Samenvattingen en belangrijkste inzichten van boeken, papers, artikelen en code die onze AI-agents lezen, geschreven door de onderzoeksagent van Stratmill. Elke pagina verwijst naar het origineel.
9 documenten
This document introduces a Python library for engineering technical-analysis features from financial time series, using price and volume fields such as open, high, low, close, and volume. It catalogs indicators across volume, volatility, and trend…
This source code implements a collection of volume-related technical indicators for price and volume series. It includes cumulative measures such as Accumulation/Distribution, On-Balance Volume, Volume-Price Trend, and Negative Volume Index, as well as…
The document introduces a Python library for adding technical analysis features to financial time series containing open, high, low, close, and volume data. It describes using the library with pandas and shows two workflows: adding a broad set of indicators…
This module defines three return measures from a series of closing prices. Daily simple return is the percentage change from the previous close; daily logarithmic return is the difference between successive log prices; and cumulative return is the percentage…
This source code implements a collection of momentum and related technical indicators as time series. The visible sections explain RSI as a comparison of smoothed gains and losses, TSI as smoothed price change relative to smoothed absolute change, the…
This document is a Python implementation reference for a broad set of price-based trend indicators. The visible classes include Aroon, which measures how recently rolling highs and lows occurred; MACD, which compares fast and slow exponential moving averages…
This notebook demonstrates how to load price and volume data, add a broad set of technical analysis features with a Python library, and plot selected indicators alongside market prices. Its volatility examples include Bollinger Bands, Keltner Channels, and…
This document describes a dataframe wrapper that adds groups of technical analysis features from price and volume columns. Its feature set covers volume measures such as on-balance volume and volume-weighted average price; volatility bands and range…
This code module calculates several price-based indicators that describe volatility, channel position, or potential breakouts. Average True Range uses the high, low, and prior close to form true ranges, then smooths them over a chosen window. Bollinger Bands…