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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
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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 post proposes screening stocks using three conditions: amplitude above 1%, a shrinking negative MACD histogram on a 15-minute chart, and a 2019 dividend payout ratio above 25%. The idea combines price movement and a possible shift in short-term momentum…

AksjerTekniske indikatorerMomentumRisikostyring
SuperMind

This post describes a stock screen that requires amplitude above 1%, a current high equal to the highest high over two days, and more than two limit-up sessions within the prior 10 days. The combination targets stocks with recent price movement, a short-term…

AksjerMomentumTekniske indikatorerKinesiske markeder
SuperMind

This post presents a Chinese-equity screening rule combining daily price amplitude above 1%, a K-line indicator below 20, and relative volume greater than 1.5 but less than 6. It offers formula and Python-style examples for calculating amplitude from the…

AksjerTekniske indikatorerStatistikkKinesiske markeder
SuperMind

This Chinese stock-screening post combines a large intraday range with recent price strength and a lower daily low. Its initial conditions look for amplitude above 1 and at least one daily gain of 10% or more in the past 25 trading days, while requiring…

AksjerMomentumTekniske indikatorerKinesiske markeder
SuperMind

This proposed Chinese A-share screen selects companies associated with the robotics theme, turnover between 3% and 12%, circulating market capitalization below 10 billion yuan, and three consecutive declining sessions. The post presents the rules as a way to…

AksjerKinesiske markederTekniske indikatorerMomentum
SuperMind

The document proposes screening A-share equities for turnover between 3% and 12%, circulating market capitalization below 10 billion yuan, no reported losses, and a share price below 12 yuan. It frames the rules as a way to identify lower-priced, smaller…

AksjerKinesiske markederFaktorinvestering
SuperMind

The post proposes a Chinese equity screen for companies classified in the metaverse industry. It combines a volume-ratio band above 1.5 and below 6 with a KDJ bullish crossover. The author then expands the proposed screen to favor stocks with forecast profit…

Kinesiske markederAksjerTekniske indikatorerMomentum
SuperMind

This equity screen combines three filters: daily high-to-low range above 1%, a reversal or engulfing-style pattern, and a concentration measure below 20%. Formula and Python examples illustrate how the conditions might be combined to produce a candidate…

AksjerKinesiske markederTilbakevending mot gjennomsnittetTekniske indikatorer
SuperMind

This stock-selection screen combines membership in the metaverse theme with a long-term price filter and a one-day price-change threshold. It selects shares whose previous-day price is above the 250-day moving average and whose current-day gain exceeds 5%.…

AksjerKinesiske markederMomentumTekniske indikatorer
SuperMind

This portfolio overlay begins with CSI 300 constituents whose index weights exceed 0.35%. At the start of each month, it measures each eligible stock’s return over the previous 21 trading days, approximately one month. Stocks with positive returns are…

Kinesiske markederAksjerMomentumPorteføljekonstruksjon
SuperMind

This document describes a Chinese stock selection screen that combines turnover, price movement, large-order trading activity, and recent strength. The stated core conditions require turnover between 3% and 12%, a positive product of price change and…

Kinesiske markederAksjerMomentumTekniske indikatorer
SuperMind

This Chinese-language post describes a stock selection screen combining three conditions: turnover within a specified range, first-level bid volume greater than ask volume, and the prior close above the 250-day moving average. Its sample formula also…

AksjerTekniske indikatorerMomentumMarkedsmikrostruktur
SuperMind

The document describes a Chinese equity screen restricted to the metaverse industry. It selects stocks whose average price is above a five-day moving average, whose daily gain exceeds a stated threshold, and whose proprietary “control” measure is above a…

AksjerKinesiske markederMomentumTekniske indikatorer
SuperMind

This tutorial introduces a basic neuron model, describing weighted inputs, a threshold, and an activation function. It explains why a smooth sigmoid function is used in practice in place of an idealized step function, then applies a neural network to…

MaskinlæringAksjerTekniske indikatorerHistorisk testing
SuperMind

This Chinese stock-screening proposal selects companies classified in the metaverse industry when price is near its 10-day moving average and at least one session in the prior 25 trading days gained 10% or more. The article presents the average-price…

Kinesiske markederAksjerMomentumTekniske indikatorer
SuperMind

The document outlines an equity screen for stocks associated with the metaverse theme. It combines three filters: membership in that concept group, a current close above the previous day’s low, and a positive daily return at least once within a rolling…

AksjerKinesiske markederMomentumTekniske indikatorer
SuperMind

This Chinese A-share screening idea combines three filters: market capitalization below 10 billion yuan, no historical losses, and current trading volume above 10,000 lots. It also describes selecting stocks that open above the previous close, framing the…

AksjerKinesiske markederMomentumRisikostyring
SuperMind

This Chinese-language post describes a short-term screen for stocks in the metaverse theme. Its initial conditions are elevated turnover on the prior day and an upward arrangement of moving averages for the current day. The expanded version also requires…

AksjerKinesiske markederMomentumTekniske indikatorer
SuperMind

The document outlines a short-term Chinese equity screen combining price movement, a morning-star candlestick pattern, and prior-day trading activity. It also presents indicator and Python examples intended to select active stocks while excluding…

AksjerKinesiske markederTekniske indikatorerMomentum
SuperMind

The post describes a stock-selection screen for companies classified in the metaverse industry. It requires relative volume to fall between 1.5 and 6 and the prior day’s turnover rate to exceed 8%. The author presents these conditions as a way to identify…

AksjerMomentumTekniske indikatorerKinesiske markeder
SuperMind

This document describes a rule-based candlestick system that uses named reversal patterns to generate entries and exits. Its bullish conditions include morning-star variants, matching lows, and bullish engulfing-style moves; bearish conditions include…

AksjerTekniske indikatorerTilbakevending mot gjennomsnittetPosisjonsstørrelse
SuperMind

The document outlines a Chinese equity screening idea combining three conditions: a market capitalization below 10 billion yuan, no reported losses, and a daily increase in holdings above 5%, alongside large net buying in the afternoon. It interprets the…

AksjerKinesiske markederTekniske indikatorerMarkedssentiment
SuperMind

This Chinese stock-screening strategy combines three conditions: daily amplitude above 1%, at least two limit-up events during the prior 500 days, and positive net buying attributed to major investors during the opening auction. It also proposes ranking…

Kinesiske markederAksjerTekniske indikatorerMomentum
SuperMind

This proposed short-term stock screen combines a price-range threshold, an opening-auction gain below six percent, and a 15-minute MACD condition described as a shortening negative histogram. The article presents these filters as a way to combine volatility,…

AksjerKinesiske markederTekniske indikatorerMomentum