LEARN / DECISION PATHS

Learn research decisions, not button sequences.

kquant learning paths follow real tasks: find a mechanism, read an outcome, detect overfitting, launch Simulation and diagnose divergence.

Open laboratory Explore the details ↓

CHOOSE YOUR NEXT READ

Learn through decisions, not button names.

Each route ends with a product action or a clearly stated boundary.

Read a report

Metrics, trades and assumptions together.

Challenge a candidate

The tests that can still reject it.

Keep it safe

API permissions and independent stop paths.

Getting started

Turn a market idea into a minimal testable rule.

Backtesting

Understand look-ahead, next-bar logic, costs and trade count.

Overfit controls

Learn holdout, DSR, PBO, walk-forward and Monte Carlo.

Simulation and live

Connect an exchange securely and know when to stop execution.

Starter collection

Four routes for your first research cycle

Why backtests lie

Look-ahead, selection bias and idealized fills

DSR in plain English

How trial count changes confidence in Sharpe

Simulation vs live

What simulation can and cannot test

Secure API access

Permissions, subaccounts and IP whitelists

Important

Historical, statistical and model results do not promise future returns. kquant provides computational tools and technical execution, but does not assess whether a specific trade is suitable for a user.