Quantitative Finance

Corporate Listings, Relistings, and Price Series Continuity

This Python-centric deep dive explains how corporate listings, relistings, mergers, suspensions, and symbol changes reshape historical price series in Indian equities. It shows how to engineer continuity-safe data pipelines, mathematically valid indicators, and robust backtests by treating corporate events as structural breaks, not cosmetic adjustments.

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Price-Based Market Data

Adjusted vs Non-Adjusted Historical Series for Index Constituents

This article uniquely examines adjusted versus non-adjusted historical price series through the lens of index-constituent data engineering, not trading signals. By focusing on corporate-action restatement logic, index maintenance rules, and Python-driven data workflows, it reveals how subtle dataset choices materially alter analytics, backtests, and long-term market interpretation.

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Price-Based Market Data

Data Gaps, Suspensions, and Missing Values in Indian Price History

Indian equity price histories are structurally discontinuous, shaped by regulatory actions, market microstructure, and corporate events. This guide explains how to identify, classify, store, and measure data gaps, trading suspensions, and missing values in NSE and BSE data, ensuring Python-based market systems remain statistically valid and production-grade.

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Price-Based Market Data
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