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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: 3,481

BigQuant

This forum exchange describes a fix for a BigQuant data query that failed with a missing date key while combining two data sources. The suggested query explicitly selects the date and instrument fields along with technical factor fields. It also filters…

AkcijasTehniskie indikatoriVēsturisko datu pārbaude
BigQuant

This research summary forecasts constituent changes for China’s CSI 300 and CSI 500 indices ahead of their scheduled December 2018 reviews. It explains that the indices are reviewed in June and December, and that changes can create trading opportunities when…

AkcijasĶīnas tirgiUz notikumiem balstīta tirdzniecībaPortfeļa veidošana
BigQuant

This brief platform discussion explains how users can call MACD in BigQuant 3.0 after an older expression format stopped working. It gives two supported expression forms: a windowed MACD function and a shorthand helper. Both calculate MACD from closing…

Tehniskie indikatoriAkcijas
BigQuant

A user reports a discrepancy between a trade’s recorded execution price and the stock’s historical prices on the same date after adjustment for corporate actions. The example contrasts a reported buy price with lower adjusted open and close values. The…

AkcijasVēsturisko datu pārbaudeStatistika
BigQuant

This excerpt summarizes a Chinese weekly research note on machine learning and commodity trading advisor strategies. It reports recent results for a neural network strategy on the CSI 500, a commodity futures strategy, and a commodity strategy combining…

MašīnmācīšanāsNākotnes līgumiAkcijasIzejvielas
BigQuant

This document explains how to remove ChiNext stocks from both the training and test portions of a visual AI stock-selection strategy on BigQuant. It instructs users to insert a shared “filter market” module before the missing-data handling module in each…

AkcijasMašīnmācīšanāsĶīnas tirgiVēsturisko datu pārbaude
BigQuant

The report describes a multifactor stock-selection process that first evaluates and selects robust factors, then combines them into a composite score. It builds separate models for six stock universes and compares direct selection with portfolios that select…

AkcijasĶīnas tirgiFaktoru ieguldīšanaPortfeļa veidošana
BigQuant

The document explains how portfolio attribution compares a portfolio with its benchmark and decomposes excess return into drivers. It distinguishes return-based approaches, including Treynor-Mazuy, Henriksson-Merton, and related factor extensions, from…

Riska pārvaldībaPortfeļa veidošanaFaktoru ieguldīšanaAkcijas
BigQuant

This historical overview traces the independent development of the Capital Asset Pricing Model by Jack Treynor, William Sharpe, John Lintner, and Jan Mossin. It connects their different starting points to portfolio selection and corporate finance, and…

AkcijasVairāku aktīvu tirdzniecībaFaktoru ieguldīšanaPortfeļa veidošana
BigQuant

The study describes a machine-learning approach for classifying the optimal rebalance frequency of a two-asset portfolio strategy. It uses minute-level prices for 50 Binance crypto assets from 2022 and 2023, forms asset pairs, and groups them by correlation.…

KriptoaktīviPāru tirdzniecībaMašīnmācīšanāsVēsturisko datu pārbaude
BigQuant

This opinion piece argues that retail traders should be cautious about relying on remembered successes and discretionary short-term trading habits as markets become more influenced by institutions and quantitative models. Its central practical message is to…

AkcijasĶīnas tirgiRiska pārvaldībaStatistika
BigQuant

This brief strategy outline proposes a weekly rotation among three of the smallest stocks that meet fundamental quality and growth screens. The listed criteria include sustained net-profit growth over three consecutive years and gross margins above 20%; it…

Ķīnas tirgiAkcijasFaktoru ieguldīšanaPortfeļa veidošana
BigQuant

This presentation transcript surveys quantitative trading practices described for overseas markets. It explains how nontraditional inputs such as news sentiment, ESG reports, satellite imagery, and weather can be converted into structured signals, while…

Vairāku aktīvu tirdzniecībaTirgus noskaņojumsUz notikumiem balstīta tirdzniecībaRīkojumu izpilde
BigQuant

This document introduces the Campisi model as a framework for explaining the performance of pure bond funds. It describes decomposing a fund’s total return and excess return into four sources: income, government-bond effects, spread effects, and security…

Fiksēta ienākuma instrumentiPortfeļa veidošanaStatistika
BigQuant

This article describes using recurrent neural networks to predict the direction of the next price change from high-frequency order-book data. The study uses data from Nasdaq stocks and keeps observations where prices change, reducing the input sequence. It…

AkcijasAugstas frekvences tirdzniecībaMašīnmācīšanāsTirgus mikrostruktūra
BigQuant

This discussion raises a timing problem in backtests that use premarket processing. In the example, a signal is generated on one day and orders are submitted the next day; the author notes that historical data queried before trading may already include that…

Vēsturisko datu pārbaudeRīkojumu izpildeStatistika
BigQuant

This discussion describes a backtest problem caused by missing historical prices in a rolling maximum calculation. The author expected the portfolio to hold ten stocks, but in earlier periods it sometimes held only one or two. The suspected cause was that a…

AkcijasVēsturisko datu pārbaudeStatistikaPortfeļa veidošana
BigQuant

This research examines whether industry rotation can enhance a CSI 500 benchmark portfolio. It compares two allocation approaches based on industry views: a moderate deviation from benchmark industry weights, and a concentrated approach that removes bearish…

Ķīnas tirgiAkcijasFaktoru ieguldīšanaPortfeļa veidošana
BigQuant

This report evaluates a China ChiNext equity index that selects stocks using profitability, accounting strength, investment discipline, default risk, and low volatility. It argues that the index offers a more fundamental and lower-volatility alternative to…

AkcijasFaktoru ieguldīšanaSvārstīgumsĶīnas tirgi
BigQuant

This study compares two ways to build multifactor equity portfolios. Integration ranks securities by a combined score and selects those with strong exposure across the target factors. Mixing first builds separate single-factor portfolios, then allocates…

AkcijasFaktoru ieguldīšanaPortfeļa veidošanaVēsturisko datu pārbaude
BigQuant

This analysis examines whether limits on how far bond yields can fall weaken bonds’ return contribution and diversification value. It models a global bond portfolio, a global 60/40 stock-bond portfolio, and a leveraged risk-balanced portfolio, using equal…

Fiksēta ienākuma instrumentiPortfeļa veidošanaRiska pārvaldība
BigQuant

The document identifies the fitness-function setting used by a genetic programming module and lists its available objectives. These include information coefficient to information coefficient ratio, mutual information, long-only Sharpe, volatility and return…

MašīnmācīšanāsStatistikaFaktoru ieguldīšana
BigQuant

This document summarizes research on how investment fund flows relate to fund performance and asset growth. It reports that international studies generally find a positive association between performance and inflows, with a nonlinear relationship to…

StatistikaPortfeļa veidošanaĶīnas tirgi
BigQuant

This forum post asks how to understand two approaches to adapting factors to market style. For a W-style split, the author proposes dividing a factor using a reference variable such as trading amount and treating the difference between the resulting groups…

Faktoru ieguldīšanaStatistikaAkcijas