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

The document shows a stock-ranking workflow that derives 30-day and 90-day returns, ranks securities cross-sectionally, filters the universe, and creates a forward-return label for model training. A StockRanker module trains on historical data and predicts…

股票動能機器學習因子投資
BigQuant

This discussion presents a daily Chinese A-share small-cap strategy that filters stocks by listing age, valuation, and turnover rank, sorts the candidates by market capitalization, and targets a basket of twenty names. Its rebalance handler identifies…

股票中國市場因子投資投資組合建構
BigQuant

The article describes a stock selection experiment in which a machine learning model used only days since listing. Its reported backtest showed positive returns, though with high volatility. The authors attribute performance partly to a rising market during…

股票機器學習因子投資回測
BigQuant

This Chinese-language article outlines a six-step process for developing stock selection rules: find an idea, define its logic, run an initial backtest, tune parameters, check for overfitting, and select strategies for combination. Its example setups look…

股票中國市場技術指標回測
BigQuant

This study summary examines active-trading (ACT) factors in Chinese equities, which distinguish aggressive from passive executions and group activity by trade size. It argues that the undivided ACT factor has weak stock-selection power, then splits…

股票中國市場因子投資市場微結構
BigQuant

The report studies how equity factors behave across groups of A-share stocks sorted by price amplitude, using ten groups from lower to higher amplitude. It reports that price and volume factor effectiveness rises as amplitude increases, while fundamental…

中國市場股票因子投資波動率
BigQuant

This page summarizes a lecture on multi-step and off-policy algorithms in reinforcement learning. It identifies the subject as methods that learn from sequences of rewards across multiple steps while handling data generated by a policy different from the one…

機器學習統計
BigQuant

This document outlines four indicators that combine price and trading volume: the Money Flow Index (MFI), On-Balance Volume (OBV), Price Volume Trend (PVT), and a simplified OBV variant called SOBV. MFI compares rolling positive and negative money flows,…

技術指標統計股票
BigQuant

This submitted assignment defines quantitative investing as making investment decisions with mathematical and statistical analysis, historical data, and computing. It describes several practical advantages: processing large datasets, applying rules…

統計回測機器學習
BigQuant

The report describes an AI-based score for assessing intraday trading opportunity in Chinese stocks and broad indices. Using 20 trading days of one-minute returns, it compares observed returns with randomly constructed return sequences. A higher score…

中國市場股票機器學習統計
BigQuant

The document introduces covariance as a measure of how two variables vary together, defining it through the expected product of each variable’s deviation from its mean. Positive covariance indicates a tendency to move in the same direction, while negative…

統計投資組合建構風險管理
BigQuant

This technical note presents the MEJT indicator as a price-action rule built from high, low, and close data. Its buy condition checks whether the current high exceeds the prior high, the close exceeds a high from two periods earlier, and the close lies…

技術指標股票動能
BigQuant

This research summary explores stock-selection signals built from Level 2, trade-by-trade data. It classifies trades by order size and direction, then constructs measures such as the share of trading represented by different order categories and net buying…

中國市場股票市場微結構因子投資
BigQuant

This report summary presents a factor model for ranking managers of Chinese public equity and equity-oriented hybrid funds. It builds a manager-level investment index by weighting the funds each manager oversees by fund size, then evaluates candidate…

中國市場股票因子投資投資組合建構
BigQuant

The document summarizes research on whether company managers’ tone in financial communications predicts equity returns. It describes building a sentiment index by applying text analysis to corporate reports and earnings-call transcripts, then comparing its…

股票市場情緒統計
BigQuant

This report summary outlines a fixed-income-plus-equity portfolio design in three stages: strategic allocation, tactical timing, and capital management. Strategic weights are set with a mean-variance model using broad equity and bond indices, with periodic…

多資產固定收益股票投資組合建構
BigQuant

This Chinese Q&A explains why a genetic programming factor-mining workflow can report factors that pass a test yet return an empty factor collection. The answer says the run log shows that the global fitness test did not pass, so no factors were retained. A…

機器學習因子投資統計
BigQuant

This guide lists reasons a submitted quantitative factor may fail to produce an evaluation score. It recommends checking factor-analysis output on the designated dataset before submission and verifying that a machine-learning model completed training and…

股票機器學習統計回測
BigQuant

The document summarizes research that classifies corporate bond funds as liquidity demanders or suppliers according to how their trades align with dealer inventory cycles. Using TRACE transactions and fund holdings, the underlying study infers inventory…

固定收益市場微結構風險管理統計
BigQuant

This introductory explanation describes how a convolutional neural network turns an image into a class prediction. A filter slides across local pixel regions to produce feature maps; filter count, stride, and zero padding affect the maps’ depth and…

機器學習統計
BigQuant

A BigQuant user reports that a stock AI strategy template fails with an index error when its prediction or backtest date range includes January 1, 2016. The issue is described as intermittent and associated with using certain factors. The suggested…

回測交易執行
BigQuant

This Chinese-language discussion addresses a backtest display that continues to list a stock after an order targets a zero portfolio weight. The listed position has a quantity of zero, which can look like an unsettled holding or a bookkeeping defect. The…

回測股票交易執行
BigQuant

This short note outlines a way to represent the cost basis of stock holdings across market participants. It proposes estimating average holding cost by weighting transaction prices by traded quantities, then using daily costs and trading volume to estimate…

股票統計因子投資