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 describes a Chinese equity-selection process built from daily price and volume data. Genetic programming generates candidate factors: Rank IC is used to find factors with linear predictive relationships, while mutual information targets nonlinear…

股票中國市場機器學習因子投資
BigQuant

This practitioner report reviews DeepAlpha, a neural model used to rank stocks from factor inputs, and compares it with other approaches. The author says a simple fully connected network appeared competitive with decision-tree and linear models, and…

機器學習股票因子投資回測
BigQuant

This overview catalogs machine learning approaches that can be applied to quantitative investing, grouping them into tree models, linear models, unsupervised methods, deep learning, ensembles, and online learning. It links model families to tasks such as…

機器學習因子投資統計回測
BigQuant

The document summarizes research on converting stock factors with strong negative-return associations into a long-only selection process. Because short selling is limited in the A-share market, it describes reversing the use of such signals: remove stocks…

中國市場股票因子投資投資組合建構
BigQuant

This report describes a monthly stock selection model that uses a random forest, an ensemble of decision trees trained with bagging, to estimate each stock’s probability of rising in the next period. Its workflow covers feature and label preparation,…

中國市場股票機器學習因子投資
BigQuant

This research review explains how earnings beta can measure a company’s exposure to systematic risk through the co-movement of its earnings with aggregate market earnings. It compares eleven earnings series built from realized or analyst-forecast earnings,…

股票因子投資統計風險管理
BigQuant

This literature summary covers two separate topics. The first describes a framework for studying how mutual fund managers’ personal characteristics relate to performance, decomposing outcomes into overall results, return and risk, and timing and security…

多資產選擇權投資組合建構波動率
BigQuant

This research summary describes an adaptation of Robert Whitelaw’s time-varying Sharpe ratio, or Tsharp, for timing the Shanghai Composite. Unlike a conventional Sharpe ratio, the measure estimates returns and variance through regression, making it…

中國市場股票統計回測
BigQuant

This study organizes fifty Wind order-flow measures into eight groups, including inflows, outflows, net active buying, and large-order net flows. It assesses their stock-selection value with industry-neutral portfolio sorts, cross-sectional regressions, and…

中國市場股票因子投資市場微結構
BigQuant

This document summarizes an ETF tracking workbook and describes the market landscape it was designed to monitor. It reports that broad-market and sector or theme ETFs formed the largest non-money-market categories, with examples of major index exposures and…

中國市場股票投資組合建構
BigQuant

This market-monitoring report reviews Chinese equities during the early 2020 pandemic shock. It combines trading activity, valuation, turnover, sentiment, sector relative performance, fund concentration, and style-factor signals. Its readings describe…

中國市場股票因子投資統計
BigQuant

The document reports a platform-specific issue in which an XGBoost classifier’s probability prediction function returns only endpoint values of zero and one. The user expected continuous class probabilities that could be used to rank securities, based on…

機器學習股票
BigQuant

This discussion distinguishes machine learning for execution optimization from machine learning for directional trading. Execution begins with a known trade and seeks to reduce its cost; alpha generation must identify price direction and capture enough of…

機器學習高頻交易市場微結構交易執行
BigQuant

This article describes combining two stock selection models designed for different Chinese equity market conditions: a rebound after an index decline, and a mild market pullback after stocks hit their daily price limit. Each model includes market environment…

中國市場股票回測動能
BigQuant

This Chinese-language support post describes a feature-engineering question: how to count, over a recent window, the days when a five-day moving average exceeds a ten-day average. The proposed first feature assigns a positive or negative value according to…

股票技術指標機器學習
BigQuant

This forum post raises a data-timing problem in a trading workflow. In the described backtest, a signal generated on one day is placed the next day, and pre-market processing can apparently retrieve that day’s opening and closing values through historical…

回測交易執行統計
BigQuant

This article describes 25 reasons retail investors may lose money in equities. It groups them around information and research gaps, overreliance on one strategy, emotional and herd-driven decisions, limited planning and experience, concentrated portfolios,…

股票風險管理投資組合建構市場情緒
BigQuant

This review explains why diversification may help more during declines than during gains, and why average correlations can hide that difference. It recommends estimating an asset pair’s downside relationship by conditioning on the portfolio’s main growth…

多資產投資組合建構風險管理統計
BigQuant

This review describes a method for identifying crowded markets and distinguishing potential bubble build-up from unwinding. It measures sector or factor clustering from return covariances and principal components, then pairs that measure with relative…

股票因子投資動能投資組合建構
BigQuant

The document raises a question about possible look-ahead bias in a stock-selection workflow. It points to a five-day return calculated from prices shifted forward in time and asks whether using that value as a feature in a test set leaks future information.…

股票機器學習回測統計
BigQuant

The document presents a modified MACD indicator built by replacing standard exponential moving averages with a three-stage smoothing expression. It applies that transformation separately to closing prices over 12- and 26-period spans to form DIF, then…

技術指標機器學習股票
BigQuant

This report summary examines a 2018 forecast of CSI 300 constituent changes and the potential trading flows associated with index funds adjusting their holdings. The forecast uses the index's periodic review rules, including measures of past-year trading…

股票事件驅動交易執行中國市場