bid-ask spread. | `references/market-participants-and-structure.md` |
| `order-lifecycle-and-execution` | How a retail order travels broker→venue→execution→clearing→settlement; order types (market/limit/stop/stop-limit) and each one's risk; payment for order flow (PFOF) and the best-execution duty; the NBBO; the $0-commission landscape. | `references/order-lifecycle-and-execution.md` |
| `market-sessions-and-venues` | Where things trade (NYSE/Nasdaq/CME/Cboe/OTC), US equity sessions & extended hours, the 2026 move toward overnight/24-hour equity trading, how forex/crypto/futures hours differ, market holidays, and circuit breakers (market-wide + LULD). | `references/market-sessions-and-venues.md` |
| `strategy-backtesting-and-development-workflow` | **The METHOD half of the strategies spoke (§5–§6).** Backtesting a discretionary strategy — sample construction, in-sample vs out-of-sample, walk-forward, transaction-cost modelling, and which metrics flatter a strategy rather than test it; plus the development workflow from hypothesis through validation to sizing and monitoring, and where that process usually breaks. The strategy families themselves stay in `trading-strategies-and-styles`. | `references/strategy-backtesting-and-development-workflow.md` |
| `trading-strategies-and-styles` | The discretionary and semi-systematic playbook: styles by time horizon (scalping, day, swing, position trading) and the two dominant dynamics any strategy must handle — momentum (Jegadeesh-Titman 1993, cross-sectional vs time-series, momentum crashes) and mean reversion (Bollinger reversion, pairs/cointegration, half-life of reversion, when it fails); trend following and breakout (a century of trend returns, the Turtle rules, ATR-based entries, when trend fails); and how to backtest a discretionary strategy (the translation problem, data and sample-size requirements). | `references/trading-strategies-and-styles.md` |
| `algorithmic-and-quant-trading` | Systematic and quantitative trading: strategy families (stat arb, market making, momentum, mean reversion), execution algorithms (TWAP/VWAP/IS), infrastructure and latency, and **§5.3 the multiple-testing problem** — the degrees-of-freedom accounting the rest of this family defers to. | `references/algorithmic-and-quant-trading.md` |
| `trading-risk-management` | Sizing and protecting trading capital: risk per trade, position-sizing methods (fixed-fractional, **volatility-targeted/ATR**, Kelly and fractional Kelly), stop placement, drawdown measurement and risk of ruin, portfolio heat, and risk-adjusted performance metrics. | `references/trading-risk-management.md` |
| `crypto-and-digital-asset-trading` | Trading digital assets on centralized exchanges: custodial CEX platforms running central limit order books, and how that differs structurally from US equities — no Regulation NMS, no NBBO, no consolidated tape, no industry-wide spot circuit breakers, and 24/7/365 sessions. Covers CEX mechanics and order types, custody and counterparty risk, perpetual futures with funding and margin, and stablecoin mechanics. | `references/crypto-and-digital-asset-trading.md` |
| `forex-and-currency-trading` | The FX market for a retail participant: market structure and participants; currency pairs (majors, minors, exotics); reading a quote; pips and exact pip-value calculation; lot sizes; leverage and margin mechanics; P&L calculation; the carry trade and rollover rates; FX sessions and overlap timing; and transaction costs (spread vs commission). | `references/forex-and-currency-trading.md` |
| `investing-vs-trading` | The central distinction — time horizon, goal, what drives decisions, the trading-styles spectrum, active vs passive, the high-level tax angle, and the **load-bearing evidence** that most active traders underperform (Barber & Odean; Taiwan & Brazil day-trader studies). | `references/investing-vs-trading.md` |
| `trading-risks-and-protections` | The risk/regulatory backbone — the Pattern Day Trader rule **and** its 2026 replacement, margin/leverage, short selling, leveraged forex/crypto/derivatives, structural & behavioral risks, and investor protection (SIPC, BrokerCheck, the SEC mandate, the standard disclaimer). | `references/trading-risks-and-protections.md` |
