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

The document introduces a quantitative way to assess an individual stock before deciding whether to buy it and how much capital to allocate. Rather than forecasting which stocks will be attractive, the proposed diagnostic approach looks backward at how the…

股票統計部位規模中國市場
BigQuant

This Chinese equity strategy screens for stocks whose opening price is above the previous close and whose five-day closing-price average is above its ten-day average. It ranks qualifying candidates by price-to-earnings ratio in ascending order and selects…

股票中國市場技術指標動能
BigQuant

This research note summarizes evidence that changes in the wording and structure of company filings can contain information about future operating performance and equity returns. The underlying study compares the text of SEC annual and quarterly reports with…

股票美國市場市場情緒統計
BigQuant

The article explains why a factor’s strong historical returns may come from an unintended exposure to market capitalization or liquidity. It uses large-order sell value as an example: because the measure is an absolute amount, it tends to be larger for…

因子投資股票回測統計
BigQuant

This research summary describes an equity selection process built from daily price and volume data. Genetic programming searches for candidate factors, using RankIC to favor linear relationships or mutual information to seek nonlinear ones. To focus on…

股票機器學習因子投資回測
BigQuant

This exchange explains how to handle a stock that remains in a backtest portfolio after it leaves the benchmark universe. The example concerns a strategy restricted to CSI 300 constituents: a stock bought while it belonged to the index may still be held…

股票回測中國市場投資組合建構
BigQuant

This brief explanation addresses why applying a one-period lag to closing prices can return a missing value. If the available data begins on the current day, the prior day’s close is outside the dataset, so there is no value for the lag operation to…

統計
BigQuant

This forum excerpt concerns constructing training labels for a Chinese stock dataset and asks why label extraction produces an empty training set. The displayed expression derives a future return from a later close divided by a later open, assigns a…

中國市場股票機器學習統計
BigQuant

This article examines how the length of an AI model’s training window can affect an equity strategy. It compares manually rolled long windows spanning several years with shorter windows ranging from a month to a few years, and recommends evaluating each…

機器學習回測股票因子投資
BigQuant

This brief Chinese market report summarizes A-share sector performance, index and sector valuations, market breadth, fund positioning, and an intermediate-term LLT model. It reports the strongest and weakest sectors, notes declining valuations across several…

股票中國市場技術指標趨勢追蹤
BigQuant

This research summary examines whether market conditions and macro variables can predict the next month’s long-short reversal-factor returns in Chinese equities. It identifies market funding sensitivity, turnover, volatility, and bid-ask spread as…

股票中國市場均值回歸因子投資
BigQuant

This BigQuant forum post describes a factor-research problem: detect a recent stock event, then later compare price with a level from the event day. The example defines an event using volume more than twice the prior value and a return above a stated…

股票統計技術指標
BigQuant

This brief BigQuant support exchange addresses a simulation error reported as having no data remaining after missing rows are dropped. The user had already tried extending the feature-extraction lookback by several different periods, without resolving the…

回測機器學習統計
BigQuant

The post asks why a daily stock-ranking strategy sells positions in backtests but appears only to buy them in simulation. Its code includes a trailing stop based on a percentage below the highest observed price since purchase, then manages capital and ranks…

股票機器學習風險管理部位規模
BigQuant

This brief BigQuant support exchange explains an error raised when a time-series minimum function receives a window argument that is not an integer. The example first derives a value from the position of the highest high within a fixed lookback, then passes…

統計機器學習
BigQuant

The document explains a data-processing approach for high-frequency factors that are first aggregated from intraday observations to daily values and then smoothed over multiple days. Instead of loading the full intraday history needed for the rolling window…

高頻交易技術指標統計
BigQuant

This note describes a single-security, multi-day approach to constructing intraday volume factors. For each trading day, the proposed measures calculate the share of full-day volume transacted within selected intervals. The intervals cover early trading,…

高頻交易市場微結構統計
BigQuant

This short exchange addresses how to sell stock shares according to the age of each entry. The example strategy opens separate lots in the same stock on consecutive days, then intends to close each lot after a specified holding period. That requires tracking…

股票交易執行部位規模風險管理
BigQuant

This note describes a reproduction of a Guosen Securities quantitative research report on daily momentum factors that combine individual stock and industry returns. Its central idea is to use the relationship between a stock’s performance and its industry’s…

股票動能因子投資回測
BigQuant

This April 2020 market note combines a long-term trend assessment, short-term liquidity view, sector preferences, and tracking of A-share fund flows. It says a market breadth model had turned bearish and describes weakening turnover and a declining stock of…

中國市場股票統計風險管理
BigQuant

The report proposes combining company-level stock selection with industry allocation for Chinese equities. Its coupling model uses each stock’s historical beta to its industry as a dynamic weight: more industry-sensitive stocks receive more influence from…

中國市場股票因子投資投資組合建構
BigQuant

This summary of a Changjiang Securities study explains a stock-selection factor based on the balance between active and passive buying. Active buying occurs when an investor’s order trades against displayed sell orders; passive buying places a limit order…

股票市場情緒因子投資統計
BigQuant

This research summary argues that factor signals weaken over time, so holding a monthly portfolio unchanged can leave later-period capital exposed to less informative signals. It proposes measuring a factor’s decay speed through the half-life of its…

因子投資回測投資組合建構交易執行