Initialize trading project — Bill & Colette learning tracks
Two-person trading team setup: Bill (quant/algorithmic) and Colette (market observer). Includes phase-by-phase curriculum, separate sprint tracks, trade journal templates, roadmap to prop firm challenge, and agent handoff documentation. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
52
shared/curriculum/README.md
Normal file
52
shared/curriculum/README.md
Normal file
@@ -0,0 +1,52 @@
|
||||
# Trading Curriculum — Overview
|
||||
|
||||
## The Model
|
||||
|
||||
Bill and Colette operate as a two-person trading team with distinct roles:
|
||||
|
||||
| Role | Person | Approach |
|
||||
|------|--------|----------|
|
||||
| Quant / Engineer | Bill | ML models, scripts, backtesting, automation, signal validation |
|
||||
| Market Observer | Colette | News, macro indicators, sector themes, trade idea generation |
|
||||
|
||||
**Workflow:** Colette spots opportunities (news catalyst, macro shift, chart pattern) → flags to Bill → Bill validates with data → team decides → Bill executes or automates
|
||||
|
||||
This mirrors how small prop desks actually work. Neither role is more important — a great model with no ideas is useless, and good ideas with no discipline lose money.
|
||||
|
||||
---
|
||||
|
||||
## Bill's Track — Quant / Algorithmic
|
||||
|
||||
See: [bill-track.md](bill-track.md)
|
||||
|
||||
Phases:
|
||||
1. Market data infrastructure (APIs, data feeds, TradingView Pine Script)
|
||||
2. Technical indicator implementation and backtesting
|
||||
3. ML signal generation (classification, regression, feature engineering)
|
||||
4. Strategy automation and alerting
|
||||
5. Prop challenge execution and monitoring
|
||||
|
||||
---
|
||||
|
||||
## Colette's Track — Market Observer
|
||||
|
||||
See: [colette-track.md](colette-track.md)
|
||||
|
||||
Phases:
|
||||
1. Chart literacy and TradingView basics
|
||||
2. News and macro awareness (what matters, what's noise)
|
||||
3. Sector rotation and high-level indicators
|
||||
4. Generating and communicating trade ideas
|
||||
5. Prop challenge: managing the watchlist and flagging setups
|
||||
|
||||
---
|
||||
|
||||
## Shared Milestones
|
||||
|
||||
| Milestone | Description |
|
||||
|-----------|-------------|
|
||||
| First paper trade | Both place one paper trade and review it together |
|
||||
| First flagged setup | Colette identifies a setup → Bill backtests it |
|
||||
| First automated alert | Bill's script triggers on a Colette-identified pattern |
|
||||
| Simulated challenge pass | Both run through a prop challenge simulation |
|
||||
| Real challenge attempt | When two simulated passes are clean |
|
||||
91
shared/curriculum/bill-track.md
Normal file
91
shared/curriculum/bill-track.md
Normal file
@@ -0,0 +1,91 @@
|
||||
# Bill's Learning Track — Quant / Algorithmic
|
||||
|
||||
**Background:** Data scientist, ML experience, cybersecurity/scripting skills
|
||||
**Role:** Build and validate — data pipelines, backtests, models, automation, alerts
|
||||
|
||||
---
|
||||
|
||||
## Phase 1 — Market Data Infrastructure
|
||||
|
||||
**Goal:** Get clean, reliable data into your toolchain
|
||||
|
||||
- [ ] TradingView Pine Script basics — indicators, alerts, screeners
|
||||
- [ ] Python market data: `yfinance`, `pandas-ta`, `ccxt` (crypto if relevant)
|
||||
- [ ] Free vs paid data sources — what's actually needed at this stage
|
||||
- [ ] Build a basic OHLCV data fetcher for a watchlist of tickers
|
||||
- [ ] Understand data quality issues: survivorship bias, split adjustments, gaps
|
||||
- [ ] Set up a local data store (SQLite or Parquet) for backtesting
|
||||
|
||||
**Deliverable:** Script that pulls daily OHLCV for a watchlist and stores it locally
|
||||
|
||||
---
|
||||
|
||||
## Phase 2 — Indicator Implementation & Backtesting
|
||||
|
||||
**Goal:** Implement and test common signals before trusting them
|
||||
|
||||
- [ ] Implement SMA, EMA, RSI, MACD, ATR from scratch (don't just use a library — understand them)
|
||||
- [ ] Build a simple backtesting loop (vectorized, not event-driven to start)
|
||||
- [ ] Understand backtest traps: look-ahead bias, overfitting, survivorship bias
|
||||
- [ ] Walk-forward validation basics
|
||||
- [ ] Metrics: win rate, expectancy, Sharpe ratio, max drawdown, Calmar ratio
|
||||
- [ ] Pine Script: build a simple strategy and view equity curve in TradingView
|
||||
|
||||
**Deliverable:** One complete backtest with proper train/test split and metrics reported
|
||||
|
||||
---
|
||||
|
||||
## Phase 3 — ML Signal Generation
|
||||
|
||||
**Goal:** Apply ML where it actually adds value (not everywhere)
|
||||
|
||||
- [ ] Feature engineering for price data (returns, rolling stats, lagged features)
|
||||
- [ ] Classification: predict direction (up/down/flat next N bars)
|
||||
- [ ] Avoid the common traps: data leakage, overfitting short samples
|
||||
- [ ] Evaluate with financial metrics, not just accuracy
|
||||
- [ ] Regime detection: is the market trending, ranging, or volatile?
