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Bias-Proof Backtesting Assistant
Build a web-based research assistant for self-directed traders that enforces hypothesis-first testing and automatically checks for common backtesting failures. The core value is not faster coding, but preventing wasted months on overfit strategies and misleading results.
これが重要な理由
You already know how to code, so starting another notebook is easy. The real problem starts after that: you produce a promising curve, then spend weeks refining something that never had a genuine edge. You are unsure whether your test leaked future information, ignored execution costs, or was quietly tuned to one lucky regime. Existing tools give you flexibility, but they do not stop you from making basic research mistakes. What you want is a workflow that behaves like a skeptical research partner, forcing cleaner assumptions, separating hypothesis from optimization, and helping you reject weak ideas before you get emotionally attached to them.
- · Retail algo traders and technically skilled swing traders who can code or use notebooks but do not trust their validation process.向けに構築。
- · 最も可能性の高い収益化モデル: SaaS subscription。
痛み · ナラティブ
You already know how to code, so starting another notebook is easy. The real problem starts after that: you produce a promising curve, then spend weeks refining something that never had a genuine edge. You are unsure whether your test leaked future information, ignored execution costs, or was quietly tuned to one lucky regime. Existing tools give you flexibility, but they do not stop you from making basic research mistakes. What you want is a workflow that behaves like a skeptical research partner, forcing cleaner assumptions, separating hypothesis from optimization, and helping you reject weak ideas before you get emotionally attached to them.
スコア内訳
市場シグナル
市場投入
Individual traders who backtest 5 to 50 ideas per month and currently work in Python notebooks or spreadsheets.
~50K active globally in the first reachable niche
SEO long-tail
$49/month
20 paying users who each run at least 3 backtests in the first 30 days
MVPの範囲 · 1～2週間
- Define the backtest input schema for strategy rules, data assumptions, and cost parameters
- Build a simple upload flow for CSV price data and a minimal strategy form
- Implement basic backtest engine with train, validation, and out-of-sample splits
- Add three rule-based bias checks for look-ahead, survivorship proxy, and sample leakage
- Create a one-page report showing returns, drawdown, and warnings
- Add walk-forward validation and parameter sweep comparison view
- Build a research journal that stores hypothesis, test setup, and results
- Add benchmark comparisons and realistic slippage or fee presets
- Integrate Stripe and gated trial limits
- Launch a landing page with one interactive demo and collect user interviews
差別化
失敗する可能性がある理由
自己反論 — 最も重要な信頼のシグナル
- 1Traders may believe they can replicate the checks themselves and view the product as educational rather than essential.
- 2Without proprietary or very clean data, the product may be blamed for bad outcomes even when the workflow is sound.
- 3The target audience is fragmented and skeptical, so acquisition may be slower than typical SaaS niches.
エビデンスの概要
AIがこのインサイトをどのように統合したか — 逐語的な引用はありません
The strongest repeated theme was that coding is not the bottleneck; research quality is. Around eight commenters emphasized overfitting, look-ahead bias, walk-forward testing, and hypothesis discipline. Several also stressed that most ideas fail and need to be discarded quickly, which supports a product focused on error prevention and fast rejection rather than strategy generation alone.
アクションプラン
コードを書く前に、この機会を検証しましょう
推奨する次のステップ
開発する
強い需要シグナルを検出。本物の課題と支払い意欲を確認 — MVPの開発を始めましょう。
ランディングページ文案キット
実際のRedditコメントから抽出したコピー、そのまま貼り付けられます
見出し
Bias-Proof Backtesting Assistant
サブ見出し
Build a web-based research assistant for self-directed traders that enforces hypothesis-first testing and automatically checks for common backtesting failures. The core value is not faster coding, but preventing wasted months on overfit strategies and misleading results.
ターゲットユーザー
対象：Retail algo traders and technically skilled swing traders who can code or use notebooks but do not trust their validation process.
機能リスト
✓ Guided hypothesis-to-backtest workflow ✓ Automatic detection prompts for look-ahead bias, survivorship issues, and weak sample design ✓ Walk-forward and out-of-sample validation templates ✓ Research log with pass/fail evidence for each strategy idea ✓ Execution-cost assumptions library for more realistic backtests
どこで検証するか
r/r/algotrading にランディングページのリンクを投稿しましょう — そこがこの課題が発見された場所です。
同じテーマの他の機会
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