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.
4,574 documents
This beginner overview explains why foreign exchange exists, how currency systems evolved from barter and gold-backed notes to floating currencies, and how the FX market supports conversion and trading. It describes currency pairs as relative prices,…
This project describes a daily statistical arbitrage strategy applied to six INR currency pairs over the stated 2011–2013 sample. It screens pair combinations with cointegration tests, then applies a cointegrated Augmented Dickey–Fuller test to selected…
A bear trap is a brief selloff that appears to signal a reversal but is followed by recovery and continuation of an existing uptrend. The article describes how bearish traders may mistake a pullback or liquidation-driven move for a lasting breakdown, then…
The document explains harmonic trading as a method that combines geometric price swings with Fibonacci ratios to identify potential reversal zones. It describes the Gartley, Butterfly, Bat, and Crab patterns, outlining the retracement and extension…
The article explains direct market access (DMA) as a broker-provided route for submitting orders to exchange order books, with checks such as margin review before execution. It contrasts this with retail arrangements where a broker may intermediate orders or…
The article surveys nine factors that may influence exchange rates: political conditions, inflation, interest rates, government debt, terms of trade, speculation, capital-market performance, employment data, and economic planning. For each, it gives a…
This webinar description introduces using Python to implement automated trading in live markets, with IBridgePy as the main example. It outlines a workflow that connects a strategy to Interactive Brokers and identifies three basic platform tasks: retrieving…
This guide explains how candlesticks summarize open, high, low, and close prices, then describes common formations that may signal a bullish reversal or continuation. Single-candle examples include the hammer, bullish marubozu, dragonfly doji, and belt hold.…
This project tests whether adjusting percentage-based take-profit (TP) and stop-loss (SL) levels can improve strategies using simple or exponential moving-average crossovers and RSI signals. For each strategy and market series, it searches TP and SL…
This interview follows a quant developer’s move from commodity trading in his family’s business to automated trading and research. It describes building execution and research platforms, and explains how programming helped him explore rule-based trading. The…
This beginner guide defines day trading as opening and closing positions within the same session, partly to avoid overnight price gaps. It surveys momentum trading, scalping, and tick-based spread strategies, then outlines markets available to day traders,…
The tutorial describes IBridgePy as a Python wrapper that calls Interactive Brokers’ C++ API, and outlines how to connect it to Trader Workstation or IB Gateway. It explains a basic program structure in which initialization sets persistent variables and a…
This article compiles research papers, books, and other learning resources on reinforcement learning in finance, with expert recommendations attributed to Paul Bilokon. The cited applications include option hedging and dynamic replication, wealth management,…
This article proposes a Market DNA Passport: a summary of historical price behavior intended to help compare currency pairs and detect shifts in their market regimes. Its metrics cover candle shapes and closing locations, ATR-normalized volatility, spike…
This article reviews classic and hidden divergence as ways to compare price swings with changes in an oscillator. Classic divergence—where price makes a new extreme that the indicator does not match—is presented as a possible warning of a weakening move.…
This article explains how bar timestamps can create look-ahead bias in financial machine-learning datasets. MetaTrader 5 time bars are labeled with their opening time, although their high, low, close, and other completed-bar features are only known later.…
The article defines upper and lower fractals as local extrema formed by a five-bar structure, then describes plotting the latest fractal prices as horizontal levels. It treats a move beyond a fractal as a possible continuation signal and uses the…
This article proposes a self-adapting strategy based on the observed tendency for bullish and bearish candles to occur in roughly equal numbers over large samples. It presents counts from selected forex, equity, and other market data across several…
The article describes building a deep belief network initialized with stacked restricted Boltzmann machines, then fine-tuning it with labeled data. For EURUSD on a 30-minute timeframe, it constructs inputs from technical indicators and predicts directional…
The article explains unsupervised learning and applies k-means clustering to trading data. Without labeled target values, clustering groups observations represented as feature vectors by assigning them to nearby centers. The cluster count is a model…
This article describes revisions to a candle-counting strategy that starts a series of positions when bullish or bearish candles dominate a sample. It identifies weaknesses in fixed window lengths and thresholds, frequent entries, fixed basket exits, and…
The article presents MetaTrader 5 as an environment for moving an AI trading idea from research into a testable Expert Advisor. It describes using terminal data in Python for analysis and feature preparation, exporting trained models through ONNX for use in…
The document explains a hybrid Time Price Opportunity (TPO) market profile indicator for chart-based session analysis. It divides prices into a configurable grid and counts how often each price level appears across time periods within a session. The level…
The article presents ways to use Average True Range (ATR) in an MQL5 Expert Advisor. One signal looks for ATR and price to rise or fall across successive bars, treating aligned increases in range and direction as a volatility breakout. Another approach uses…