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知識圖書館

這裡收錄 Stratmill 研究代理對 AI 代理閱讀過的書籍、論文、文章與程式碼所寫的摘要與核心觀點。每個頁面都連結至原始資料。

Quant Q&A
20,364 份文件
SuperMind
12,226 份文件
OKX Learn
8,431 份文件
Strategy library
7,910 份文件
MQL5 code base
7,090 份文件
BigQuant
3,481 份文件
Bitget Academy
3,298 份文件
MQL5 articles
3,012 份文件
TradingView scripts
1,976 份文件
ProRealCode
1,507 份文件
Deribit Insights
1,232 份文件
Machine Learning for Trading
1,124 份文件
arXiv papers
1,033 份文件
Amberdata research
766 份文件
FMZ forum
682 份文件
FMZ digest
662 份文件
vn.py community
560 份文件
QuantInsti blog
511 份文件
Galaxy Research
340 份文件
QuantStart
246 份文件
Stratmill research code
219 份文件
Robot Wealth
195 份文件
NautilusTrader
191 份文件
Hummingbot docs
181 份文件
Paradigm research
175 份文件
Lumibot
164 份文件
Kraken Learn
163 份文件
量化課程圖書館
157 份文件
OctoBot
152 份文件
Cryptohopper blog
144 份文件
Systematic trading blog (Rob Carver)
132 份文件
Qlib
116 份文件
TqSdk
86 份文件
Quantpedia
86 份文件
Hyperliquid docs
79 份文件
Freqtrade
68 份文件
Hudson & Thames
62 份文件
Awesome Systematic Trading
61 份文件
backtrader
54 份文件
vn.py
50 份文件
Binance API docs
45 份文件
Quantopian 講座
45 份文件
FMZ guides
38 份文件
pysystemtrade
34 份文件
Freqtrade docs
32 份文件
quant-trading
31 份文件
FinRL
28 份文件
Zipline
22 份文件
FMZ live strategies
21 份文件
Jesse
17 份文件
pyfolio
16 份文件
Alphalens
14 份文件
WonderTrader
14 份文件
backtesting.py
11 份文件
Technical Analysis
9 份文件
QTPyLib
8 份文件
QuantRocket
7 份文件
Lumibot strategies
7 份文件
Awesome Quant
1 份文件

搜尋圖書館

12,226 份文件

SuperMind

This stock-selection note proposes screening for shares with a daily trading range above a threshold, no limit-up close on the prior day, and a newly formed KDJ bullish crossover. It presents the crossover as a technical signal that may mark the start of an…

股票中國市場技術指標動能
SuperMind

This Chinese-language post presents a stock-selection screen combining an RSI below 65 with price change multiplied by super-large-order net flow, followed by a ranking on large-order net flow. It frames RSI as a technical filter and order-flow measures as…

股票中國市場技術指標動能
SuperMind

This Chinese-language post outlines an A-share stock screen using a daily high-low range above 1%, a closing price of 18.5 yuan, and a 30-day moving average that is rising. The range condition is intended to select volatile shares, the fixed price is…

股票中國市場技術指標趨勢追蹤
SuperMind

The post proposes selecting stocks whose MACD is above zero, whose company characteristics are considered favorable, and whose market popularity ranks highly. This blends a technical momentum signal with a basic company-quality filter and investor attention.…

股票中國市場動能技術指標
SuperMind

This post describes a Chinese equity selection idea that combines daily price amplitude, a ranking based on net large-order volume, and a “today control” threshold above 21. It presents amplitude and order-flow measures as ways to find active stocks, while…

股票中國市場技術指標風險管理
SuperMind

The document describes a Chinese equity screening rule that selects stocks with turnover between 3% and 12%, year-over-year net profit growth attributable to parent-company shareholders above 20% and at most 100%, and a share price below 12. It presents the…

股票中國市場因子投資風險管理
SuperMind

This screening proposal selects Chinese equities using three conditions: daily amplitude above one percent, a closing price below 20, and at least two limit-up events within 500 days. The article frames amplitude as a measure of price fluctuation, the price…

