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.
16,761 documents
The document describes a U.S. equity strategy based on balance-sheet accruals, the noncash component of reported earnings. It estimates accruals from annual changes in current assets, cash, current liabilities, short-term debt, income taxes payable, and…
This Expert Advisor uses changes in the direction of a moving average associated with the Balance of Power Histogram to generate trading signals when a bar closes. The document frames the strategy around a directional shift in the indicator rather than a…
This analysis classifies bars by whether their highs and lows rise or fall relative to prior bars, then splits each configuration by candle color. The resulting eight groups cover rising-range and falling-range patterns, wider-range engulfing bars, and…
This guide describes ways to organize AI agents inside a trading strategy, from a single analyst to specialist research teams, opposing bull and bear views, and sequential debate. It distinguishes deterministic strategies, agent-led decisions, and hybrid…
The article tests whether a convolutional neural network can classify stock direction from chart-like images generated from OHLC data. Each sample uses 32 time steps, normalized to a 128-by-128 binary image: groups of columns mark open, high-low range, and…
This forum post raises an implementation question about deploying BigQuant StockRanker models for live trading through a brokerage server. The author believes StockRanker includes a gradient boosting decision tree model and asks whether deployment transfers…
This indicator measures weekend price gaps for a selected instrument and timeframe to assess whether fading a gap may be viable. It divides observations into recent gaps, the last twelve months, and the full available history. For each period, it reports gap…
The report describes a CTA approach for Chinese stock index futures that combines weekday return patterns with intraday effects. Its analysis notes higher return probabilities overnight and during the first half hour after the open, and different weekday…
This post presents a simple Chinese equity screen that selects stocks associated with the metaverse theme, with a positive return condition and a share price below a stated threshold. It describes the intended criteria in plain language and gives example…
This developer note explains two ways to inspect and work with a trading bot’s strategy tests. It says historical candles collected for backtesting are stored in SQLite files, which can be opened in a database browser to examine the available market data.…
This Expert Advisor trades changes in the direction shown by the ColorJJRSX indicator. It opens a position when the indicator changes color at a bar close, then can close the position once its holding time exceeds a configured limit. The holding-time exit is…
The proposed stock screen selects companies in the metaverse sector whose closing price is above its five-day moving average, then ranks candidates by opening-auction amount and keeps the top five. The document presents this as a way to combine a sector…
This Chinese equity screening proposal selects non-ST stocks before 10 a.m. using a range threshold, a five-session closing-high condition, and an external-to-internal trading volume ratio above 1.3. It presents the setup as a way to find active shares with…
This Expert Advisor trades signals from the Fisher_org_v1_Sign indicator. A signal is taken when a colored indicator icon appears at a bar close, so decisions are made using completed bars. The EA requires the compiled indicator file to be installed in the…
This article outlines a machine-learning stock selection strategy intended to find shares that may rebound after declines while limiting drawdowns during weak market conditions. It targets China’s small and medium-sized board, chosen for its activity and…
This guide explains how to participate in a BigQuant quantitative challenge using A-share minute bars and order-book snapshots to predict future 30-minute VWAP returns. It covers the factor-mining and end-to-end modeling tracks, available templates and data…
This document describes an Expert Advisor that trades signals from an RSIOMA histogram. Depending on its selected mode, a signal is evaluated at bar close when the histogram breaks support or resistance, changes direction, or crosses its signal line. An…
This discussion examines whether the length of a model’s training window changes an AI strategy’s results. It describes manually rolling training for a visual template strategy, comparing longer histories of five to ten years with shorter windows ranging…
This strategy description presents a long-only EUR/USD setup on the four-hour chart. It requires the 21-, 40-, and 100-period exponential moving averages to be ordered upward and rising. A candle must dip below the fastest average and close back above it,…
This beginner’s guide explains futures grid trading bots, which place long and short orders at preset price levels around a contract price. The approach aims to capture repeated movements within a range by systematically buying and selling, rather than…
The document answers how to allocate weights across strategies in a multi-strategy backtest. Its proposed workflow is to extract each strategy’s daily return series and use an optimization package to find portfolio weights. This frames the task as portfolio…
Qlib separates forecasting signals from portfolio construction. A strategy turns prediction scores into trading decisions, while a weight-based base class lets users specify target holdings and delegates order generation to the framework. The documented…
The article explains how leveraged perpetual futures positions can be liquidated when traders fail to meet maintenance margin requirements. It treats liquidation data as forced buy or sell order flow that may reveal short-term market pressure, and describes…
This article outlines factors to assess before depositing token pairs into a decentralized exchange liquidity pool. Liquidity providers receive a share of swap fees, generally represented by redeemable pool tokens, and some pools may also distribute…