| `stock-and-equity-trading` | **Market side of equities (§1, §5, §6):** what a share is and where it trades, order handling and single-name/ETF mechanics, long and short mechanics including the borrow, and the active-vs-passive evidence (SPIVA, Bessembinder). The issuer side (§2–§4) is split out — see `equity-fundamentals-and-corporate-actions`. | `references/stock-and-equity-trading.md` |
| `options-trading-and-strategies` | Listed equity/ETF/index options for a US retail participant — calls/puts, the Greeks, implied vol, and defined- vs undefined-risk strategies (spreads, straddles, condors). | `references/options-trading-and-strategies.md` |
| `defi-and-onchain-trading` | On-chain/decentralized trading: **AMM x·y=k**, concentrated liquidity (v3), **impermanent-loss math**, price impact and slippage, **MEV sandwich attacks and defence** (private RPC, intent protocols), CoW/UniswapX/1inch Fusion, perpetual DEXs (GMX/dYdX/Hyperliquid), and cross-chain bridges with their risk model. Wallets and key security are split out — see `self-custody-wallets-and-key-security`. | `references/defi-and-onchain-trading.md` |
| `ai-and-ml-for-trading` | Machine learning applied to trading, part 1: feature engineering (information bars, fractional differentiation, PIT normalization), gradient boosting with SHAP and purged CV, neural architectures, alt-data taxonomy, LLM hallucination risk, and RL for execution. Backtesting pitfalls and production systems are split out — see `ml-backtesting-pitfalls-and-production-systems`. | `references/ai-and-ml-for-trading.md` |
| `jupiter-perps-trading` | **Trader side of Jupiter Perps** — oracle-priced peer-to-pool execution, the **borrow-fee model** contrasted against funding rates (both sides always pay, never negative, utilization-driven), leverage and margin, and **liquidation-price drift** as borrow fees accrue against the position. | `references/jupiter-perps-trading.md` |
| `jlp-risk-profile-and-anti-patterns` | **The risk half of the JLP position (§3–§4) — what you are actually exposed to as the counterparty to Jupiter Perps traders.** Net open-interest skew (**85–90% long**) making JLP structurally **short leverage into rallies**; oracle and cheap-liquidity risk per Chaos Labs' 2024 warnings; audit history; and the **hedging trap** — the Drift exploit destroyed the *hedge* leg (41.7M JLP, ~$155M) while the JLP leg was fine, converting market risk into counterparty risk on the hedge venue. Plus the twelve LP-side anti-patterns. | `references/jlp-risk-profile-and-anti-patterns.md` |
| `jupiter-perps-leverage-and-liquidation` | **How a Jupiter Perps position is margined and how it dies (§3–§4).** The 1.1x–250x range and collateral rules; why the **liquidation price DRIFTS** as borrow fees accrue against the position rather than sitting fixed; the **100%-of-remaining-collateral** liquidation penalty; the stop-vs-liquidation race; and the trader-side anti-patterns, chief among them treating the borrow fee as a funding rate. | `references/jupiter-perps-leverage-and-liquidation.md` |
| `jupiter-jlp-pool` | **LP side of Jupiter Perps** — JLP composition and target weights, mint/redeem mechanics, how trader fees accrue into the virtual price, the **LP-as-counterparty payoff** (you are short trader P&L), and the resulting risk profile. | `references/jupiter-jlp-pool.md` |
| `grid-trading-strategy` | **Grid trading as a systematic strategy, and the reporting illusion at its centre.** Arithmetic vs geometric spacing, level count and width, the martingale property and why inventory accumulates against you; fee-drag arithmetic that kills over-dense grids; and the **measured closed-trade illusion** — a bear month logging +$95 closed P&L at a 100% win rate while the account fell 37.5%. | `references/grid-trading-strategy.md` |
| `jupiter-swap-routing-and-orders` | **Jupiter's swap/aggregation and order layer** — how a route is built and split across venues, quote-vs-fill drift and slippage settings, versioned transactions and address-lookup tables, and the order products (limit, DCA, recurring) with what each actually guarantees. | `references/jupiter-swap-routing-and-orders.md` |
