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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
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
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

79,386 dokumenter

SuperMind

This Chinese stock-selection approach narrows its universe to metaverse-related companies, then applies a positive institutional-flow condition and a threshold for the ratio of external to internal trading volume. The article’s prose gives a ratio threshold…

AksjerKinesiske markederMarkedssentimentMarkedsmikrostruktur
MQL5 code base

ZoneUS30 is an Expert Advisor for the US30 index that opens short positions when its internal conditions detect an upward price extension that may be followed by a correction. The approach combines counter-trend mean reversion with the possibility of…

Tilbakevending mot gjennomsnittetCarry-avkastningRisikostyringPosisjonsstørrelse
SuperMind

This Chinese equity screen combines current turnover, year-over-year net profit growth attributable to parent-company shareholders, and the previous day’s turnover. It selects stocks with turnover from 3% through 12%, profit growth above 20% and no more than…

AksjerKinesiske markederMomentumFaktorinvestering
MQL5 code base

The indicator presents CandlesticksBW color signals from ten timeframes as separate lines, allowing a trader to compare trend readings across multiple horizons in one display. Each line represents one instance of the underlying indicator, and its colors…

Tekniske indikatorer
SuperMind

The document presents a Chinese equity screening idea focused on metaverse-related stocks. Its initial criteria combine a volume ratio between 1.5 and 6 with a stated prior-year return threshold. The post then proposes adding a market-cap floor, a forecast…

AksjerKinesiske markederMomentumTekniske indikatorer
ProRealCode

The document describes a MACD variant that replaces its fast, slow, and signal moving averages with Arnaud Legoux Moving Averages (ALMA). It calculates weighted averages using a Gaussian-shaped weighting scheme, then subtracts the slow average from the fast…

Tekniske indikatorerTrendfølgende handelHistorisk testing
MQL5 code base

This document outlines an Expert Advisor that trades when the KWAN_NRP indicator changes its direction, represented by a color change. The signal is evaluated when a bar closes, making the bar close the decision point for detecting a change and generating a…

ValutahandelTekniske indikatorerHistorisk testing
SuperMind

This document describes a Chinese stock screen that selects shares with turnover between 3% and 12%, a listing year of 2021, and a MACD value below zero two trading days earlier. It presents the conditions as a way to combine a liquidity filter with a…

AksjerKinesiske markederTekniske indikatorer
BigQuant

This BigQuant forum entry addresses an error caused by referencing a locally created stock list as though it were an attribute of the backtest context. Its central correction is to use the variable where it was defined, without the context prefix, unless the…

AksjerKinesiske markederTekniske indikatorerHistorisk testing
Amberdata research

This weekly market commentary reviews Bitcoin and Ether options positioning before a US inflation release in February 2023. It connects macro uncertainty and recent spot declines to implied volatility, realized volatility, term structure, and risk reversals.…

KryptoOpsjonerVolatilitetPrising av derivater
SuperMind

This document describes a Chinese stock screen that combines an intraday price range filter with a 15-minute MACD histogram condition, limited to 2021. The accompanying examples implement the filters in indicator and Python workflows. The intended use is to…

AksjerKinesiske markederTekniske indikatorerVolatilitet
SuperMind

This stock screen selects companies with strong money-flow readings, share prices below 12 yuan, market capitalization under 10 billion yuan, and no reported losses. The proposed ranking orders candidates from strongest to weakest by money-flow intensity.…

AksjerKinesiske markederMomentumFaktorinvestering
Hyperliquid docs

This document explains the conditions for enabling a token as a spot quote asset on Hyperliquid. Requirements include specified token precision, no deployer fee share, a USD peg mechanism, and liquidity thresholds across the quote token’s USDC and HYPE…

KryptoSpotmarkederMarkedsmikrostrukturRisikostyring
BigQuant

This study outlines an experiment applying a Transformer model to short-horizon stock selection in China’s A-share market. Its target is each stock’s return over the next five trading days, using daily market data from 2015 through 2021. The inputs begin…

AksjerKinesiske markederMaskinlæringFaktorinvestering
Amberdata research

This recap reviews Bitcoin and Ether options and volatility conditions in early April 2023. It tracks realized volatility, term structure, put and call skew, options flow, and dealer gamma positioning as a compact framework for reading the derivatives…

KryptoOpsjonerVolatilitetPrising av derivater
BigQuant

This Chinese-language excerpt summarizes a report about automatically generating trading strategies from time-series data. It frames conventional factor research, factor combinations, and rule combinations as labor-intensive manual work, then proposes using…

StatistikkFaktorinvesteringRisikostyring
MQL5 code base

This indicator description is based on a method attributed to Markos Katsanos and a 2018 magazine article. It describes average penetration bars and adds configurable choices for how penetration is measured: the original method uses closing prices, while…

Tekniske indikatorerTrendfølgende handelAksjer
SuperMind

This A-share stock screen combines three technical conditions: a 14-period RSI below 65, MACD above its zero line, and a rising 30-day moving average. The stated rationale is to find stocks with moderate momentum and an upward price trend. The article also…

AksjerKinesiske markederTekniske indikatorerMomentum
BigQuant

This document summarizes a research paper on factor timing, connecting it to market timing and factor investing. Its theoretical starting point is that an optimal portfolio corresponds to the stochastic discount factor (SDF). Under a conditional factor model…

FaktorinvesteringPorteføljekonstruksjonStatistikk
MQL5 code base

This document describes an indicator for detecting harmonic chart patterns. These patterns use five price turning points and constraints on their relative proportions, which can be difficult to assess consistently by eye. The tool uses a ZigZag indicator to…

Tekniske indikatorerMarkedsmikrostrukturRisikostyring
SuperMind

This post describes a stock-selection rule focused on the metaverse sector. It screens for positive returns and prior-day auction turnover above a stated threshold, then proposes adding a positive return over the preceding six months. The rationale is that…

AksjerKinesiske markederMomentumTekniske indikatorer
SuperMind

This post outlines an A-share stock screen combining a metaverse-sector classification, positive recent returns, and positive auction turnover. It proposes an additional six-month positive-return filter, and later suggests valuation and trend conditions such…

AksjerKinesiske markederMomentumTekniske indikatorer