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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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Bitget Academy
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MQL5 articles
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TradingView scripts
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Deribit Insights
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Machine Learning for Trading
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arXiv papers
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Amberdata research
766 dokumenter
FMZ forum
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FMZ digest
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vn.py community
560 dokumenter
QuantInsti blog
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Galaxy Research
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QuantStart
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Stratmill research code
219 dokumenter
Robot Wealth
195 dokumenter
NautilusTrader
191 dokumenter
Hummingbot docs
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Paradigm research
175 dokumenter
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164 dokumenter
Kraken Learn
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Bibliotek for kvantkurs
157 dokumenter
OctoBot
152 dokumenter
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Systematic trading blog (Rob Carver)
132 dokumenter
Qlib
116 dokumenter
Quantpedia
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Hyperliquid docs
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Hudson & Thames
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backtrader
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vn.py
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Quantopian-forelesninger
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Binance API docs
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FMZ guides
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pysystemtrade
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Freqtrade docs
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quant-trading
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Zipline
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Jesse
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pyfolio
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backtesting.py
11 dokumenter
Technical Analysis
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QTPyLib
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QuantRocket
7 dokumenter
Lumibot strategies
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Awesome Quant
1 dokumenter

Søk i biblioteket

79,386 dokumenter

BigQuant

This report describes a fundamental equity quality framework spanning profitability, growth stability, earnings quality, cash flow, operating efficiency, and solvency. It screens factors for historical long-term return behavior, then builds a composite…

AksjerFaktorinvesteringStatistikkKinesiske markeder
BigQuant

This research summary reviews dynamic ways to allocate among equity style factors, contrasting them with static allocation and grouping methods by whether they rely on returns, risk, or both. It first builds the investable factor set: 28 underlying factors…

AksjerFaktorinvesteringPorteføljekonstruksjonRisikostyring
MQL5 code base

This document describes an Expert Advisor that trades when the Bear Bulls Power histogram changes color. It checks for a color change at bar close and uses that change as the entry signal. The page notes that the strategy depends on a separately compiled…

ValutahandelTekniske indikatorerHistorisk testing
BigQuant

The document addresses a stock-selection model whose chosen stocks and reported backtest returns change when the backtest end date is moved forward by about twenty days. The explanation is that the training data differs across the runs. A model trained on a…

AksjerMaskinlæringHistorisk testingStatistikk
MQL5 code base

The document describes a forex Expert Advisor that places market orders in one direction at fixed price intervals. A configured maximum price sets the top of the trading range; the examples show a range extending ten yen or ten cents below that level. The…

ValutahandelRutenettshandelPosisjonsstørrelseRisikostyring
MQL5 code base

The VKW_Bands_Modify indicator is described as a timing aid for placing pending orders. It draws a channel using thick pink and light green boundary lines, alongside a fast blue line from the METRO indicator. The proposed setup occurs when that fast line…

Tekniske indikatorerOrdreutførelseHistorisk testing
SuperMind

This short-term stock screen combines three filters: a prior-day price amplitude above 1%, appearance on the previous day's top-trader list, and a current-day price decline between 4% and 5%. The post presents the decline as a potential pullback entry and…

Kinesiske markederAksjerVolatilitetTekniske indikatorer
vn.py community

This post describes adapting VeighNa to use the GoldMiner market data service as a source of historical bars. It outlines the author's account of the free tier's available history, then highlights integration details: mapping bar intervals, reversing the…

FuturesAksjerOrdreutførelse
SuperMind

This stock screen combines a metaverse-sector filter with prior-day turnover above 8% and a 15-minute MACD condition intended to identify a shortening bearish histogram. The article presents the combination as a way to bring sector interest, trading…

Kinesiske markederAksjerTekniske indikatorerMomentum
BigQuant

The document raises a question about comparing backtested factors when they produce different numbers of trades. Its example contrasts one factor with 100 trades and a 2:1 profit-loss ratio against another with 1,000 trades and a 1.5:1 ratio, asking whether…

