Skip to content

Knowledge library

Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.

Quant Q&A
20,364 documents
SuperMind
12,226 documents
OKX Learn
8,431 documents
Strategy library
7,910 documents
MQL5 code base
7,090 documents
BigQuant
3,481 documents
Bitget Academy
3,298 documents
MQL5 articles
3,012 documents
TradingView scripts
1,976 documents
ProRealCode
1,507 documents
Deribit Insights
1,232 documents
Machine Learning for Trading
1,124 documents
arXiv papers
1,033 documents
Amberdata research
766 documents
FMZ forum
682 documents
FMZ digest
662 documents
vn.py community
560 documents
QuantInsti blog
511 documents
Galaxy Research
340 documents
QuantStart
246 documents
Stratmill research code
219 documents
Robot Wealth
195 documents
NautilusTrader
191 documents
Hummingbot docs
181 documents
Paradigm research
175 documents
Lumibot
164 documents
Kraken Learn
163 documents
Quant course library
157 documents
OctoBot
152 documents
Cryptohopper blog
144 documents
Systematic trading blog (Rob Carver)
132 documents
Qlib
116 documents
Quantpedia
86 documents
TqSdk
86 documents
Hyperliquid docs
79 documents
Freqtrade
68 documents
Hudson & Thames
62 documents
Awesome Systematic Trading
61 documents
backtrader
54 documents
vn.py
50 documents
Quantopian lectures
45 documents
Binance API docs
45 documents
FMZ guides
38 documents
pysystemtrade
34 documents
Freqtrade docs
32 documents
quant-trading
31 documents
FinRL
28 documents
Zipline
22 documents
FMZ live strategies
21 documents
Jesse
17 documents
pyfolio
16 documents
Alphalens
14 documents
WonderTrader
14 documents
backtesting.py
11 documents
Technical Analysis
9 documents
QTPyLib
8 documents
QuantRocket
7 documents
Lumibot strategies
7 documents
Awesome Quant
1 documents

Search the library

61 documents

Awesome Systematic Trading

This post describes a Chinese A-share stock screen combining three conditions: daily amplitude above 1%, a closing price of 18.5 yuan, and a positive MACD value. It frames these as a volatility filter, a fixed-price constraint, and a momentum or trend…

EquitiesChina marketsTechnical indicatorsMomentum
Awesome Systematic Trading

This strategy forms a dollar-neutral stock portfolio by identifying securities that rank among the strongest or weakest performers over two overlapping six-month return windows. It buys stocks in the top decile in both windows and shorts those in the bottom…

EquitiesMomentumPortfolio constructionPosition sizing
Awesome Systematic Trading

This strategy ranks stocks by their return during the month one year earlier, then buys the strongest group and shorts the weakest. It forms portfolios monthly and rebalances at month end. The described source approach uses equal weighting and a large-cap…

EquitiesMomentumFactor investingBacktesting
Awesome Systematic Trading

This algorithm describes a weekly long-short strategy among large U.S. equities. It first filters for liquid stocks, then selects the largest companies by market capitalization. From that group, it buys the ten stocks with the weakest returns over the prior…

EquitiesMean reversionMomentumBacktesting
Awesome Systematic Trading

This strategy ranks country exchange-traded funds by estimated market beta, measured against a U.S. equity index using a rolling year of daily prices. Each month, it divides the available funds around the median beta, going long the lower-beta group and…

EquitiesFactor investingPortfolio constructionRisk management
Awesome Systematic Trading

The strategy allocates across five exchange-traded funds representing US equities, foreign equities, bonds, real estate, and commodities. At a monthly rebalance, it holds each asset class whose price is above its 10-month simple moving average and moves the…

Multi-assetTrend followingTechnical indicatorsPortfolio construction
Awesome Systematic Trading

The strategy forms a monthly long-short equity portfolio from NYSE, AMEX, and NASDAQ stocks priced above five dollars. It first keeps the larger half of the eligible universe by market capitalization, then ranks stocks by six-month realized return and…

EquitiesUS marketsMomentumMean reversion
Awesome Systematic Trading

The document describes a chart indicator for calculating trade size from an entry price, stop level, and a user-selected risk budget. Traders can set risk as a percentage of account balance, a percentage of equity, or a fixed cash amount. The calculation…

