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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

FMZ forum

The document describes a Chinese equity screening rule that combines three conditions: today's position-increase ratio must exceed a threshold, large-order net volume must remain above a threshold for several consecutive days, and the stock must have reached…

EquitiesMomentumBreakoutSentiment
Cryptohopper blog

This article presents a qualitative checklist for researching crypto investments during a market downturn. It recommends examining a project’s purpose and competitive edge, practical utility, developer team, community, revenue, liquidity, treasury…

CryptoDeFiRisk managementSentiment
SuperMind

This article proposes screening Chinese A-shares in the metaverse theme using a pre-open price-change threshold and a “control” indicator above 21. It frames the control measure as a gauge of buying versus selling pressure and the opening condition as a way…

EquitiesChina marketsSentimentTechnical indicators
SuperMind

The document outlines a Chinese stock-selection screen combining RSI below 65, an external-to-internal trading-volume ratio above 1.3, and a run of seven declining daily closes. It frames the combination as a way to find stocks that have weakened steadily…

China marketsEquitiesMean reversionTechnical indicators
SuperMind

This article develops two monthly equity factors from Chinese market flow data. The first, called institutional-versus-retail harvesting, adds the cross-sectional ranks of large-order net buying and small-order net buying. The author interprets the factor as…

EquitiesFactor investingSentimentChina markets
SuperMind

This proposed Chinese equity screen targets companies classified in the metaverse sector that appeared on the prior day's exchange trading list and had been listed for more than a year. The article presents the trading-list appearance as a way to identify…

EquitiesChina marketsEvent-drivenSentiment
Quant Q&A

The document outlines a basic workflow for studying whether investors favor value or growth stocks during crises. It suggests obtaining constituent stock prices from market data sources, using an established equity research classification to separate value…

EquitiesFactor investingSentimentUS markets
Quant Q&A

The discussion offers several explanations for why stock prices may hold up even when current corporate earnings fall sharply during an economic shock. Lower interest rates can support higher valuation multiples because future cash flows are discounted less…

EquitiesUS marketsEvent-drivenSentiment
Quant Q&A

The discussion explains reflexivity as a feedback loop: traders form expectations from information and prices, act on those expectations, and thereby change prices and later beliefs. It points to Keynesian beauty contests, game theory, agent-based models,…

Market microstructureStatisticsExecutionSentiment
Quant Q&A

The document asks whether an anomaly detector can be trained on normal gift-card activation transactions and then evaluated on anomalous cases. It also describes a setting with no reliable fraud labels and transaction-level fields such as merchant, location,…

Machine learningStatisticsEvent-drivenRisk management
Quant Q&A

The document asks how to make a trading bot imitate a typical nonprofessional foreign exchange trader, including whether such traders can be treated as acting randomly regardless of market conditions. The response rejects assuming random behavior as a sound…

ForexMachine learningSentiment
Quant Q&A

The answers distinguish implied volatility, inferred from option prices and reflecting priced expectations, from realized volatility measured from observed price movements. They describe volatility as potentially reflecting uncertainty, investor positioning,…

EquitiesOptionsVolatilityFixed income
Quant Q&A

The document asks where to obtain analysts’ earnings estimates and whether data shown on a website can be imported into a personal database. The response points to Bloomberg terminals available at some local universities or colleges, particularly in business…

EquitiesSentiment
Quant Q&A

The document discusses why out-of-the-money puts may be priced above calls with strikes equally distant from the underlying price, and why this does not necessarily imply an immediate expected decline. It attributes the skew partly to demand from long…

OptionsDerivatives pricingMarket microstructureSentiment
Quant Q&A

The document addresses why nearby option strikes can show sharply different open interest. Its proposed explanation is a preference for round-number strikes: traders may concentrate positions at salient levels such as 7,400, leaving a nearby strike like…

OptionsMarket microstructureSentiment
Quant Q&A

The document explains the phrase “no shorts left” in a market commentary passage describing an increasingly bullish market. In this context, shorts are investors holding positions that benefit from falling prices, reflecting a negative market outlook. The…

EquitiesSentimentOptions
Quant Q&A

The document surveys research and practical ideas for using news, blogs, social media, and company reports to forecast equity returns or other financial variables. It describes vendor sentiment scores and studies that apply nonlinear models, including trees,…

EquitiesSentimentMachine learningEvent-driven
Quant Q&A

The document explains implied correlation as a measure of how closely investors expect the assets in an index or portfolio to move together. It distinguishes correlation indices, which can be calculated from index and constituent options, from correlation…

OptionsEquitiesVolatilitySentiment
Quant Q&A

The document considers whether technical patterns may lose predictive value as central banks, passive investors, and algorithmic trading change market structure. Its answer separates patterns that work because traders believe in and act on them from patterns…

Technical indicatorsMarket microstructureSentiment
Quant Q&A

The document considers whether indicators can reliably identify sharp market reversals, including reversals following major market declines. The response lists RSI divergence, MACD crossovers or divergence, and breaks of resistance or trend lines as possible…

Technical indicatorsVolatilityOptionsSentiment
Quant Q&A

The document considers which market variables might be studied alongside Twitter activity, including index and stock prices, price differences, trends, and expected returns. A response recommends treating posts as a source of market sentiment rather than…

EquitiesSentimentMomentumBacktesting
Quant Q&A

The document surveys proposed uses of social media and online discussion data in trading. Suggested signals include investor attention, the popularity of individual stocks, shifts in discussion volume, and changes in sentiment. One cited behavioral…

SentimentEquitiesVolatilityEvent-driven
Quant Q&A

The document presents a technical definition of a financial bubble attributed to a research work on bubble mechanisms and diagnostics. In this account, prices during a bubble rise faster than an exponential growth path, sometimes displaying log-periodic…

StatisticsEquitiesSentiment
Quant Q&A

The document clarifies a market interpretation of declining open interest in long Bitcoin futures positions. The question asks how closing futures longs could limit further declines in Bitcoin, given that futures are often viewed as bets on the underlying…

CryptoFuturesMarket microstructureSentiment