Quantitative Finance
Independent Algorithmic Trader
"DaaS Labs delivered an entire product suite in the time it took us to hire our last engineer..."
The Challenge
An independent algorithmic trader had spent years developing a proprietary trading methodology — a carefully designed set of signal rules, entry/exit conditions, and risk parameters that existed only in his head and in rough documentation. He had the intellectual edge. What he didn't have was software.
He needed a full-stack developer who could take his algorithm from concept to code without simplifying it — building a system that could ingest live financial data, run his exact logic, generate reliable buy/sell signals, and present everything inside a professional dashboard he could act on in real time.
Off-the-shelf tools wouldn't cut it. The algorithm was too specific, and the client needed full ownership of the logic. He needed a bespoke build — and he needed it to be accurate enough to trade live capital against.
What DAAS Labs Built
01 — CUSTOM SIGNAL ENGINE (PYTHON + FASTAPI)
We built the core of the platform: a Python backend powered by FastAPI that encodes the client's proprietary trading algorithm in full. The engine ingests live and historical market data, runs the complete analytical pipeline — including all custom indicator logic, entry/exit conditions, and signal filters — and outputs structured buy/sell triggers with supporting data. The algorithm was not adapted or simplified. Every rule the client specified was faithfully implemented, tested, and validated against historical data before going anywhere near a live market.
02 — YAHOO FINANCE DATA INTEGRATION
We integrated Yahoo Finance as the market data layer, giving the engine access to real-time and historical price feeds across the client's target instruments. The data pipeline handles fetching, normalisation, and caching — ensuring the algorithm always runs on clean, consistent inputs regardless of market hours or data availability.
03 — METATRADER 4/5 COMPATIBILITY (MQL4/MQL5)
We built compatibility with MetaTrader 4 and MetaTrader 5, the industry-standard platforms for retail algorithmic trading — allowing the client's signals to interface with his existing brokerage infrastructure and execute trades within his established workflow.
04 — NEXT.JS TRADING DASHBOARD
We built a full Next.js frontend that gives the client a professional trading interface: real-time signal feeds, interactive price charts with overlaid buy/sell markers, historical signal performance, and the ability to analyse data directly on the charts. The UI was designed for a single power user who needs fast, dense information — not a generic SaaS template.
05 — ACCURACY TESTING & LIVE DEPLOYMENT
Before going live, the client ran an extensive accuracy validation regime — backtesting the signals against historical data and forward-testing against live market conditions in a paper trading environment. The system achieved 95% signal accuracy. The client then moved to live trading, using the platform to execute real capital trades.
"An amazing job done by the team, I would recommend them to anyone looking for a full-stack developer."