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We publish when we have something specific to say about no-code backtesting, version traceability, or systematic research workflow — not on a fixed schedule.
A practical guide to no-code crypto strategy backtesting, what to check before trusting results, and how Traseq keeps research version-linked.
How to express a moving average crossover strategy as no-code rules in Traseq, why crossovers whipsaw, and the honest SMA(200) result on real BTC/USDT 1H data.
A no-code RSI mean reversion strategy guide for crypto research, with the 30/70 rule set, current Traseq BTC/USDT demo metrics, and the limits of one historical sample.
The turtle-style Donchian breakout idea as no-code rules, plus an honest BTC/USDT backtest result and why breakout win rates are low by design.
A fair, use-case-based comparison of TradingView and Traseq for crypto backtesting, focused on workflow fit rather than a generic winner.
How curve fitting makes trading strategy backtests look great in-sample, why fresh data can break them, and how to compare one variable at a time before trusting a result.
A practical no-code backtesting guide for crypto spot strategies, from turning a chart idea into rules to reading results and avoiding common traps.
A practical trend following vs mean reversion comparison for crypto researchers, with a quick answer, metric signatures, failure modes, and Traseq demo evidence from one BTC/USDT window.
Direct definitions, crypto examples, Traseq's bar-close and next-bar-open model, and a checklist for auditing any backtest before trusting the result.
A practical guide to holdout periods, walk-forward testing, and running the same finalized Traseq strategy across separate crypto backtest windows.
A practical guide to reading win rate with expectancy, profit factor, average win/loss, and max drawdown before trusting a crypto backtest.
Skip the ranked lists. Use this checklist to evaluate no-code backtesting tools by market fit, execution assumptions, version traceability, and research workflow.
How an AI agent can support crypto strategy research in Traseq through SignalGraph v2, scoped API keys, validation, version-linked backtests, and human review.
How small trading desks turn scattered screenshots and untracked tweaks into reproducible research using version-traceable strategies, comparison sets, and shared workspaces.
A professional workflow for comparing backtest results side by side so strategy decisions come from tradeoffs, not one attractive metric.
A practical first-backtest workflow for crypto spot strategy research: choose a finalized version, configure assumptions, run the test, and read the first result.
A practical workflow for turning chart ideas into no-code crypto strategy rules, finalizing a version, and preparing the strategy for a reproducible backtest.
A senior-level guide to research traceability in backtesting: why every result needs a locked strategy version, explicit run settings, and a clean comparison path.
A senior-level guide to reading backtest metrics in the right order: validate the test first, screen profitability, inspect drawdown, then compare risk-adjusted returns.
A practical guide to reading drawdown depth, duration, recovery behavior, and comparison workflows before trusting a crypto strategy backtest.