Crypto strategies should not be evaluated as if every exchange is the same. Binance, OKX, Bybit, and Coinbase-style markets can differ in fees, liquidity, available instruments, funding behavior, API reliability, regional access, and operational risk. A strategy that looks attractive on one venue profile may be fragile on another.
The iTapGo Quant Crypto Strategy Lab is designed as an educational comparison tool. It does not fetch live exchange data or place orders. Instead, it uses deterministic simulated price paths and exchange-specific assumptions so readers can see how methodology changes outcomes.
The first strategy profile is AI trend following. It models a simplified score based on fast and slow moving averages, then changes exposure when the score crosses a threshold. This is useful for learning how momentum assumptions interact with volatility and trading costs.
The second profile is volatility mean reversion. It looks for moves away from a recent average and assumes partial reversion. This can perform differently across assets and exchanges because volatile assets may keep trending instead of reverting.
The third profile is funding pressure. It uses simulated perpetual futures funding as a proxy for crowded positioning. This profile is more relevant for derivatives-heavy venues such as Binance, OKX, and Bybit than for a spot-oriented Coinbase profile.
The important lesson is not which simulated result is highest. The lesson is that exchange assumptions belong inside the research process. Fees, slippage, funding, liquidity, and operational risk should be visible before anyone discusses performance.
Readers can use the lab to learn how total return, maximum drawdown, trade count, and Sharpe-style risk-adjusted return respond to different assumptions. Those metrics are educational outputs, not investment recommendations.