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.
12,303 documents
This Chinese stock-screening note describes a rule that combines daily price amplitude, a bounded turnover rate, and a ranking based on large-order net flow. Its rationale is to find shares with meaningful price movement and trading activity while using net…
This Chinese-language post describes an equity screen combining price amplitude above 1, a 2019 dividend ratio above 25%, market capitalization below 10 billion yuan, and positive profits. It frames the criteria as a way to find smaller companies with…
The article defines altcoins broadly as cryptocurrencies other than Bitcoin and groups many of them into four categories: utility tokens, security tokens, non-fungible tokens, and stablecoins. Utility tokens can provide access to network services or…
This stock-selection method combines price range, recent large gains, and a trading-activity proxy. It looks for stocks with amplitude above 1, at least one daily gain of 10% or more during the past 25 trading days, and an external-to-internal trading volume…
The document describes a chart indicator that displays the high and low for a selected time frame on the current chart. Users can limit how many earlier higher-time-frame values remain visible, which helps reduce chart clutter while retaining recent…
This Chinese A-share screen combines daily price range, company size, profitability, an industry rating, and share price. It selects stocks with at least a 1% high-to-low range, positive net profit, market capitalization no greater than 10 billion yuan, an…
This document describes a price envelope built around a smoothed estimate of the underlying trend. It uses an endpoint Nadaraya-Watson estimator with kernel weights to calculate the centerline, then estimates deviations from that line using an exponentially…
This Chinese equity screen combines three daily price conditions: an amplitude above 1%, a session low below the previous session’s low, and an opening gain below 6% in absolute terms. The post interprets the combination as a way to find volatile stocks that…
This document describes a chart indicator that draws two colored filled rectangles between values of two Bollinger channels on a bar. The channels are based on a configurable smoothed average and two deviation settings, with separate colors for the upper and…
The document describes a stop indicator that uses smoother momentum both to determine stop direction and to set stop distance from an average. Momentum therefore serves two roles: it signals the prevailing direction, and its value controls how widely the…
This document describes a short-term stock screen combining a prior-day amplitude threshold, appearance on the previous day's market activity list, current trading volume above a stated threshold, and an open price above the close. It explains the intended…
AlphaTrend is presented as a trend-following indicator derived from Trend Magic. Its line uses the Money Flow Index to choose a price anchor: below the low when money flow is at or above its midpoint, and above the high when it is below that level. An…
The indicator combines several elements associated with the Trading Chaos approach. It displays the Alligator’s jaws, teeth, and lips, then marks countertrend divergent bars, momentum signals from three same-colored Awesome Oscillator bars, and trend signals…
This post describes a Chinese equity screen that selects stocks using three price conditions: daily amplitude above 1%, a positive but less than 35% return over ten days, and a price move below 6% at the 9:25 reference point. It explains amplitude as a proxy…
The document explains how implied volatility (IV) surfaces organized by option moneyness can help identify relative pricing anomalies. A floating surface compares options at their actual listed expirations, while a constant surface interpolates or…
This note describes a simple Chinese-equity screen: select stocks whose daily high-low range exceeds 1% of the previous close, whose codes begin with 60, and which are outside the STAR Market. It provides corresponding formula and Python examples, making the…
This weekly market review surveys Bitcoin and Ether options through realized and implied volatility, term structure, skew, relative value, option flows, and dealer gamma positioning. It describes falling front-end implied volatility, a pronounced shift…
The Count Back Line (CBL), attributed to Daryl Guppy, is presented as a volatility-based indicator with upper and lower levels that can mark potential trend boundaries. The supplied implementation searches backward from a new high for two successively lower…
This indicator combines a recursive Kalman filter, a Hull-style moving average, and Supertrend logic. It filters the selected price input through multiple Kalman states, uses those estimates to form a smoother baseline, then places volatility bands around…
The document presents an adaptive exponential moving average whose calculation uses normalized Average True Range. Its motivation is that fixed-period indicators may respond poorly when market conditions change, while an EMA can accommodate fractional…
This post describes a stock screen using three conditions: a daily high-low range exceeding one percent of the previous close, a trading date in 2021, and a smoothed stochastic-style K value below 20. It supplies formula and Python examples for calculating…
This article describes ways to adjust market-making configurations for range-bound, rising, and falling markets. In a range, it proposes estimating the price span to capture and splitting that span between bid and ask offsets around the midpoint. It also…
The document presents an A-share stock screen combining daily price amplitude above 1%, a nonempty name for an outstanding convertible bond, and a three-session limit-up condition on the previous day. It describes these filters as a way to find volatile,…
This note describes a daily stock screen that selects A-shares in 2021 when the intraday high-low range exceeds 1% and the daily return is between -5% and 2.6%. It gives example implementations using a market formula and Python data processing, although the…