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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
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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
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QuantInsti blog
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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
Quantopian lekcijas
Dokumentu skaits: 45
Binance API docs
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
WonderTrader
Dokumentu skaits: 14
Alphalens
Dokumentu skaits: 14
backtesting.py
Dokumentu skaits: 11
Technical Analysis
Dokumentu skaits: 9
QTPyLib
Dokumentu skaits: 8
Lumibot strategies
Dokumentu skaits: 7
QuantRocket
Dokumentu skaits: 7
Awesome Quant
Dokumentu skaits: 1

Meklēt bibliotēkā

Dokumentu skaits: 3,481

BigQuant

This proposed Chinese equity screen combines membership in the metaverse industry with a rounded price pattern and seven consecutive down sessions. The accompanying explanation frames the falling-price condition as an added technical filter intended to…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
BigQuant

This report explains how the MSCI China A50 Connect Index selects and weights large-cap Chinese equities. It chooses stocks across GICS industries, first taking leading free-float market-cap names by industry and then filling to 50 constituents; weights are…

AkcijasĶīnas tirgiFaktoru ieguldīšanaPortfeļa veidošana
BigQuant

This study examines quantitative stock selection within China’s electronics and electronic-components sectors. It reviews conventional fundamental and price-volume factors, reporting promising selection results for valuation, quarterly profit growth, return…

AkcijasFaktoru ieguldīšanaĶīnas tirgiVēsturisko datu pārbaude
BigQuant

The document introduces the Bias indicator, which expresses a closing price’s percentage deviation from its moving average over a chosen number of days. The calculation compares the close with the moving average, subtracts the average, and scales the…

Tehniskie indikatoriStatistika
BigQuant

Return on equity (ROE) measures net income relative to shareholders’ equity, expressing how much profit a company generates from its equity base. The document gives the formula and a simple numerical illustration, then describes how investors may interpret…

AkcijasFaktoru ieguldīšanaStatistikaRiska pārvaldība
BigQuant

The document describes a stock strategy that scores candidates with a neural network, buys up to three holdings, and aims to sell each after three trading days. It stores each stock and its entry-day index in a context list, then compares that index with the…

AkcijasPozīcijas apjoma noteikšanaRīkojumu izpildeVēsturisko datu pārbaude
BigQuant

This weekly report assesses Chinese equity-market sentiment after a sharp March decline and a subsequent rebound. Its composite sentiment score rose from 38 to 51, while the authors judged that near-term further weakness had become less likely, despite…

AkcijasTirgus noskaņojumsNākotnes līgumiOpcijas
BigQuant

This tutorial develops a stock factor from the sum of trading volume during the first 15 minutes of a session. It explains why opening activity may be informative: overnight news is reflected in early trading, the opening period contributes to price…

AkcijasTehniskie indikatoriFaktoru ieguldīšanaAugstas frekvences tirdzniecība
BigQuant

The discussion compares quantitative research practices in China and overseas. It says Chinese investors more often try to predict stock prices directly, while overseas researchers may estimate missing observations, factor values, company revenue, or…

MašīnmācīšanāsStatistikaAkcijasĶīnas tirgi
BigQuant

This post describes a live-order funding problem in an equities strategy. A buy signal was calculated using the previous close for 18,100 shares, while the stock opened higher and the trader submitted the order near the open using the fifth ask level. With…

AkcijasRīkojumu izpildePozīcijas apjoma noteikšanaRiska pārvaldība
BigQuant

The document addresses how to combine multiple stock-selection factors when they have different preferred directions. Its example asks how to score one factor from low to high and another from high to low, then rank securities by the average of their scores.…

AkcijasFaktoru ieguldīšanaPortfeļa veidošana
BigQuant

This brief explanation describes “doing T” in Chinese equities: using intraday buys and sells to adjust the cost basis of an existing position, despite the market’s T+1 settlement rule. It says the trader needs to keep cash available rather than invest the…

AkcijasĶīnas tirgiRežģa tirdzniecībaPozīcijas apjoma noteikšana
BigQuant

This guide outlines a workflow that combines TQ EDB market and indicator data services with Coze as a conversational research assistant. After adding the EDB skill, a researcher can describe a task and request data retrieval, idea checks, simple backtests,…

Nākotnes līgumiIzejvielasVēsturisko datu pārbaudeStatistika
BigQuant

This Chinese-language research summary describes a stock-selection factor built from quarterly profitability data. It defines a trend measure as the sensitivity of profitability to time in a linear regression, with separate versions based on…

AkcijasFaktoru ieguldīšanaStatistikaVēsturisko datu pārbaude
BigQuant

The article reviews research on the 2016 launch of Morningstar’s sustainability ratings for U.S. mutual funds. The ratings use portfolio holdings and company ESG scores to assign funds one to five stars within their categories; the star display appears more…

AkcijasStatistikaTirgus noskaņojumsUz notikumiem balstīta tirdzniecība
BigQuant

This guide recommends choosing community trading strategies according to an investor's capital, return expectations, and tolerance for drawdown. It distinguishes a conservative profile, associated with diversified holdings, a smoother equity curve, a longer…

Riska pārvaldībaVēsturisko datu pārbaudePortfeļa veidošanaPozīcijas apjoma noteikšana
BigQuant

This indicator description explains a ZigZag variant that calculates turning points from the high and low values of Heikin Ashi candles. The Heikin Ashi period is configurable, and users can choose whether the Heikin Ashi candles themselves are displayed.…

Tehniskie indikatoriSvārstīgums
BigQuant

This article examines whether financial factors such as value, size, profitability, investment, and momentum can be timed using predictive signals. It groups candidate signals into financial conditions, economic conditions, investor sentiment, factor…

Faktoru ieguldīšanaAkcijasCenas impulssTirgus noskaņojums
BigQuant

The report describes an asset allocation approach that measures cycle states and uses machine learning to estimate the probability that assets will outperform one another. It reviews macroeconomic timing frameworks, then describes cycle factors derived from…

Vairāku aktīvu tirdzniecībaMašīnmācīšanāsStatistikaPortfeļa veidošana
BigQuant

This tutorial surveys support vector machines, k-nearest neighbors, naive Bayes, and the perceptron as lightweight classifiers for relatively small datasets and feature sets. It explains SVM’s maximum-margin boundary, the role of support vectors, soft…

MašīnmācīšanāsStatistika
BigQuant

This April 2020 market note combines valuation, trading activity, sentiment, sector flows, and style factor monitoring to assess Chinese equities. It describes subdued market turnover and relatively low overall valuations, while agriculture-related stocks…

AkcijasĶīnas tirgiFaktoru ieguldīšanaCenas impulss
BigQuant

This forum question concerns adding a moving-average exit condition to an AI stock-selection backtest. The proposed logic waits until a minimum holding period has passed, then examines positions in reverse StockRanker prediction order and sells eligible…

AkcijasTehniskie indikatoriVēsturisko datu pārbaudeRīkojumu izpilde
BigQuant

The document presents a way to estimate how often a one-minute Chinese convertible-bond bar closes above its open after three consecutive up bars. It converts each bar’s return into a binary up-or-not indicator, scans the series for three up bars, and counts…

StatistikaVēsturisko datu pārbaudeTehniskie indikatoriFiksēta ienākuma instrumenti
BigQuant

This review of factor performance during the 2018–2020 quant crisis examines why diversified equity strategies struggled. It analyzes standard size, value, investment, profitability, and momentum factors, alongside portfolios formed by sorting stocks on size…

AkcijasFaktoru ieguldīšanaCenas impulssStatistika