跳至內容

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

3,481 份文件

BigQuant

This article introduces discrete-time stochastic control as a method for dynamic asset allocation. Unlike a traditional mean-variance allocation made without an explicit sequence of future decisions, the approach models portfolio choices across multiple…

多資產投資組合建構統計中國市場
BigQuant

This brief support exchange explains why a MACD histogram value can shift substantially when the start date of a stock data list changes. The explanation points to the initialization of the exponential moving average: its first value is not fully smoothed,…

技術指標統計
BigQuant

This document describes a Chinese stock strategy that combines classification and regression models to forecast intraday returns. It uses XGBoost and an ensemble of machine learning models, drawing on 15 features related to overnight returns, opening auction…

中國市場股票機器學習回測
BigQuant

This intraday system trades the CAC 40 on a 15-minute chart, taking both long and short positions during a defined daytime session. Long entries require the MACD line to cross above its signal line, RSI to remain below an upper threshold, and price to be…

股票技術指標回測交易執行
BigQuant

This report summary explores whether macroeconomic indicators can help select individual Chinese stocks, rather than serving only for asset allocation or industry rotation. It proposes estimating each stock’s sensitivity, or MacroBeta, to economic indicators…

中國市場股票因子投資統計
BigQuant

This brief BigQuant platform note explains how to use a factor written as a SQL function and field within a strategy workflow. It distinguishes platform expression factors, described as an operator paired with a field, from SQL factors, described as a…

因子投資回測
BigQuant

This research review describes a study of whether year-over-year changes in company filings contain information about future stock returns and business performance. It compares filings using four text-similarity measures, sorts stocks by similarity, and…

股票市場情緒機器學習因子投資
BigQuant

The report describes a weekly market-timing model based on a linear-chain conditional random field (CRF). It frames the task as inferring market direction states from observed features, with CRFs able to represent dependencies between observations and…

股票中國市場機器學習回測
BigQuant

The document compares two ways to build multifactor equity portfolios. Integration ranks securities using a combined score for all target factors and selects a subset. Mixing first builds separate single-factor portfolios, then allocates among them. The…

股票因子投資投資組合建構回測
BigQuant

This overview presents a multi-factor model as a way to explain stock returns through shared risk exposures, factor returns, and stock-specific residual returns. It frames quantitative management as estimating factor behavior and managing portfolio…

股票因子投資統計投資組合建構
BigQuant

This article describes modifying OpenFE’s automated feature engineering workflow for futures research. It adds rolling mean, standard deviation, and sum operators across instrument groups, with preset window lengths, and explains how these operators are…

期貨機器學習因子投資統計
BigQuant

This personal account explains how an equity prediction model can appear strong in-sample yet fail when applied to unfamiliar stocks or later periods. The described experiment uses fundamental and technical features, including valuation, profitability,…

股票機器學習統計回測
BigQuant

This example describes a short-horizon stock rotation strategy. It selects shares whose prior-day return was between 2% and 8% and whose turnover was between 3% and 8%, then removes special-treatment shares, halted stocks, and listings younger than the…

股票動能中國市場交易執行
BigQuant

This report summary describes a method for refining traditional liquidity factors by incorporating intraday trading structure specific to China’s A-share market. The idea is to adapt a broad factor to market-specific trading patterns, with the report…

股票因子投資市場微結構統計
BigQuant

The note turns a discretionary stock method into explicit rules: admit a stock to an initial universe when its daily low stays above 99% of the 34-day moving average for ten consecutive days, buy when its profitable-chip proportion exceeds 73%, and sell when…

股票技術指標因子投資回測
BigQuant

This Chinese-language example sets up a test of whether stocks that have risen on each of the prior three days are more likely to rise the next day. It defines the condition as three consecutive daily price increases, each exceeding one percent, and labels…

股票動能統計
BigQuant

This strategy combines model-based stock ranking with trend filters for a selected universe of China A-shares drawn from the CSI 150 and related large-cap core-asset stocks. It aims to rank candidates for potential five-day strength, then apply timing…

中國市場股票機器學習動能
BigQuant

This research note examines an equity-selection factor built from differences in stock price behavior across the trading day. It reports that the original APM factor performed well in its in-sample period, weakened out of sample, and suffered a sustained…

股票因子投資統計回測
BigQuant

This article is a catalog of beginner-oriented examples for learning TensorFlow and TFLearn. It lists introductory operations, nearest-neighbor and regression models, neural networks, autoencoders, model saving, visualization, and multi-GPU basics. The…

機器學習
BigQuant

The document compares a traditional Chinese equity strategy that buys the smallest market-cap stocks with a StockRanker model that ranks stocks using market capitalization as its sole feature. Both are evaluated over 2015–2016, illustrating how a…

股票因子投資機器學習回測
BigQuant

The article reviews the 2021 revision of China's Shenwan industry classification and its possible uses in quantitative investing. The revision expanded coverage to A-shares, Stock Connect shares, and selected Chinese firms listed overseas, added three…

中國市場股票因子投資投資組合建構
BigQuant

The document describes a daily process for building a short-term stock watchlist. It starts by ranking stocks by traded value and keeping the top 50. It then removes stocks that gained less than 5% that day, those whose 30-day moving average is flat or…

股票動能突破技術指標
BigQuant

The document surveys the development of enhanced ETFs in China alongside the expansion of actively managed ETFs in the United States. It presents enhanced ETFs as an effort to seek returns above a benchmark while retaining ETF features such as intraday…

股票投資組合建構交易執行風險管理
BigQuant

This 2020 China equity-sector note combines macroeconomic regime signals, earnings relative to valuation, trend signals, historical regime matching, and public-fund holdings to discuss sector allocation ahead of interim reports. It argues that weaker growth…

中國市場股票動能因子投資