Resumos e ideias principais, escritos pelo agente de investigação da Stratmill, dos livros, artigos científicos, artigos e código consultados pelos nossos agentes de IA. Cada página inclui uma ligação para o original.
79,386 documentos
This guide describes how NautilusTrader builds and maintains positions from fills. It covers signed exposure, average entry and exit prices, realized and unrealized PnL, commissions, funding adjustments, and closure when net quantity reaches zero. It…
This brief indicator description explains that momentum expresses the relationship between a current price and the price a chosen number of periods earlier. It describes a visual display in which the indicator receives different color fills depending on…
This Chinese equity screening idea combines an RSI threshold below 65 with a circulating market value between 5 billion and 10 billion yuan and more than two limit-up days in a 10-day window. The stated rationale is to find relatively strong short-term…
Bridge Bands combine a price-based Bridge Range, Bollinger Bands, and a Hurst exponent to create a changing range around a security’s price. The described weighting uses Bollinger Bands when the Hurst estimate is near 0.5; as the estimate moves farther from…
This document describes a stock screen combining three conditions: amplitude above 1, a shortening negative MACD histogram on a 15-minute chart, and positive net buying attributed to major participants during the auction. The stated rationale is to find…
This trading system uses a color change in the JBrainTrend1Stop indicator at bar close as its entry signal. It adds to an existing trend-following position when open profit, measured in points, passes a threshold set in the Expert Advisor inputs. Position…
This note proposes selecting Chinese stocks associated with both the metaverse theme and beverage or alcohol import-export businesses, subject to prior-day actual turnover between 3% and 28%. It frames thematic exposure as a possible source of growth and…
This note describes a simple China A-share stock screen combining a turnover range of 3% to 12%, market capitalization below 10 billion yuan, no reported loss, and a closing price of 18.5 yuan. It presents the screen as a way to identify candidates for…
This document presents a daily stock-selection screen based on three price conditions: an intraday range greater than 1%, a reversal or engulfing-style candle pattern, and a daily return between -5% and 2.6%. It characterizes the idea as a possible…
This guide explains support and resistance as price areas where buying or selling pressure may stall or reverse a market move. It recommends starting with horizontal levels drawn around prior turning points, while emphasizing higher-timeframe references such…
This document describes a simple daily stock screen combining a turnover-rate band, the sign of a price-change and large-order-flow product, and a comparison of consecutive daily lows. It selects stocks with turnover between 3% and 12%, a positive product of…
The post proposes a stock screen requiring MACD above zero, positive trailing price-to-earnings, and previous-day turnover above 60 million. It says selection is performed before 10 a.m. and suggests sorting qualifying stocks by turnover. The stated…
This guide explains how to connect OctoBot’s GPT interface to a language model for trading evaluations. For OpenAI, it describes adding an API key in the interface configuration, enabling the GPTEvaluator, and choosing a model through evaluator settings. It…
The document describes an Expert Advisor that uses a three moving average cross to trigger trades and MACD as an additional entry check. A later update adds fixed percentage risk sizing and sets stop loss and take profit levels from ATR ranges, linking…
A forum exchange clarifies whether a strategy can retrieve tick data for futures product indices or weighted continuous contracts, using iron ore and an example continuous symbol. The reply explains that symbols ending in a continuous-contract convention are…
The proposed stock screen combines three signals: intraday amplitude above a stated threshold, ranking among the top five by that day’s auction amount, and short moving averages ordered above longer ones. The accompanying rationale treats amplitude and…
This research note describes two revisions to AlphaNet, a neural model that learns stock selection factors from raw price and volume data. Version two adds ratio features, replaces pooling and dense layers with an LSTM to capture temporal patterns, and gives…
The document presents a Chinese equity screening rule: select stocks whose codes begin with 60, whose turnover rate falls between 3% and 12%, and that did not hit the upper price limit on the previous day. It also includes a Python example that retrieves a…
The post describes a time-based controller for starting and stopping automated domestic futures trading robots. It checks the current time and weekday, uses a status flag to avoid repeated starts, and calls platform functions to restart or stop two named…
The document explains a Fisher Transform oscillator for price data. It first scales prices using a recent high-low range, smooths and bounds the normalized value, then applies a logarithmic transform and recursive blending. This process is intended to make…
This document presents a Chinese stock-selection screen using price amplitude, a concentration-related measure, and moving-average direction. Its initial description calls for amplitude above 1%, a concentration condition, and an upward 30-day average. A…
This document describes a modified Pretty Good Oscillator (PGO) that allows its values to be smoothed with a Timm Morris moving average. The stated purpose of smoothing is to filter some false signals. It recommends interpreting crossings of the zero line as…
This document describes a Chinese equity screening rule that selects metaverse-related stocks when an institutional-flow measure is positive and the prior day's actual turnover falls between 3% and 28%. It presents the conditions as a way to combine industry…
This FORTS Expert Advisor places limit orders around the best bid and ask when its spread condition is met. The spread input is measured in minimum price steps, so the threshold is converted using the instrument’s tick size. Once an order is accepted and a…