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Zināšanu bibliotēka

Stratmill pētniecības aģenta sagatavoti kopsavilkumi un galvenās atziņas par grāmatām, pētījumiem, rakstiem un kodu, ko lasa mūsu MI aģenti. Katrā lapā ir saite uz oriģinālu.

Quant Q&A
Dokumentu skaits: 20,364
SuperMind
Dokumentu skaits: 12,226
OKX Learn
Dokumentu skaits: 8,431
Strategy library
Dokumentu skaits: 7,910
MQL5 code base
Dokumentu skaits: 7,090
BigQuant
Dokumentu skaits: 3,481
Bitget Academy
Dokumentu skaits: 3,298
MQL5 articles
Dokumentu skaits: 3,012
TradingView scripts
Dokumentu skaits: 1,976
ProRealCode
Dokumentu skaits: 1,507
Deribit Insights
Dokumentu skaits: 1,232
Machine Learning for Trading
Dokumentu skaits: 1,124
arXiv papers
Dokumentu skaits: 1,033
Amberdata research
Dokumentu skaits: 766
FMZ forum
Dokumentu skaits: 682
FMZ digest
Dokumentu skaits: 662
vn.py community
Dokumentu skaits: 560
QuantInsti blog
Dokumentu skaits: 511
Galaxy Research
Dokumentu skaits: 340
QuantStart
Dokumentu skaits: 246
Stratmill research code
Dokumentu skaits: 219
Robot Wealth
Dokumentu skaits: 195
NautilusTrader
Dokumentu skaits: 191
Hummingbot docs
Dokumentu skaits: 181
Paradigm research
Dokumentu skaits: 175
Lumibot
Dokumentu skaits: 164
Kraken Learn
Dokumentu skaits: 163
Kvantitatīvās tirdzniecības kursu bibliotēka
Dokumentu skaits: 157
OctoBot
Dokumentu skaits: 152
Cryptohopper blog
Dokumentu skaits: 144
Systematic trading blog (Rob Carver)
Dokumentu skaits: 132
Qlib
Dokumentu skaits: 116
TqSdk
Dokumentu skaits: 86
Quantpedia
Dokumentu skaits: 86
Hyperliquid docs
Dokumentu skaits: 79
Freqtrade
Dokumentu skaits: 68
Hudson & Thames
Dokumentu skaits: 62
Awesome Systematic Trading
Dokumentu skaits: 61
backtrader
Dokumentu skaits: 54
vn.py
Dokumentu skaits: 50
Binance API docs
Dokumentu skaits: 45
Quantopian lekcijas
Dokumentu skaits: 45
FMZ guides
Dokumentu skaits: 38
pysystemtrade
Dokumentu skaits: 34
Freqtrade docs
Dokumentu skaits: 32
quant-trading
Dokumentu skaits: 31
FinRL
Dokumentu skaits: 28
Zipline
Dokumentu skaits: 22
FMZ live strategies
Dokumentu skaits: 21
Jesse
Dokumentu skaits: 17
pyfolio
Dokumentu skaits: 16
Alphalens
Dokumentu skaits: 14
WonderTrader
Dokumentu skaits: 14
backtesting.py
Dokumentu skaits: 11
Technical Analysis
Dokumentu skaits: 9
QTPyLib
Dokumentu skaits: 8
QuantRocket
Dokumentu skaits: 7
Lumibot strategies
Dokumentu skaits: 7
Awesome Quant
Dokumentu skaits: 1

Meklēt bibliotēkā

Dokumentu skaits: 79,386

MQL5 code base

The document presents a small open-source shield intended to check trading against prop firm account limits. Its usage outline initializes the tool with account balance and a firm profile, then updates it with equity and balance information on each tick.…

Riska pārvaldībaPozīcijas apjoma noteikšana
vn.py

The document introduces VeighNa, an open-source Python framework for quantitative trading, with particular attention to its vnpy.alpha module. That module organizes research into feature creation, model training, strategy development, and workflow…

MašīnmācīšanāsFaktoru ieguldīšanaVēsturisko datu pārbaudeVairāku aktīvu tirdzniecība
MQL5 code base

This brief description presents a higher-timeframe variant of the ColorMFI_X20_Cloud indicator. Its key feature is a configurable timeframe input, with a four-hour period shown as the default. The indicator can therefore calculate using a period different…

Tehniskie indikatoriAugstas frekvences tirdzniecība
SuperMind

This note outlines a Chinese equity screen for metaverse-themed stocks. It combines a relationship to the five-day moving average with three consecutive sessions in which the close is below the open. The article interprets the moving-average condition as a…

AkcijasTehniskie indikatoriĶīnas tirgi
SuperMind

This note describes a simple Chinese equity screen combining metaverse-theme membership, a close above the previous session’s low, and a closing price fixed at 18.5 yuan. It presents the prior-low comparison as a short-term price-strength condition and…

AkcijasTehniskie indikatoriĶīnas tirgi
BigQuant

This guide presents a relative strength index strategy using overbought and oversold thresholds. It describes calculating RSI from rolling average gains and losses, generating short signals above 70 and long signals below 30, and optionally filtering trades…

