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78点数
r/algotrading
SaaS subscription
Build

Skipped-Trade Edge Journal

Create a trade journaling platform that records both executed and skipped setups so traders can evaluate whether filters improve edge or merely reduce activity. This solves a blind spot that normal broker histories and journals do not cover.

上昇 +80%5 チャネル30日間の言及傾向: latest 8, peak 8, 30-day series
Redditで見る
発見 2026年7月21日

これが重要な理由

You think your filter is improving your strategy because the trades you took look better. The problem is you never measured what would have happened if you had taken the opportunities you skipped. That means you cannot tell whether your rules add real value, cut out losers, or simply make you trade less. Standard journaling tools mostly start at the moment an order exists, which leaves a major gap in the research loop. For traders who mix discretion with rules, this missing dataset quietly prevents learning and causes false confidence in filter logic.

  • · Rule-based discretionary traders and light-automation users who generate many candidate setups and want to quantify whether their filters and overrides help.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 think your filter is improving your strategy because the trades you took look better. The problem is you never measured what would have happened if you had taken the opportunities you skipped. That means you cannot tell whether your rules add real value, cut out losers, or simply make you trade less. Standard journaling tools mostly start at the moment an order exists, which leaves a major gap in the research loop. For traders who mix discretion with rules, this missing dataset quietly prevents learning and causes false confidence in filter logic.

スコア内訳

課題の強さ8/10
支払い意欲6/10
構築のしやすさ6/10
持続性8/10

市場シグナル

30日間の言及傾向ピーク: 8
Sparkline: latest 8, peak 8, 30-day series
対象チャネル
algotradingDaytradingoptionssaasChatGPT

市場投入

正確なターゲットユーザー

Active discretionary or semi-automated traders who evaluate 10 or more candidate setups per week and already keep some form of trading journal.

推定ユーザー数

~100K-300K globally

主要な獲得チャネル

r/<community> organic

価格アンカー

$29/month

最初のマイルストーン

50 weekly active users logging both taken and skipped setups for 4 consecutive weeks

MVPの範囲 · 1~2週間

1週目
  • Design a setup schema for candidate trade, filter state, and horizon outcome
  • Build manual and CSV-based setup logging flow
  • Create dashboard for taken versus skipped trade outcome comparison
  • Add expectancy and win-rate breakdown by filter or reason code
  • Publish a simple onboarding guide for spreadsheet users
2週目
  • Add browser-based form for rapid intraday setup capture
  • Implement reminder system to finalize horizon outcomes automatically
  • Build rule tags for common filters like volatility, trend, and liquidity
  • Add import from one broker export and one charting alert source
  • Interview first 10 active users to refine workflow friction
MVP機能: Capture engine for all detected setups, not only placed orders · Side-by-side analysis of taken versus skipped outcomes · Filter attribution dashboard showing impact on expectancy and frequency · Missed-trade reminders and review workflow

差別化

既存のソリューション
Treeova
当社のアプローチ
There is an unmet need for beginner-to-intermediate algo trading software that combines realistic backtesting, skipped-trade analysis, production monitoring, and non-programmer usability in one workflow.

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

  1. 1If setup capture feels like extra admin work, users will not log enough data for the product to prove value.
  2. 2Many traders lack a systematic signal-generation step, reducing fit for the product.
  3. 3The insight may be valuable but too niche to support a large standalone business without adjacent journaling features.

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 clearest unique insight in the discussion was that traders rarely measure the opportunities they reject, leaving them unable to judge whether filters create edge. Another comment reinforced the consistency problem by noting that partial automation reduced missed trades. Together, these signals support a product focused on the untracked area between signal and execution.

1 1 件の投稿を分析5 5 チャネルAI · AIが統合 · 逐語的ではありません

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

Skipped-Trade Edge Journal

サブ見出し

Create a trade journaling platform that records both executed and skipped setups so traders can evaluate whether filters improve edge or merely reduce activity. This solves a blind spot that normal broker histories and journals do not cover.

ターゲットユーザー

対象:Rule-based discretionary traders and light-automation users who generate many candidate setups and want to quantify whether their filters and overrides help.

機能リスト

✓ Capture engine for all detected setups, not only placed orders ✓ Side-by-side analysis of taken versus skipped outcomes ✓ Filter attribution dashboard showing impact on expectancy and frequency ✓ Missed-trade reminders and review workflow

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。

サインアップして詳細な深掘り分析をアンロック

GTM、MVPスコープ、失敗する理由、ActionPlanコピーキット。無料サインアップで月10件の詳細ビューが利用可能です。

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同じテーマの他の機会

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よくある質問

誰がこのペインを感じていますか?
Rule-based discretionary traders and light-automation users who generate many candidate setups and want to quantify whether their filters and overrides help.
これは本物のビジネスチャンスですか?
このビジネスチャンスは、Pain Spotterの総合指標(ペインの強さ、支払意欲、技術的実現可能性、持続可能性)で78/100のスコアを獲得しています。エンジニアリングの時間を割く前に、さらに検証を行ってください。
どのように検証すべきですか?
ターゲット層と5回の顧客発見の会話を行い、ウェイトリスト付きのランディングページを公開し、開発前にリンク元の投稿で最近のアクティビティを確認してください。