ramseshk
b59dcc3629
Set up the directory structure and wrote placeholder logic for: - Order Book Imbalance: trades on L2 bid/ask skew - Iceberg/TWAP detection: follows whale accumulation patterns - Funding rate arbitrage: delta-neutral carry on perp funding - Pairs trading: BTC/ETH spread mean reversion - Avellaneda-Stoikov market making: optimal bid/ask quoting Also added shared risk manager, portfolio tracker, and a plain-language strategy walkthrough in docs/.
2.9 KiB
FTDT Quant Lab - Strategy Walkthrough
A plain-language explanation of each strategy: what it does, why it works (or might work), and what to watch out for.
1. Order Book Imbalance
What it does: Watches the order book in real time. If there are way more buy orders than sell orders stacked up, it buys. If the opposite, it sells.
Why it might work: When one side of the book is heavy, market orders eat into that side and push the price toward the thinner side. You're basically front-running that move.
Risks:
- Fake walls — someone puts up a huge order to bait you, then cancels it.
- Low signal quality in ranging markets.
2. Iceberg / TWAP Detection
What it does: Looks for big traders slicing their orders into small pieces. When it spots the pattern, it trades in the same direction.
Why it might work: If someone is accumulating a lot of BTC slowly, they probably know something (or at least their buying pressure will move the price). You're piggybacking their flow.
Risks:
- False positives — random noise looks like a pattern.
- The whale could be wrong. You're copying someone who might lose money.
3. Funding Rate Arbitrage
What it does: Hyperliquid charges a funding rate every 8 hours. When it's positive, people who are long pay people who are short. This strategy goes long spot (no funding) and short perp (collects funding), staying delta-neutral the whole time.
Why it works: It doesn't bet on direction — it bets on the funding mechanism itself. You earn the rate regardless of whether BTC goes up or down.
Risks:
- Funding rate can flip (you'd have to close and reopen the other way).
- Execution risk — if one leg fails, you're no longer delta-neutral.
4. Pairs Trading (BTC/ETH)
What it does: Tracks the price ratio between BTC and ETH. When the spread gets unusually wide, it bets it will narrow. Short the expensive one, long the cheap one.
Why it might work: BTC and ETH tend to move together over time. Big moves apart from each other often snap back. This trades the snap-back.
Risks:
- Regime change — if something fundamentally changes the BTC/ETH relationship, the spread might never revert.
- Needs enough data to calculate a reliable mean.
5. Avellaneda-Stoikov Market Making
What it does: Places buy and sell orders at optimal prices around the midpoint, adjusting based on how much inventory you're holding and how much time is left in your trading session.
Why it works: Market makers profit from the spread (buy low, sell high). The A-S model tells you exactly where to place your bid and ask to balance profit vs risk.
Risks:
- Adverse selection — someone who knows more than you picks off your quotes.
- Requires low latency and accurate volatility estimates.
- More of a "keep the machine running" strategy than a get-rich-quick one. The edge is small per trade.