Tehniskie indikatoriAtgriešanās pie vidējās vērtībasVēsturisko datu pārbaudeRiska pārvaldība
SuperMind

This note describes a stock-selection screen for Chinese equities that keeps stocks with turnover between 3% and 12%, excludes Beijing-listed shares, and ranks candidates by a money-flow strength measure. Its formula reference relates the strength measure to…

AkcijasĶīnas tirgiTirgus noskaņojumsTirgus mikrostruktūra
SuperMind

This note outlines an A-share stock screen combining metaverse sector membership, a rounded or arc-shaped price pattern, and return on equity above 15% for five consecutive years. It then adds a monthly five-period moving average crossing above the…

AkcijasĶīnas tirgiTehniskie indikatoriFaktoru ieguldīšana
SuperMind

The proposed screen combines three stock characteristics: price amplitude above one, a circulating share count no greater than 5.5 billion, and a 20-day concentration measure below 70%. The article presents the amplitude condition as a way to find more…

AkcijasĶīnas tirgiTehniskie indikatoriSvārstīgums
SuperMind

This screen focuses on stocks classified in the metaverse industry. It selects the five highest-ranked by the day's opening auction amount and requires the 30-day moving average to be above the 60-day moving average, using the relationship as a basic trend…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

The article proposes screening Chinese stocks using price amplitude, company quality, and performance tied to 2021. Its expanded version adds valuation and fundamental comparisons, allows technical indicators such as KDJ, RSI, or MACD, and suggests…

AkcijasĶīnas tirgiTehniskie indikatoriFaktoru ieguldīšana
SuperMind

This stock screen combines three signals: rank stocks by money-flow strength, require weekly MACD to be above zero, and look for shrinking negative MACD histogram bars on a 15-minute chart. The weekly condition is intended to favor stocks in an established…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
BigQuant

This summary describes a method for constructing broad stock factor exposures and checking factor usefulness in a multifactor model. It presents returns as a linear combination of factor contributions plus an unexplained residual, and emphasizes examining…

AkcijasFaktoru ieguldīšanaStatistikaPortfeļa veidošana
vn.py community

This short forum exchange addresses whether users can add their own trading strategies to the VeighNa community edition. A user with little programming experience asks how to implement a strategy already used by a friend. The reply says custom development is…

Nākotnes līgumiRīkojumu izpilde
SuperMind

The document proposes a stock screen combining three criteria: recent price amplitude above a stated threshold, circulating market capitalization above a stated level, and a stock code beginning with 60. It frames the screen as a way to find larger,…

AkcijasĶīnas tirgiSvārstīgumsTehniskie indikatori
MQL5 code base

This document outlines a simple Expert Advisor that evaluates a pivot derived from the prior bar’s high and low. It describes opening trades from the relationship between the current bar’s open, the prior high, and the pivot, then comparing successive pivots…

Valūtu tirgusTehniskie indikatoriAtgriešanās pie vidējās vērtības
Amberdata research

This beginner-oriented guide recommends planning trades in advance, researching assets before buying, and avoiding impulsive decisions driven by hype or fear of missing out. It advocates diversification across crypto assets, monitoring Bitcoin as a possible…

KriptoaktīviRiska pārvaldībaPozīcijas apjoma noteikšanaTehniskie indikatori
Amberdata research

This weekly crypto market report assesses a recovery in prices by combining spot performance with trading volume, volatility, open interest, funding, order book depth, ETF flows, stablecoin issuance, and DeFi credit measures. It interprets rising prices…

KriptoaktīviSvārstīgumsTirgus mikrostruktūraTirgus noskaņojums
MQL5 code base

This document describes a market sentiment indicator that classifies conditions as bullish or bearish using limit order book data on centralized markets. Its inputs include minimum qualifying order volume, minimum order count, and thresholds for differences…

Tirgus noskaņojumsTirgus mikrostruktūraNākotnes līgumiTehniskie indikatori
SuperMind

This A-share stock-selection proposal combines three conditions: RSI below 65, year-over-year growth in net profit attributable to parent-company shareholders within a stated positive range, and a recent two-day high condition. It presents the combination as…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
BigQuant

This research report proposes improving a conventional stock reversal signal by splitting each stock’s recent daily returns according to average trade size. For each lookback window, it ranks days by daily turnover divided by trade count, compounds returns…

AkcijasAtgriešanās pie vidējās vērtībasFaktoru ieguldīšanaTirgus mikrostruktūra
SuperMind

This Chinese A-share screening proposal combines a technical filter, a trading-flow condition, and a turnover range. It selects stocks with RSI below 65, positive multiplication of price change by net flow from very large orders, and turnover above 2% but…

AkcijasTehniskie indikatoriTirgus mikrostruktūraĶīnas tirgi
MQL5 code base

This brief description presents a standard ZigZag indicator supplemented with support and resistance levels. ZigZag marks selected price swings, while the added levels provide a way to view potential areas where price may encounter support or resistance. The…

Tehniskie indikatori
SuperMind

This proposed Chinese equity screen combines three conditions: the stock's intraday high-low range exceeds one percent of its closing price, the prior session was not limit-up, and the article's external-to-internal trading measure exceeds 1.3. The author…

AkcijasTehniskie indikatoriCenas impulssRiska pārvaldība