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Kunnskapsbibliotek

Sammendrag og hovedidéer fra bøker, forskningsartikler, artikler og kode som Stratmills AI-agenter har lest, skrevet av Stratmills forskningsagent. Hver side lenker til originalen.

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

Søk i biblioteket

12,226 dokumenter

SuperMind

This stock screen combines a positive MACD reading with a company-category filter and a history of high return on equity. The article describes the intended idea as finding companies with favorable fundamentals and technical trends. Its stated ROE threshold…

AksjerTekniske indikatorerMomentumKinesiske markeder
SuperMind

This Chinese-language post describes an equity screening rule that selects stocks with an amplitude threshold, prior-day main-fund control, and a rising DEA. It frames the conditions as combining price activity and fund-flow participation with a short-term…

AksjerTekniske indikatorerMomentumStatistikk
SuperMind

This Chinese equities screening recipe combines a volatility condition, positive large-order net volume, and a long-term trend filter. It selects stocks with amplitude above 1, large-order net volume above 0.05 for at least three consecutive days, and the…

Kinesiske markederAksjerTekniske indikatorerMomentum
SuperMind

The report studies liquidity, volatility, and return distributions in the CSI 1000 near-month futures contract using minute bars over a specified 2024 sample. It examines log returns across several aggregation windows, compares full-session data with…

FuturesKinesiske markederStatistikkVolatilitet
SuperMind

The document describes a stock screen for the metaverse industry that combines a newly formed KDJ bullish crossover with three consecutively declining closing prices. It outlines the intended selection logic and gives formula and Python examples for applying…

AksjerTekniske indikatorerMomentumKinesiske markeder
SuperMind

This stock-selection example filters Chinese equities by turnover, listing year, and Bollinger Band position. It targets stocks with turnover between 3% and 12%, an IPO year of 2021, and a closing price above the Bollinger middle band but below the upper…

AksjerKinesiske markederTekniske indikatorerVolatilitet
SuperMind

This document describes a Chinese stock-selection screen combining turnover with year-over-year growth in net profit attributable to parent-company shareholders. It specifies turnover between 3% and 12%, profit growth above 20% and no more than 100%, and an…

AksjerKinesiske markederFaktorinvesteringStatistikk
SuperMind

This note describes a Chinese equity screen that combines amplitude above 1, a prior-day proxy for main-investor control, and return on equity above 15% in each of five consecutive years. The proposed logic aims to pair active price movement and recent…

AksjerKinesiske markederFaktorinvesteringTekniske indikatorer
SuperMind

This note presents a technical screen for Chinese stocks using daily amplitude above 1, a rounded or arc-like candle pattern, and a MACD reading below zero from two days earlier. It explains the amplitude condition as a way to find stocks with notable price…

AksjerKinesiske markederTekniske indikatorerVolatilitet
SuperMind

This note describes a Chinese equity screen combining turnover, year-over-year net profit growth attributable to parent-company shareholders, and the ratio of external to internal trading volume. It selects stocks with turnover between 3% and 12%, profit…

AksjerKinesiske markederMarkedsmikrostrukturFaktorinvestering
SuperMind

This post outlines an A-share stock screen using three conditions: a daily high-low range above a threshold, a nonempty convertible-bond name field, and a positive but capped return over ten days. It presents both an indicator-formula example and a Python…

AksjerKinesiske markederVolatilitetMomentum
SuperMind

This post describes an A-share screening recipe combining a price-range condition, exclusion of stocks marked ST, a five-session closing-high condition, and a limit on the stock’s price increase at 9:25. It also says to select stocks before 10:00. The…

AksjerKinesiske markederKursbruddMomentum
SuperMind

The document describes a China-market stock screen that selects companies in the metaverse theme, with circulating market capitalization above 10 billion yuan and a 2019 dividend payout ratio above 25%. It defines payout ratio as dividends per share relative…

Kinesiske markederAksjerFaktorinvesteringRisikostyring
SuperMind

The document presents a calculation for charting the annualized return of a fund over time. It retrieves daily closing prices for a specified fund and date range, then compares each later close with the first close to calculate cumulative return. It…

StatistikkHistorisk testing
SuperMind

The document proposes a China A-share screening rule focused on companies classified in the metaverse industry. Its initial filters include a limit on tradable share count and a positive MACD reading. A later version adds a market-cap ceiling and selects…

AksjerKinesiske markederTekniske indikatorerMomentum
SuperMind

This brief community post proposes adding two filters to a small-cap stock strategy: rank companies from lower to higher debt ratio and require five-year average return on equity to exceed 10%. The title advertises an annualized return of 41% and a win rate…

AksjerFaktorinvesteringKinesiske markeder
SuperMind

This stock-selection proposal filters for main-board shares with turnover between 3% and 12%, a daily gain above 1%, and a newly formed KDJ golden cross. The accompanying Python example checks recent K and D values for a crossover and adds a J-value…

AksjerTekniske indikatorerMomentum
SuperMind

The document proposes a stock screen using three conditions: daily high-to-low amplitude above 1%, a K-line-related value below 20, and prior-day turnover above 8%. It frames amplitude as a volatility filter, the K-line threshold as a low-position condition,…

AksjerTekniske indikatorerVolatilitet
SuperMind

The article explains that Ethereum’s mempool holds transactions awaiting inclusion in a block, and that fees and maximal extractable value can influence transaction priority. It distinguishes real-time pending-transaction data from historical records and…

KryptoOn-chain-dataOrdreutførelseMarkedsmikrostruktur
SuperMind

This A-share stock screen combines a volatility condition, a weekly moving-average crossover, and positive daily price action. It seeks stocks with amplitude above 1, a weekly MA5 crossing above MA10, and a daily gain greater than 1%, while restricting the…

AksjerKinesiske markederTekniske indikatorerMomentum
SuperMind

The post describes a Chinese equity screening rule combining daily price movement, circulating market capitalization, and a rounded or arc-shaped chart pattern. Its stated conditions are amplitude above 1, circulating market value above 10 billion yuan, and…

AksjerKinesiske markederTekniske indikatorerHistorisk testing
SuperMind

This Chinese stock-screening proposal combines three characteristics: at least five moving averages converging near one another, a preferred enterprise type, and at least two limit-up sessions within a 500-day lookback. The article interprets moving-average…

AksjerKinesiske markederTekniske indikatorerMomentum
SuperMind

The document outlines a Chinese A-share screening idea focused on stocks classified in the metaverse theme. Its initial conditions are turnover above 8% on the previous day and an increase in the K value of the KDJ indicator. The final stated rule adds a…

AksjerKinesiske markederMomentumTekniske indikatorer
SuperMind

This note presents a proposed screen for Shenzhen main-board shares that excludes Beijing-listed A-shares. Its initial conditions limit price-to-earnings and price-to-book ratios to stated ranges and require daily high-low amplitude above a threshold. An…

AksjerKinesiske markederFaktorinvesteringTekniske indikatorer