| `solana-dex-and-amm-landscape` | **The Solana venue layer** — Raydium, Orca, Meteora, Phoenix and the CLOB/AMM split; concentrated-liquidity and DLMM mechanics; how liquidity is actually fragmented across venues and what that means for a router; LP economics and impermanent loss in the Solana context. | `references/solana-dex-and-amm-landscape.md` |
| `sampling-frequency-and-bar-aggregation` | **How often you sample the market — the most under-examined parameter in retail strategy design.** What it controls (signal-to-noise, indicator lag, trade count and fee drag); the **period × interval coupling** that makes "EMA(24)" meaningless alone; aliasing and why a faster feed is not a better one; bar types (time/tick/volume/dollar); and the measured **~50pp swing on SOL from frequency alone**, with hourly selected in 0 of 48 months. | `references/sampling-frequency-and-bar-aggregation.md` |
| `solana-oracles-pyth-switchboard` | **The price layer underneath Solana perps, lending and liquidations.** Push-vs-pull architecture and why Pyth moved to pull in V2; ~400ms publisher cadence; the **confidence interval** that quantifies publisher disagreement and how to gate on it; Switchboard's customisable aggregator; who pays for the update and the staleness surface that creates; and oracle risk as it reaches a trader. | `references/solana-oracles-pyth-switchboard.md` |
| `solana-execution-agents-keepers-and-rfq` | **Who actually executes your order when you do not.** The keeper model and the economics deciding whether one shows up for *your* order — small orders can go unexecuted with the condition met, and keeper reliability degrades exactly when volatility spikes. Where keepers appear (Perps request/fulfill, Trigger, Recurring, liquidations); RFQ/market-maker flow; liquidators as adversarial keepers and the stop-vs-liquidation race. | `references/solana-execution-agents-keepers-and-rfq.md` |
| `trading-bot-infrastructure-and-monitoring` | **Running a strategy as software rather than describing one.** RPC/data access (websockets failing silently; your data source is a strategy parameter); state, restarts and idempotency (on-chain as single source of truth, the submitted-but-unconfirmed window, why grids are especially exposed); the live-vs-backtest divergence checklist; **monitoring equity not trades**; alerting on absence; and opsec for a key that moves money. | `references/trading-bot-infrastructure-and-monitoring.md` |
| `sleeve-weighting-and-objective-selection` | **How much capital each sleeve gets — and first, what you are optimising for.** Mean return, worst month, risk-adjusted and hit rate rank the same blends *oppositely* (measured: three objectives, three different winners on identical data). The scheme ladder (equal, inverse-vol, risk parity, min-variance, Kelly) ordered by how much each must **estimate**; why correlation-based schemes are fragile when the input swings −0.58 to +0.68; the **plateau** argument for round-number weights. | `references/sleeve-weighting-and-objective-selection.md` |
| `cross-asset-generalisation-testing` | **Whether a result is a property of the strategy or of the one price series you tested it on.** The five-rung generalisation ladder and what each rung actually rules out; why a correlated second asset **falsifies well but confirms poorly**, so a break is strong evidence and a pass is weak; what to hold fixed (logic, protocol) vs re-fit (parameters, via the *same* procedure); and **parameter stability as a more informative signal than returns**. | `references/cross-asset-generalisation-testing.md` |
| `asset-specific-vs-universal-parameters` | **Which parameters travel between assets and which must be re-fitted.** Three classes (structural / scale-dependent / asset-specific) and the test that assigns one: run the identical selection procedure on both assets and compare **selected values, not returns**. Normalisation converts most apparently-asset-specific parameters into structural ones. Measured: 10-level grid and 4-hourly sampling modal on both SOL and BTC, while trend's edge **flipped sign** — agreeing parameters do not imply a universal edge. | `references/asset-specific-vs-universal-parameters.md` |
