Pairs trading on Korean equities: cointegration that actually held
If you have ever tried running a statistical arbitrage book on global equities, you know the painful cycle of backtesting a promising pairs trading strate…
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Orchestrating data to model to execution in one Temporal workflow
I spent the first half of my career trying to glue three different worlds together: data pipelines (Spark/Airflow), ML serving (FastAPI/Triton), and execu…
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Velero backups for CloudNativePG: testing restores before you need them
A backup is nothing more than an unverified promise. In the world of stateful Kubernetes workloads, relying on untested backups is a classic operational f…
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Walk-forward optimization that didn’t lie to me: a practical setup
Three years ago, I fell into the same trap that claims most algorithmic traders. I engineered a volatility-breakout strategy on BTC/USDT hourly data, opti…
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Local Kubernetes dev environments: k3d, Tilt, and the inner loop that finally stuck
The worst part of building distributed execution systems is the time wasted waiting for Docker images to compile, push, pull, and deploy. When you are wri…
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Spring Cloud Gateway as the front door: routing, retries, and the timeouts that bit me
When you are routing high-frequency order flows and real-time market data enrichment requests, milliseconds are not just metrics—they are PnL. In our algo…
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ArgoCD app-of-apps: structuring GitOps for a dozen microservices
Eighteen months ago, my team transitioned our core algorithmic execution engine from a tightly coupled Django monolith to twelve specialized microservices…
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Prompt-versioning a trading research assistant with Temporal
Six months ago, I deployed an LLM-based research assistant designed to ingest quarterly earnings transcripts, extract qualitative sentiment signals (e.g.,…
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Backtesting pitfalls: survivorship bias in Korean equities
Two years ago, I built a long-short equity strategy targeting small-cap equities listed on the Korean KOSDAQ exchange. On paper, the strategy was a money…
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Turning earnings calls into structured features with an LLM
For years, quant desks have treated earnings call transcripts with a blunt instrument: sentiment analysis. We used to clean the raw text, run it through F…
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