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:
102
AGENT_HANDOFF.md
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# Agent Handoff Note
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This file is for Claude (or any AI assistant) picking up this project mid-stream.
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Read this before touching anything in this repo.
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---
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## What This Project Is
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Bill and his mom Colette are learning to trade together with the goal of passing a prop firm challenge and managing a firm account for income.
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Bill is a data scientist with ML and cybersecurity/scripting skills.
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Colette is new to trading but actively watches financial news and markets.
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They operate as a two-person team:
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- **Bill** = quant/engineer — builds models, scripts, backtests, automation
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- **Colette** = market observer — spots macro themes, news catalysts, trade ideas
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Colette surfaces ideas. Bill validates them with data. They decide together.
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---
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## Current State
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- TradingView installed on Bill's Ubuntu Linux machine (`~/trading/` is the project root)
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- Both tracks are in **Phase 1 / Sprint 01** — nothing has been built yet
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- No prop firm has been chosen yet (decision due end of Sprint 01)
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- No asset class has been decided yet (stocks, futures, or forex)
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---
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## Directory Structure
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```
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~/trading/
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├── README.md ← project overview
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├── ROADMAP.md (in shared/) ← timeline, prop firm options
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├── AGENT_HANDOFF.md ← this file
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├── shared/
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│ ├── ROADMAP.md
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│ ├── curriculum/
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│ │ ├── README.md ← team model overview
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│ │ ├── bill-track.md ← Bill's 5-phase quant curriculum
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│ │ └── colette-track.md ← Colette's 5-phase observer curriculum
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│ ├── sprints/ ← shared sprint files (currently empty)
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│ └── resources/ ← links, PDFs, reference material
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├── bill/
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│ ├── sprints/sprint-01.md ← data pipeline + Pine Script setup
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│ ├── journal/template.md
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│ ├── backtests/
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│ ├── watchlists/
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│ ├── notes/
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│ └── scripts/ ← Python scripts live here
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└── colette/
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├── sprints/sprint-01.md ← chart literacy (TradingView basics)
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├── journal/template.md
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├── backtests/
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├── watchlists/
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└── notes/
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```
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---
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## Key Decisions Already Made
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- No HFT — target is algorithmic swing/day trading on daily or hourly timeframes
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- Paper trading first, then simulated prop challenge passes, then real challenge
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- Colette's track avoids heavy math — she communicates ideas in a structured format, Bill backtests them
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- Sprint cadence: separate sprints per person, reviewed together
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---
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## What To Do When Helping
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**For Bill:** He can handle Python, ML, Pine Script, scripting, and data pipelines.
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Jump straight to implementation — he doesn't need concepts explained from scratch.
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Frame suggestions in terms of data quality, edge validation, and risk math.
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**For Colette:** She reads this repo too. Keep language clear and non-condescending.
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Her intuition about markets and news is an asset, not a liability.
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When she asks questions, connect the answer to something she already understands.
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---
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## Next Steps (as of project init)
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1. Bill: complete Sprint 01 — build `fetch_data.py` data pipeline
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2. Colette: complete Sprint 01 — TradingView chart literacy exercises
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3. Both: decide asset class focus and target prop firm
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4. Bill: set up TradingView alerts → webhook pipeline
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5. First collaborative milestone: Colette flags a setup, Bill backtests it
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---
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## Technical Environment
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- OS: Ubuntu Linux
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- Shell: bash
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- Python: available (venv to be set up in `bill/scripts/`)
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- TradingView: installed as .deb
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- Git remote: Gitea at borgswarm:3000
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- SSH key: `~/.ssh/id_ed25519.pub`
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34
README.md
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README.md
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# Bill & Colette — Trading Project
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## Goal
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Learn to trade systematically, build a proven strategy, and pass a prop firm challenge.