| `selection-rule-design` | **The third walk-forward knob nobody tests — the RULE that picks a config from the training window.** Five candidates (argmax mean, median, Sharpe, maximin, rank aggregation) and what each implicitly believes carries forward; **the two controls that make a selection experiment interpretable** — a RANDOM baseline (does selection beat blind picking?) and an ORACLE bound (how much was even available?). Measured over 48 OOS months: all five rules beat random (-1.61%) and the incumbent sits outside random's 95% band, but captured only **29% of the random->oracle span** and **buy-and-hold (+5.64%) still beat every rule**. The **maximin paradox** — selecting on the worst training month produced the WORST out-of-sample tail, because a 12-month minimum is one noisy observation. Rule and window interact, so they cannot be tuned separately. | `references/selection-rule-design.md` |
| `walk-forward-window-length-and-refit-cadence` | **The two walk-forward knobs almost everyone inherits without testing: selection-window length and refit cadence.** The **common-OOS-window trap** (a longer window leaves fewer test months, so naive comparisons confound knob with sample). Measured over 28 cells on identical months: **monthly refitting was sub-optimal at 7 of 7 window lengths**; the inherited window (12) was good, the inherited cadence was not; **all 28 cells lost money**. Two seductive sub-readings that do NOT survive scrutiny: the worst-month column is ONE month, and the raw config-switch drop reverses once normalised. | `references/walk-forward-window-length-and-refit-cadence.md` |
| `empirical-backtest-findings-log` | **The measured-results log for this family — including the runs that FALSIFIED claims made elsewhere in it.** The closed-trade illusion measured; two caveats this data disproved (bar fills were NOT optimistic; a trend prediction that was simply wrong); a 240-config sweep in which **zero configs rescued the bear month**; walk-forward quantifying selection bias (+42% in-sample → +4.24% OOS); the out-of-sample result that **reversed** an earlier in-sample rejection; correlation instability; the cross-asset test. | `references/empirical-backtest-findings-log.md` |
| `regime-detection-and-classification` | **How to tell which regime you are in, and whether acting on that belief is worth anything.** Four axes worth classifying separately (trend↔range, vol level, vol direction, liquidity); detector families — ADX/Bollinger bandwidth, Hurst and variance ratio, GARCH/MS-GARCH, Markov-switching/HMM, CUSUM/Bayesian changepoint; **the lag problem** — every method lags, so a filter cuts wrong-regime exposure but never prevents the transition loss. | `references/regime-detection-and-classification.md` |
| `strategy-failure-modes-and-synergy` | **What breaks each strategy and indicator, and how to combine them so failures offset rather than compound.** Per-strategy and per-indicator failure atlases with the observable signature of each; the **convex-vs-concave payoff principle** behind real diversification; a compensation matrix (failure → detector → offsetting instrument); five synergy architectures; and the anti-synergies that look diversifying but are not. | `references/strategy-failure-modes-and-synergy.md` |
| `onchain-pnl-and-tax-accounting` | Knowing what you actually made on-chain: realized vs unrealized P&L, the **denominator problem** (up in SOL terms, down in USD terms), cost-basis methods (FIFO/LIFO/HIFO/spec-ID), P&L attribution splitting result into price move vs fees vs borrow vs slippage vs failed-transaction waste, and crypto tax lots — token-to-token swaps as taxable disposals, per-wallet tracking, wash-sale status. | `references/onchain-pnl-and-tax-accounting.md` |