StatistikkHistorisk testing
SuperMind

The document proposes a Chinese equity screen combining three conditions: membership in the metaverse industry, an arc-shaped price pattern, and institutional flow above zero. It presents the positive flow reading as a sign of institutional buying and…

AksjerKinesiske markederTekniske indikatorer
SuperMind

This stock screen selects beverage and alcohol-related companies with turnover between 3% and 12%, then requires the current price to sit above a set of moving averages ranging from short to long horizons. The stated rationale combines an industry filter,…

AksjerMomentumTekniske indikatorerAmerikanske markeder
SuperMind

This stock-selection idea combines an amplitude threshold, a rounded price-range pattern, and a company or industry classification. The accompanying indicator expression uses recent high-low ranges over several lookback windows to identify a compressed,…

AksjerTekniske indikatorerVolatilitet
vn.py community

A trader reports that a VeighNa RiskManager configured with very low limits still allowed repeated large buy orders to execute in a SimNow simulation. The reported behavior raises a practical question about how risk controls interact with the platform’s…

RisikostyringOrdreutførelseFutures
SuperMind

This Chinese-language post presents a technical stock-selection idea combining three conditions: daily price amplitude above one, three consecutive limit-up sessions ending the previous day, and three consecutive declining sessions. It frames the conditions…

AksjerTekniske indikatorerMomentumKinesiske markeder
SuperMind

This Chinese-language post describes a simple stock screen for companies classified in the metaverse sector, with a positive recent return and market capitalization above 200 million yuan. It outlines the selection logic using sector membership, a price…

AksjerFaktorinvesteringTekniske indikatorerKinesiske markeder
Cryptohopper blog

This article explains how to combine centralized exchange market data with blockchain data through multiple Model Context Protocol servers. Exchange tools provide prices, candles, and order books; on-chain tools can reveal transfers, holders, decentralized…

KryptoOn-chain-dataMarkedsmikrostrukturOrdreutførelse
Amberdata research

This weekly crypto options analysis links macroeconomic events, including US debt ceiling negotiations, inflation data, Fed minutes, and upcoming employment figures, to Bitcoin and Ethereum volatility. It argues that the market may remain in a wait-and-see…

KryptoOpsjonerVolatilitetCarry-avkastning
BigQuant

This report describes a stock rotation strategy that seeks timely events associated with excess returns. Its event factors cover shareholder actions, dividend policies, earnings forecasts and reports, growth measures, and private placements. The strategy…

AksjerHendelsesdrevet handelFaktorinvesteringStatistikk
SuperMind

This note describes a stock screen for shares whose codes begin with 60, whose turnover rate is between 3% and 12%, and whose price gain at 9:25 is below 6%. It presents turnover as a liquidity filter and the early price move as a rough indicator of market…

AksjerKinesiske markederMarkedsmikrostrukturTekniske indikatorer
SuperMind

This note presents a China A-share screening rule for stocks classified in the metaverse sector. It selects stocks that appeared on the prior day’s trading leaderboard and whose weekly close crosses above the 30-week moving average. The proposed rationale is…

AksjerKinesiske markederTrendfølgende handelTekniske indikatorer
MQL5 code base

This document explains a MetaTrader 4 script that builds an offline chart for a user-defined basket of instruments and updates it as new ticks arrive. It calculates basket prices using a geometric mean, allows directional weights—including fractional…

Flere aktivaklasserPorteføljekonstruksjonValutahandelAksjer
SuperMind

This note describes a short-term A-share selection rule combining three filters: intraday amplitude above 1, a top-five ranking by today’s opening-auction amount, and prior-day auction turnover above 0.26. It frames the combination as a way to find stocks…

AksjerKinesiske markederTekniske indikatorerMarkedsmikrostruktur
Stratmill research code

This overview describes research on forecasting and trading commodity spreads, including gasoline crack, soybean-oil crush, and corn-ethanol crush spreads. It explains why spreads can be less exposed to market-wide information shocks and speculative bubbles…

RåvarerArbitrasjeOrdreutførelseHistorisk testing