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
TqSdk
86 documents
Quantpedia
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
Binance API docs
45 documents
Quantopian lectures
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

4,510 documents

Amberdata research

This market snapshot interprets a sharp crypto selloff using spot prices and volume alongside derivatives positioning, exchange traded fund flows, stablecoin supply, order book depth, and spreads. It frames falling open interest and negative funding as…

CryptoDerivatives pricingPerpetual futuresVolatility
SuperMind

This stock-selection approach filters for an RSI below 65, bid-side displayed volume greater than ask-side volume, and positive afternoon net inflow from large orders. It combines a technical indicator with order-book pressure and a money-flow measure, on…

EquitiesChina marketsTechnical indicatorsMarket microstructure
SuperMind

This post proposes screening stocks in the metaverse theme for prior-day turnover above 8% and simultaneous bullish crossovers in MACD, KDJ, and RSI. It names the MACD parameters as 12, 26, and 9; describes a KDJ comparison; and compares RSI values…

China marketsEquitiesMomentumTechnical indicators
SuperMind

This Chinese equity screening idea selects stocks with an amplitude greater than one, a prior-day 9:15 matching price at the lower price limit, and exclusion of the STAR Market. The post interprets large amplitude as a source of potential opportunity and the…

EquitiesChina marketsTechnical indicatorsVolatility
SuperMind

This post proposes a daily, end-of-day screen for Chinese equities. It first selects stocks with the MACD line above zero, then ranks candidates by a measure of stock attention and by net large-order flow. The accompanying rationale treats positive MACD as a…

China marketsEquitiesMomentumTechnical indicators
BigQuant

The article challenges the claim that Chinese stock index futures expiry reliably causes equity market declines. It argues that these contracts settle in cash, so settlement itself does not require buying or selling ETFs or underlying shares. Hedgers can…

FuturesEquitiesStatisticsSentiment
BigQuant

This report surveys gold’s supply and demand, major trading venues, and common investment instruments. It notes that investment demand and central bank purchases are especially relevant to prices, and describes the roles of London spot trading, U.S. futures,…

CommoditiesFuturesSentimentBacktesting
SuperMind

This document presents a Chinese equity screen for metaverse-related stocks. Its core conditions are a volume ratio between 1.5 and 6 and a positive reading for a measure described as prior-day main-force control. The final version also adds a…

EquitiesChina marketsTechnical indicatorsSentiment
Kraken Learn

This survey describes how more than 800 U.S. crypto holders use stablecoins, how much they allocate to them, and what affects their trust in specific assets. It reports that 88% hold stablecoins and gives allocation ranges, common uses, and differences by…

CryptoSentimentArbitragePortfolio construction
BigQuant

This research summary tests whether negative sentiment in posts on Xueqiu, a Chinese investing forum, can help time major Chinese equity indexes. It describes using machine learning to classify post sentiment and building a weekly negative-sentiment ratio…

SentimentMachine learningEquitiesChina markets
BigQuant

The article summarizes research on how speculative stocks perform around earnings announcements. It measures speculative characteristics using proxies such as maximum daily return, idiosyncratic volatility, price, expected skewness, and jackpot probability,…

EquitiesEvent-drivenSentimentFactor investing
SuperMind

This Chinese equity screening proposal combines three conditions: amplitude above 1, at least one daily gain of 10% or more during the previous 25 trading days, and an opening auction move between -2% and 5%. The post frames the first two as ways to find…

EquitiesTechnical indicatorsMomentumVolatility
SuperMind

This Chinese stock-screening note combines three technical conditions: amplitude above 1, a “morning star” candlestick pattern, and at least one limit-up day within the previous 25 days. It describes the pattern and recent limit-up activity as signs of…

EquitiesTechnical indicatorsMomentumSentiment
Amberdata research

The document explains funding rates as periodic transfers between long and short holders of perpetual futures. The payment direction depends on whether the contract trades above or below its reference index: positive rates charge longs and credit shorts,…

CryptoFuturesPerpetual futuresArbitrage
SuperMind

This stock-selection recipe combines three conditions: membership in the metaverse segment, positive net buying attributed to major participants during the auction, and a nonempty name for an outstanding convertible bond. The post interprets the auction…

EquitiesChina marketsSentimentTechnical indicators
BigQuant

The article explains five behavioral traps that it associates with retail trading losses: confirmation bias, reacting to noisy opening-auction signals, trying to recover losses through riskier trades, loss aversion that delays selling, and greed that delays…

Risk managementSentimentEquitiesChina markets
Amberdata research

This report explains how bid and ask quantities, volume profiles, and order book imbalance can be used to interpret trading conditions in ETH markets. It describes watching changes in displayed bid and ask size alongside price, and treating divergence or…

CryptoMarket microstructureSentimentTechnical indicators
Amberdata research

This market update reviews Bitcoin and Ether derivatives conditions using realized volatility, options term structure, skew, option flows, and dealer gamma positioning. It reports that realized volatility had fallen into the low twenties, with Bitcoin’s…

CryptoOptionsVolatilitySentiment
SuperMind

This Chinese-language article proposes an A-share screening rule: require a daily high-low range above one percent, detect a newly formed KDJ crossover, then rank candidates by stock popularity or trading volume. The selected stocks enter a watch or…

China marketsEquitiesTechnical indicatorsMomentum
Lumibot

The document presents a QuantStats tear sheet for a strategy named fear-greed-plain-v2, compared with SPY over a brief January 2026 test period. It reports returns, drawdowns, risk-adjusted metrics, benchmark correlation, time in the market, and daily gains…

BacktestingRisk managementSentimentEquities
BigQuant

The report explains how option prices can be used to construct volatility and skew measures for the Chinese equity market. VIX represents expected volatility over a forward period, while SKEW captures the market’s pricing of asymmetric returns and tail risk.…

OptionsVolatilityDerivatives pricingChina markets
Cryptohopper blog

This overview explains how large cryptocurrency holders may affect token supply, liquidity, and prices, then describes on-chain tracking as a way to monitor their activity. It distinguishes transfers from wallets to exchanges, exchanges to wallets, and…

CryptoOn-chain dataSentiment
Cryptohopper blog

This article outlines ways to manage cryptocurrency holdings during falling markets. It discusses buying assets after declines for a longer-term recovery thesis, favoring established coins over highly volatile tokens, short selling, diversifying across…

CryptoPortfolio constructionRisk managementSentiment
BigQuant

The article argues that algorithmic trading can exploit retail investors’ predictable reactions to price action and news in China’s A-share market. It illustrates this with two anecdotal patterns: a sharp late-session reversal in high-flying consumer stocks…

EquitiesChina marketsMarket microstructureSentiment