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

The document presents a framework for testing stock-selection factors. It evaluates each trading day’s stock factor values against returns over subsequent holding periods, aiming to show how predictive information changes as the holding period grows. Daily…

股票因子投資統計回測
BigQuant

The post asks how to adapt a portfolio-selling routine so that, when the equity allocation exceeds 60% of total portfolio value, the excess exposure is sold from the lowest-ranked holdings. The supplied routine builds a set of currently held securities,…

股票投資組合建構部位規模交易執行
BigQuant

The post reports an observation from more than six months of intraday modeling in Chinese equities using five-minute bars. At each time point, the author independently tuned parameters with tree-structured Parzen estimation. The reported optimization…

股票中國市場機器學習統計
BigQuant

This research summary examines where mutual fund excess returns may come from, separating security-selection skill from timing skill. Timing is framed as adjusting a fund's market beta, with stronger exposure during rising markets and reduced exposure during…

股票因子投資統計投資組合建構
BigQuant

The document introduces quantitative investing as an approach that uses numerical models to build an investment process, contrasting it with methods that rely more on qualitative judgment. It describes how quantitative methods can combine computing with…

多資產股票統計投資組合建構
BigQuant

This short assignment response defines quantitative investing as turning recurring patterns observed through statistical analysis of financial markets into structured methods for future trading. It mentions stocks, futures, and digital assets, and describes…

多資產統計機器學習風險管理
BigQuant

The note explains how a Chinese stock daily bar series relates to adjusted and unadjusted prices. It identifies the cited index daily data as back-adjusted and shows that dividing the close by its adjustment factor can recover an unadjusted price. The…

股票中國市場
BigQuant

This guide explains how to carry training data for a StockRanker model from BigQuant’s 1.0 environment into version 3.0. In the older environment, it exports the training dataset with date, instrument, label, and the selected feature columns. The file is…

機器學習股票
BigQuant

This weekly market report organizes several indicators of Chinese equity liquidity by sector: ETF subscriptions and redemptions, northbound investor flows, estimated allocations from pending and newly raised equity funds, company buybacks, and…

股票中國市場統計市場情緒
BigQuant

The document examines how trend following could address the equity risk concentration in conventional target-date funds. Their glide paths reduce stock allocations as retirement approaches, yet the portfolio may remain dominated by equity risk, leaving…

趨勢追蹤多資產風險管理投資組合建構
BigQuant

This BigQuant support exchange explains a possible source of confusion in backtests: the platform’s `hold_days` setting defines a build-up period during which the strategy can buy, and does not itself require each purchased stock to remain in the portfolio…

回測投資組合建構交易執行
BigQuant

The document explains a two-stage model that uses gradient-boosted decision trees to create features for logistic regression. The trees split and combine the original inputs; each sample is then represented by a binary vector marking the leaf it reaches in…

機器學習統計回測
BigQuant

This tutorial demonstrates extracting minute-level stock data for a selected date range with a distributed query platform, then calculating features through SQL-style operators. The examples cover a five-period moving average of closing prices, a…

股票技術指標統計機器學習
BigQuant

The document presents an individual-investor approach inspired by Peter Lynch: use familiar products and services to generate company ideas, then assess business quality, growth, debt, and valuation. Its suggested checks include sustained profit growth,…

股票部位規模投資組合建構風險管理
BigQuant

This research summary examines why stocks can earn excess returns before earnings announcements. It proposes that investors and analysts resolve some uncertainty ahead of the report, supporting price gains before the announcement itself. The study measures…

股票選擇權事件驅動波動率
BigQuant

The document reports a single-factor study of operating-efficiency and growth measures. For six operating factors, it says the analysis used grouped portfolio net values, long-short group returns, information coefficients, and Fama–MacBeth methods. Four…

股票因子投資統計回測
BigQuant

The study summary examines whether active stock selection that increases a mutual fund portfolio’s technological similarity predicts subsequent performance. Company patent distributions are compared using cosine similarity, and a fund’s active technological…

股票因子投資統計投資組合建構
BigQuant

This Chinese-language forum post raises practical questions about what factor weights from a labeling or training process represent. It distinguishes possible interpretations, including neural-network parameters, regression coefficients, and tree-based…

因子投資機器學習統計
BigQuant

This summary of an equity research report explains portfolio optimization as a framework for managing risk exposures, holdings, weights, turnover, and market impact while incorporating investor views. It argues that simple portfolio construction may perform…

股票投資組合建構風險管理統計
BigQuant

This brief report summarizes a quantitative market-timing view of Chinese A-shares as of early April 2020. It describes the market as being in a bottoming phase with limited downside, and lists sector strength, index and industry valuations, stock-market…

股票中國市場技術指標統計
BigQuant

The document presents Wyckoff analysis as a way to interpret market supply and demand through price and volume. It describes three guiding principles: compare demand with supply, treat trading ranges as potential causes of later moves, and assess whether…

股票中國市場技術指標突破
BigQuant

The article argues that quantitative trading depends on market understanding as well as technical implementation. It contrasts trend-following and mean-reversion approaches as examples of strategies grounded in different views of market behavior, and…

因子投資趨勢追蹤均值回歸風險管理
BigQuant

The article describes a supervised learning approach that classifies whether a stock’s closing price will be higher or lower after a chosen horizon. It smooths historical prices with exponential weighting, then uses six technical indicators—including RSI,…

股票機器學習技術指標回測