Project

NaijaAlphas

Institutional-grade equity intelligence for the Nigerian Exchange: eight research signals fused into a single explainable conviction score, delivered as an automated daily brief.

PythonNGX equitiesQuant researchConviction scoringAutomated reporting

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research signals per name

fused conviction score

Daily

automated brief cadence

NGX

Nigerian Exchange coverage

Overview

What it is

Institutional-grade equity intelligence for the Nigerian Exchange (NGX). Eight research signals are fused into a single explainable conviction score, and the result is published as an automated daily brief.

Build

What I built

Eight independent research signals, computed per name.
A fusion layer combining them into one conviction score.
Explainability by design: the score exposes which signals drove it, so a reader can see why a name ranks where it does.
A scheduled run that publishes the automated daily brief without anyone remembering to open a dashboard.

Findings

What held up

Explainable beats opaque. A score emitted on its own has to be taken on trust. Surfacing the contributing signals turns the output into something a reader can argue with, which is the only way it earns a place in a decision.

It arrives on its own. Scheduled delivery turns the research layer into a habit rather than a dashboard someone has to remember to check.

Stack

Built with

Language

Python

Market

NGX equity market data

Research

Multi-signal quant researchConviction scoringExplainability

Delivery

Automated daily brief

Want the detail?

The source is on GitHub. If this is the kind of system your team needs, I would like to hear about it.

View NaijaAlphas on GitHub Get in touch