AI quantitative trading research desk
iTapGo Quant is a research-first content site for AI-assisted market analysis, strategy validation, backtesting discipline, and risk management. We focus on process, reproducibility, and limitations.
Featured note
A professional quant site should teach readers how to reason about models, data, validation, execution, and risk before discussing any strategy.
A research framework for comparing crypto strategy assumptions across Binance, OKX, Bybit, and Coinbase-style markets.
Crypto markets are open 24/7, fragmented across exchanges, and shaped by funding rates, liquidity shocks, and on-chain behavior.
Perpetual futures funding rates can reveal leverage pressure, but they require careful timing, normalization, and regime analysis.
Crypto backtests need explicit rules for time zones, session boundaries, exchange outages, liquidity, and weekend volatility.
On-chain data can enrich crypto research, but wallet flows, exchange balances, and protocol metrics are noisy and easy to misinterpret.
Research tracks
Each track is structured around practical research questions and conservative claims, which helps the site read like a durable reference instead of a campaign.
Machine learning workflows, feature engineering, model validation, and AI-assisted market research.
AI-assisted crypto market research, funding rates, exchange data, on-chain signals, and 24/7 risk controls.
Systematic strategy design with hypotheses, rules, validation windows, and failure tests.
Backtest construction, walk-forward evaluation, realistic costs, and data integrity checks.
Drawdown, sizing, execution risk, governance, and operational controls for trading systems.
Practical AI assistant workflows, documentation patterns, Python research habits, and review checklists.
Crypto quant focus
Crypto research needs special treatment: fragmented venues, funding rates, on-chain data, exchange risk, and uninterrupted trading hours.
Run educational backtests across four exchange profiles with trend following, mean reversion, and funding pressure strategies.
A research framework for comparing crypto strategy assumptions across Binance, OKX, Bybit, and Coinbase-style markets.
Crypto markets are open 24/7, fragmented across exchanges, and shaped by funding rates, liquidity shocks, and on-chain behavior.
Perpetual futures funding rates can reveal leverage pressure, but they require careful timing, normalization, and regime analysis.
Review essentials
These guides support the site's central promise: better research habits, clearer limitations, and more respect for risk.
Backtests are useful research tools, but they can become dangerously persuasive when costs, slippage, data leakage, and overfitting are ignored.
How to turn a familiar moving average crossover idea into a disciplined research plan with rules, costs, metrics, and failure checks.
Maximum drawdown explains the deepest peak-to-trough loss in a strategy and helps investors understand pain, recovery, and position sizing.