| `technical-analysis` | Reading price and volume, part 1 (§1–§7): chart types and candlestick patterns, chart patterns (H&S, double top/bottom, triangles, flags, wedges), trend analysis and trendlines, support/resistance, and the core indicators — RSI, MACD, Bollinger Bands, SMA/EMA, ATR, stochastics. Breadth, the classical frameworks and the academic evidence are split out — see `technical-analysis-breadth-frameworks-and-evidence`. | `references/technical-analysis.md` |
| `indicator-signal-implementation-and-backtesting` | **Runnable pandas/numpy implementations of the price-derived signal families** — trend/MA, momentum oscillators, volatility — with exact equations and input dependencies; plus the implementation substrate that silently breaks them: **Wilder smoothing vs `ewm(span=n)`** (5.24 RSI points, 64% more signals), warm-up convergence, **one bar of look-ahead = +3.8 Sharpe**, repainting, TA-Lib parity. Backtest protocol and the other three signal families are split out (see next two rows). | `references/indicator-signal-implementation-and-backtesting.md` |
| `signal-backtest-protocol-and-regime-evidence` | **How to backtest ONE signal without lying to yourself, plus the cited record of when each family actually worked.** Anchored vs rolling walk-forward, purging, embargo, overlapping labels; explicit cost model and **break-even cost in bps**; the mandatory multiple-testing battery (Reality Check, SPA, FDR, PBO, Deflated Sharpe); and the regime evidence — BLL 1992 vs Sullivan-Timmermann-White 1999 vs Bajgrowicz-Scaillet FDR, decay, the TSMOM smile. | `references/signal-backtest-protocol-and-regime-evidence.md` |
| `signal-pairing-volume-and-pattern-signal-sets` | **Whether two signals are independent confirmation or one bet counted twice** — runnable independence test (correlation, agreement rate, PCA effective dimensionality; six "different" indicators measured as three bets; Williams %R proven identical to Stochastic %K-100). Plus the three non-oscillator families: volume/breadth, candlesticks, and price-action structure (BOS/ChoCH, S/R zones, pivots, Fibonacci). | `references/signal-pairing-volume-and-pattern-signal-sets.md` |
| `technical-analysis-breadth-frameworks-and-evidence` | **The market-internals, framework and evidence half of technical analysis (§8–§12).** Volume and breadth (OBV, anchored VWAP, Volume Profile/POC, A-D line, McClellan Oscillator and Summation, Zweig Breadth Thrust); the classical frameworks (Dow Theory, Elliott Wave and the Batchelor-Ramyar critique); multi-timeframe analysis; and the **empirical record** — Fama, BLL 1992, Sullivan et al. 1999, Park & Irwin 2007, Lo et al. 2000, the Adaptive Market Hypothesis. | `references/technical-analysis-breadth-frameworks-and-evidence.md` |
| `ml-backtesting-pitfalls-and-production-systems` | **Why an ML backtest overstates what a live model will do, and what keeps a deployed one honest.** The four-mechanism look-ahead taxonomy (data leakage, point-in-time failure, survivorship, label-construction leakage); multiple testing and strategy mining (Harvey/Liu/Zhu's 316-factor audit, the t > 3.0 threshold); PBO and Deflated Sharpe; and production concerns — IC monitoring, drift detection, retraining discipline. | `references/ml-backtesting-pitfalls-and-production-systems.md` |
| `equity-fundamentals-and-corporate-actions` | **Issuer side of the equity spoke — the company behind the share.** Valuation multiples and their limits (P/E, earnings yield, PEG, basic vs diluted EPS, P/B), what a company does with its capital (dividends, buybacks, splits), and how shares are first created and sold (IPOs, direct listings, SPACs, lockups). Split verbatim from `stock-and-equity-trading` §2–§4 with numbering preserved. | `references/equity-fundamentals-and-corporate-actions.md` |
| `self-custody-wallets-and-key-security` | **Holding your own keys — the custody layer beneath on-chain trading.** Browser hot wallets (MetaMask vs Rabby, pre-transaction simulation, BIP-39 derivation); hardware wallets (Ledger Secure Element vs Trezor open-source firmware, the Ledger Recover controversy, **blind-signing risk** on complex DeFi calldata); seed-backup practice; and token-approval hygiene. | `references/self-custody-wallets-and-key-security.md` |

