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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

Stratmill research code

The distance approach forms pairs by rescaling each asset’s training-period prices to a common range, calculating the sum of squared differences between each pair’s normalized series, and selecting the closest matches. In the cited original study, the…

ParhandelTilbakevending mot gjennomsnittetArbitrasjeStatistikk
OctoBot

This guide introduces statistical learning through an example of predicting the S&P 500 from company fundamentals. It frames the task as estimating a response from predictor features plus residual error, then distinguishes prediction, which prioritizes…

MaskinlæringStatistikkAksjer
SuperMind

This note describes a Chinese equity screen that combines a turnover band of 3% to 12%, a rising DEA condition, and a prior-day closing price of 18.5 yuan. It provides a platform formula and a Python-oriented example, both intended to identify stocks meeting…

AksjerTekniske indikatorerMomentum
SuperMind

The document proposes screening Chinese equities for price amplitude above a threshold, a high daily control measure, and at least five overlapping or aligned moving averages. It presents this as a technical filter intended to narrow the universe, then…

Kinesiske markederAksjerTekniske indikatorerRisikostyring
MQL5 code base

This document outlines a simple foreign exchange Expert Advisor built around Williams Percent Range (WPR). It sells when the oscillator crosses downward through an overbought level and buys when it crosses upward through an oversold level. The signal is…

ValutahandelTekniske indikatorerHistorisk testingRisikostyring
MQL5 code base

The document describes a script that writes closing prices for all symbols available on a trading platform to a CSV file. The user can choose the output filename and select which bar’s close to export, making the script a basic way to collect a cross-section…

Historisk testingStatistikk
BigQuant

This report overview surveys supervised learning methods with potential uses in investment research. For regression, it distinguishes penalized models such as Lasso, ridge, and elastic net, which can address correlated inputs, from nonparametric approaches…

MaskinlæringStatistikkAksjerHistorisk testing
SuperMind

This Chinese-language post outlines an A-share screening idea focused on metaverse stocks. Its initial filters are prior-day turnover above 8% and a measure intended to identify afternoon large-order net inflows. The author discusses dependence on…

AksjerKinesiske markederMarkedssentimentTekniske indikatorer
vn.py community

This short forum exchange distinguishes callbacks triggered by incoming tick data from callbacks that run when a bar has been completed. It says the ordinary bar callback runs when a tick marks a new minute, while window-bar callbacks run when the aggregated…

OrdreutførelseMarkedsmikrostruktur
Amberdata research

This weekly market note connects Federal Reserve expectations and US economic releases with crypto and equity volatility. It argues that rates and inflation data could influence risk assets, then compares Bitcoin and gold implied volatility as a way to frame…

KryptoOpsjonerVolatilitetPrising av derivater
MQL5 code base

The Random Walk Index (RWI) is presented as a way to assess whether price movement is more consistent with a statistically meaningful trend or with random, choppy behavior. It compares observed price ranges over a chosen period with a range expected under a…

Tekniske indikatorerStatistikkTrendfølgende handel
MQL5 code base

DI Cluster overlays three versions of an ADX-family indicator calculated with separate periods. Rather than applying fixed threshold levels, it uses intersections among the three lines to define changing reference points. The display can show the ADX…

Tekniske indikatorerTrendfølgende handelStatistikk
SuperMind

This note presents an equity screen combining turnover between 3% and 12%, seven consecutive non-rising closes, and a positive daily MACD reading. It frames the setup as a way to identify stocks that have recently weakened while retaining a positive trend…

AksjerTekniske indikatorerMomentumStatistikk
SuperMind

This note describes a short-term A-share screening rule for stocks classified in the metaverse industry. It looks for an opening price crossing above the 10-day moving average after the previous close and open were below that average, along with a daily…

AksjerTekniske indikatorerVolatilitetRisikostyring
SuperMind

This post describes a Chinese equity selection rule that combines an amplitude threshold, a morning-star style candlestick condition, and an estimate of prior-day dominant capital control. The accompanying implementation sketch adds moving-average alignment…

AksjerKinesiske markederTekniske indikatorerMomentum
SuperMind

The document proposes a short-term Chinese equity screen combining an amplitude threshold, a 15-minute MACD histogram that is negative but contracting, exclusion of special-treatment stocks, an early-morning selection time, and a limit-up pattern referred to…

AksjerKinesiske markederTekniske indikatorerMomentum
SuperMind

This stock screen selects shares with turnover between 3% and 12%, a positive product of daily price change and net large-order flow, and a bullish alignment among three moving averages. The accompanying example uses the 5-, 10-, and 20-day averages,…

Kinesiske markederAksjerTekniske indikatorerMomentum
SuperMind

This stock-selection idea combines three conditions: an amplitude measure above a stated threshold, a rising price bottom, and shortening green bars in the 15-minute MACD histogram. The article frames amplitude and rising lows as ways to identify active…

Kinesiske markederAksjerTekniske indikatorerMomentum
MQL5 code base

The document describes an automated strategy that places buy-stop and sell-stop orders around the current price. It uses a configurable initial distance and checks the spread before placing orders; if the spread is above a set limit, it skips placement. The…

OrdreutførelseRisikostyringHistorisk testingKursbrudd
SuperMind

This A-share screening idea selects stocks whose daily high-to-low range exceeds 1% of the opening price, whose codes begin with 60, and which appeared on the prior day’s top-trader list. The example code further filters for stocks near the upper end of…

AksjerKinesiske markederVolatilitetTekniske indikatorer
SuperMind

This Chinese A-share screening proposal combines a metaverse industry filter and a custom arc-shaped price pattern with positive auction-period price change and large plus extra-large buy orders above 70 million yuan. Its refined version adds average…

AksjerKinesiske markederTekniske indikatorerMarkedsmikrostruktur
MQL5 code base

This document describes a MetaTrader 5 indicator that adds a timeframe input to an average bar size indicator. The user can select a chart period, with a four-hour period shown as the default, so the indicator can present average bar size information from a…

Tekniske indikatorerStatistikk
ProRealCode

This indicator calculates a central pivot from the previous day’s high, low, and close, then derives support and resistance levels using 38.2%, 61.8%, and 100% of that day’s trading range. It displays the resulting levels for the current day, offering…

Tekniske indikatorerAksjer
vn.py community

The discussion addresses how to trade a cross-sectional, multi-factor strategy when the platform’s alpha section offers backtesting but no apparent live-trading module. The proposed workflow is to generate a CSV of the strategy’s selections each day and…

FaktorinvesteringOrdreutførelse