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
WonderTrader
14 份文件
Alphalens
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 document explains how time-series momentum (TSMOM) and moving-average crossover (MACROSS) strategies can represent closely related ways to measure price trends. It describes expressing trend signals through past prices or returns, and using “signature”…

趨勢追蹤動能技術指標統計
BigQuant

This document describes a Chinese A-share selection screen combining robot-industry exposure, small free-float market capitalization, turnover, and the stock’s price change at 9:25. The stated selection logic calls for turnover between 3% and 12%, robot…

股票中國市場動能技術指標
BigQuant

A platform forum exchange addresses whether a daily backtest that predicts a five-day return using the current day’s closing price can access that day’s prediction before the close is available. The response explains that, in the described daily setup, the…

回測機器學習統計
BigQuant

This guide presents local checks for two common failures in factor submissions: missing values near the evaluation window’s start and look-ahead bias. For time-series factors, it recommends querying enough earlier data to cover the longest lag or rolling…

股票機器學習統計回測
BigQuant

The article summarizes research that uses active share, or portfolio deviation from a benchmark, as a proxy for a fund manager’s conviction. It reports that strong past performance is associated with subsequent increases in active share, particularly for…

股票因子投資投資組合建構風險管理
BigQuant

This dated market note reports RSRS timing-model views for several Chinese equity benchmarks on April 8, 2020. The model remained bullish on the Shanghai Composite, CSI 500, and ChiNext, while taking a more cautious view of the SSE 50 and CSI 300. No…

股票中國市場趨勢追蹤技術指標
BigQuant

The article presents regular investing in broad market index funds as a low-effort, long-term approach, arguing that it can reduce the need for stock picking and market timing. It attributes active managers’ difficulty beating indexes to fees, short-term…

多資產中國市場美國市場投資組合建構
BigQuant

The document summarizes research on combining market anomalies and on refining multi-factor models. For anomaly strategies, it reports that returns to many well-known anomalies declined after academic publication, while diversified long-short portfolios…

股票因子投資動能統計
BigQuant

This page summarizes several quantitative investing topics: timing equity factors with cross-sectional and time-series indicators; adjusting portfolios to target volatility; modeling changing stock-bond correlations; assessing tactical asset-allocation…

多資產因子投資波動率投資組合建構
BigQuant

This note summarizes when to use several portfolio allocation approaches. A naïve allocation is presented as a practical choice when the universe is broad and return forecasts are difficult. Risk parity and minimum variance are associated with settings where…

多資產投資組合建構風險管理
BigQuant

This Chinese-language summary presents a 2021 survey of reinforcement learning in financial decision-making. It introduces Markov decision processes as a foundation, then identifies value-based and policy-based learning approaches, including extensions that…

機器學習投資組合建構交易執行做市
BigQuant

This strategy combines model-based stock ranking with technical timing. It starts from a manually defined CSI 150-related universe, then ranks candidates using an AI prediction score and volume, turnover, and large-order money-flow factors. Timing filters…

股票機器學習趨勢追蹤動能
BigQuant

This guide surveys how machine learning can support quantitative investing, from data preparation and model evaluation to portfolio selection. It explains supervised, unsupervised, and reinforcement learning, and reviews methods including regularized…

機器學習統計因子投資投資組合建構
BigQuant

This Chinese strategy discussion combines hand-built stock selection rules with a CNN classifier. It describes converting screening conditions into Boolean features so a model can learn to identify stocks expected to show short-term strength. The feature…

中國市場股票機器學習動能
BigQuant

The document presents a short-term timing approach based on the Hilbert transform. It assumes price movements contain a long-term trend, shorter cyclical fluctuations, and noise. The proposed process first smooths the data with a 20-period moving average,…

股票技術指標統計動能
BigQuant

This weekly Chinese equity factor note compares value and growth styles and reports relative performance across six industry-neutral long-short factor groups. Value and growth were described as broadly balanced, while quality measures such as return on…

中國市場股票因子投資均值回歸
BigQuant

The article describes combining two Chinese equity selection models designed for different market conditions: a rebound after an index decline and a mild index pullback. Each model includes market environment features so that it produces candidates only when…

股票中國市場回測動能
BigQuant

This research summary describes a dynamic rebalancing overlay for multi-factor equity portfolios. The portfolio keeps its regular monthly rebalance, while market-cap factor exposure is checked daily mid-month. If exposure breaches a set threshold, the…

股票因子投資風險管理投資組合建構
BigQuant

The post contains a proposed Chinese stock screen built from financial, valuation, price-action, and intraday-style indicators. Its filters include market-cap and asset thresholds, revenue growth and return on equity conditions, turnover and price-change…

中國市場股票技術指標統計
BigQuant

The article explains genetic algorithms as population-based search methods inspired by biological evolution. It walks through encoding candidate solutions as chromosomes, evaluating them with a fitness function, selecting parents, combining them through…

機器學習統計回測
BigQuant

This study applies Lasso, adaptive Lasso, and Elastic Net to select equity factors and combine them into stock-selection signals. Its motivation is that correlated predictors can make ordinary multivariate regression unstable. The reported experiments show…

股票中國市場因子投資機器學習
BigQuant

The post asks whether a factor-analysis module’s rebalance period measures returns before or after the factor observation. The author expected each factor-sorted group’s reported return to represent the return earned by holding its stocks for the stated…

因子投資回測統計
BigQuant

This April 2020 brokerage-report summary argues that overseas pandemic concerns had weakened prices without materially lowering broad-market valuations or company earnings forecasts at that point. It frames semiconductor shares against a late-2018 price…

股票中國市場因子投資投資組合建構
BigQuant

This document summarizes Ibbotson and Chen’s supply-side approach to estimating long-run equity returns and risk premiums. It decomposes US stock returns over 1926–2000 using inflation, earnings, dividends, valuation multiples, payout ratios, book value,…

股票統計因子投資美國市場