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 overview describes eight groups it presents as influential in China’s A-share market: foreign investors, short-term speculative funds, social security and insurance funds, securities firms’ proprietary desks, corporate insiders, public funds, and…

股票中國市場市場情緒市場微結構
BigQuant

This forum post reports a disagreement in 24-period and 72-period moving averages for a market series on a specified date. The author compares values from two retail charting sources with results from a quantitative platform, noting that the two external…

技術指標統計
BigQuant

A user reports that every label in a trading demo appears to be zero. The response explains that the platform’s visualization shows only a subset of the data, and the displayed rows may all happen to carry the zero label. It recommends inspecting the full…

機器學習統計
BigQuant

The document outlines why quantitative investors use machine learning to analyze growing financial datasets, forecast market movements, and help select portfolios. It describes machine learning's capacity to represent nonlinear relationships and process data…

機器學習回測統計
BigQuant

This overview describes Chan theory as a chart-analysis framework built from nested price structures. It moves from processed candlestick fractals to strokes, segments, and overlapping consolidation zones, then classifies larger moves as advances, declines,…

技術指標趨勢追蹤動能多資產
BigQuant

This meetup Q&A covers several practical quantitative trading topics. It explains rolling training as repeatedly updating a model using a moving or expanding historical window, and distinguishes incremental updates from retraining on the full dataset. It…

機器學習因子投資回測投資組合建構
BigQuant

The document summarizes a research paper that uses a neural network to produce portfolio weights for exchange-traded funds. Instead of forecasting expected returns and then feeding those forecasts into a conventional optimizer, the approach directly tunes…

多資產投資組合建構機器學習風險管理
BigQuant

This Chinese-language seminar summary frames AI adoption as a response to falling asset-management margins despite growing assets under management. It sketches a progression from adjusting active portfolios using factor analysis, to building long-short…

多資產因子投資動能機器學習
BigQuant

This study outlines a Deep Q Network approach to timing trades in one stock. Instead of storing action values for every possible market state in a table, a neural network estimates values for available actions. The agent stores state, action, reward, and…

股票機器學習回測風險管理
BigQuant

This report proposes diversifying portfolios across market, style, and strategy risk premia rather than allocating only among broad asset classes. It uses representative global equity, bond, and commodity indices to construct long-only strategies reflecting…

多資產因子投資動能波動率
BigQuant

This introduction explains the Skip-gram model as a method for predicting nearby context words from a chosen center word. It uses a short example sentence and a window extending two words to either side. The explanation defines one-hot representations, dense…

機器學習統計
BigQuant

This article presents volume as a way to assess the force behind price movements. It argues that record volume alone should not be treated as proof of a market top, since trading activity can continue to set new highs. Instead, it singles out expanding…

股票技術指標趨勢追蹤突破
BigQuant

This review summarizes historical evidence on how assets and active strategies performed during periods of high and rising inflation in the United States, United Kingdom, and Japan. It defines inflation episodes using accelerating year-over-year inflation…

多資產大宗商品趨勢追蹤動能
BigQuant

This analyst note reviews a Chinese bank IT provider’s 2019 results and argues that its business is shifting toward financial technology software and services. It reports revenue growth, a sharp increase in net profit, and software and technology services…

股票中國市場事件驅動
BigQuant

This study examines whether a third-party platform’s rapid redistribution of sell-side analyst upgrades and downgrades changes price discovery and the value brokers provide to clients. Using US recommendation data from 2009–2013, leak timestamps, intraday…

股票市場微結構交易執行美國市場
BigQuant

This article introduces one-dimensional convolutional neural networks as a way to process financial sequences. A convolution applies shared filters across local time windows, allowing the model to learn patterns that can appear at different points in a…

股票機器學習統計回測
BigQuant

The document offers a brief allocation recommendation for bond funds in a period of increasing credit risk. It advises favoring funds with higher credit scores and specifies a threshold of 2.7 or above according to the authors’ credit scoring table. The…

固定收益風險管理投資組合建構
BigQuant

This document is available here only as a Chinese-language title and outline, with the body represented by a link to a PDF. The outline describes a quantitative approach to asset allocation that separates strategic allocation from tactical allocation. It…

多資產投資組合建構風險管理統計
BigQuant

This document outlines an asset-allocation approach that separates asset selection from portfolio weighting and market timing. It explains a hidden Markov model as a way to infer unobserved market regimes from observable data, represent complex observations…

股票中國市場機器學習統計
BigQuant

This article explains how to configure an older BigQuant workflow to analyze alpha expressions in a manner modeled on WorldQuant’s WebSim. Users specify a factor expression and set the stock universe, data delay, linear decay, market or industry…

股票因子投資回測投資組合建構
BigQuant

This brief troubleshooting exchange addresses a quant model that fails when configured with a single factor, even though the factor values appear normal. The proposed fix is to assign the factor a shorter alias; the author reports that using a very brief…

機器學習統計回測
BigQuant

This BigQuant support note addresses a strategy that can read an uploaded CSV during development but fails to access it after being launched in simulated trading. It recommends storing the data as a platform data source and loading it within the trading…

交易執行回測
BigQuant

This brief BigQuant support note explains why a cloned strategy can work in backtesting yet fail in simulated trading. The example strategy was designed only for backtests, so its date range and instrument reference need changes before simulation: bind the…

期貨回測交易執行
BigQuant

This research summary argues that standard single-factor information coefficient tests may not reflect index-enhancement practice. A factor’s performance in a broad shared universe may not transfer to a benchmark’s eligible stocks, and simple tests may omit…

股票因子投資投資組合建構回測