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## Directory Structure
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```
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~/trading/
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├── README.md ← you are here
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├── shared/
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│ ├── ROADMAP.md ← timeline and prop firm options
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│ ├── curriculum/
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│ │ └── README.md ← full phase-by-phase learning plan
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│ ├── sprints/
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│ │ └── sprint-01.md ← current sprint tasks
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│ └── resources/ ← links, PDFs, reference material
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├── bill/
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│ ├── journal/ ← trade log (copy template.md per trade)
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│ ├── backtests/ ← backtest results and notes
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│ ├── watchlists/ ← saved tickers and setups
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│ ├── notes/ ← learning notes
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│ └── scripts/ ← Pine Script / Python scripts
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└── colette/
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├── journal/ ← trade log
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├── backtests/
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├── watchlists/
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└── notes/
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```
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## Where to Start
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1. Read [shared/ROADMAP.md](shared/ROADMAP.md)
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2. Open [shared/sprints/sprint-01.md](shared/sprints/sprint-01.md)
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3. Work through Sprint 01 tasks together
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26
bill/journal/template.md
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bill/journal/template.md
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# Trade Journal — Bill
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## Trade Entry Template
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**Date:**
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**Ticker:**
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**Direction:** Long / Short
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**Timeframe:**
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**Entry Price:**
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**Stop Loss:**
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**Target:**
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**Risk/Reward:**
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**Position Size:**
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**Setup Description:**
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_(Why did you take this trade? What did you see?)_
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**Result:**
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- Exit Price:
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- P&L:
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- Outcome: Win / Loss / Breakeven
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**Review:**
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_(Did you follow your rules? What would you do differently?)_
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---
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44
bill/sprints/sprint-01.md
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# Bill — Sprint 01: Market Data Infrastructure
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**Track:** Quant / Algorithmic — Phase 1
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**Duration:** 2 weeks
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**Goal:** Get a working data pipeline and understand the data landscape before building anything on top of it.
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---
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## Tasks
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### Environment Setup
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- [ ] Create Python virtual environment in `~/trading/bill/scripts/`
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- [ ] Install: `yfinance pandas pandas-ta matplotlib sqlite3 requests`
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- [ ] Verify TradingView Pine Script editor opens (Chart → Pine Editor)
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### Data Pipeline
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- [ ] Write a script that pulls daily OHLCV for a list of tickers via yfinance
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- [ ] Store results in SQLite or Parquet in `~/trading/bill/backtests/data/`
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- [ ] Handle edge cases: missing data, stock splits, delisted tickers
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- [ ] Pull at least 5 years of history for SPY, QQQ, and 3 tickers of your choice
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### TradingView Orientation
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- [ ] Write a basic Pine Script indicator (start with a simple EMA crossover)
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- [ ] Understand how TradingView alerts work and what webhook delivery looks like
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- [ ] Explore the built-in Strategy Tester — understand what the equity curve and metrics mean
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### Research
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- [ ] Survey free vs paid data sources (yfinance limitations, Alpaca, Polygon.io)
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- [ ] Understand what a prop firm's execution environment looks like — do they support algos?
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- [ ] Read one article on walk-forward validation vs simple train/test split
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---
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## Deliverable
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A script (`fetch_data.py`) that:
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1. Takes a list of tickers and a date range
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2. Fetches OHLCV from yfinance
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3. Saves to local storage
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4. Prints a summary: rows fetched, date range, any gaps flagged
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---
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## Notes
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_(add as you go)_
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colette/journal/template.md
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# Trade Journal — Colette
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## Trade Entry Template
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**Date:**
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**Ticker:**
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**Direction:** Long / Short
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**Timeframe:**
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**Entry Price:**
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**Stop Loss:**
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**Target:**
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**Risk/Reward:**
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**Position Size:**
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**Setup Description:**
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_(Why did you take this trade? What did you see?)_
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**Result:**
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- Exit Price:
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- P&L:
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- Outcome: Win / Loss / Breakeven
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**Review:**
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_(Did you follow your rules? What would you do differently?)_
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---
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colette/sprints/sprint-01.md
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# Colette — Sprint 01: Chart Literacy
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**Track:** Market Observer — Phase 1
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**Duration:** 2–3 weeks (go at your own pace)
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**Goal:** Be able to look at any stock chart and describe what the price is doing.
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No math. No formulas. Just learning to read the picture the market is drawing.
