Abonelik sistemimiz henüz aktif değildir.
Abone olmak istemeniz bizi çok mutlu etti. O yüzden sizi bir anketimize davet etmek istedik. Bolfinans'ın fiyatında sizin de bir etkiniz olabilir.
Every serious investor eventually asks the same question: not "should I buy this stock?" but "is the risk I'm taking worth the return I expect?" Fair Price Engine was built to answer that question — automatically, continuously, and at scale.
Equity valuation has a scale problem. A rigorous DCF model takes hours to build for a single stock. Factor models require infrastructure most teams don't have. And by the time a quarterly report is processed, the market has already moved.
We built Fair Price Engine to close that gap — a continuously updating valuation engine that processes price data, financial reports, macro signals, and market news simultaneously, outputting a single fair price signal for every stock in the universe. No spreadsheets. No manual refresh cycles. No stale assumptions.
Fair Price Engine runs on a three-layer architecture. Each layer is independent and updates continuously as new data arrives — no human supervision required.
The Forecaster Swarm generates multi-horizon price trajectories using OHLCV data enriched by the Latent Comprehension Engine — which continuously scans financial reports and market news to extract forward-looking signals unavailable from price data alone.
Risk factors are calculated from traditional models — CAPM and Fama-French — combined with unique forward-looking factors derived from Latent Comprehension forecasts. Each factor is converted into a numeric value applied directly to the fair price calculation.
Expected return from the stock is compared against the risk-free rate and discounted to today — producing the fair price. It answers one question: is the risk you are taking worth the return you expect?
Fair Price Engine is designed as infrastructure — not a consumer app. Three distinct use cases, three distinct integration models.
Fair value signals across an entire stock universe — without building or maintaining the underlying models. Plugs directly into existing platforms via REST API.
Continuous valuation gap monitoring without rebuilding models every quarter. Know when a gap opens or closes — automatically.
Fair price data as a structured REST API feed. JSON output, low latency, raw factor data per layer. Built for systematic strategies.
Bedirhan holds a Physics degree from Boğaziçi University and completed postgraduate studies in Artificial Intelligence at Özyeğin University. His investment journey began with fundamental and technical analysis, deepened through factor models and quantitative strategies, and culminated in a single realisation: fair value is the intersection point of every serious valuation approach — and no tool was computing it continuously, at scale, for the markets he cared about. Fair Price Engine is his answer to that gap.
LinkedIn →We are actively working with early brokerage and quant partners, and open to conversations with investors who understand the infrastructure layer of financial markets.
Formu başarıyla kaydettiniz.
Uyarı: Bu ürün beta sürümündedir ve deneysel analiz modellemelerini test etmek amacıyla sunulmaktadır. Sağlanan çıktılar yatırım tavsiyesi değildir. Geçmiş performans, gelecekteki performansın garantisi değildir.
Abone olmak istemeniz bizi çok mutlu etti. O yüzden sizi bir anketimize davet etmek istedik. Bolfinans'ın fiyatında sizin de bir etkiniz olabilir.
Abone olmak istemeniz bizi çok mutlu etti. Abonelik sisteminden en erken haberdar olmak için kaydolmayı unutmayın.