## How to answer from this hub (output contract)

When answering directly from this foundation: (1) for any advice-seeking question, **lead with the educational-only / not-advice framing** and that trading carries risk of loss; (2) **cite the primary regulator** (SEC/Investor.gov, FINRA, CFTC, SIPC) for load-bearing facts, and stamp volatile facts *as of 2026* with a "verify current" pointer; (3) when the question belongs to a spoke whose **reference file exists** in the Foundation references table above, `Read` its `references/<slug>.md` and answer from it — if a standalone installed skill also exists for that spoke, the standalone skill takes precedence; if the Read fails or the reference is silent on the specific question, degrade to foundation depth; (4) when the question belongs to a spoke **not yet in the Foundation references table**, first check the available-skills list for a standalone installed skill of that spoke's slug — if found, invoke it; otherwise name the destination spoke and answer at foundation depth; (5) when a query spans two spokes, identify the **primary spoke** (the one that owns the action) and answer from it, citing the secondary spoke for supplementary detail. Keep US-centric, flagging where a fact (T+1, PDT, SIPC, Reg NMS, CFTC caps) is US-only.

## First, the account (the gate before anything else)

Everything downstream runs through a **brokerage account** opened with a broker-dealer (after identity verification, funded from a bank). The one account choice that gates the rest is **cash vs margin**: a **cash account** trades only settled funds (no borrowing); a **margin account** lets the broker **lend you money** against the account as collateral — which is what enables short selling and triggers the margin and Pattern-Day-Trader rules in `references/trading-risks-and-protections.md`. Account *type* (individual/joint/retirement-wrapper) sits on top of that; a retirement-wrapper account points to the passive sibling, `investing-and-retirement`.

## The one-paragraph foundation (if you only read the hub)

A **retail participant** buys and sells **instruments** (equities, bonds, FX, commodities, crypto, pooled funds like ETFs/mutual funds, and derivatives) through a **broker-dealer**, which routes the order to an **execution venue** (an exchange like NYSE/Nasdaq, a wholesaler/market maker, or an ATS); the trade then **clears** through a central counterparty (NSCC for US equities, OCC for listed options) and **settles** the next business day (**T+1**, as of 2026). The issuer raises money only once, in the **primary market** (an IPO or new issue); everything after is the **secondary market**, where investors trade among themselves and prices are discovered. **Investing** means holding for the long term to build wealth through compounding; **trading** means buying and selling frequently to profit from price moves — and the evidence is strong that **most active retail traders underperform or lose money**, so trading capital should be money you can afford to lose. Markets are regulated (SEC, FINRA, CFTC) and your *brokerage account* is protected against broker failure by **SIPC** — but **nothing protects you against market losses**.

## Cross-cutting notes

**`as of 2026` volatile claims to re-verify** (detail in the references) — one line each, highest-stakes first:

- **Pattern Day Trader rule is being replaced** (highest-stakes): FINRA amended Rule 4210 to drop the $25k/PDT designation for a new **intraday-margin** framework, **effective June 4, 2026** (transition through Oct 20, 2027). Most third-party sites still describe the legacy $25k rule — verify your broker's *current* policy.
- **Settlement is T+1** (since May 28, 2024); **SIPC** limits are **$500k / $250k cash** — both change, verify at the regulator.
- **Spot Bitcoin ETFs** (approved Jan 2024) and **spot Ether ETFs** (Jul 2024) exist and have grown large.
- **Nasdaq 23-hour trading** was SEC-approved (Apr 10, 2026), launch targeted H2 2026; **CME launched 24/7 crypto futures** (May 29, 2026).
- US retail **forex leverage** is capped (~50:1 majors / ~20:1 others) by CFTC/NFA; **$0 stock/ETF commissions** are standard; capital-gains breakpoints change yearly.

Other seams:

- **Commodities routing.** Commodities are an asset class in the foundation, but there is **no dedicated commodities spoke** — route commodity *futures* depth to `derivatives-futures-and-swaps` and commodity *ETP/ETF* depth to `stock-and-equity-trading`.
- **Tax seam.** This family's `trading-regulation-compliance-and-taxes` spoke owns the *trader's* tax detail (wash sales, trader-tax-status, active-trader capital-gains mechanics). The consumer-finance family's `personal-income-taxes` owns ordinary individual filing. Keep deep tax out of the foundation — it states only the short-vs-long-term-gains distinction at a high level.
- **Fraud seam.** Spotting an investment scam and the "is this a Ponzi / guaranteed-returns" pattern is shared with `investing-and-retirement`; recovery *after* a scam → `consumer-credit-and-debt` (references/identity-theft-and-credit-fraud.md).
- **Blockchain seam.** Trader-side DeFi (executing swaps on DEXs, managing liquidity positions, MEV defense, perp DEX trading, bridge mechanics for moving assets) is owned here in `defi-and-onchain-trading`. Protocol mechanics, cryptoeconomics, and the academic/research layer (AMM math derivation, MEV supply-chain/PBS theory, tokenomics, consensus) → `blockchain` / `blockchain-economics`.
- **Per-asset coin seam.** The foundation covers crypto as an *asset class*; the per-coin facts a sizing or backtest decision actually needs (is the market cap real, float/unlocks/concentration, turnover and exit depth, which venues list it and how much history exists, per-coin vol/beta/correlation, whether a result on one coin transfers to another) → `crypto-coin-intelligence`.
- **Data/quant seam.** The math/ML *techniques* behind quant and ML-for-trading (regression, time-series, feature engineering, backtesting statistics) draw on the `da-*` data-analysis hubs; the trading spokes own the market application, the `da-*` hubs own the method.
- **International note.** This family is **US-centric**. Other major markets (LSE, Euronext, Tokyo, Hong Kong, Shanghai) run their own hours, regulators, settlement cycles, and tax regimes; the foundation flags where the US specifics (T+1, PDT, SIPC, Reg NMS, CFTC leverage caps) are US-only and would differ abroad.

