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
Lumibot strategies
7 份文件
QuantRocket
7 份文件
Awesome Quant
1 份文件

搜尋圖書館

3,481 份文件

BigQuant

A trader reports that a stock-selection strategy using TA-Lib indicators produces different results each time it is run. The response points to an SQL query in one module that lacks an explicit sort order as the likely cause. When rows arrive in an…

回測統計
BigQuant

This article proposes a compact framework for reviewing the equity market by sector rather than inspecting every stock individually. To gauge sector persistence, it counts stocks moving from an initial limit-up session to a second consecutive limit-up…

股票動能風險管理中國市場
BigQuant

This research summary describes a study of retail investor attention and asymmetric volatility in China’s A-share market. The authors use the balance of positive, negative, and neutral posts on online stock message boards to construct a proxy for asymmetry…

股票中國市場市場情緒波動率
BigQuant

This user post describes rolling model training for stock forecasts using two approaches. The StockRanker example updates the model annually, fitting on one year of data and predicting over the following year. The XGBoost example instead constructs monthly…

股票機器學習回測
BigQuant

This Chinese equity research excerpt analyzes the beer industry’s shift from pursuing output scale toward improving profitability through premium products. It separates the outlook into volume and price per ton: production depends on the number of operating…

股票中國市場因子投資
BigQuant

This article examines how training-window length affects an AI stock-selection model. It compares long windows, expanded year by year from 2005 to 2021, with shorter windows ranging from a month to a few years. The author recommends checking each window…

機器學習回測因子投資統計
BigQuant

This discussion addresses how to use factors from BigQuant's factor library as model features. The question asks whether a factor identifier can be used directly or whether users must copy its expression, and whether factors associated with a brokerage are…

因子投資機器學習股票
BigQuant

This article introduces Granger causality and transfer entropy as ways to study directional predictive relationships in time series. Granger causality tests whether a source series improves forecasts of a target beyond the target’s own history, commonly…

統計股票機器學習市場情緒
BigQuant

This article explains a proposed arbitrage mechanism involving Chinese A-shares, stock purchases, securities borrowing, and short sales. Its example describes buying shares to push the price higher, borrowing shares to sell at that higher price, and later…

股票中國市場套利市場微結構
BigQuant

This Chinese-language note describes a stock prediction exercise using four cross-sectional inputs: total market capitalization, turnover, trailing price-to-earnings, and quarterly net-profit year-over-year growth. It compares linear regression, XGBoost, and…

中國市場股票因子投資機器學習
BigQuant

This document summarizes an introductory treatment of graph neural networks (GNNs), which learn from data represented as entities and their relationships. It explains how convolutional ideas used with images can be generalized to graph structures, whose…

機器學習統計
BigQuant

The article reviews the long decline in mutual fund and ETF expense ratios and links it to investor choices, competition, and changes in financial advice and retirement plans. It distinguishes asset-weighted averages, which reflect where investors put their…

統計投資組合建構美國市場
BigQuant

This research review summarizes a study of manager changes at Chinese equity funds, distinguishing internal transfers, moves to another public fund, moves to a private fund, and exits from the fund industry. The study compares benchmark-adjusted buy-and-hold…

股票中國市場統計風險管理
BigQuant

The article introduces a custom coded stock selection strategy built from five rules, mainly intended to identify stocks that have fallen sharply and begun to stabilize, with some rules meant to capture potential strong advances. It contrasts AI generated…

股票因子投資回測部位規模
BigQuant

The document asks whether minute or second level price and volume data can be aggregated into daily net flow measures for very large, large, medium, and small trades. It points readers to two implementations: a general set of high frequency factors and a…

股票高頻交易因子投資市場微結構
BigQuant

The document explains gold contracts for difference as cash-settled derivatives that provide exposure to gold price changes without holding bullion or futures. It outlines features such as leverage, smaller contract sizes, the ability to take long or short…

大宗商品衍生品定價風險管理
BigQuant

This event description focuses on why quantitative strategy results in backtests can differ from live trading performance, a concern it identifies specifically for Chinese A-share strategies. It presents the topic as a practical challenge for traders and…

股票回測統計
BigQuant

This article recommends a three-part process for improving trading discipline: record each trade’s rationale, timing, size, planned risk and reward, and emotional state; review those records regularly for rule violations and emotional decisions; then analyze…

風險管理部位規模統計
BigQuant

The article argues that trading researchers should judge machine learning papers by simplicity, reproducibility, and generality, alongside reported empirical results. A method that performs well on a benchmark may not transfer to financial prediction, and a…

機器學習統計回測因子投資
BigQuant

This study compares ARIMA, a multilayer perceptron, an LSTM, and an ARIMA-GARCH combination for next-day NVIDIA share-price forecasts. It describes ARIMA as a model for linear time-series structure, neural networks as ways to capture nonlinear patterns, and…

股票機器學習統計波動率
BigQuant

The report proposes improving traditional liquidity factors for Chinese A-share stock selection by incorporating information about intraday trading structure. It frames the approach as a reusable factor research method: identify market information omitted by…

中國市場股票因子投資市場微結構