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Aug 7 market research



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Latest market analysis


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The Failure of My 100% C++ Trading Application: A Full Breakdown Thread Rating: ⭐⭐⭐⭐⭐ (Informative)

Introduction

After 30+ years of coding experience, I decided to challenge myself: build an entire trading application using 100% C++ with no compromises.

The result? A humbling failure.

But failure is the best teacher, and I want to share what happened, what I learned, and what the community taught me during a recent live stream discussion.


Part 1: The Starting Point

When I began this project, my thinking was:


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My Python Pipeline Generates 3,600 Strategies Daily — Here's Why Only ~36 Are Actually Deployable

Date: August 2026 Tag: Systematic Trading | Algorithmic Strategies | Risk Management


Hey everyone,


Been running this systematic pipeline for a while now and wanted to share some real numbers from today's output. Maybe it'll spark some discussion on strategy filtering and live deployment.


TL;DR:


  • Generated 3,600 backtested strategies today

  • After Barchart liquidity validation + composite risk scoring = 36 deployable (about 1%)


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