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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 market commentary considers whether foreign investor outflows and a rise in shares becoming tradable would materially affect Chinese equities. It distinguishes short-term trading flows from longer-term institutional allocations, including new mutual…

中國市場股票市場情緒事件驅動
BigQuant

This meetup summary covers several practical quant trading questions. It suggests examining order book behavior with Level 2 data when developing capital-flow signals, and describes using a Plotly heatmap to inspect correlations among factors. It also points…

市場微結構因子投資統計風險管理
BigQuant

This review describes machine-learning approaches to predicting stock returns from accounting data and company characteristics. It compares linear methods, including ordinary least squares, LASSO, and ridge regression, with nonlinear models such as random…

股票中國市場機器學習因子投資
BigQuant

This submission reflects on a quantitative strategy test whose results changed substantially when the author replaced its default factors or broadened the stock universe to include main-board and ChiNext shares. The observation highlights two practical…

因子投資機器學習回測中國市場
BigQuant

The article reviews research on whether individual commitment within US equity mutual fund management teams affects performance. It classifies managers as committed when they work only for one fund, and noncommitted when they also manage other funds. The…

股票因子投資統計投資組合建構
BigQuant

The report studies whether intraday return distributions contain stock selection information beyond conventional daily factors. Using one-minute stock prices, it constructs factors from intraday return variance, skewness, and kurtosis, then examines…

股票因子投資高頻交易統計
BigQuant

This guide describes a workflow for training an end-to-end stock model locally on compressed minute and multi-minute bar data, then submitting its weights and training code for cloud prediction. It explains that local files store prices and amounts as scaled…

股票機器學習回測交易執行
BigQuant

This note tests an A-share stock screen inspired by a “Beautiful 50” concept. It selects companies using three annual-report criteria: net profit growth above 15%, return on equity above 15% for three consecutive years, and a price-to-earnings ratio below…

股票因子投資回測中國市場
BigQuant

This article argues that a high percentage of winning trades does not guarantee profits. It emphasizes the relationship between win rate and the relative size of gains and losses, using examples to illustrate how a strategy with fewer winning trades may…

風險管理部位規模市場情緒股票
BigQuant

This overview introduces artificial intelligence and machine learning as tools for analyzing financial data and supporting investment decisions or trading operations. It groups methods by task: supervised learning for prediction and classification,…

機器學習統計風險管理投資組合建構
BigQuant

This note addresses a mismatch in factor analysis: a prediction set has been restricted by strategy conditions, so only a small number of stocks receive scores, while the analysis module still expects broad market coverage. The suggested response is to skip…

股票因子投資回測
BigQuant

This community post describes a discrepancy between a CNN-based stock strategy's backtest and simulated-trading signals. With a rolling window of five, both reportedly signal the same stock on January 4. With a window of ten, the simulation notification…

股票機器學習回測交易執行
BigQuant

The article argues that unusually high trading volume after a stock advance is an ambiguous event rather than an automatic sell signal. Every trade has both a buyer and a seller, so volume alone cannot reveal whether existing holders are distributing shares…

股票技術指標動能
BigQuant

This educational overview introduces common inputs for quantitative stock selection, beginning with simple and exponential moving averages, RSI, Bollinger Bands, MACD, moving-average crossovers, VWAP, and historical volatility. It describes their usual…

股票技術指標機器學習統計
BigQuant

This research summary revisits the capital asset pricing model by splitting daily stock returns into open-to-close intraday returns and close-to-open overnight returns. It reports that, in the US sample, beta is negatively related to intraday returns but…

股票統計因子投資美國市場
BigQuant

The document outlines a Chinese stock screening and trading strategy that targets shares which closed at the daily limit-up on each of the previous two days. Candidates must trade above their five-day moving average, have a price-to-earnings ratio of roughly…

股票中國市場動能突破
BigQuant

This article describes a modification to random forest models that lets an investor express factor preferences directly in the tree-building process. Selected factors are forced to drive splits near the top of each decision tree, increasing their influence.…

機器學習因子投資股票中國市場
BigQuant

The strategy selects Chinese stocks on the day they lose ST designation, buys qualifying names at the open, and holds them for three days. It describes closing trades at the end of the holding period and applying the rule to every stock that meets the event…

股票事件驅動中國市場
BigQuant

This research explores whether online search interest can serve as a timely measure of investor sentiment and help identify shifts between large-cap and small-cap Chinese equities. It treats search activity related to each style as a sentiment proxy,…

股票市場情緒中國市場回測
BigQuant

This exchange asks whether MACD components and a short-window swing-volatility feature used in model training and prediction contain future information. The response says these factors are calculated from historical data, implying that the indicators…

技術指標機器學習回測統計
BigQuant

This research note proposes an equity factor based on how each stock’s intraday volume pattern differs from the market’s. It starts from the common U-shaped market volume profile and argues that a stock with unusually concentrated or uneven trading may have…

股票因子投資統計市場微結構
BigQuant

The document introduces stationarity and cointegration as the basis for pairs trading. It describes a stationary series as having a stable mean and variance, and presents a pair as cointegrated when the difference between their prices is stationary. Under…

期貨配對交易均值回歸統計
BigQuant

This brief support note answers when a newly purchased position’s cost information appears in BigQuant. It distinguishes three operating modes: backtests and simulated trading update the value after the market close on the trade date, while live trading…

回測股票