|
||||
- [ ] Understand when ML helps vs when simple rules beat it
|
||||
|
||||
**Deliverable:** A classifier that outputs trade signals with a documented edge (positive expectancy on out-of-sample data)
|
||||
|
||||
---
|
||||
|
||||
## Phase 4 — Automation & Alerting
|
||||
|
||||
**Goal:** React to markets without staring at screens
|
||||
|
||||
- [ ] TradingView alerts → webhook → Python handler
|
||||
- [ ] Build a market watch script (runs on schedule, flags setups from Colette's criteria)
|
||||
- [ ] Notification system (email, SMS, or Telegram bot)
|
||||
- [ ] Paper trading automation: auto-log triggered trades to journal
|
||||
- [ ] Understand execution risk: slippage, partial fills, latency (not HFT, but real)
|
||||
|
||||
**Deliverable:** Script that monitors a watchlist and sends an alert when Colette's setup criteria are met
|
||||
|
||||
---
|
||||
|
||||
## Phase 5 — Prop Challenge Execution
|
||||
|
||||
**Goal:** Apply the system under challenge conditions
|
||||
|
||||
- [ ] Simulate challenge rules in paper trading: daily loss limit, max drawdown, profit target
|
||||
- [ ] Risk sizing formula locked in (never manual)
|
||||
- [ ] Dashboard: daily P&L, drawdown remaining, progress toward profit target
|
||||
- [ ] Post-trade review script: auto-generate stats from journal
|
||||
- [ ] Two clean simulated challenge passes before paying
|
||||
|
||||
**Deliverable:** Automated prop challenge tracker with real-time status
|
||||
|
||||
---
|
||||
|
||||
## Tools & Stack
|
||||
|
||||
| Purpose | Tool |
|
||||
|---------|------|
|
||||
| Charting | TradingView |
|
||||
| Data | yfinance, pandas, pandas-ta |
|
||||
| Backtesting | Custom vectorized or `backtesting.py` |
|
||||
| ML | scikit-learn, lightgbm |
|
||||
| Automation | Python scripts + cron or systemd |
|
||||
| Alerts | TradingView webhooks + custom handler |
|
||||
| Storage | SQLite or Parquet files |
|
||||
117
shared/curriculum/colette-track.md
Normal file
117
shared/curriculum/colette-track.md
Normal file
@@ -0,0 +1,117 @@
|
||||
# Colette's Learning Track — Market Observer
|
||||
|
||||
**Background:** News-aware, macro-focused, strong intuition for market narratives
|
||||
**Role:** Observe and flag — identify macro themes, news catalysts, sector strength, and trade ideas
|
||||
|
||||
The goal is to build on the market awareness you already have and give it a framework.
|
||||
You're not learning to trade from scratch — you're learning to translate what you see into
|
||||
structured ideas that can be tested and acted on.
|
||||
|
||||
---
|
||||
|
||||
## Phase 1 — Chart Literacy (TradingView Basics)
|
||||
|
||||
**Goal:** Read a chart and understand what it's showing — no indicators yet
|
||||
|
||||
- [ ] What a candlestick shows (open, high, low, close)
|
||||
- [ ] What timeframes mean (daily vs weekly vs monthly)
|
||||
- [ ] How to spot a trend (is price making higher highs, or lower lows?)
|
||||
- [ ] What volume tells you (is this move significant?)
|
||||
- [ ] How to use TradingView: add a ticker, change timeframe, draw a line
|
||||
- [ ] What a 52-week high/low means and why people watch it
|
||||
|
||||
**Exercise:** Pull up 3 tickers. For each: is it in an uptrend, downtrend, or sideways? Is volume rising or falling?
|
||||
|
||||
**Milestone:** Can look at a chart and describe what the price is doing
|
||||
|
||||
---
|
||||
|
||||
## Phase 2 — News & Macro Awareness
|
||||
|
||||
**Goal:** Connect the news you're already reading to what it means for price
|
||||
|
||||
- [ ] What the Fed does and why interest rates matter to stocks
|
||||
- [ ] What earnings season is and how it affects price
|
||||
- [ ] What sector rotation means (money moving from tech → energy, etc.)
