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 research summary describes a bull-bear indicator built from changes in equity-market volatility and turnover. It classifies conditions according to whether each measure is rising or falling. Rising volatility with falling turnover is presented as a…

股票中國市場波動率技術指標
BigQuant

The article surveys execution algorithms by their main objective: reducing market impact, controlling total trading costs, or adapting execution to favorable market conditions. It describes TWAP as time-based order slicing, VWAP as matching execution to…

交易執行市場微結構風險管理
BigQuant

This study summary examines an improvement to a one-sided volatility-difference timing model. It reports that bullish signal accuracy rises with trading amount, while bearish signal win rates show no similar relationship. The proposed change uses relative…

中國市場股票技術指標回測
BigQuant

This research summary argues that low valuation alone can select weak businesses, so investors should assess company quality before deciding whether its price is reasonable. It evaluates A-share companies using indicators related to profitability, growth,…

中國市場股票因子投資投資組合建構
BigQuant

This research summary compares five classifiers for predicting stock returns from historical equity factors: multinomial logistic regression, linear support vector machines, random forests, XGBoost, and deep neural networks. It distinguishes the linear…

股票因子投資機器學習統計
BigQuant

The document reports a mismatch between a portfolio strategy’s expected rebalance schedule and its simulated trading activity. The author says the backtest rebalances every five days or after a take-profit trigger, while the simulation records trades on many…

回測交易執行投資組合建構中國市場
BigQuant

The document summarizes an analysis of Chinese A-share investor research visits, using public company announcements to identify when institutions visit firms. These events are usually targeted visits involving five or fewer institutions, and announcements…

股票事件驅動統計中國市場
BigQuant

This note diagnoses a backtest error in BigQuant position-condition functions. Both the opening and closing condition functions attempt to filter a DataFrame using a column named “fantanbili.” The author points out that the prediction output supplied by an…

回測統計
BigQuant

The document outlines a systematic stock-selection model built from valuation, profitability, growth, operating-efficiency, and technical factors. It describes a scoring approach: choose candidate factors, test their predictive usefulness, remove redundant…

股票因子投資統計回測
BigQuant

This summary examines whether frequent constituent changes weaken returns for a portfolio tracking the CSI 300. It reports a Wilcoxon test finding short-term price effects around index adjustments: additions tended to rise and removals to fall, with the…

股票中國市場投資組合建構回測
BigQuant

The article explains “price desensitization”: a cyclical company’s shares stop advancing, or weaken, while the underlying commodity price continues to rise. Its proposed rationale is that equity prices anticipate earnings and may have priced in future gains…

股票大宗商品動能風險管理
BigQuant

This research digest summarizes two studies on equity signals. The first trains a deep neural network on five years of fundamental data to forecast future fundamentals. The summary reports that, relative to a simple forecast assuming current data persist,…

股票機器學習因子投資市場情緒
BigQuant

This document summarizes a framework for deciding whether and how to combine single-factor smart beta strategies with multifactor portfolios. It represents each candidate strategy as exposures to a small set of investable elementary smart betas—initially…

因子投資投資組合建構風險管理股票
BigQuant

This introductory guide surveys algorithmic trading, from the history and terminology of financial markets to the roles of quants, traders, and market makers. It describes common benefits of automation, such as speed and scalability, alongside constraints…

回測風險管理動能均值回歸
BigQuant

This strategy seeks to outperform the CSI 1000 while controlling industry, style, and individual-stock exposures. It proposes combining value, growth, size, quality, volatility or liquidity, and alternative signals. Factors are cleaned for outliers,…

中國市場股票因子投資投資組合建構
BigQuant

The document summarizes a study of a composite fundamental factor based on the Piotroski framework and its stock-selection value in the Chinese A-share market. It reports that stocks in the highest factor decile outperformed those in the lowest by an average…

股票中國市場因子投資統計
BigQuant

A user asks how to express a specific six-session price pattern in a platform’s daily factor-expression syntax. The condition is that the latest close exceeds each of the previous five closes, while the close from five sessions earlier also exceeds the…

股票技術指標因子投資
BigQuant

This example equity strategy selects stocks using valuation and trading activity. At each 30-trading-day interval, it buys at the open shares with positive price-to-book ratios below 1.5, price-to-earnings ratios below 15, and volume between 1.5 and 2.5…

股票中國市場技術指標回測
BigQuant

The document presents asset allocation as a combination of choosing assets and timing the market, with portfolio risk and expected return as the objectives. It explains that a hidden Markov model infers unobservable market states from observable data, then…

機器學習統計投資組合建構中國市場
BigQuant

This study describes a revised deep Q-network approach for timing individual Chinese stocks. The earlier version used daily OHLCV data and several common factors as its state. The revision instead takes a configurable window of recent closing prices and…

股票機器學習回測部位規模
BigQuant

This forum discussion asks how a visual stock-selection strategy combines multiple factors when no explicit weights are visible, and how the same logic might be represented in SQL. The example lists dividend yield, price-to-book, return on equity, and profit…

股票因子投資投資組合建構
BigQuant

The document explains why a stock filter set to the CSI 500 can return fewer securities than the index membership count. In the cited example, the filter is applied to a particular date, and some constituents were suspended, leaving their five-day return…

股票中國市場統計