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 report overview describes Vanguard’s growth, product mix, and emphasis on keeping investment costs low. It presents historical figures for assets, product counts, investor reach, and average fees, and discusses the firm’s expansion into ETFs and…

多資產股票固定收益投資組合建構
BigQuant

This essay contrasts three broad approaches to investing through Warren Buffett, George Soros, and James Simons. It describes Soros’s reflexivity framework, in which investor beliefs can move prices and price changes can then reinforce those beliefs. Buffett…

多資產市場情緒統計機器學習
BigQuant

This essay presents five principles for discretionary and system traders: focus on the traded price rather than attaching to an investment label, treat each position as an uncertain wager, respond through a plan instead of trying to forecast every move,…

風險管理交易執行統計
BigQuant

This study summary examines whether index futures information can improve high-frequency technical trading rules for Chinese index ETFs. It uses genetic programming to evolve rules from five-minute price data for CSI 300 and CSI 500 ETFs and their…

期貨股票中國市場高頻交易
BigQuant

This analysis estimates how difficult it is to earn excess returns by allocating among industries. It simulates quarterly selections of Chinese industry groups over 2005 Q1 through 2018 Q1. In the random-selection tests, portfolios choosing five industries…

中國市場股票投資組合建構回測
BigQuant

This introductory guide compares two versions of a quantitative data platform and outlines programming skills for building research workflows. It describes the newer platform as using SQL for data access and calculations, while the older version uses a…

多資產
BigQuant

This note describes a method for splitting a stock’s recent trading days by average transaction value, calculated as daily traded value divided by trade count. Over an even-length lookback window, it ranks days by this measure, sums returns for the…

股票均值回歸動能因子投資
BigQuant

This study examines whether U.S. equity mutual fund managers adjust market exposure when stock misvaluation is unusually high. It measures common misvaluation with a financing-based factor that buys repurchasing firms and sells issuing firms, then removes…

股票因子投資統計回測
BigQuant

The document summarizes a position-sizing method derived from a drawdown adjustment lemma. It describes a strategy that uses observed data to adjust market exposure toward a chosen drawdown tolerance, without relying on future prices. A related index-timing…

中國市場股票風險管理部位規模
BigQuant

This support post reports a KeyError during a Chinese equities factor analysis. The example defines an operating cash flow growth factor, selects the CSI 300 universe and benchmark, and requests ten portfolio groups. The failure occurs when the analysis…

股票因子投資統計
BigQuant

This report describes combining individual-stock timing with multi-factor stock selection in a T+0 strategy. It uses deep-learning ideas to reduce a multidimensional space of parameter settings and win rates, then examines how performance changes across…

股票高頻交易機器學習回測
BigQuant

This report compares machine-learning stock-selection models trained with conventional return labels against models using information ratio or Calmar ratio labels. The alternative labels incorporate aspects of the path within the evaluation period, including…

股票機器學習因子投資統計
BigQuant

This research summary examines why analyst earnings forecasts can vary widely and how that dispersion relates to subsequent stock returns. It focuses on the possibility that companies delay disclosing bad news, leaving analysts with incomplete information…

股票統計市場情緒
BigQuant

This brief outlines a stock-selection approach that first looks for shares with recent market activity, checks for changes in capital flows, and applies multiple factors. It presents these as broad screening ideas rather than a fully specified trading…

股票因子投資
BigQuant

This explanation describes a factor evaluation score derived from rolling Elastic Net regressions that include all submitted factors together. The model predicts each stock’s next-day return after cross-sectional standardization, fits on rolling windows, and…

機器學習統計因子投資投資組合建構
BigQuant

This page summarizes a research report on high-frequency factors derived from intraday trading activity. Its central idea is to select particular time windows within a trading day, calculate each window’s traded volume as a share of the day’s total volume,…

高頻交易市場微結構統計
BigQuant

This article reviews an international study of whether mutual funds benefit when their investors are less exposed to the same market shocks as the stocks held by the fund. It describes two measures: whether sales and investment countries differ, and an…

股票投資組合建構風險管理統計
BigQuant

This systematic literature review summarizes research on artificial intelligence in financial trading published from 2015 to 2023. It reports screening 143 papers across multiple research databases and compares the markets and assets studied, analytical…

機器學習統計回測風險管理
BigQuant

This review summarizes research comparing the returns of published stock market anomalies before and after academic publication. The study examines 241 anomalies across the United States and 38 international markets, constructing long-short returns and…

股票因子投資統計美國市場
BigQuant

This research summary examines residual momentum, also called idiosyncratic momentum: a stock’s return after removing shared market influences. It reports that, in China’s A-share market, stronger residual returns in the prior period are associated with…

股票動能因子投資中國市場
BigQuant

This paper summary describes an online learning method based on adversarial experts for selecting parameters in a zero-cost portfolio of technical trading strategies. The method combines a collection of historically tested strategies and studies their…

機器學習技術指標套利回測
BigQuant

The document summarizes research on an adversarial-experts online learning algorithm that adjusts parameters for a zero-cost portfolio of technical trading strategies. The approach combines a collection of strategies into an aggregate portfolio and studies…

股票技術指標機器學習統計
BigQuant

This opinion essay argues that individual investors should be cautious about short-term stock speculation as algorithmic trading becomes more prominent. It attributes the challenge to faster execution and competition from technically sophisticated firms, and…

股票風險管理統計
BigQuant

The article advises individual equity investors to trade less frequently, favor larger and more stable companies over small speculative stocks, and follow explicit risk rules. Its suggested practices include avoiding fully invested positions, setting profit…

股票風險管理部位規模交易執行