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---
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## Setup
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- [ ] Log into TradingView (Bill will help with first login)
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- [ ] Set chart type to "Candles" and timeframe to "1D" (daily)
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- [ ] Add these tickers to a watchlist: SPY, QQQ, NVDA, DXYZ, AAPL
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---
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## Week 1 — Reading Candlesticks
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A candlestick shows 4 things: where price **opened**, where it **closed**, the **highest** point, and the **lowest** point that day.
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**Tasks:**
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- [ ] Watch: look up "how to read a candlestick chart" on Investopedia (read the article, not YouTube)
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- [ ] On TradingView, hover over 5 different candles on SPY. Read the open/high/low/close values.
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- [ ] Find one green candle with a long wick on top — what does that wick mean?
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- [ ] Find one red candle with a long wick on the bottom — what does that mean?
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**Question to answer:** On SPY's daily chart, is the price higher or lower than it was 6 months ago?
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---
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## Week 2 — Spotting Trends
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A trend is just: is price generally going up, down, or sideways?
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**Tasks:**
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- [ ] Look at SPY on a weekly chart (change "1D" to "1W"). Describe the trend in one sentence.
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- [ ] Look at DXYZ on a daily chart. When did it spike? What was happening in the news at that time?
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- [ ] Look at QQQ. Draw a line (use the Line tool) connecting the recent lows. Is that line going up or down?
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- [ ] Compare NVDA and AAPL — which one has been stronger over the last 3 months?
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**Question to answer:** If a stock is making higher highs and higher lows, is that an uptrend or downtrend?
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---
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## Week 3 — Volume
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Volume is how many shares were traded that day. High volume = people care. Low volume = nobody cares.
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**Tasks:**
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- [ ] Find a day on SPY where volume was much higher than usual. What was happening?
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- [ ] Find a big up day on any ticker with LOW volume. Is that move trustworthy?
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- [ ] Look at DXYZ — was volume high when the price spiked? What does that tell you?
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---
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## Sprint Milestone
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By the end of this sprint, you should be able to:
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- [ ] Look at any chart and say: uptrend, downtrend, or sideways
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- [ ] Identify if a candle had a significant wick and explain what it means
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- [ ] Explain why volume matters
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- [ ] Describe what DXYZ did and why it's risky
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---
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## Notes & Questions
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_(write down anything confusing — Bill can explain or we can look it up together)_
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shared/ROADMAP.md
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# Trading Roadmap — Bill & Colette
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## Target Outcome
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Pass a prop firm challenge and trade a firm account for income.
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## Timeline (estimated)
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```
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Month 1 [Phase 1] Foundations + TradingView setup
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Month 2 [Phase 2] Technical Analysis
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Month 3-4 [Phase 3] Strategy Development + Backtesting
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Month 5-6 [Phase 4] Paper Trading (live simulation)
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Month 7 [Phase 5] Prop Challenge Prep
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Month 8+ [Phase 6] Challenge Attempt
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```
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This is a realistic timeline if you put in 5–10 hours/week.
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Rushing phases 3–5 is the most common mistake — a strategy needs real testing time.
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## Prop Firm Options (to decide by end of Sprint 01)
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| Firm | Challenge Cost | Account Size | Rules |
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|------|---------------|--------------|-------|
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| Apex Trader Funding | $167 | $50K sim | Popular for futures |
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| TopStep | $165 | $50K sim | Futures focused |
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| FTMO | ~$155 | $10K | Forex/stocks |
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| MyFundedFutures | varies | varies | Futures |
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## Key Principles
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1. **Never risk more than 1% per trade** during paper trading — practice the habit now
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2. **Journal every trade** — no journal = no improvement
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3. **Backtest before you trust** — a strategy that "feels right" is not a strategy
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4. **Paper trading results are optimistic** — live will be harder
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5. **Pass 2 simulated challenges before paying for a real one**
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## Current Sprints
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→ Bill: [bill/sprints/sprint-01.md](../bill/sprints/sprint-01.md) — Market Data Infrastructure
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→ Colette: [colette/sprints/sprint-01.md](../colette/sprints/sprint-01.md) — Chart Literacy
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## Completed Sprints
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_(none yet)_
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shared/curriculum/README.md
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# Trading Curriculum — Overview
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## The Model
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Bill and Colette operate as a two-person trading team with distinct roles:
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| Role | Person | Approach |
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|------|--------|----------|
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| Quant / Engineer | Bill | ML models, scripts, backtesting, automation, signal validation |
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| Market Observer | Colette | News, macro indicators, sector themes, trade idea generation |
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**Workflow:** Colette spots opportunities (news catalyst, macro shift, chart pattern) → flags to Bill → Bill validates with data → team decides → Bill executes or automates
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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.
