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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
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
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FinRL
28 dokumenter
Zipline
22 dokumenter
FMZ live strategies
21 dokumenter
Jesse
17 dokumenter
pyfolio
16 dokumenter
WonderTrader
14 dokumenter
Alphalens
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 A-share screening idea selects stocks whose intraday high-low range exceeds 1%, whose day low is between 4% and 5% below the prior close, and whose MACD is above zero. The rationale combines elevated volatility and a sharp intraday decline with…

AksjerTekniske indikatorerVolatilitetTilbakevending mot gjennomsnittet
SuperMind

This proposed stock screen selects shares with a daily high-low range above 1, three consecutive limit-up sessions as of the previous day, and at least two limit-up events during the prior 500 days. The post interprets the range as a sign of activity and the…

AksjerKinesiske markederMomentumKursbrudd
SuperMind

This proposed Chinese stock screen looks for a daily price range above 1, a ratio between 0.5 and 2 formed from the previous day’s turnover rate and the current auction volume relative to the previous day’s volume, and a current large-order accumulation…

AksjerKinesiske markederMarkedsmikrostrukturTekniske indikatorer
SuperMind

This Chinese stock screen combines a positive MACD reading, an external-to-internal trading volume ratio above 1.3, and more than two limit-up days in the prior ten days. It ranks qualifying stocks by percentage gain, favoring recent price strength and…

AksjerKinesiske markederMomentumTekniske indikatorer
MQL5 code base

This document describes an example of a multicurrency Expert Advisor that processes symbols one at a time in a loop. It uses a timer event to run trading logic independently of ticks arriving for any particular symbol, and Bollinger Band values provide the…

ValutahandelTekniske indikatorerOrdreutførelse
SuperMind

This example turns a CAPM regression into a monthly stock-selection process. It takes a recent window of daily returns for eligible constituents, adjusts stock and benchmark returns by a stated daily risk-free rate, and regresses each stock’s returns against…

AksjerStatistikkFaktorinvesteringHistorisk testing
BigQuant

This brief coding question outlines a way to calculate fund performance statistics from a price series. It first derives periodic returns from price changes, then uses a performance-analysis library to compute cumulative return, annualized return, Sharpe…

StatistikkRisikostyringVolatilitet
SuperMind

This screening proposal combines three conditions: price amplitude above one, a value for today’s control measure above 21, and a date in or after 2021. The description frames the first two conditions as filters for more volatile stocks and stocks with…

AksjerKinesiske markederTekniske indikatorerRisikostyring
SuperMind

This stock-screening proposal targets companies in the metaverse industry that have had more than two limit-up sessions in the recent ten-day window and have just formed a KDJ golden cross. It calls for screening before 10:00 on each trading day and…

AksjerKinesiske markederMomentumTekniske indikatorer
BigQuant

The document summarizes CapTE, a model for predicting stock movements from social media text. A Transformer encoder extracts semantic features from posts, while a capsule network is used to represent structural relationships in the text. The approach is…

AksjerMaskinlæringMarkedssentimentStatistikk
BigQuant

This short platform discussion explains that an adjust factor is used to convert a stock’s real price into an adjusted price. Adjusted prices, including forward- and backward-adjusted series, are intended to keep price charts continuous across corporate…

AksjerHistorisk testing
SuperMind

This Chinese stock-screening post describes a rule based on price range, recent turnover, and limit-up frequency. Its initial description calls for an amplitude above 1, prior-day actual turnover between 3% and 28%, and more than two limit-up sessions in a…

AksjerTekniske indikatorerMomentumKinesiske markeder
BigQuant

This short forum exchange explains how to configure BigQuant’s trading engine to rebalance on a weekly or monthly schedule. For weekly scheduling, it specifies the weekly trading-day mode and a day value of 5; for monthly scheduling, it specifies the monthly…

PorteføljekonstruksjonHistorisk testingOrdreutførelse
SuperMind

This stock-screening rule selects shares with turnover between 3% and 12%, a seven-day falling-price pattern, and no limit-up session on the previous day. The document gives both a platform-style condition and a Python example, and explains the intended…

AksjerTekniske indikatorerMomentumKinesiske markeder
Qlib

The document introduces Temporal Routing Adaptor (TRA), a model designed to learn multiple trading patterns from stock market data. It describes using TRA with Qlib datasets and workflows, and notes that the paper’s reproduction setup first trains a backbone…

AksjerMaskinlæringHistorisk testingStatistikk
SuperMind

This Chinese equity screen combines price amplitude above one, appearance on the previous day’s market top list, and a positive price-to-earnings ratio. The article interprets amplitude as a sign of short-term volatility, top-list inclusion as a possible…

AksjerVolatilitetHendelsesdrevet handelKinesiske markeder
SuperMind

This Chinese equity screen looks for stocks with price amplitude above one, an opening price near the ten-day moving average, and simultaneous bullish crossover signals from three indicators. The examples use MACD, RSI, and KDJ: MACD and KDJ cross above…

AksjerTekniske indikatorerMomentumKinesiske markeder
SuperMind

This article introduces the autoregressive moving-average model as a combination of AR terms, which use past observations, and MA terms, which represent past shocks. It describes choosing the orders p and q with autocorrelation and partial autocorrelation…

StatistikkVolatilitet
SuperMind

This stock screen combines three conditions: net buying today must exceed five percent, the previous day’s turnover must be above 60 million, and the ten-day price gain must be positive but below 35 percent. The document presents these as signs of buying…

AksjerMomentumKinesiske markeder
MQL5 code base

The document describes an Expert Advisor that trades when the i-KlPrice histogram crosses an overbought or oversold level. A signal is confirmed at bar close, so the strategy acts on completed-bar threshold breaks rather than intrabar movement. The advisor…

Tekniske indikatorerValutahandelHistorisk testing
MQL5 code base

The document explains that MetaTrader 5 exposes generic, loss-side, and profit-side tick values for each symbol, and that these values may not be identical. This matters when an expert advisor calculates trade size from a risk budget: using a tick value that…

RisikostyringPosisjonsstørrelseValutahandel
BigQuant

The document summarizes a study that develops a probabilistic classifier to identify high-frequency trading activity from intraday order data. Using French BEDOFIH market records, the researchers engineered features describing orders, including their prices,…

HøyfrekvenshandelMaskinlæringStatistikkMarkedsmikrostruktur
FMZ forum

The document describes three high-frequency trading approaches through an example in which an institution splits a large stock order into smaller child orders. Liquidity rebate trading detects likely follow-on orders and provides liquidity to earn exchange…

HøyfrekvenshandelMarkedsmikrostrukturOrdreutførelseMarket making
SuperMind

The document proposes a Chinese equity screening approach that selects robot concept stocks with daily amplitude above 1%, float capitalization below 10 billion, and no ST designation. It specifies screening before 10 a.m. and says a five-step limit-up…

Kinesiske markederAksjerTekniske indikatorerFaktorinvestering