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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-screening approach selects securities with MACD above zero and a weekly close crossing above its 30-week moving average, then ranks candidates by market attention or heat. It runs after each trading day’s close. The stated rationale is to pair a…

股票動能趨勢追蹤技術指標
SuperMind

This document presents a Chinese equity screen that combines a turnover band with seven consecutive declining sessions and a nonempty name for an outstanding convertible bond. It then proposes adding fundamental filters: market capitalization above the…

股票中國市場技術指標統計
SuperMind

This stock-selection rule combines three filters: a high-to-low daily range above 1%, a daily decline between 4% and 5%, and a positive price-to-earnings ratio. The article offers formula and Python examples, although the displayed formula does not appear to…

股票技術指標統計回測
SuperMind

This stock-selection idea screens shares whose codes begin with 60, whose high-to-low daily range exceeds 1%, and that meet a reversal or “wraparound” candlestick condition. The article gives formula and Python examples, but the definitions are not fully…

股票技術指標中國市場回測
SuperMind

This screening method selects stocks with market capitalization below 10 billion yuan, positive earnings, and an RSI below 65, then orders candidates by money-flow strength. It describes the money-flow measure as Chaikin Money Flow and gives a 20-period…

股票技術指標動能因子投資
SuperMind

This stock screen combines three conditions: daily amplitude above 1, at least one limit-up event within the past month, and a 20-day moving average above the 120-day moving average. The moving-average relationship is intended to identify an upward trend,…

股票趨勢追蹤技術指標中國市場
SuperMind

This Chinese stock-screening idea ranks candidates by volume ratio and filters for turnover between 2% and 9% and a positive ten-day gain below 35%. The article interprets stronger volume ratio as greater investor attention, the turnover range as a sign of…

股票中國市場動能技術指標
SuperMind

This stock-selection rule combines a turnover filter, a beverage and alcohol industry screen, and a weekly moving-average crossover. It selects stocks with turnover between 3% and 12% when the weekly five-period moving average crosses above the ten-period…

股票中國市場技術指標
SuperMind

The post describes a stock-selection screen based on three technical conditions: price amplitude above a threshold, a rounded price shape, and a rising DEA indicator. It interprets the amplitude condition as a way to select active stocks without excessive…

股票技術指標動能
SuperMind

This stock-selection rule combines a 14-period RSI below 65 with three consecutive declining sessions and a condition intended to identify upward divergence between short- and longer-term moving averages. The post presents the rule as a way to screen for…

股票中國市場技術指標動能
SuperMind

This stock-selection proposal combines a price-amplitude filter with a turnover and auction-volume condition, then requires return on equity (ROE) to exceed a stated threshold over five years. The central liquidity-style condition is yesterday's turnover…

中國市場股票因子投資技術指標
SuperMind

This Chinese-language community discussion asks how to calculate a market measure commonly translated as main-force net inflow. The post proposes defining it as the sum of actively initiated buy orders classified as large and extra-large. This frames the…

股票市場微結構統計
SuperMind

This post proposes a short-term China A-share screen combining three conditions: prior-session amplitude above 1%, tradable shares no greater than 5.5 billion, and more than two limit-up days within ten sessions. The rationale is to find active, relatively…

中國市場股票動能技術指標
SuperMind

This stock-selection screen combines trading activity, company size, market value, and profitability. Its final criteria require turnover of up to 12%, circulating market value between 10 and 100 billion yuan, circulating share count no greater than 5.5…

中國市場股票因子投資部位規模
SuperMind

The document describes an A-share stock screen for companies associated with robotics. Its stated filters include turnover between 3% and 12%, total market value below 10 billion yuan, positive net income, and circulating market value below 10 billion yuan.…

股票中國市場因子投資
SuperMind

This document presents an A-share stock selection idea that combines turnover between 3% and 12%, a K indicator below 20, and three consecutive days of falling closing prices. It describes the signal as a technical screen for stocks that might merit…

股票技術指標均值回歸
SuperMind

This document outlines an equity screen beginning with stocks whose daily price range exceeds 1%, market capitalization is at most 10 billion yuan, and average net profit is positive, while excluding stocks that hit the daily limit on the prior session. Its…

股票技術指標因子投資風險管理
SuperMind

This document presents an equity selection rule using a turnover range of 3% to 12%, seven consecutive down days, and a pattern described as the start of a strong advance. It gives indicator-formula and Python examples intended to identify the setup,…

股票技術指標動能突破
SuperMind

This document describes an equities screening rule combining a turnover range, beverage and alcohol industry classification, and a comparison between displayed best bid and ask quantities. It presents the intended screen as selecting stocks with turnover…

股票市場微結構技術指標回測
SuperMind

This document describes a short-term Chinese equity screen using three conditions: a share price below 12, more than two limit-up sessions within ten days, and amplitude above one. It frames repeated limit-ups as a possible sign of continued upside and…

股票動能突破中國市場
SuperMind

This stock-screening idea combines three conditions: a rising 30-day moving average, three consecutive declining sessions, and a reported increase in position or capital inflow greater than five percent. The rationale pairs a positive longer-term trend with…

股票技術指標均值回歸動能
SuperMind

This reference catalog groups Python libraries used across quantitative finance. It covers strategy research and backtesting, technical indicators, risk and portfolio analysis, scientific computing, derivatives pricing, factor and time-series analysis,…

回測技術指標風險管理投資組合建構
SuperMind

This Chinese equity screen requires turnover between 3% and 12%, a rising DEA condition, and a reversal pattern described as a rebound after a short pullback. The note frames turnover as a measure of trading activity and rising DEA as evidence of an upward…

股票技術指標動能中國市場
SuperMind

This Chinese stock-selection rule combines three filters: rank stocks among the top 100 by volume ratio, rank the top 100 by the absolute difference between the previous day’s limit-down price and opening price, and require at least two limit-up days within…

股票動能波動率中國市場