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Dynamic Position Sizing Optimizer API
An API service that takes a user's raw trading signal and automatically calculates the mathematically optimal position size to maximize the edge while accounting for transaction costs and account drawdown limits.
Pourquoi c'est important
You have finally found a market signal that predicts price movements with decent accuracy. Yet, at the end of the month, your trading account is flat or negative. You realize that when you are right, your position sizes are too small to cover the times you are wrong, and fixed broker fees are eating away at your smaller trades. Calculating the optimal bet size for every single trade—while factoring in current account equity, historical volatility, and exact execution costs—is mathematically exhausting. You need a dedicated engine that tells your script exactly how much capital to allocate the moment a signal fires.
- · Conçu pour Algorithmic traders who have a working signal but struggle with risk management and capital allocation..
- · Monétisation la plus probable : API usage tier / SaaS subscription.
La douleur · Récit
You have finally found a market signal that predicts price movements with decent accuracy. Yet, at the end of the month, your trading account is flat or negative. You realize that when you are right, your position sizes are too small to cover the times you are wrong, and fixed broker fees are eating away at your smaller trades. Calculating the optimal bet size for every single trade—while factoring in current account equity, historical volatility, and exact execution costs—is mathematically exhausting. You need a dedicated engine that tells your script exactly how much capital to allocate the moment a signal fires.
Détail du score
Signal du marché
Mise sur le marché
Algorithmic traders utilizing Python scripts who are actively trading live markets but experiencing stagnant equity curves.
~30K active globally
Hacker News launch / GitHub open-source core
$29/month base API access
100 free API keys generated with 10 converting to paid tiers within 30 days.
Périmètre MVP · 1–2 semaines
- Draft the mathematical formulas for Kelly Criterion, Fixed Fractional, and Volatility-adjusted sizing.
- Build a Python library containing these core sizing algorithms.
- Integrate a parameter that subtracts expected transaction costs from the expected return before calculating size.
- Create documentation explaining the inputs (account size, win rate, risk tolerance).
- Publish the core logic as an open-source GitHub repository to attract developer interest.
- Build a REST API wrapper around the Python library using FastAPI.
- Set up user authentication and rate-limiting using a service like Supabase or Auth0.
- Deploy the API to a reliable serverless environment.
- Create an interactive documentation page (Swagger/ReDoc) with copy-pasteable code snippets for popular trading frameworks.
- Launch on developer-focused platforms detailing how optimizing size fixes broken algorithms.
Différenciation
Pourquoi cela pourrait échouer
Auto-contre-argument — le signal de confiance le plus important
- 1Traders might prefer to code their own sizing logic rather than relying on an external API that introduces latency.
- 2The value proposition might be too narrow to justify a recurring subscription, leading to users just copying the math once.
- 3If a user inputs incorrect win-rate assumptions, the API will output dangerous position sizes, creating liability.
Résumé des preuves
Comment l'IA a synthétisé cet aperçu — pas de citations textuelles
Several community members highlighted that their primary breakthrough came not from finding a better entry signal, but from fixing their position sizing. Around three users noted that their initial setups looked like broken noise overlaid on fees, and that adjusting the capital allocation per trade was the actual key to clearing transaction costs and revealing the strategy's edge.
Plan d'Action
Validez cette opportunité avant d'écrire du code
Prochaine Étape Recommandée
Construire
Signaux de demande forts. Vraie douleur et volonté de payer détectées — commencez à construire un MVP.
Kit de Textes pour Landing Page
Textes prêts à coller, basés sur le langage réel de la communauté Reddit
Titre Principal
Dynamic Position Sizing Optimizer API
Sous-titre
An API service that takes a user's raw trading signal and automatically calculates the mathematically optimal position size to maximize the edge while accounting for transaction costs and account drawdown limits.
Pour Qui
Pour Algorithmic traders who have a working signal but struggle with risk management and capital allocation.
Liste des Fonctionnalités
✓ REST API endpoint for real-time size calculations ✓ Kelly Criterion and fractional sizing algorithms ✓ Cost-drag awareness (sizing up to overcome fixed fees) ✓ Drawdown limit circuit breakers ✓ Backtesting module to isolate the impact of sizing alone
Où Valider
Partagez votre landing page sur r/r/algotrading — c'est exactement là que ces points de douleur ont été découverts.
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