Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.
4,510 documents
This article is a curated overview of resources on sentiment analysis for trading rather than a single strategy or empirical study. It points readers to approaches that use news, social media, earnings information, macroeconomic data, and other sources to…
The document explains share prices through the market’s changing expectations of future company earnings and business conditions. It uses an Indian automaker’s valuation expansion and later earnings growth to distinguish price gains driven by a higher…
The article describes three sentiment measures and proposes contrarian trades based on them. VIX is presented as an options-derived estimate of expected S&P 500 volatility; high readings are associated with fear and falling prices, while low readings are…
The document outlines conditions in which quantified news sentiment may be more useful for equity trading. It suggests that small-cap stocks can react more strongly than larger firms, low-beta stocks may be sensitive to sentiment shifts, and low-volatility…
The document introduces sentiment analysis, also called opinion mining, as a way to classify the tone expressed in text as positive, negative, or neutral. In a trading context, this can be applied to news and other unstructured information, which automated…
The article introduces spaCy as a Python library for processing text, with an emphasis on its production-oriented pipelines. It contrasts spaCy with NLTK and describes a workflow using a trained language model to convert text into tokens, lemmas, sentences,…
This guide explains VADER, a rule-based text sentiment tool that assigns word-level valence and combines it into a normalized compound score. It describes how the lexicon incorporates words, slang, and emoticons, and how sentence-level heuristics account for…
This article describes market sentiment as the collective outlook of participants and explains how text sentiment analysis attempts to classify opinions as positive, negative, or neutral. It outlines a workflow of collecting news, social media, or financial…
Tomás García-Purriños describes a medium- to long-term approach to multi-asset investing that combines technical indicators with fundamental measures, especially macroeconomic data, and indicators of investor sentiment and market flows. He argues that no…
The document defines the Arms Index, or TRIN, as the ratio of advancing stocks to declining stocks divided by advancing volume to declining volume. It interprets readings below 1 as generally bullish and readings above 1 as generally bearish, while unusually…
This article presents a basic text sentiment workflow for financial commentary using R. It applies a bag-of-words approach: prepare positive and negative term lists, clean an earnings-call transcript, tokenize it into words and n-grams, and compare the…
The article surveys data sources that can supplement price and volume analysis. It covers company ratios and financial statements, macroeconomic indicators, earnings dates, financial news, tweets, and sentiment scores. It names services and Python libraries…
This analysis uses daily Nifty 50 futures data from exchange files to examine price, trading volume, open interest, rollover percentages, and foreign and domestic institutional activity during the first quarter of 2020. It explains how to interpret price…
The article defines market inefficiency as a divergence between an asset’s traded price and its fair value, and links such gaps to crises, earnings information, speculation, and delayed investor reactions. It uses the dotcom boom and the U.S. housing and…
The document outlines a daily sentiment-based strategy for China A-share stocks using posts from recognized financial accounts on Weibo. It proposes collecting posts during the pre-market period, considering four actively discussed sectors, and identifying a…
The article introduces Bitcoin’s public blockchain, mining, capped issuance, and wallet transactions, then connects these features to ransomware payments and Bitcoin’s appeal as a tradable asset. It frames price as primarily demand-driven and names…
This year-in-review lists educational and industry events related to quantitative trading. The most substantive strategy topics include momentum linked to autocorrelation and market inefficiencies, with sessions described as covering backtesting and…
This project describes a news-based trading strategy for Nvidia shares. It collects news articles and historical prices, extracts article text, and scores sentiment using TextBlob and VADER. The strategy uses VADER scores, aggregating each day’s highest and…
This article describes a simple way to test whether website sentiment indicators can inform stock trades. The author collects buy, sell, and hold readings for a stock list by extracting values from a financial portal, then stores them in a data frame or…
The document introduces the Bag of Words (BoW) method for representing text as counts of vocabulary terms. It outlines basic preprocessing and explains how a document collection becomes a matrix in which rows represent documents, columns represent unique…
This presentation overview describes a pipeline for converting news text into numerical signals that an automated strategy can use. It identifies sentiment, relevance, novelty, event type and potential market impact as core features, with news volume, search…
The document lays out a workflow for turning financial text into trading signals: collect news or social posts, preprocess the text, assign sentiment scores, combine those scores with technical indicators to form signals, and backtest the resulting model. It…
The article extends a MetaTrader 5 chart display that already shows upcoming economic-calendar events by adding headlines from an external financial-news API. It uses Alpha Vantage as the example provider, explains API keys, HTTP requests, JSON responses,…
This tutorial demonstrates connecting an MQL trading program to an external JSON data service, saving and parsing API responses, and using forecast data as a filter for a moving-average crossover. The example combines a directional moving-average signal with…