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 review examines the low-risk effect: securities with lower measured risk have historically delivered stronger risk-adjusted returns than the standard CAPM relationship would predict. It explains betting against beta (BAB), which leverages a low-beta…

股票因子投資風險管理投資組合建構
BigQuant

This research summary compares two ways to incorporate analyst expectations into equity selection. A parallel approach blends forecasts with other factors or uses them jointly to predict returns. The proposed serial approach first builds a conventional…

股票因子投資投資組合建構風險管理
BigQuant

This brief BigQuant support exchange explains two ways to control which stocks enter a factor analysis. One approach is to select a predefined universe, such as the CSI 300 or CSI 500, which fixes the eligible stock set through an index-based pool. The other…

股票因子投資
BigQuant

This report tracks equity factors using information coefficient (IC) summaries and the relative returns of factor-ranked long portfolios. It describes ranking stocks by factor values, selecting the top decile for each factor, and weighting holdings by the…

股票因子投資回測投資組合建構
BigQuant

The document explains ways traders might use live stock index quotes: to gauge broad market direction, compare sector conditions, assess a portfolio against a benchmark, adjust asset allocation, and inform stop levels or futures hedges. These are general…

股票期貨投資組合建構風險管理
BigQuant

This discussion addresses whether a trader should use hyperparameter search to find an optimal combination of existing factors. The response says that “optimal” needs a clear definition: it could mean the best backtest result or the best factor-analysis…

因子投資機器學習回測統計
BigQuant

This overview traces major developments in deep learning from the perceptron and backpropagation through convolutional and recurrent networks, generative models, residual networks, Transformers, and BERT. It describes the basic contribution associated with…

機器學習統計
BigQuant

This Chinese A-share backtest example uses a five-day versus twenty-day moving-average crossover to generate buy and sell signals. Its trading handler divides available cash equally among the stocks signaled for purchase, so if only one stock qualifies on a…

股票回測部位規模技術指標
BigQuant

This brief forum post asks how to translate a BigQuant expression into a newer SQL interface. The expression groups a daily count of securities whose limit-status condition is true, then divides that count by its 180-period mean. The post also suggests…

股票技術指標統計
BigQuant

This research applies feature selection to multi-factor stock selection in the full Chinese A-share universe, with the CSI 300 and CSI 500 as benchmarks. It constructs industry- and market-cap-neutral strategies and tests feature ranking methods with…

股票中國市場因子投資機器學習
BigQuant

The article argues that knowing market facts or technical concepts does not by itself produce successful trading. It recommends turning information into a complete trading framework that specifies entries, exits, position sizing, and risk controls. It also…

股票風險管理部位規模交易執行
BigQuant

This brief BigQuant project note describes a stock strategy built from three factors that had undergone stability testing. It says the factor weights were selected through a grid search over three parameters, with a reported weighting of 1:8:1. The note also…

股票因子投資回測風險管理
BigQuant

The document outlines a strategy that dynamically evaluates macroeconomic event factors and selects those more closely associated with asset movements. It considers more than thirty indicators spanning economic growth, inflation, monetary conditions, and…

多資產事件驅動因子投資投資組合建構
BigQuant

This overview introduces ten machine learning methods and sketches how they work, with examples of possible financial uses. It covers linear and logistic regression, K-nearest neighbors, support vector machines, decision trees, random forests, neural…

機器學習統計股票回測
BigQuant

The document discusses converting one-minute stock data into daily observations for high-frequency price and volume factors. The example query constructs features such as volume shares across intraday intervals, price and volume correlations, correlations…

高頻交易因子投資統計中國市場
BigQuant

This article proposes a qualitative framework for finding Chinese stocks with potential for medium- to long-term growth during annual and quarterly reporting periods. It combines three checks: whether recognized active investment firms appear among…

股票中國市場因子投資統計
BigQuant

This platform discussion addresses how to understand a precomputed factor, using a MACD signal-line factor as its example. The response says that the platform does not provide the calculation process for such precomputed data. Users can inspect the factor's…

因子投資技術指標統計股票
BigQuant

This research summary describes ranking international liquid stocks with a random forest trained on technical features. Rather than forecasting exact returns, the model estimates the likelihood that a stock will outperform an average-return threshold. The…

股票機器學習投資組合建構回測
BigQuant

This quarterly review surveys crypto market developments in early 2024, including Bitcoin spot ETF flows, Ethereum’s EIP-4844 upgrade, memecoin activity, real-world asset tokens, and regulatory changes. It combines token performance and exchange volume…

加密貨幣現貨市場技術指標鏈上資料
BigQuant

This article presents a discretionary framework for evaluating Chinese stocks after a limit-up day. It advises watching names that recently hit the daily limit and waiting several sessions for price and volume behavior to confirm whether a pullback may be…

中國市場股票技術指標突破
BigQuant

This overview proposes constructing fund of funds portfolios from four groups: broad-market index ETFs, sector ETFs, index-enhanced funds, and quantitative funds. It compares passive index funds, enhanced products, and quantitative funds by their typical fee…

中國市場多資產投資組合建構風險管理
BigQuant

This introductory tutorial presents active equity management as a connected process: forecast stock-level excess returns with an alpha model, estimate exposures with a risk model, combine expected returns and risk through portfolio optimization, execute…

股票因子投資風險管理投資組合建構
BigQuant

This Chinese-language discussion describes problems encountered when reusing a saved XGBoost model in a separate strategy and moving a feature-based strategy from research into simulated trading. Keeping visible strategy settings unchanged did not reproduce…

機器學習交易執行回測
BigQuant

This research summary examines four MSCI smart beta equity indexes—value weighted, equal weighted, momentum, and minimum volatility—against a capitalization-weighted benchmark. Using monthly observations from 1999 through 2014, it applies principal component…

股票因子投資統計投資組合建構