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---
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## Bill's Track — Quant / Algorithmic
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See: [bill-track.md](bill-track.md)
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Phases:
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1. Market data infrastructure (APIs, data feeds, TradingView Pine Script)
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2. Technical indicator implementation and backtesting
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3. ML signal generation (classification, regression, feature engineering)
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4. Strategy automation and alerting
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5. Prop challenge execution and monitoring
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---
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## Colette's Track — Market Observer
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See: [colette-track.md](colette-track.md)
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Phases:
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1. Chart literacy and TradingView basics
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2. News and macro awareness (what matters, what's noise)
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3. Sector rotation and high-level indicators
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4. Generating and communicating trade ideas
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5. Prop challenge: managing the watchlist and flagging setups
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---
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## Shared Milestones
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| Milestone | Description |
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|-----------|-------------|
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| First paper trade | Both place one paper trade and review it together |
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| First flagged setup | Colette identifies a setup → Bill backtests it |
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| First automated alert | Bill's script triggers on a Colette-identified pattern |
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| Simulated challenge pass | Both run through a prop challenge simulation |
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| Real challenge attempt | When two simulated passes are clean |
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91
shared/curriculum/bill-track.md
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# Bill's Learning Track — Quant / Algorithmic
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**Background:** Data scientist, ML experience, cybersecurity/scripting skills
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**Role:** Build and validate — data pipelines, backtests, models, automation, alerts
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---
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## Phase 1 — Market Data Infrastructure
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**Goal:** Get clean, reliable data into your toolchain
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- [ ] TradingView Pine Script basics — indicators, alerts, screeners
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- [ ] Python market data: `yfinance`, `pandas-ta`, `ccxt` (crypto if relevant)
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- [ ] Free vs paid data sources — what's actually needed at this stage
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- [ ] Build a basic OHLCV data fetcher for a watchlist of tickers
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- [ ] Understand data quality issues: survivorship bias, split adjustments, gaps
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- [ ] Set up a local data store (SQLite or Parquet) for backtesting
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**Deliverable:** Script that pulls daily OHLCV for a watchlist and stores it locally
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||||
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||||
---
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||||
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||||
## Phase 2 — Indicator Implementation & Backtesting
|
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**Goal:** Implement and test common signals before trusting them
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- [ ] Implement SMA, EMA, RSI, MACD, ATR from scratch (don't just use a library — understand them)
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- [ ] Build a simple backtesting loop (vectorized, not event-driven to start)
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- [ ] Understand backtest traps: look-ahead bias, overfitting, survivorship bias
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- [ ] Walk-forward validation basics
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- [ ] Metrics: win rate, expectancy, Sharpe ratio, max drawdown, Calmar ratio
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||||
- [ ] Pine Script: build a simple strategy and view equity curve in TradingView
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||||
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||||
**Deliverable:** One complete backtest with proper train/test split and metrics reported
|
||||
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||||
---
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||||
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||||
## Phase 3 — ML Signal Generation
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**Goal:** Apply ML where it actually adds value (not everywhere)
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- [ ] Feature engineering for price data (returns, rolling stats, lagged features)
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- [ ] Classification: predict direction (up/down/flat next N bars)
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- [ ] Avoid the common traps: data leakage, overfitting short samples
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- [ ] Evaluate with financial metrics, not just accuracy
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- [ ] Regime detection: is the market trending, ranging, or volatile?
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- [ ] Understand when ML helps vs when simple rules beat it
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**Deliverable:** A classifier that outputs trade signals with a documented edge (positive expectancy on out-of-sample data)
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||||
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||||
---
|
||||
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||||
## Phase 4 — Automation & Alerting
|
||||
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||||
**Goal:** React to markets without staring at screens
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||||
|
||||
- [ ] 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