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
Quantopian 講座
45 份文件
Binance API docs
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 report discusses using optimization methods for asset allocation and portfolio construction, especially when objectives are complex, high dimensional, discontinuous, or heavily constrained. It argues that the in-sample optimum may not remain optimal in…

投資組合建構回測多資產統計
BigQuant

This Chinese-language document outlines how asset allocation models and fund portfolios can support wealth management. It frames portfolio design as a way to make investment choices more accessible to clients facing gaps in financial knowledge, behavioral…

投資組合建構多資產中國市場
BigQuant

This report extends a factor attribution framework for equity funds from quantitative strategies to actively managed funds. It argues that the factor set should reflect the fund’s likely investment approach and risk exposures. Active managers may share…

股票因子投資投資組合建構統計
BigQuant

The article describes training BigQuant’s StockRanker machine-learning model using an overnight-return factor, following earlier factor research that links this signal to informed trading. Training uses all A-share stocks from 2013 through the start of 2021.…

股票中國市場機器學習因子投資
BigQuant

This research summary examines how market-cap style relates to trader behavior and trading activity in Chinese equities. It argues that shifts between large- and small-cap stocks involve changes in capital flows, and that market capitalization is closely…

股票因子投資統計中國市場
BigQuant

The report summary describes a strategy that varies fundamental factor exposures according to recurring seasons around company financial reports. It groups the calendar into four windows: annual-report disclosure, post-report performance trading,…

股票中國市場因子投資投資組合建構
BigQuant

The document introduces an index-enhancement research report about building longer-horizon price and volume factors from mid- and high-frequency data. Its central motivation is a mismatch between data frequency and forecast horizon: as sampling frequency…

股票市場微結構因子投資統計
BigQuant

This overview explains how environmental, social, and governance considerations can enter investment decisions alongside conventional financial analysis. It surveys approaches including positive and negative screening, thematic allocation, impact investing,…

股票多資產因子投資投資組合建構
BigQuant

This brief strategy entry describes an A-share stock-selection example built around a k-nearest neighbors classifier. The accompanying discussion clarifies that the target is binary: a stock is labeled positive when its five-day return is above zero and…

股票中國市場機器學習統計
BigQuant

This overview explains structured snowball options, focusing on how their coupons and risks arise. It describes coupon sources as exposure to the underlying asset's volatility, futures basis convergence for products linked to the China 500 index, and returns…

選擇權衍生品定價波動率風險管理
BigQuant

This research summary tests stock selection factors built from return and trading-volume data, using moments from the first through fourth orders. It places these measures in a broader taxonomy: factors can use one data dimension, combine dimensions at one…

股票高頻交易因子投資統計
BigQuant

The article argues that traders should avoid entering sectors after a short burst of broad attention and instead look for less crowded themes. It proposes treating three consecutive strong sessions and a sharp cumulative rise in leading stocks as a possible…

股票動能突破市場情緒
BigQuant

The discussion addresses how to combine daily observations with data from a longer period, such as the previous month, when constructing factors. Its suggested workflow is to convert daily market data into weekly or monthly bars with Python resampling, then…

因子投資統計回測
BigQuant

This Chinese-language survey discusses fundamental allocation, mean-variance optimization, Kelly-CVaR, Black-Litterman, and risk-parity approaches. Fundamental methods include mapping economic-cycle phases to asset weights and using macroeconomic factors to…

多資產投資組合建構風險管理回測
BigQuant

This Chinese research abstract proposes using sales data from Pinduoduo to follow consumption patterns, particularly among consumers in China’s lower tier cities. It frames the analysis against rising household leverage, high housing costs, and slowing…

中國市場統計股票
BigQuant

This brief discussion shows how to retrieve financial factor data through a data-access module using an SQL query. Its example selects dates, instrument identifiers, and a trailing-twelve-month operating-profit growth field from a Chinese stock…

因子投資股票機器學習回測
BigQuant

This short strategy note describes an iterative experiment in which initial parameter adjustments appeared unpromising. The author then added a weight based on closing-price ranking and reports that the resulting Sharpe ratio exceeded 1.5. The takeaway is…

股票因子投資回測技術指標
BigQuant

The document outlines a dynamic scenario alpha model (DCAM), which layers scenario classification over a conventional static alpha model. It argues that scenarios are useful when their subdivisions correspond to meaningfully different drivers or importance…

股票因子投資統計投資組合建構
BigQuant

This research overview explains how knowledge graphs represent entities and their relationships, then outlines a construction process: gather data, preprocess it, identify entities and links, reconcile information from different sources, form relationship…

股票事件驅動因子投資機器學習
BigQuant

This research summary reviews a study of whether mutual fund managers’ personal investments in their own funds are related to fund risk. Using disclosures of investment ranges, fund holdings, and risk measures for actively managed U.S. equity funds from 2007…

股票風險管理投資組合建構統計
BigQuant

This article summarizes research on how mutual funds’ trading decisions can lead other funds and how this herding relates to fund returns. It defines buy-leading and sell-leading funds according to whether peers follow their stock purchases or sales in…

股票統計市場微結構美國市場
BigQuant

This research note adapts the four phase investment clock to Chinese equities. It describes recovery, overheating, stagflation, and recession as distinct macroeconomic environments, and explains the traditional asset preferences associated with each. Because…

股票中國市場因子投資投資組合建構
BigQuant

The document describes an integrated model for estimating how crowded equity factor strategies may be. It combines five standardized signals: valuation spreads between high and low factor-ranked stocks, short-interest spreads, within-group return…

股票因子投資風險管理波動率
BigQuant

The document describes an Expert Advisor that uses a single-layer neural network, identified as a perceptron, to classify the direction of quote movement. The implementation draws on the iAC indicator and bar opening-time history. It also reports a testing…

機器學習外匯回測