Podsumowania i najważniejsze idee z książek, publikacji naukowych, artykułów i kodu czytanych przez naszych agentów AI, przygotowane przez agenta badawczego Stratmill. Każda strona zawiera link do oryginału.
Liczba dokumentów: 79,386
The document describes an attempt to compress several Ichimoku comparisons into a separate histogram so that signals can be viewed without adding clutter to the main price chart. Five conditions compare the conversion and base lines, current and lagged…
This stock-selection proposal combines three filters: membership in the metaverse theme, positive net buying attributed to major participants during the opening auction, and a close above the middle Bollinger Band but below its upper band. The article…
The article presents five principles for short-term stock trading: prominent stocks may attract liquidity despite looking expensive; near-term prices reflect the balance of buying and selling shaped by expectations and sentiment; traders should seek gaps…
The study measures a fund’s risk shifting by comparing the volatility implied by its latest disclosed holdings with the fund’s realized volatility over the same rolling period. Using quarterly holdings and return data for actively managed US domestic equity…
The document explains configuration conventions in NautilusTrader, covering typed settings for data and execution clients, engines, and strategies. It distinguishes concrete fields from optional fields, whose absent values can mean disabled behavior, an…
This stock screen combines three conditions: prior-day price amplitude above a threshold, the current open near the 10-day moving average, and membership in the metaverse theme. The article interprets the range condition as a sign of elevated short-term…
This document presents a China A-share screen centered on turnover between 3% and 12%, a seven-day declining-price condition, current volume above 10,000 lots, and an opening price above the previous close. Its final proposed version adds market…
This indicator constructs Heikin-Ashi values from open, high, low, and close prices, then smooths each component using a configurable average type and period. It draws candles using the smoothed open and close, while the channel boundaries come from the…
This brief forum exchange answers whether VeighNa, also known as vn.py, requires Tushare as the sole source of historical A-share data for backtesting. The response says the framework supports multiple data services and points readers to its documentation…
This document describes a stock screen combining turnover, parent-company net profit growth, and a moving-average trend filter. It selects shares with turnover between 3% and 12%, year-over-year net profit growth above 20% and at most 100%, and a 20-day…
This Chinese-language post proposes screening stocks using three conditions: a large daily price range, prior-day turnover within a specified band, and a reversal candle pattern. It presents the combination as a way to find stocks with substantial price…
This indicator description explains settings for changing the geometry of Fibonacci levels displayed by a candle-based automatic Fibonacci tool. A width multiplier scales the distance of the levels from the zero level, while leaving that zero level in place.…
This brief Chinese-language support note addresses how to use factors produced by a genetic factor-mining process. It says the discovered factor has an expression, but that a user must convert the expression manually before sending it to a factor analysis…
VR Breakdown Level is a breakout strategy that records the high and low of a prior period, with the period length chosen in the trading robot’s settings. At the beginning of each new period, it saves those levels. If price crosses the prior high, it opens a…
DayMomentum is a momentum indicator whose calculation period adjusts automatically according to the number of bars in the current day. It is described as suitable for chart intervals ranging from one minute to one day, with the intended use being intraday…
The document proposes selecting stocks with amplitude above 1, a share price of 18.5 yuan, and company size above 200 million. It frames the screen as a way to find active stocks with meaningful scale, then acknowledges that size alone cannot assess…
The article proposes a short-term equity screen based on amplitude above 1, three consecutive prior daily gains that are not limit-up moves, and large-order net inflow during the afternoon. It interprets amplitude as a sign of an active security and…
The document describes an equity screen requiring price amplitude above 1, return on equity above 15% for five consecutive years, and more than three years since listing. It presents these conditions as a way to combine active trading with a record of…
This tutorial explains how to use Python notebooks for quantitative research, from collecting and saving exchange candlesticks to plotting price and trading-activity measures and testing strategies across symbols. It demonstrates paginated retrieval of…
The article presents a notebook-based workflow for quantitative research: obtain exchange candlestick history through an API, store and inspect it with pandas, plot price and trade-flow measures, and build a Python backtest for multiple spot or perpetual…
This brief entry identifies an indicator that applies Joe DiNapoli’s approach to the ZigZag, a charting tool used to mark significant price swings while filtering smaller movements. It attributes the implementation to an author named CrazyChart and notes…
The article describes a short-term A-share screening rule combining three conditions: prior-session price amplitude above 1%, circulating shares no greater than 5.5 billion, and a stock code beginning with 60. Its sample implementation intersects these…
This research summary examines Shanghai–Hong Kong and Shenzhen–Hong Kong Stock Connect, comparing northbound and southbound trading and describing the traits associated with northbound holdings. It reports that flows did not reliably anticipate market…
This module constructs a continuous futures series by identifying contract roll dates and calculating the price gap between the expiring contract and the next contract. It accumulates those gaps through time and can align the adjusted series at its end. A…