|
||||
- [ ] Understanding the difference between a news catalyst and a hype cycle
|
||||
- [ ] How to cross-reference a news story with the actual chart — was the move already priced in?
|
||||
- [ ] The DXYZ case study: what premium-to-NAV means, and what the historical pattern looks like
|
||||
|
||||
**Key habit:** When you see a headline or hear a recommendation, check the chart first:
|
||||
1. Did the price already move before this news broke?
|
||||
2. What's the proposed exit — where would you get out if wrong?
|
||||
3. What does the broader sector look like?
|
||||
|
||||
**Exercise:** Read a financial headline and check the chart of the ticker mentioned. Write one sentence: did the chart confirm the story, or had the move already happened?
|
||||
|
||||
**Milestone:** Can explain why the DXYZ premium exists and what historical precedents look like
|
||||
|
||||
---
|
||||
|
||||
## Phase 3 — Sector & Macro Indicators
|
||||
|
||||
**Goal:** Know the high-level picture before looking at individual stocks
|
||||
|
||||
- [ ] The major S&P 500 sectors (XLK, XLE, XLF, XLV, etc.) and how to track them
|
||||
- [ ] What the VIX is and what elevated fear looks like on a chart
|
||||
- [ ] How to read a sector heatmap (TradingView has one built in)
|
||||
- [ ] What the yield curve is (simplified: are long rates higher than short rates?)
|
||||
- [ ] Dollar strength (DXY) and its relationship to commodities and international stocks
|
||||
- [ ] How to identify the strongest sector and focus there
|
||||
|
||||
**Exercise:** Every Sunday, look at the sector ETFs for the past week. Which sector was strongest? Which was weakest? Write it down. Do this for 4 weeks in a row.
|
||||
|
||||
**Milestone:** Can give a 2-minute sector summary each week
|
||||
|
||||
---
|
||||
|
||||
## Phase 4 — Generating Trade Ideas
|
||||
|
||||
**Goal:** Turn observations into structured, communicable ideas for Bill to evaluate
|
||||
|
||||
A strong trade idea connects what you're seeing in the news or macro picture to what's happening on the chart.
|
||||
|
||||
**Example:**
|
||||
- Weak: "I read that SpaceX is doing something big."
|
||||
- Strong: "XLK has been the strongest sector 3 weeks running, NVDA just broke to a new 52-week high on heavy volume, and earnings are in 3 weeks — might be worth a look."
|
||||
|
||||
**Format for flagging an idea:**
|
||||
```
|
||||
Ticker:
|
||||
Why I noticed it: (news, chart, sector strength)
|
||||
What the chart looks like: (uptrend / breakout / pullback to support)
|
||||
Timeframe: (daily / weekly)
|
||||
Questions for Bill: (anything to backtest or dig into)
|
||||
```
|
||||
|
||||
- [ ] Submit 2 trade ideas per week using the format above
|
||||
- [ ] Review together: did the idea have merit? What happened?
|
||||
- [ ] Build a personal watchlist of 10–15 tickers you understand well
|
||||
|
||||
**Milestone:** 8 trade ideas submitted, at least 3 that Bill validated as having a testable edge
|
||||
|
||||
---
|
||||
|
||||
## Phase 5 — Prop Challenge Support
|
||||
|
||||
**Goal:** Be the eyes during the trading day while Bill's system runs
|
||||
|
||||
- [ ] Monitor the watchlist for news that could affect open trades
|
||||
- [ ] Flag upcoming macro events (Fed meeting, CPI report, earnings)
|
||||
- [ ] Keep a simple daily log: what happened in the market today (2–3 sentences)
|
||||
- [ ] Review open positions: is the original thesis still intact?
|
||||
|
||||
**Milestone:** Consistent daily market log for 30 days
|
||||
|
||||
---
|
||||
|
||||
## Recommended Resources
|
||||
|
||||
| Resource | What It's Good For |
|
||||
|----------|-------------------|
|
||||
| TradingView (free) | Charts, sector heatmap, economic calendar |
|
||||
| Finviz.com | Sector/market overview at a glance |
|
||||
| FRED (St. Louis Fed) | Real macro data — interest rates, inflation, jobs |
|
||||
| Investopedia | Clear definitions for any term |
|
||||
|
||||
**A useful filter for any recommendation you encounter:** Does the person showing you this also show you the data behind it? A good idea holds up to a chart check.
|
||||
Reference in New Issue
Block a user