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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.

Quant Q&A
20,364 dokumenter
SuperMind
12,226 dokumenter
OKX Learn
8,431 dokumenter
Strategy library
7,910 dokumenter
MQL5 code base
7,090 dokumenter
BigQuant
3,481 dokumenter
Bitget Academy
3,298 dokumenter
MQL5 articles
3,012 dokumenter
TradingView scripts
1,976 dokumenter
ProRealCode
1,507 dokumenter
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
Quantpedia
86 dokumenter
TqSdk
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
Quantopian-forelesninger
45 dokumenter
Binance API docs
45 dokumenter
FMZ guides
38 dokumenter
pysystemtrade
34 dokumenter
Freqtrade docs
32 dokumenter
quant-trading
31 dokumenter
FinRL
28 dokumenter
Zipline
22 dokumenter
FMZ live strategies
21 dokumenter
Jesse
17 dokumenter
pyfolio
16 dokumenter
Alphalens
14 dokumenter
WonderTrader
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-screening approach selects securities with MACD above zero and a weekly close crossing above its 30-week moving average, then ranks candidates by market attention or heat. It runs after each trading day’s close. The stated rationale is to pair a…

AksjerMomentumTrendfølgende handelTekniske indikatorer
SuperMind

This document presents a Chinese equity screen that combines a turnover band with seven consecutive declining sessions and a nonempty name for an outstanding convertible bond. It then proposes adding fundamental filters: market capitalization above the…

AksjerKinesiske markederTekniske indikatorerStatistikk
SuperMind

This stock-selection rule combines three filters: a high-to-low daily range above 1%, a daily decline between 4% and 5%, and a positive price-to-earnings ratio. The article offers formula and Python examples, although the displayed formula does not appear to…

AksjerTekniske indikatorerStatistikkHistorisk testing
SuperMind

This stock-selection idea screens shares whose codes begin with 60, whose high-to-low daily range exceeds 1%, and that meet a reversal or “wraparound” candlestick condition. The article gives formula and Python examples, but the definitions are not fully…

AksjerTekniske indikatorerKinesiske markederHistorisk testing
SuperMind

This screening method selects stocks with market capitalization below 10 billion yuan, positive earnings, and an RSI below 65, then orders candidates by money-flow strength. It describes the money-flow measure as Chaikin Money Flow and gives a 20-period…

AksjerTekniske indikatorerMomentumFaktorinvestering
SuperMind

This stock screen combines three conditions: daily amplitude above 1, at least one limit-up event within the past month, and a 20-day moving average above the 120-day moving average. The moving-average relationship is intended to identify an upward trend,…

AksjerTrendfølgende handelTekniske indikatorerKinesiske markeder
SuperMind

This Chinese stock-screening idea ranks candidates by volume ratio and filters for turnover between 2% and 9% and a positive ten-day gain below 35%. The article interprets stronger volume ratio as greater investor attention, the turnover range as a sign of…

AksjerKinesiske markederMomentumTekniske indikatorer
SuperMind

This stock-selection rule combines a turnover filter, a beverage and alcohol industry screen, and a weekly moving-average crossover. It selects stocks with turnover between 3% and 12% when the weekly five-period moving average crosses above the ten-period…

AksjerKinesiske markederTekniske indikatorer
SuperMind

The post describes a stock-selection screen based on three technical conditions: price amplitude above a threshold, a rounded price shape, and a rising DEA indicator. It interprets the amplitude condition as a way to select active stocks without excessive…

AksjerTekniske indikatorerMomentum
SuperMind

This stock-selection rule combines a 14-period RSI below 65 with three consecutive declining sessions and a condition intended to identify upward divergence between short- and longer-term moving averages. The post presents the rule as a way to screen for…

AksjerKinesiske markederTekniske indikatorerMomentum
SuperMind

This stock-selection proposal combines a price-amplitude filter with a turnover and auction-volume condition, then requires return on equity (ROE) to exceed a stated threshold over five years. The central liquidity-style condition is yesterday's turnover…

Kinesiske markederAksjerFaktorinvesteringTekniske indikatorer
SuperMind

This Chinese-language community discussion asks how to calculate a market measure commonly translated as main-force net inflow. The post proposes defining it as the sum of actively initiated buy orders classified as large and extra-large. This frames the…

AksjerMarkedsmikrostrukturStatistikk
SuperMind

This post proposes a short-term China A-share screen combining three conditions: prior-session amplitude above 1%, tradable shares no greater than 5.5 billion, and more than two limit-up days within ten sessions. The rationale is to find active, relatively…

Kinesiske markederAksjerMomentumTekniske indikatorer
SuperMind

This stock-selection screen combines trading activity, company size, market value, and profitability. Its final criteria require turnover of up to 12%, circulating market value between 10 and 100 billion yuan, circulating share count no greater than 5.5…

Kinesiske markederAksjerFaktorinvesteringPosisjonsstørrelse
SuperMind

The document describes an A-share stock screen for companies associated with robotics. Its stated filters include turnover between 3% and 12%, total market value below 10 billion yuan, positive net income, and circulating market value below 10 billion yuan.…

AksjerKinesiske markederFaktorinvestering
SuperMind

This document presents an A-share stock selection idea that combines turnover between 3% and 12%, a K indicator below 20, and three consecutive days of falling closing prices. It describes the signal as a technical screen for stocks that might merit…

AksjerTekniske indikatorerTilbakevending mot gjennomsnittet
SuperMind

This document outlines an equity screen beginning with stocks whose daily price range exceeds 1%, market capitalization is at most 10 billion yuan, and average net profit is positive, while excluding stocks that hit the daily limit on the prior session. Its…

AksjerTekniske indikatorerFaktorinvesteringRisikostyring
SuperMind

This document presents an equity selection rule using a turnover range of 3% to 12%, seven consecutive down days, and a pattern described as the start of a strong advance. It gives indicator-formula and Python examples intended to identify the setup,…

AksjerTekniske indikatorerMomentumKursbrudd
SuperMind

This document describes an equities screening rule combining a turnover range, beverage and alcohol industry classification, and a comparison between displayed best bid and ask quantities. It presents the intended screen as selecting stocks with turnover…

AksjerMarkedsmikrostrukturTekniske indikatorerHistorisk testing
SuperMind

This document describes a short-term Chinese equity screen using three conditions: a share price below 12, more than two limit-up sessions within ten days, and amplitude above one. It frames repeated limit-ups as a possible sign of continued upside and…

AksjerMomentumKursbruddKinesiske markeder
SuperMind

This stock-screening idea combines three conditions: a rising 30-day moving average, three consecutive declining sessions, and a reported increase in position or capital inflow greater than five percent. The rationale pairs a positive longer-term trend with…

AksjerTekniske indikatorerTilbakevending mot gjennomsnittetMomentum
SuperMind

This reference catalog groups Python libraries used across quantitative finance. It covers strategy research and backtesting, technical indicators, risk and portfolio analysis, scientific computing, derivatives pricing, factor and time-series analysis,…

Historisk testingTekniske indikatorerRisikostyringPorteføljekonstruksjon
SuperMind

This Chinese equity screen requires turnover between 3% and 12%, a rising DEA condition, and a reversal pattern described as a rebound after a short pullback. The note frames turnover as a measure of trading activity and rising DEA as evidence of an upward…

AksjerTekniske indikatorerMomentumKinesiske markeder
SuperMind

This Chinese stock-selection rule combines three filters: rank stocks among the top 100 by volume ratio, rank the top 100 by the absolute difference between the previous day’s limit-down price and opening price, and require at least two limit-up days within…

AksjerMomentumVolatilitetKinesiske markeder