Q-Sim™️: Crypto Portfolio Backtesting & Simulation

Q-Sim is Turnqey's backtesting engine for crypto portfolio strategies. It models how a portfolio would have performed during historical market events, using real price data, configurable weights, and adjustable parameters.

What Q-Sim Does

Advisers use Q-Sim to answer questions like:

•⁠ ⁠"How would a 60/40 BTC/ETH portfolio have performed during the 2022 crypto winter?"

•⁠ ⁠"What happens to a top-10 market cap strategy if I rebalance quarterly vs monthly?"

•⁠ ⁠"How much does adding a 5% SOL allocation change risk-adjusted returns over 3 years?"

Q-Sim runs these scenarios against historical data and returns performance metrics, drawdown analysis, and comparison charts.

Backtesting Modes

Manual Backtest

Define exact portfolio weights, date range, and parameters. Full control over asset selection, rebalancing frequency, fee assumptions, and staking reward inclusion.

Top-N Backtest

Automatically select the top N assets by market cap at each rebalancing period. Models what happens when you follow a rules-based market-cap-weighted strategy over time.

Historical Event Coverage

Q-Sim includes data through major market events:

COVID-19 crash — March 2020

2020–2021 bull run — Oct 2020 – Nov 2021

2022 crypto winter — Nov 2021 – Nov 2022

FTX collapse — November 2022

2023 recovery — Jan 2023 – Dec 2023

Bitcoin halving cycle — April 2024

2024–2025 institutional adoption — Jan 2024 – Present

Configurable Parameters

•⁠ ⁠Asset weights — Fixed or market-cap-weighted

•⁠ ⁠Rebalancing rules — Daily, weekly, monthly, quarterly, or threshold-based

•⁠ ⁠Fee structures — Exchange trading fees, gas costs, spread assumptions

•⁠ ⁠Staking rewards — Include or exclude yield from staking positions

•⁠ ⁠Start amount — Custom initial investment (default $10,000)

Output

Each backtest returns:

•⁠ ⁠Total return — Absolute and percentage

•⁠ ⁠Annualized return — CAGR over the period

•⁠ ⁠Max drawdown — Worst peak-to-trough decline

•⁠ ⁠Sharpe ratio — Risk-adjusted return

•⁠ ⁠Portfolio value over time — Daily or weekly data points

•⁠ ⁠Rebalancing events — When rebalances occurred and what changed

•⁠ ⁠Comparison to benchmarks — BTC-only and ETH-only baselines

Use Cases

Client Education

Show clients how crypto behaves during market stress. Visual backtests communicate risk better than any disclaimer.

Strategy Validation

Before allocating client capital, test the strategy against real market data. Identify failure modes before they cost money.

Proposal Support

Include backtest results in investment proposals. "Here's how this allocation performed during 5 historical scenarios."

Authentication

All Q-Sim endpoints require an API key via the ⁠ x-api-key ⁠ header.

Try It

Test Q-Sim endpoints in the Developer Sandbox Portal