Risk managementPosition sizing
Awesome Systematic Trading

This Japanese-language README curates resources for systematic trading research and implementation, including backtesting and live-trading frameworks, analytics tools, data sources, books, papers, blogs, and courses. Its practical framing is to reproduce…

BacktestingStatisticsMachine learningEquities
Awesome Systematic Trading

This strategy ranks stocks monthly by the share of their trading volume occurring in recent earnings-announcement months. It uses a 48-month history and focuses on the latest 16 announcement months, then divides stocks into quintiles by the resulting…

EquitiesEvent-drivenFactor investingPortfolio construction
Awesome Systematic Trading

The document outlines a short-horizon SPY strategy based on changes in synthetic lending or borrowing intensity. It averages borrow-intensity readings across a broad set of stocks and ETFs, compares the daily aggregate with the prior day, and uses the sign…

EquitiesUS marketsMean reversionBacktesting
Awesome Systematic Trading

This document describes a cross-sectional momentum strategy for equity mutual funds. It first limits the universe to no-load funds, then ranks eligible funds by their trailing six-month returns. The portfolio holds the top decile, equally weighted, and…

EquitiesMomentumFactor investingPortfolio construction
Awesome Systematic Trading

This strategy uses SPY, VIX, and the Brain Market Sentiment indicator to determine exposure to an overnight SPY trade. It checks each series against its 20-day average: SPY and sentiment must be above their averages, while VIX must be below its average. Each…

EquitiesSentimentTechnical indicatorsTrend following
Awesome Systematic Trading

This Chinese-language README catalogs resources for systematic trading research and implementation, including backtesting frameworks, trading libraries, data sources, strategies, books, videos, blogs, and courses. Its listings span multiple asset classes and…

BacktestingStatisticsMulti-asset
Awesome Systematic Trading

This document outlines a dispersion trade using options on constituents of the S&P 100 and options on the index. The research concept measures disagreement in analyst earnings forecasts, scaled by an earnings-uncertainty measure, and sorts stocks into groups…

OptionsEquitiesVolatilityArbitrage
Awesome Systematic Trading

This strategy ranks commodity futures by roll return each month, buys the highest-return group, and shorts the lowest-return group. The groups are equally weighted, and positions are held for one month. The implementation calculates roll return from the…

CommoditiesFuturesCarryBacktesting
Awesome Systematic Trading

The strategy tracks the daily price difference between continuous WTI and Brent crude futures and compares it with a 20-day simple moving average. When the spread is above its average, it takes positions intended to profit from a decline toward that…

FuturesCommoditiesMean reversionPairs trading
Awesome Systematic Trading

The document describes a cross-market futures reversal strategy. It groups contracts by recent changes in trading volume and open interest, then selects contracts in the high-volume, low-open-interest group. Within that subset, the stated method goes long…

FuturesMean reversionMomentumBacktesting
Awesome Systematic Trading

The strategy ranks currency futures using purchasing power parity data as a currency-value signal. Its description proposes a universe of roughly ten to twenty currencies, estimates fair values using OECD PPP figures adjusted with monthly CPI and…

ForexFuturesFactor investingBacktesting
Awesome Systematic Trading

The strategy described in the code sorts stocks around earnings announcements by their returns from four to two trading days before the event. The underlying research description first divides stocks by firm size, then sorts the largest size group into…

EquitiesEvent-drivenMean reversionBacktesting
Awesome Systematic Trading

This QuantConnect algorithm ranks six U.S. equity style ETFs covering small-, mid-, and large-cap value and growth. It measures each ETF’s momentum over roughly twelve months of daily data, then takes a long position in the strongest style and a short…

EquitiesMomentumFactor investingPortfolio construction
Awesome Systematic Trading

The document implements a monthly long-only stock-selection approach based on historical volatility. It describes ranking large-cap stocks by the volatility of weekly returns over roughly three years, then holding an equally weighted group from the…

EquitiesFactor investingVolatilityPortfolio construction
Awesome Systematic Trading

The strategy shorts publicly traded soccer club stocks at the close before a major match and holds positions for one day. When several clubs play on the same date, their short positions are equally weighted. The implementation uses match-date data to…

EquitiesEvent-drivenArbitrageBacktesting
Awesome Systematic Trading

The strategy ranks equities by a short-activity measure and forms a monthly long-short portfolio. It sorts stocks into deciles using short interest relative to shares outstanding, buys the lowest-ratio group, and shorts the highest-ratio group, with equal…

EquitiesFactor investingBacktestingUS markets