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 critiques trend lines built from DeMark pivot points or Bill Williams fractals when key points are identified using only a minimum-bar rule. It proposes removing that minimum and defining a point's dimension as the smallest count of bars on…
This brief platform support exchange addresses why a historical-data call for the CSI 300 index is not recognized. The response says the newer backtest engine retrieves data through SQL and suggests using the platform’s data interface to obtain index data…
This note proposes screening Chinese stocks for prior-day trading-list appearances with buy amounts greater than sell amounts, an amplitude threshold, and membership in a beverage or alcohol-related industry. It presents the combination as a way to capture…
This note describes a short-term Chinese stock screen using three conditions: amplitude above a stated threshold, a rising-bottom pattern, and more than two limit-up days within a ten-day window. Its stated rationale is to find shares with strong recent…
This Chinese stock-screening note combines a 14-period RSI threshold below 65 with a recent candle pattern, then ranks qualifying shares by auction value and selects the top five. The stated rationale is to pair a technical condition described as oversold…
This article outlines a process for developing equity selection rules, from finding market examples and forming a hypothesis to implementing factors, running an initial backtest, reviewing losses, and deciding whether to adjust the logic. It proposes several…
This tutorial outlines a Fisher Transform indicator calculated from the midpoint of each price bar and the highest high and lowest low over a rolling period. A ratio between zero and one controls how much the newly normalized price affects the recursively…
This Chinese-language forum post asks whether factor analysis should pair a factor observed on a given day with that same day's prices or with prices from the following day. The author cites the Alphalens introduction as a reason to use next-day data and…
This FAQ explains practical design and troubleshooting points for FMZ Quant Workflow strategies. It covers host-version requirements, JavaScript-only code nodes, sequential execution, trigger behavior, reading data from connected parent nodes, and sharing…
This article introduces the KDJ stochastic oscillator, formed from the close’s position within a recent high-low range and smoothed into K and D lines, with J derived from them. It describes common interpretations: high and low readings as overbought or…
This brief troubleshooting post presents a ValueError raised while a BigQuant workflow runs an automatic labeling module. The traceback ends in pandas' binning routine and reports that the generated bin edges are not unique: after negative and positive…
This document describes a Chinese equity screen that combines daily price range, sustained profitability, and dividend payout history. The initial rule requires amplitude above 1, return on equity above 15% for five consecutive years, and a dividend payout…
The document describes an Expert Advisor that trades when the Laguerre_ADX indicator’s cloud changes color. It generates a signal at the close of the bar where the color change occurs. The strategy therefore uses an indicator-state transition as its entry…
This document presents a Chinese equity selection rule combining daily price amplitude, a price threshold, and historical revenue growth. The stated conditions are amplitude above 1, closing price below 20, and 2021 revenue more than 1.1 times 2018 revenue.…
This document describes a Chinese equity screen using three filters: RSI below 65, 2021 revenue more than 1.1 times 2018 revenue, and a positive 10-day gain below 35%. It proposes selecting the first N qualifying stocks and holding them for a year. The…
The post asks how to persist and reload a model produced by the newer BigQuant DAI stock-ranking workflow. It describes reading a model data source, saving it with pandas pickle, then loading it in a custom Python module and writing it back as a data source.…
This brief post presents a modified Damiani Volatmeter indicator for MetaTrader 5. Its author says a subtle implementation error caused the indicator to produce different values in visual backtesting, non-visual backtesting, and live charts. The stated…
The document describes a timing question in a daily trading strategy. Signals are created in an after-market routine, while orders are submitted in a data handler and intended to fill at the opening price. The author expects a signal generated after one…
This catalog describes built-in quantitative data fields for Chinese A-share equities. Its factor families include historical prices, returns, trading volume and value, turnover, active money flows, valuation ratios, profitability and balance-sheet measures,…
This document describes an Expert Advisor that generates a trading signal when the i4_DRF_v3 indicator histogram changes color as a bar closes. It is an indicator-driven rule: the EA reads the color transition at the completed bar and forms a signal, with…
This Chinese-language Q&A clarifies two optional inputs for BigQuant strategy backtests or simulations. Backtest historical data is the replayed market bar data and corresponds to the data argument of the trade function. Other data input supplies external…
This article describes a daily pre-market stock screen for Chinese equities. It selects stocks whose MACD value is above zero, whose trailing price-to-earnings ratio is positive, and whose observation falls in 2021. The article interprets positive MACD as an…
This document is a historical trading-platform report for an EURGBP system on daily data covering October 2021 through September 2022. It lists extensive configuration settings, including ATR, ADX, moving-average periods, spread and margin limits, trend…
This beginner’s reflection defines quantitative investing as identifying relationships between inputs, or factors, and future returns, checking those relationships against historical data, then using current observations to estimate future opportunities. It…