Volume Weighted Average Price (VWAP) is often misunderstood as a single indicator, but its meaning changes fundamentally at stock and index levels. This Python-centric guide explains mathematically correct VWAP computation, data engineering workflows, and trading interpretation across time horizons in Indian equity markets.
Stock-Level vs Index-Level VWAP Computation Read More »
Price-Based Market Data
In Indian equity markets, the closing price is a statistically engineered, exchange-published value—not the last trade. This article explains how NSE and BSE construct the close using constrained aggregation, liquidity safeguards, and fallback logic, and why Python market systems must treat closing prices as immutable, authoritative anchors for valuation, returns, and backtesting.
Closing Price Determination Methodology on NSE and BSE Read More »
Price-Based Market Data
In Indian equity markets, the official opening price is discovered through a structured pre-open auction, not the first trade. This article explains how that auction-derived price anchors OHLC data, overnight returns, gaps, and volatility, and why Python market analytics must treat opening prices as immutable, auction-origin values.
Pre-Open Session Impact on Official Opening Price Read More »
Price-Based Market Data
Indian equity prices do not move continuously—every Last Traded Price is constrained by an exchange-defined tick size. This article explains how price granularity shapes LTP formation, return resolution, volatility floors, and backtesting accuracy, showing why tick-aware, integer-based modeling is foundational for realistic Python market analytics.
Tick Size and Price Granularity in LTP Formation Read More »
Price-Based Market Data
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.
Data Gaps, Suspensions, and Missing Values in Indian Price History Read More »
Price-Based Market Data
Indian equity price data is not just historical numbers—it is regulated, session-bound, and structurally complex. This in-depth Python-centric guide explains how Indian historical price series are built, adjusted, validated, and governed, enabling traders and quants to create reliable analytics across intraday, swing, and long-term investment horizons.
Structure of Historical Price Series in Indian Equity Markets Read More »
Price-Based Market Data