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 brief response defines quantitative investing as using tools to extract patterns from historical data. It frames time-series analysis as a way to improve the odds of making a successful decision and cross-sectional analysis as a way to seek better…

統計機器學習投資組合建構
BigQuant

The document explains a model-training error caused by a feature stored as an object or string rather than a numeric value. Its diagnostic approach is to inspect the training data and identify which input column has the incompatible type. The example points…

機器學習統計
BigQuant

This forum post asks how to migrate several legacy factors from an earlier version of a quantitative research platform into a newer one. The expressions cover an industry-grouped beta adjustment, a rolling correlation between log volume and absolute returns,…

股票因子投資統計
BigQuant

This Chinese research note explores bull-bear indicators in three equity applications: timing broad indices, rotating among industries, and setting index constituent exposure. For direct index timing, it adapts the dual moving average idea by comparing…

股票中國市場趨勢追蹤技術指標
BigQuant

This research summary explains how alpha factors can be represented by factor-mimicking portfolios (FMPs) under a stock covariance model, and how linear combinations of factors correspond to combinations of their mimicking portfolios. It frames factor…

股票因子投資投資組合建構統計
BigQuant

This description explains a limit-order market-making strategy based on the Avellaneda–Stoikov framework. It sets a reservation price and optimal bid-ask spread using estimated volatility, order-book liquidity, inventory relative to a target allocation, the…

做市加密貨幣市場微結構交易執行
BigQuant

This report outlines a short-term reversal strategy for China’s CSI 800 stocks. It combines a moving-average system intended to classify trend state through cycle analysis with multi-timeframe MACD divergence. A bullish divergence occurs when price makes a…

股票均值回歸技術指標回測
BigQuant

This research report studies portfolio construction around a weekly stock-selection model called AlphaNet, built from price and volume data. It examines several portfolio optimization approaches intended to accommodate different risk and return objectives.…

股票因子投資投資組合建構風險管理
BigQuant

This research summary proposes a stock illiquidity factor based on the shortest path through intraday candlestick data. It aims to improve on a conventional proxy that relates price returns to trading volume, which the authors say can be unreliable during…

股票因子投資高頻交易市場微結構
BigQuant

The document explains two settings in a rolling-data module used to prepare features for securities. The window size controls how many consecutive observations are grouped into each sample. Its example uses five sequential values and a window of three to…

機器學習統計
BigQuant

This research summary reviews the low-volatility equity factor across overseas markets and mainland Chinese shares. It describes the behavioral explanation that highly volatile stocks may be more vulnerable to speculation and rich valuations, while…

股票中國市場波動率因子投資
BigQuant

The document outlines a single-asset strategy based on the average of 30-day and 72-day moving averages. It treats a close below 80% of that average as a deeply discounted condition, then waits for a 5% rebound from the triggering close before buying. For an…

股票均值回歸技術指標回測
BigQuant

This essay describes quantitative trading as the automated execution of investment models designed and assessed by people, rather than as an independent mechanism for discovering profitable strategies. It emphasizes that rule-based systems can apply…

交易執行風險管理回測
BigQuant

This BigQuant support exchange explains a prediction error associated with missing or infinite values while constructing label bins. It suggests checking whether the target label is absent or contains many missing values. The further diagnosis is that the…

股票機器學習統計中國市場
BigQuant

This review summarizes research testing whether small-cap stocks continued to outperform large caps across calendar effects in US equities. The underlying study forms portfolios from the smallest and largest size groups and examines the return spread around…

股票因子投資統計美國市場
BigQuant

A BigQuant forum answer addresses why a stock selection strategy’s returns changed from positive to negative after neutralizing and standardizing its inputs. The reply explains that StockRanker uses a tree-based structure and, according to the respondent,…

股票機器學習回測統計
BigQuant

This study examines whether generative adversarial networks can produce realistic multi-asset financial time series. It combines the convolutional architecture of DCGAN with the Wasserstein-distance loss used by WGAN: convolutional layers replace some…

機器學習統計多資產股票
BigQuant

This strategy rotates among a fixed pool of 11 ETFs spanning several asset classes and markets. Every five trading days, it ranks candidates using a 25-day linear-regression slope multiplied by R-squared, then adds a short-term signal based on the five-day…

多資產趨勢追蹤動能投資組合建構
BigQuant

This report summarizes stock-selection results for several machine-learning models across broad Chinese equity universes and constituent groups tied to the CSI 300, CSI 500, and CSI 800. It compares weekly, recent-month, and 2018-to-date excess returns, and…

中國市場股票機器學習因子投資
BigQuant

This brief forum entry addresses an SQL error encountered while trying to neutralize a rolling turnover measure against total market capitalization. It points readers toward a regression-residual function as an alternative to a direct neutralization call.…

股票因子投資統計