Hopp til innhold

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

This document introduces HftBacktest, a Rust framework for developing and running high-frequency trading and market-making strategies. Its backtesting approach replays tick-level market data and aims to model important execution effects, including feed…

HøyfrekvenshandelMarket makingMarkedsmikrostrukturHistorisk testing
SuperMind

The post presents a stock screen based on three conditions: today’s position-growth share exceeds 5%, the close is above the previous day’s low, and the 10-day return is positive but below 35%. It frames these filters as a way to find stocks with recent…

AksjerKinesiske markederMomentumTekniske indikatorer
MQL5 code base

This Expert Advisor tests a time-based breakout approach. At 15:00 Moscow time, it places a buy stop and a sell stop 100 points from the current price, with a 200-pip stop loss on each order and no take-profit target. If one order triggers, the other remains…

KursbruddOrdreutførelseRisikostyringHistorisk testing
SuperMind

This A-share screening proposal combines a 2019 dividend payout ratio above 25%, a daily gain above 1% for main-board stocks, and reported buying activity above 5%. The article interprets the dividend measure as a possible sign of business strength and the…

AksjerKinesiske markederMomentumFaktorinvestering
SuperMind

This Chinese equity screening proposal combines an intraday high-low range of at least 1%, a nonempty name for an outstanding convertible bond, and positive net buying attributed to major participants during the opening auction. The accompanying indicator…

AksjerKinesiske markederVolatilitetMarkedsmikrostruktur
SuperMind

This proposed Chinese stock screen selects companies associated with the metaverse theme, with a 14-period RSI below 65 and a positive 10-day return under 35%. The article frames RSI as a short-term sentiment gauge and the theme filter as a way to target a…

AksjerKinesiske markederTekniske indikatorerMomentum
SuperMind

This A-share screening idea combines three signals: a reported increase in buying activity above 5%, year-over-year parent-company net profit growth above 20% and no more than 100%, and a positive 10-day return below 35%. The article then proposes adding…

AksjerKinesiske markederMomentumFaktorinvestering
Freqtrade

This Freqtrade strategy defines long entries on a five-minute chart using MACD, RSI, and Bollinger Bands. It requires MACD to be above zero and its signal line, the upper Bollinger Band to be rising, and RSI to exceed 70. Long exits are triggered when RSI…

Tekniske indikatorerMomentumHistorisk testingRisikostyring
ProRealCode

The article explains an RSI divergence indicator that avoids confirmed pivots. Instead, it compares the current price and RSI with extremes from an earlier short window, then requires elevated volume and an RSI extreme before marking a bullish or bearish…

Tekniske indikatorerMomentumStatistikkHistorisk testing
Amberdata research

This report reviews 2024 activity in centralized crypto spot and derivatives markets. It describes how exchange and asset trading volumes changed through the year, noting periods of high activity across major venues and tokens. It suggests using volume…

KryptoFuturesEvigvarende futuresArbitrasje
SuperMind

This proposed A-share screen looks for stocks with RSI below 65, an external-to-internal trading volume ratio above 1.3, and no limit-up close on the previous day. The article frames the RSI threshold as a way to avoid heavily overbought stocks, treats the…

AksjerTekniske indikatorerMarkedssentimentKinesiske markeder
BigQuant

This article explains how the Fama-French model extends CAPM first with size and value factors, then with profitability and investment factors. It describes double sorts by size and book-to-market, return on equity, or asset growth, and forms RMW from…

AksjerFaktorinvesteringStatistikkKinesiske markeder
MQL5 code base

This expert-advisor design periodically searches recent price history for RSI or MFI thresholds that produced the greatest simulated monetary profit. It tests buy and sell signals separately across candidate indicator levels, using crossings of oversold and…

ValutahandelTekniske indikatorerMaskinlæringHistorisk testing
SuperMind

The proposed short-term stock screen selects shares with an amplitude above a threshold, an indicated 9:25 price gain below a cap, and an exclusion for the STAR Market. The author presents these filters as a way to combine a volatility condition, an…

AksjerKinesiske markederVolatilitetTekniske indikatorer
BigQuant

The document explains how combinatorially symmetric cross-validation (CSCV) can estimate the probability of backtest overfitting (PBO). It distinguishes training overfitting, where a model performs poorly on held-out data, from backtest overfitting, where a…

Historisk testingStatistikkMaskinlæringFaktorinvestering
MQL5 code base

BoDi measures the distance between the upper and lower Bollinger Bands and displays that width as a histogram. Because the bands widen as volatility rises and contract as it falls, the author interprets expansion as an active directional impulse and…

Tekniske indikatorerVolatilitetTrendfølgende handelKursbrudd
SuperMind

The article summarizes Burton Malkiel’s broad investing principles: use index funds, choose capable fund managers, or invest independently after analysis. For individual stock selection, it emphasizes sustained above-market earnings growth, avoiding prices…

AksjerFaktorinvesteringKinesiske markederHistorisk testing
FMZ forum

This tutorial shows how to use a strategy interface to modify and inspect a running JavaScript trading program. The strategy polls an API for a command, extracts the text after a delimiter, logs the submitted expression, and passes it to JavaScript’s eval…

Ordreutførelse
SuperMind

This post describes a historical stock screen for shares whose codes begin with 60 and whose daily high-to-low range exceeds 1% of the opening price. It restricts observations to 2021 and ranks qualifying rows using a 50-period measure based on the distance…

AksjerVolatilitetTekniske indikatorerKinesiske markeder
BigQuant

This introductory article presents ten practical points about machine learning for non-specialists. It emphasizes that machine learning finds patterns in data, so data quality, accurate labels, representative samples, and careful transformations often matter…

MaskinlæringStatistikkRisikostyring
BigQuant

The article explains how a long-only smart beta portfolio can combine equity factors to seek steadier returns than relying on one factor. It highlights value, low beta, profitability, investment, momentum, and size, arguing that their different return…

AksjerFaktorinvesteringPorteføljekonstruksjonMomentum
BigQuant

This report evaluates whether changes in listed companies’ employee compensation can help distinguish future stock returns. It compares growth in compensation payable, which represents amounts owed, with growth in compensation already paid, and also…

AksjerFaktorinvesteringKinesiske markeder
SuperMind

The document describes a technical stock screen based on daily amplitude, a price threshold, and the close relative to Bollinger Bands. Its stated criteria select stocks with amplitude above 1%, a close below 20, and a close above the middle band but no…

AksjerTekniske indikatorerKinesiske markeder