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
WonderTrader
14 份文件
Alphalens
14 份文件
backtesting.py
11 份文件
Technical Analysis
9 份文件
QTPyLib
8 份文件
Lumibot strategies
7 份文件
QuantRocket
7 份文件
Awesome Quant
1 份文件

搜尋圖書館

511 份文件

QuantInsti blog

This article presents the five-point pivot system, calculating the central pivot from the previous period's high, low, and close, then deriving two support and two resistance levels from that pivot and the prior range. It describes using prior-day data for…

技術指標股票交易執行
QuantInsti blog

The article explains the triple-barrier method as a way to create supervised learning labels using an upper profit-taking threshold, a lower stop threshold, and a time limit. It frames these barriers as a risk-aware alternative to fixed thresholds and…

機器學習回測風險管理波動率
QuantInsti blog

This career guide outlines the work of quantitative analysts, traders, data scientists, and developers, then describes skills that may be assessed in quant interviews. It emphasizes practical market knowledge, programming, statistical analysis, and…

統計機器學習市場微結構交易執行
QuantInsti blog

The article introduces support vector machines as classifiers that separate labeled observations with a boundary chosen to maximize the margin around nearby points. It explains support vectors, hard-margin classification, and soft margins that permit some…

機器學習統計股票回測
QuantInsti blog

The article describes a bull call spread, formed by buying a call and selling another call on the same underlying with the same expiration but a higher strike. The net premium paid is the maximum loss, while the difference between strikes less that premium…

選擇權風險管理衍生品定價
QuantInsti blog

The article surveys nine factors that may influence exchange rates: political conditions, inflation, interest rates, government debt, terms of trade, speculation, capital-market performance, employment data, and economic planning. For each, it gives a…

外匯中國市場美國市場
QuantInsti blog

The article explains cloud computing as internet-delivered access to computing resources and outlines service models—software, platform, and infrastructure—as well as private, hybrid, and public deployment. It describes possible trading uses, including…

多資產回測交易執行
QuantInsti blog

The document explains how to use a spreadsheet model to price calls and puts with the Black–Scholes formulas and chart the payoff of a portfolio across underlying prices. Users enter each option’s expiry, type, strike, premium, contract count, volatility,…

選擇權衍生品定價波動率部位規模
QuantInsti blog

This study compares two systematic futures trend approaches across indices, bonds, currencies, and commodities: a one-year time-series momentum rule and a continuous-forecast framework inspired by systematic trading methods. The first takes long or short…

期貨趨勢追蹤動能突破
QuantInsti blog

This project report explains portfolio diversification through Modern Portfolio Theory and introduces measures including alpha, beta, standard deviation, R-squared, and the Sharpe ratio. It describes the Fama-French three-factor model as an extension of CAPM…

股票投資組合建構統計風險管理
QuantInsti blog

This interview follows an experienced IT professional who developed an interest in algorithmic trading and built a short-duration intraday system for futures alongside a full-time job. He describes drawing on engineering, programming, mathematics, and…

期貨回測風險管理
QuantInsti blog

This introduction presents Julia as a language intended to combine high computational performance with the ease of a dynamic language, addressing the need to rewrite demanding scientific code in lower-level languages. It outlines Julia’s origins and compares…

回測交易執行技術指標衍生品定價
QuantInsti blog

The article introduces the Central Limit Theorem (CLT) through simulated samples from exponential and binomial populations. It explains that, under suitable conditions, sample means approach a normal sampling distribution as sample size grows; the…

統計股票風險管理
QuantInsti blog

The article demonstrates foundational analysis of stock price and volume data with Python and pandas. It describes loading OHLCV records, inspecting the date index, counting observations, finding the maximum closing price and its date, calculating daily…

股票技術指標統計
QuantInsti blog

The document outlines a session about private equity secondary markets: transactions in existing investments, with coverage of seller and buyer types, their motivations, and factors that may make a secondary investment attractive compared with a primary one.…

股票事件驅動投資組合建構
QuantInsti blog

This project builds daily trading signals for the Nifty 50 using logistic and linear regression. It derives predictors from OHLC relationships, including whether the close is nearer the high or low and whether the current high or low exceeds the prior day’s…

股票中國市場機器學習回測
QuantInsti blog

This recap of an industry Q&A discusses learning quantitative and algorithmic trading, career paths, and how AI tools affect research. Its central advice is to focus on process and evidence rather than the excitement of profit and loss or the novelty of…

機器學習風險管理回測
QuantInsti blog

This tutorial presents a workflow for adapting Pyfolio, a Python library for portfolio performance and risk analysis. It outlines the library’s reporting features, including return and risk statistics, rolling measures, drawdowns, and tear sheets, then…

投資組合建構風險管理回測
QuantInsti blog

The article explains how OHLC bars can be built using different measures of market activity. Time bars group trades into fixed intervals, while tick bars form after a set number of transactions. The examples show that equal-length time bars can conceal…

市場微結構統計技術指標股票
QuantInsti blog

This article introduces factor investing as portfolio construction based on characteristics associated with differences in investment returns and risks. It distinguishes macroeconomic factors, such as growth, interest rates, and inflation, from style…

因子投資投資組合建構動能風險管理
QuantInsti blog

This tutorial explains how a neural network adjusts its weights after forward propagation produces an incorrect prediction. It defines a squared-error loss for predicted class probabilities, then describes gradient descent as repeated weight updates based on…

機器學習統計
QuantInsti blog

This project compares ARIMA time-series modeling with an LSTM neural network for next-day Nifty index price forecasts. The author used five years of adjusted closing-price data, selected an ARIMA specification after stationarity checks and parameter…

股票機器學習統計回測
QuantInsti blog

This article introduces seven indicators commonly used in chart analysis and describes what each measures: moving averages smooth price changes; Bollinger Bands reflect volatility around a moving average; RSI and MFI assess momentum and possible overbought…

技術指標動能波動率
QuantInsti blog

The article introduces machine learning as a way to learn patterns from data and use them to classify or predict outcomes. It outlines supervised learning with labeled examples, including classification and regression; unsupervised learning that groups…

機器學習統計股票回測