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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
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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
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
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

BigQuant

This tutorial introduces Apache Arrow as a columnar format for in-memory computing and PyArrow as its Python interface, with integration for pandas, NumPy, and native Python objects. It demonstrates creating an Arrow scalar, converting a pandas DataFrame…

Statistikk
SuperMind

This A-share screening rule combines a daily high-low range greater than 1%, a newly formed KDJ crossover, and positive main-fund net inflow on the prior day. The post presents the range condition as a way to find volatile stocks, the crossover as a possible…

AksjerKinesiske markederTekniske indikatorerMomentum
ProRealCode

The document describes a three-candle Popgun pattern: an inside candle is enclosed by two outside candles. It uses the direction of the second outside candle to choose long or short bias, then treats a break beyond that candle’s high or low within the next…

KursbruddTekniske indikatorerTrendfølgende handelHistorisk testing
SuperMind

This A-share screening concept selects stocks with at least five converging moving averages, ranks them by individual-stock “heat,” and requires at least two limit-up sessions within the prior 500 days. The accompanying explanation interprets the…

AksjerKinesiske markederTekniske indikatorerMomentum
SuperMind

This proposed A-share screen combines three conditions: at least five moving averages converge, the opening price is near the 10-day average, and the stock has hit the daily limit at least twice in the past 500 days. The accompanying rationale treats average…

AksjerKinesiske markederTekniske indikatorerMomentum
Amberdata research

This market snapshot reviews several digital-asset areas: centralized exchange share, spot price moves, futures long-short ratios, DeFi lending activity, and blockchain transaction patterns. It describes Binance losing exchange-volume share after regulatory…

KryptoSpotmarkederEvigvarende futuresDeFi
FinRL

This tutorial demonstrates a graph convolutional policy, GPM, inside a reinforcement-learning portfolio workflow. It loads historical stock features and a sector and industry graph, then reduces the graph to nodes within two hops of the selected portfolio…

AksjerPorteføljekonstruksjonMaskinlæringHistorisk testing
SuperMind

This stock-selection note describes a Chinese equities screen that combines three signals: membership in the metaverse theme, positive net buying by major participants during the opening auction, and an increase in the KDJ K value. It interprets these as a…

AksjerKinesiske markederTekniske indikatorerMomentum
SuperMind

The document outlines a Chinese A-share stock screen centered on a metaverse industry classification, elevated recent turnover, share prices above a stated threshold, larger market capitalization, and return on equity. It first presents a simpler theme,…

Kinesiske markederAksjerMomentumFaktorinvestering
MQL5 code base

This short description presents a simplified indicator based on the 14-period Average Directional Index (ADX) and its positive and negative directional components. It says the relative position of the positive component, negative component, and main ADX line…

Tekniske indikatorerTrendfølgende handel
MQL5 code base

The document introduces the VIX as an options-derived measure of expected volatility over roughly the next 30 days, then describes the idea of adapting a similar measure to markets beyond the major US stock indexes. It names possible applications such as…

VolatilitetTekniske indikatorerFlere aktivaklasser
SuperMind

This post outlines a Chinese equity selection idea that ranks stocks by capital-flow strength, choosing the top 100, and filters for an opening-stage price rise below 6% at 9:25. It associates strong flow rankings with market attention and treats a limited…

Kinesiske markederAksjerMarkedsmikrostrukturMomentum
SuperMind

This post describes a short-term Chinese equity screen using RSI below 65, an outside-volume to inside-volume ratio above 1.3, and a share-price filter. Although the headline mentions a specific price, the body shifts to a range: its example uses prices from…

Kinesiske markederAksjerTekniske indikatorerMarkedsmikrostruktur
SuperMind

This post proposes screening Chinese equities for daily price amplitude above 1, return on equity above 15% for five consecutive years, and a rounded price pattern. It presents the combination as a way to pair a volatility condition with sustained…

Kinesiske markederAksjerTekniske indikatorerFaktorinvestering
SuperMind

This Chinese-language post outlines a stock selection rule using price amplitude, relative trading volume, and return on equity. It specifies amplitude above 1%, a volume ratio between 1.5 and 6, and ROE above 15% in each of the past five years. The intended…

AksjerKinesiske markederVolatilitetFaktorinvestering
SuperMind

This Chinese-language post describes an A-share stock screen combining price amplitude, a 2019 dividend yield threshold, and a range for floating market capitalization. The intended logic selects stocks with amplitude above 1, dividend yield above 25%, and…

AksjerKinesiske markederVolatilitetFaktorinvestering
Cryptohopper blog

The article explains how to estimate gains from cryptocurrency investments, trades, fiat conversions, and mining. Its basic method subtracts acquisition cost from sale proceeds to find gross profit, then deducts transaction and other costs—such as exchange…

KryptoSpotmarkederRisikostyringStatistikk
BigQuant

This BigQuant platform report investigates Beijing Stock Exchange records in the Chinese stock factors table and how they interact with a basic stock-selection query. The author queries instruments with the Beijing suffix for a single date and reports 249…

Kinesiske markederAksjerStatistikkHistorisk testing
MQL5 code base

This indicator description presents a TRIX variation that uses Wilder-style double exponential smoothing and floating signal levels. It offers three possible ways to mark changes on a chart: crossing the outer levels, crossing a dynamic middle or zero level,…

Tekniske indikatorerMomentumHistorisk testing
MQL5 code base

This brief script description outlines a tool for estimating the margin needed to open a trade at a specified volume. It also says the tool calculates the maximum number of lots that can be traded for a chosen symbol. The only example identified is CADJPY…

ValutahandelPosisjonsstørrelseRisikostyring
SuperMind

This Chinese stock-screening note combines a large-order net-flow ranking with a moving-average trend filter. It proposes ranking stocks by large-order net volume, treated as a measure of buying pressure, and keeping those whose 20-day moving average is…

Kinesiske markederAksjerTekniske indikatorerMomentum
MQL5 code base

This indicator description explains pivot-point analysis as a way to derive potential support and resistance levels from the prior period’s high, low, and pivot. The first support and resistance levels use the distance between the pivot and the corresponding…

Tekniske indikatorerAksjer
BigQuant

This factor-monitoring summary compares Chinese equity signals over weekly, monthly, year-to-date, and one-year windows. It reports rankings for long-only absolute returns, long-short returns, information ratios, and relative strength. The factors discussed…

AksjerKinesiske markederFaktorinvesteringStatistikk
SuperMind

This post describes a stock screen for main-board shares that combines a daily turnover-rate band of 3% to 12%, a circulating market value between 5 billion and 10 billion yuan, and an additional company-type criterion chosen by the user. It gives equivalent…

AksjerKinesiske markederStatistikk