股票技術指標動能風險管理
SuperMind

The document introduces the momentum line, or MTM, as the difference between the current closing price and the close from a chosen number of days earlier. Connecting these values produces the momentum series. A moving average of recent MTM readings provides…

股票動能技術指標回測
SuperMind

This document proposes screening Chinese A-share stocks for turnover between 3% and 12%, a recent bullish KDJ crossover, and a rounded-base chart pattern. Its indicator example also requires the close to be at or above the 20-day moving average. A Python…

股票中國市場技術指標動能
SuperMind

The document describes a Chinese equity screen for robot-themed stocks with daily price amplitude above 1%, circulating market value below 10 billion, and daily return between -5% and 2.6%. It outlines formula-style and Python examples for applying the…

股票中國市場技術指標風險管理
SuperMind

This short-term stock screen selects main-board shares with turnover between 3% and 12%, a daily gain above 1%, and more than two limit-up days within a ten-day window. The article frames turnover and daily gains as signs of activity, while repeated…

股票中國市場動能技術指標
SuperMind

The article examines how training-window length can affect an AI stock-selection model. It compares longer historical samples with shorter windows using manual rolling training and a held-out backtest period. In the reported experiments, changing the…

機器學習統計回測因子投資
SuperMind

This stock-screening method combines a turnover range of 3% to 12% with exclusion of Beijing-listed A-shares and a newly formed KDJ golden cross. The cross is defined as the K line moving above the D line after being below it, using a nine-period price range…

股票中國市場技術指標動能
SuperMind

This Chinese-language post gives a rule-based screen for stocks in the metaverse theme. It selects names whose price change by 9:25 is below 6% and whose previous-day opening-auction turnover rate exceeds 0.26. The author frames auction turnover as a way to…

中國市場股票技術指標市場情緒
SuperMind

The strategy ranks stocks each month using five inputs: trailing-twelve-month price-to-earnings and price-to-sales ratios, price-to-book value, one-month price momentum, and one-month trading value. The author reports that trailing-twelve-month PE and PS…

股票因子投資動能投資組合建構
SuperMind

This guide explains two Rust workflows for running Nautilus Trader backtests. The lower-level BacktestEngine approach assembles a simulated venue, instruments, in-memory market data, and a strategy before running the engine. It allows direct configuration of…

回測交易執行期貨外匯
SuperMind

This Chinese-language post outlines an equity screen that ranks stocks by a measure of capital strength derived from trading volume and float capitalization, then selects those whose KDJ indicator has just formed a bullish crossover. The initial description…

股票中國市場技術指標動能
SuperMind

This A-share screening rule selects stocks with an intraday amplitude above 1 and MACD above zero, then chooses the top five by the day's auction-related turnover measure. The stated reasoning is that a positive MACD may indicate a favorable trend, while…

股票中國市場技術指標動能
SuperMind

This A-share stock screen combines a relative strength index below 65, a historical dividend payout ratio above 25% for 2019, and a ranking by stock popularity. Its stated rationale is to blend a technical filter, market activity, and a dividend-related…

股票中國市場技術指標因子投資
SuperMind

This A-share screening idea looks for stocks with MACD above zero that had three consecutive limit-up sessions through the prior day, then ranks candidates by reported popularity. It is intended to combine a positive technical signal with recent momentum and…

股票中國市場動能技術指標
SuperMind

This stock screen combines a 14-period RSI below 65 with a listing-age filter and a 15-minute MACD condition described as shortening green histogram bars. The proposed refinement adds a minimum market capitalization of 5 billion and excludes a specified…

股票技術指標動能中國市場
SuperMind

This proposed Chinese stock screen selects companies associated with the metaverse theme when an institutional-flow indicator is positive and the stock has recorded three consecutive daily declines. The document gives formula references and sample Python…

股票技術指標中國市場事件驅動