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This Chinese community post outlines an equity screen combining a price-range condition, five consecutive years of return on equity above 15%, membership in a robotics-related concept group, and circulating market value below 10 billion yuan. It presents the…
The document introduces an MQL4 display tool for showing daily percentage changes across symbols in a Market Watch list. It describes three visual modes—scale, gradient, and heatmap—and says the example uses RGB colors with the standard string-to-color…
The document outlines a technical stock screen requiring price amplitude above 1%, a high equal to the highest high over two days, and a newly formed KDJ golden cross. It presents these conditions as a way to find stocks with active price movement, recent…
This Chinese A-share screening strategy combines a technical condition, a fundamental growth condition, and a market price filter. It selects stocks with RSI below 65, year-over-year growth in net profit attributable to parent-company shareholders above 20%…
The document describes an indicator that uses principal component analysis to choose coefficients for instruments in a pseudo-stationary portfolio intended to return toward zero. It frames each instrument as a dimension in a multivariate dataset and uses PCA…
The document introduces a channel indicator that redraws using a specified number of bars ahead. Its only parameter described is a look-up distance of 24 bars, which controls how far the indicator looks forward. This makes the indicator’s plotted channel…
This overview describes an interactive Moody’s data story examining prominent stablecoin depegs through dynamic charts. The reported episodes include Terra’s collapse, an FTX-related USDT depeg, USDC losing its peg amid stress in traditional finance, and a…
This Chinese A-share selection screen combines an intraday price-movement filter with size, profitability, and pre-open price-change conditions. It seeks stocks with an amplitude above 1, market capitalization no greater than 10 billion yuan, positive net…
This indicator uses a rolling linear regression of closing prices to identify directional trend changes. It plots a blue line during a positive regime and a red line during a negative regime. The described settings use a 100-bar regression window and a…
This stock screen selects companies in the metaverse industry whose volume ratio is between 1.5 and 6 and whose best bid volume exceeds best ask volume. The article presents the conditions as a way to combine an industry theme with signs of elevated trading…
The proposed screen combines a volatility condition, a business-quality assessment, and a positive ten-day return capped below 35%. Its initial description calls for stocks with an amplitude above one and favorable enterprise characteristics. The expanded…
This stock screen selects Chinese equities whose codes begin with 60, whose intraday high-low range exceeds one percent of the prior close, and whose one-day return is below 2.6% but above negative 5%. The document gives both formula-style conditions and a…
The document describes an indicator that displays BrainTrend2_V2 candle colors across ten user-selected timeframes. Its inputs specify the timeframes and the bar from which to read a signal, along with the underlying indicator's ATR period. The display uses…
The discussion describes a rolling-window backtest in which parameters are optimized on a sequence of historical months and then applied to the next month. As the test advances, the training window shifts forward by one month, so each new period is evaluated…
This document explains how a backtest matching engine assigns fill prices across depth books, top-of-book data, and bar-based triggers. Market orders can walk available levels; limit orders use crossed prices when taking liquidity and their limit when…
The document describes a Chinese stock-selection screen combining turnover, order-flow imbalance, and positive returns. Its stated selection logic looks for stocks with turnover between 3% and 12%, an external-to-internal volume ratio above 1.3, and positive…
The document clarifies why a chart may show two values for the MESA Adaptive Moving Average (MAMA). It identifies the second value as the Following Adaptive Moving Average (FAMA), a companion average associated with John Ehlers. The two values are used…
This stock screen combines three conditions: amplitude above one, a prior-day 9:15 auction matched price at the limit-down level, and an appearance on the prior day’s trading list. The article interprets the filters as capturing volatility, weak market…
This document describes an Expert Advisor that acts on signals from a technical indicator called Stalin. A trade signal is generated when a colored arrow appears at the close of a bar, so the system’s entries depend on the indicator’s plotted direction cues.…
This stock screen selects shares with an amplitude above one, a price average above the five-day moving average, and high current-day auction turnover, retaining the top five by turnover. The article interprets the amplitude filter as a way to find volatile…
This Chinese equity screen combines a positive MACD reading with positive price change and positive large-order net buying. It also limits candidates to companies with market capitalization at or below 10 billion yuan and positive profit. The article frames…
This Chinese equity screening strategy selects robot-concept stocks with a turnover rate between 3% and 12%, a circulating market value below 10 billion yuan, and prior-session opening-auction turnover above 0.26. The article suggests the auction activity…
The document describes a simple indicator intended to assess autocorrelation in a price series. Positive readings are presented as signs of more directional movement, which might accompany a developing trend or a possible reversal. Negative readings are…
The document briefly introduces the Keltner channel as an indicator whose upper and lower boundaries depend on a multiplier and a chosen measure of range. It identifies two calculation approaches: averaging candle-body size or using average true range data.…