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.
9,797 documents
This note describes a five-minute trading rule that uses returns from an Indian equity ETF as a lead signal for MSCI futures. When the ETF’s average return exceeds the futures’ average return, the spreadsheet generates a buy signal; when it is lower, it…
This interview follows a trader’s education in economics, technical analysis, and algorithmic trading. He describes using data and backtests to examine discretionary trading ideas while continuing to place trades manually, rather than operating a fully…
This project compares intraday futures strategies built from daily pivot levels. It calculates pivot points using classic, Camarilla, and Fibonacci approaches, then tests textbook support-and-resistance rules alongside two alternatives on one-minute data for…
This tutorial describes a basic workflow for retrieving continuous futures data with a Python finance library, preparing date-indexed price data, and plotting closing prices. It demonstrates fetching one contract and then multiple contracts, grouping the…
The article describes an experiment applying meta-labeling to S&P 500 E-mini futures data. It combines event-based sampling, the triple-barrier method, and meta-labeling with two example strategies: trend following and mean reversion using Bollinger Bands.…
The article explains why financial time series are often made stationary for statistical inference and supervised machine learning, then presents fractional differentiation as a way to reduce nonstationarity while retaining more of a price series’ memory…
This analysis asks whether futures with more negative return skew earn higher returns, both across assets and when skew changes over time. It estimates skew from percentage returns after filtering extreme volatility-normalized observations, then uses…
This document outlines three futures trading rules built from skew and kurtosis: a standalone skew signal, skew conditioned on kurtosis, and kurtosis conditioned on skew. Signals are normalized by a robust volatility estimate and smoothed; conditioned…
This article studies stacking as a way to combine predictions from an ensemble of extreme learning machine classifiers. The base models produce outputs on separate training and evaluation samples; those outputs become features for a second-level combiner.…
This article explains how MetaTrader 5 exposes exchange order book data and how to build a reusable MQL5 class to simplify access. It describes subscribing to book-change events for selected symbols, retrieving second-level quotes, and organizing price…
The article tests how often markets qualify as trending versus flat by comparing five classification methods: ADX above a threshold, a Bollinger based trend indicator, Percentage of Trend, an RSI filter, and a ZigZag trend detector. It describes an MQL5 tool…
The article presents a workflow for preparing labeled market time series and training an N-HiTS forecasting model with PyTorch Lightning and PyTorch Forecasting. It retrieves M15 price data through MetaTrader 5, converts it to a dataframe, and adds time and…
This article describes an automated grid built from Buy Stop and Sell Stop orders around a reference price on Moscow Exchange futures. Orders are spaced by a chosen step within upper and lower bounds; as price triggers an order, the system may update the…
This article describes an object-oriented MQL5 Expert Advisor designed to help traders place pending orders from chart-selected prices. Its examples cover adjusting prices to an instrument’s tick size, calculating contract volume and monetary take-profit and…
This article presents a method for estimating long-range dependence in NQ one-minute futures returns and using it to characterize market regimes. It combines three estimators: rescaled range, aggregated variance, and absolute moments. Each estimator fits a…
This installment explains how to adapt a market replay system to rely on recorded traded ticks, including using tick files to generate preview bars. The author argues that minute bars may diverge from traded prices around events such as corporate actions,…
The article connects supply-and-demand theory with the Commitments of Traders report, using the positions of different trader groups to assess market conditions. It presents Larry Williams’s approach to turning COT data into indicators intended to identify…
The article explains how to use a MetaTrader indicator to compare seasonal price behavior for individual instruments and weighted spreads. It defines a spread as the difference between two instruments’ opening prices, with configurable multipliers, and…
This installment in an MQL5 library series addresses pending-order requests that fail because a trading class supplied hard-coded defaults unsupported by a symbol's specification. In particular, an unsupported expiration mode could lead to a server error and…
This installment explains how to make a chart timer behave consistently in live trading and historical replay. A live timer can use the platform’s current time to count down to the next bar, but that clock does not represent replay time, which can pause or…
This article’s first installment explains how to bring parts of the Kronos candlestick foundation model into native MQL5. It covers offline export of PyTorch parameters to binary float files, candle preprocessing, and the tokenizer encoder, which compresses…
This article explains how to make a chart-based MetaTrader Expert Advisor calculate order sizes and protective levels across instruments with different contract specifications. The author compares Brazilian shares, futures contracts, and forex, highlighting…
The article compares MetaTrader 5 and QUIK using three measures: elapsed time for sequential confirmed market orders, time to send a sequence of unconfirmed orders, and the frequency of market-depth updates. The tests were run on the same hosted computer,…
This document introduces the CFTC’s Commitments of Traders and Traders in Financial Futures reports as sources of aggregated futures positioning. It describes commercial hedgers, non-commercial speculators, and smaller traders, and explains how TFF breaks…