## References

Each foundation reference carries its own cited `## References` / `## Sources` section anchored to primary authorities — **SEC / Investor.gov, FINRA, CFTC, SIPC, DTCC, OCC, the Federal Reserve / BIS, S&P Dow Jones Indices (SPIVA)**, and the peer-reviewed household-finance literature (**Barber & Odean**; the **Taiwan** and **Brazil** day-trader studies). Volatile facts are dated *as of 2026* with "verify current" pointers. Start from the relevant reference above; as further spokes are built, each will carry its own deeper citations.

<!-- cross-hub-map -->
## Cross-hub map — where every trading-and-investing topic lives

All active-trading material lives under this single hub. Built reference files are listed below; for unbuilt spokes, check whether a standalone installed skill exists for that slug and invoke it, or answer at foundation depth.

| Hub | Owns | Example reference files |
| --- | --- | --- |
| `trading-and-investing` | Trading & Investing — all active trading, markets, and risk topics | `references/asset-classes-and-instruments.md`, `references/market-participants-and-structure.md`, `references/order-lifecycle-and-execution.md`, `references/market-sessions-and-venues.md`, `references/investing-vs-trading.md`, `references/trading-risks-and-protections.md`, `references/stock-and-equity-trading.md`, `references/options-trading-and-strategies.md`, `references/defi-and-onchain-trading.md`, `references/ai-and-ml-for-trading.md`, `references/technical-analysis.md`, `references/jupiter-perps-trading.md`, `references/jupiter-jlp-pool.md`, `references/grid-trading-strategy.md`, `references/onchain-pnl-and-tax-accounting.md`, `references/indicator-signal-implementation-and-backtesting.md`, `references/strategy-failure-modes-and-synergy.md`, `references/regime-detection-and-classification.md`, `references/sleeve-weighting-and-objective-selection.md`, `references/cross-asset-generalisation-testing.md`, `references/asset-specific-vs-universal-parameters.md`, `references/walk-forward-window-length-and-refit-cadence.md`, `references/selection-rule-design.md`, `references/strategy-backtesting-and-development-workflow.md`, `references/jlp-risk-profile-and-anti-patterns.md`, `references/jupiter-perps-leverage-and-liquidation.md`, `references/signal-backtest-protocol-and-regime-evidence.md`, `references/signal-pairing-volume-and-pattern-signal-sets.md`, `references/equity-fundamentals-and-corporate-actions.md`, `references/technical-analysis-breadth-frameworks-and-evidence.md`, `references/ml-backtesting-pitfalls-and-production-systems.md`, `references/self-custody-wallets-and-key-security.md`, `references/empirical-backtest-findings-log.md`, `references/sampling-frequency-and-bar-aggregation.md`, `references/solana-oracles-pyth-switchboard.md`, `references/solana-execution-agents-keepers-and-rfq.md`, `references/trading-bot-infrastructure-and-monitoring.md`, `references/solana-dex-and-amm-landscape.md`, `references/jupiter-swap-routing-and-orders.md` |