Free module · Research & investment
Quant Strategy Development
Find an economic edge, measure the variables that drive it, and build a bot that can express it after costs.
edge discovery · features · trading systems
The building blocks
A strategy joins a forecast to an action, an exit and a risk budget. Keep those pieces separate so a useful idea can be tested and debugged.
- Describe the proposed economic edge
- Translate it into observable rules
- Evaluate net payoff and operating limits
Lessons in this module
- 01 / Start with a source of return
- 02 / The variables that actually enter the decision
- 03 / Test predictive information before a complex model
- 04 / Momentum and trend: information that persists
- 05 / Mean reversion and relative value
- 06 / Carry, events, and liquidity provision
- 07 / Convert a forecast into a trade decision
- 08 / Build a bot that preserves the experiment
- 09 / Decide whether the edge is real enough to continue
Practice and apply
- Find the break-even trade size — Gross expected holding return 20 bp. Fees and spread 5 bp; borrow and funding 3 bp. Impact is 4 bp at the reference size and follows the square-root model.
- Translate residual decay into an expected opportunity — An AR(1) spread is $2 above its long-run mean, φ = 0.8 per day. Assume a tradable spread unit with $1 P&L per $1 decline when short. Hold two days. Total round-trip cost is $0.30 per spread unit.
- A high win rate can conceal negative expectancy — A bot wins 70% of trades. Average gross win $40, average gross loss $100. Round-trip cost $3 on every trade.
Work through the practice exercises · Quant development tools