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.
79,386 documents
The Volatility Quality Index is described as a trend-oriented indicator that marks upward and downward direction with green and red signals. Its calculation uses smoothed open, high, low, and close values, compares the current close with a lagged smoothed…
This document describes a MACD variation that uses a nonlag moving average in place of the conventional exponential moving average for the MACD calculation. It also applies the nonlag average to the signal line, presenting the indicator as a faster-reacting…
This study builds a convertible-bond strategy that separates bonds into equity-like, balanced, and bond-like groups using parity premium relative to bond value. It models each bond as a floor component plus option time value, then examines where factor…
This research proposes treating convertible bonds differently according to whether they are bond-like, balanced, or equity-like, classified by the premium of parity value over bond value. It explains a valuation decomposition in which a bond floor or…
This selection method looks for stocks with amplitude above 1, ranks them by large-order net volume, and excludes stocks that closed at the upper price limit on the previous day. The article includes sample screening logic and Python-style data retrieval,…
This stock screen combines three conditions: daily price amplitude above 1, a dividend yield above 25% for 2019, and a Shanghai listing code beginning with 60. The article gives example formula and Python implementations, with the Python example sorting…
This document describes an MDAC indicator that colors chart bars to communicate trend state. Green denotes an uptrend, red denotes a downtrend, and blue bars appearing after either of those colors indicate a possible trend change. The color scheme offers a…
The document describes Humanoids, an Ethereum-based NFT collection of robotic characters, and outlines its two editions: Gen 1 and Gen 1.1. It compares the collection’s visual and collectible framing with CryptoPunks, while emphasizing its polished 3D…
This stock selection approach looks for shares with MACD above zero and short-term moving averages spreading upward, while excluding stocks from China’s STAR Market. It presents the screen as a way to identify stocks with positive trend signals and avoid a…
This document outlines a two-stage workflow for calculating Alpha101 factors. First, it reads daily stock data, derives base series such as returns and VWAP, and computes time-series intermediate variables for storage. Later, factor construction retrieves…
This proposed screen combines price movement, company size, profitability, exchange segment, valuation, and share price. It selects stocks with amplitude above 1, market capitalization below 10 billion yuan, positive net profit, and Shenzhen Main Board…
This document describes an A-share stock screen that looks for amplitude above 1 and a weekly five-period moving average crossing above the ten-period average, while excluding Beijing-listed companies. It presents the crossover as a trend condition and…
The Fractal Graph Dimension Indicator is presented as a way to distinguish trending conditions from unstable, volatile conditions. It has three inputs: the calculation period, the applied price, and a threshold. Readings below the threshold are classified as…
This indicator is designed to alert when market price crosses a moving average. Users set the moving-average length, with 200 periods given as the default, and choose a point-distance threshold that determines when movement across the average counts as a…
This brief note describes CHO_HTF, a version of the CHO indicator that lets the user select a calculation timeframe independently through an input parameter. The example default is a four-hour period, allowing the indicator to be applied while viewing a…
This configuration describes a Qlib workflow for training a KRNN model on China’s CSI 300 universe with Alpha360 features. It sets a historical data range, uses robust feature normalization and cross-sectional label ranking, and defines a two-day forward…
This algorithm implements a monthly cross-sectional momentum strategy in US equities. It ranks eligible stocks by their trailing 12-month return, with the most recent month skipped to reduce microstructure and liquidity biases. The highest-ranked group is…
The post proposes selecting stocks using three recent market-activity measures: daily high-to-low amplitude above 1, actual turnover between 3% and 28% on the prior day, and prior-day trading value above 60 million yuan. It frames the combination as a way to…
This post outlines a Chinese equity screen that combines recent capital accumulation with company fundamentals. Its initial filters seek stocks with a market capitalization below the stated ceiling, no history of losses, and parent-company net profit growth…
The guide explains how FMZ handles sensitive account details and strategy parameters. It says these values are encrypted in the browser and stored as encrypted data, with decryption available on the user's private device. It also cautions against exposing…
This note outlines a Chinese stock screen focused on the metaverse theme, smaller share float, positive price change, and a “main uptrend start” signal. Its final stated rules add a market-value ceiling of 10 billion yuan and cap circulating shares at 5.5…
This note proposes selecting non-ST stocks with turnover between 3% and 12%, a rising DEA signal, and a limit-up move before 10:00. It describes this as a short-term limit-up approach, using the early timing of the price move alongside a trend filter and…
This note presents a stock screen for shares with daily amplitude above 1%, an opening price near the 10-day moving average, current volume above 10,000 lots, and a high open. The example formulas define “near” as within 5% of the average and identify a high…
This note describes a short-term stock screen combining turnover rate, recent price performance, and a newly formed KDJ golden cross. It selects stocks with turnover between 3% and 12%, a positive 10-day gain below 35%, and a fresh bullish KDJ crossover. The…