Initial project scaffold: five quant strategies for Hyperliquid Testnet

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/.
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# 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.