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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
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

MQL5 code base

This brief description introduces an expert advisor built around two moving averages. It pairs their signals with a trailing stop, which adjusts the exit level as a position moves favorably. The document credits one person with the trading idea and another…

Tekniske indikatorerTrendfølgende handelRisikostyring
MQL5 code base

This indicator classifies closes by their relationship to the previous bar and tracks the length of each resulting sequence. It describes internal closes as closes within the prior bar’s range, which may reflect sideways or slowly drifting price action; a…

Tekniske indikatorerTrendfølgende handelRisikostyring
BigQuant

This forum post describes a reproducibility question in a quantitative modeling workflow. The author sets a learning-rate parameter to the same value in the model and in a hyperparameter-search module, and configures the search grid to contain only that…

MaskinlæringStatistikkHistorisk testing
SuperMind

This document proposes a Chinese stock-selection screen focused on companies associated with the robotics theme. Its initial criteria are daily amplitude above 1%, circulating market capitalization below 10 billion yuan, and return on equity above 15% in…

AksjerKinesiske markederFaktorinvesteringRisikostyring
SuperMind

This document describes a short-term A-share stock screen that excludes Beijing-listed shares, selects stocks with turnover between 3% and 12%, and looks for upward ordering of five moving averages, from the 5-day through the 120-day average. It explains the…

AksjerKinesiske markederTekniske indikatorerTrendfølgende handel
SuperMind

The proposed stock screen combines three signals: daily amplitude above one percent, a reversal or engulfing-style pattern appearing within the recent three-session window, and pre-open auction buying volume from large and very large orders above seven…

AksjerKinesiske markederTekniske indikatorerMarkedsmikrostruktur
SuperMind

This proposed A-share screen selects stocks whose turnover rate is between three and twelve percent, whose codes begin with 60, and whose previous-day turnover exceeds eight percent. The code example retrieves daily basic data, applies these filters, then…

AksjerKinesiske markederMarkedsmikrostrukturMarkedssentiment
SuperMind

This A-share stock screen combines three conditions: daily high-low amplitude above one percent, a closing price of 18.5 yuan, and the 20-day moving average above the 120-day moving average. The moving-average comparison is intended to select stocks with a…

AksjerKinesiske markederTekniske indikatorerTrendfølgende handel
SuperMind

This post describes a stock-selection screen that combines daily price amplitude above 1, at least one limit-up event during the prior month, and a 2019 dividend ratio above 25%. It frames the conditions as a blend of price movement, recent market attention,…

AksjerMomentumHendelsesdrevet handelHistorisk testing
SuperMind

This proposed stock screen combines elevated price movement with a sector-related condition. It looks for amplitude above 1%, at least one daily gain of 10% or more during the preceding 25 trading days, and a link to beverage or alcohol imports and exports.…

AksjerMomentumVolatilitetKinesiske markeder
SuperMind

This stock screen combines three conditions: daily high-to-low amplitude above 1%, a dividend yield associated with 2019 above 25%, and a rising K value in the KDJ oscillator. The accompanying examples describe calculating amplitude from high, low, and open…

AksjerTekniske indikatorerFaktorinvesteringKinesiske markeder
MQL5 code base

The document introduces an indicator that changes the spacing of price bands according to price’s position relative to a central average. Conventional bands are described as symmetric around that average, which can leave the band on the opposite side far…

Tekniske indikatorerKursbruddTrendfølgende handel
ProRealCode

This proposed EUR/USD strategy on an hourly chart looks for a sharp move through a Bollinger Band followed by a close beyond the opposite band. The long setup also requires the positive directional indicator to exceed the negative one, while the short setup…

ValutahandelTekniske indikatorerTilbakevending mot gjennomsnittetRisikostyring
BigQuant

The document explains sliced inverse regression (SIR) as a supervised dimension-reduction method for financial prediction. Unlike principal component analysis, which summarizes variation in predictors without using the target, SIR uses the forecast variable…

AksjerStatistikkFaktorinvesteringPorteføljekonstruksjon
SuperMind

This stock-selection proposal combines volatility and momentum conditions to find Chinese equities with pronounced price movement. Its initial screen looks for an amplitude threshold, at least one daily gain of 10% or more during the recent 25 trading days,…

AksjerKinesiske markederMomentumKursbrudd
FMZ forum

This introductory explanation presents support vector machines as supervised classification models. In a simple two-class example, many lines can separate the data, but SVM selects a boundary that maximizes the margin between the two classes. The closest…

MaskinlæringStatistikk
SuperMind

This Chinese A-share screening idea selects stocks with a daily high-low range above 1%, a newly formed KDJ crossover, and a concentration measure below 70%. The post interprets a wide range as elevated volatility and the crossover as improving market…

AksjerKinesiske markederTekniske indikatorerMomentum
SuperMind

This proposed Chinese equity screen combines three filters: daily turnover between 3% and 12%, an appearance on the previous day’s 龙虎榜 (a list highlighting unusual trading activity), and external volume exceeding internal volume by a ratio above 1.3. The…

AksjerKinesiske markederTekniske indikatorerMarkedssentiment
Amberdata research

The article explains how data supports several spot Bitcoin ETF functions: calculating net asset value (NAV) and intraday indicative value, checking reserves, and helping authorized participants trade around price deviations. Because Bitcoin trades…

KryptoSpotmarkederOn-chain-dataArbitrasje
SuperMind

The document describes a daily Chinese-equity stock screen combining price action, trading activity, market capitalization, and profitability. The proposed filters require an intraday range above 1% relative to the prior close, market capitalization below 10…

AksjerKinesiske markederTekniske indikatorerStatistikk
MQL5 code base

This Expert Advisor combines a random-number gate with a moving-average price relationship to decide whether to open a position. The random draw is compared with one of eight thresholds represented by poker-hand labels; if it falls below the selected…

FuturesTekniske indikatorerStatistikkHistorisk testing
OctoBot

The document introduces spot trading as buying or selling cryptocurrency at the current market price, where the trader transacts in the asset rather than a futures or options contract. It outlines basic setup: choose an exchange that lists the desired pair,…

KryptoSpotmarkederOrdreutførelseRisikostyring
BigQuant

This overview surveys models used to relate asset values or expected returns to risk and other inputs. It describes CAPM as linking expected return to the risk-free rate and market exposure, then introduces multifactor models such as Fama–French, which add…

Flere aktivaklasserFaktorinvesteringPrising av derivaterRentepapirer