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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: 3,481

BigQuant

This short discussion outlines data-related challenges faced by quantitative investment teams as they develop and test strategies. It describes quantitative investing as turning historical market behavior into data, using statistics and programming to…

StatistikaMašīnmācīšanāsVēsturisko datu pārbaude
BigQuant

This report summary examines how disclosure requirements and historical accuracy of earnings previews differ across Chinese equity-market boards. It compares preview disclosure rates, reports that the ChiNext board generally has the broadest coverage and the…

AkcijasĶīnas tirgiStatistikaFaktoru ieguldīšana
BigQuant

This forum post raises a portfolio-selection question about factor neutralization when the stock universe changes over time. The author describes selecting the five highest-scoring stocks from an initial group, then adding more stocks the next day and…

Faktoru ieguldīšanaPortfeļa veidošanaStatistika
BigQuant

This document presents the case for an ETF tracking a Chinese innovative-drug industry index, which covers related companies listed in Shanghai and Shenzhen. It describes the index as spanning the drug-development value chain and frames the fund as a way to…

AkcijasĶīnas tirgiPortfeļa veidošana
BigQuant

This brief BigQuant Q&A addresses whether to exclude stocks listed on China’s ChiNext and STAR Market boards when building an AI trading strategy. Its central recommendation is to apply the exclusion during both model training and prediction, so the model is…

Ķīnas tirgiMašīnmācīšanāsVēsturisko datu pārbaude
BigQuant

The document presents Follow-the-Leader, a factor-based method for constructing a smaller portfolio that tracks a broad equity index. Instead of selecting stocks only by index weight or correlation with index returns, the method estimates the number of…

AkcijasFaktoru ieguldīšanaPortfeļa veidošanaVēsturisko datu pārbaude
BigQuant

This brief help note answers how to test Python code with breakpoints, including whether a workflow similar to PyCharm’s breakpoint debugging is available. It suggests using Python’s built-in pdb debugger to pause execution and inspect a program while it…

Statistika
BigQuant

This research overview outlines a framework for constructing high-frequency equity factors from Level 2 market data. It recommends reducing tick or intraday observations into daily measures, then transforming those measures over time with operations such as…

AkcijasAugstas frekvences tirdzniecībaFaktoru ieguldīšanaStatistika
BigQuant

This brief BigQuant forum exchange addresses a report that a configured holding period of ten days did not trigger a sale. The response points to the strategy’s complexity, which includes both profit-taking and stop-loss logic, as a possible obstacle to…

Rīkojumu izpildeRiska pārvaldība
BigQuant

This Chinese-language research summary examines factors associated with the assets of index funds, separating them into fixed product attributes, accumulated long-term characteristics, and changing short-term variables. Fixed attributes include fund…

Ķīnas tirgiAkcijasStatistikaFaktoru ieguldīšana
BigQuant

This document describes a Chinese equity screening rule that combines a price-movement threshold, an outstanding convertible-bond name field, and an indicator of recent large-investor activity. It initially presents yesterday’s control by major funds as a…

Ķīnas tirgiAkcijasTehniskie indikatoriTirgus noskaņojums
BigQuant

The post raises a reproducibility question: two strategy templates reportedly use the same model, factors, parameters, and data, yet produce substantially different backtest results. The author asks which result is correct and whether one template contains…

AkcijasMašīnmācīšanāsVēsturisko datu pārbaudeStatistika
BigQuant

This report evaluates 18 financial-quality, price-volume, and analyst-expectation factors for Chinese equities. It compares factor-ranked portfolios, including high-ranked and low-ranked groups, considers the stability of their performance differences, and…

AkcijasFaktoru ieguldīšanaCenas impulssAtgriešanās pie vidējās vērtības
BigQuant

The article examines whether the rise of the Chinese A-share market from 3,000 to 4,000 points marks a peak or the beginning of a larger bull market. It attributes the 2025 advance mainly to technology stocks and proposes looking beyond price charts to…

AkcijasĶīnas tirgiCenas impulssTirgus noskaņojums
BigQuant

This document indexes 50 articles published in 2017, grouped into topics such as computer vision, recommendation, games, speech, language processing, and prediction. The list includes a stock-price forecasting tutorial alongside examples from other fields,…

Mašīnmācīšanās
BigQuant

This short note introduces the Moving Average Convergence and Divergence indicator, or MACD, and specifies its inputs: closing prices and fast, slow, and comparison periods. It describes three calculated series. DIF is the difference between the fast and…

Tehniskie indikatoriCenas impulss
BigQuant

This article describes four Chinese stock chart patterns that it interprets as possible signs of accumulation or a coming recovery: low-volume consolidation after a rise, low-volume decline near a high, a sharp drop followed by stabilization near a low, and…

AkcijasĶīnas tirgiTehniskie indikatori
BigQuant

This research overview introduces six broad model families used in investment work: neural, graphical, clustering and encoding, linear, tree-based, and ensemble methods. It describes their general strengths, such as nonlinear function fitting, relationship…

MašīnmācīšanāsStatistikaPortfeļa veidošana
BigQuant

The post introduces machine learning as an increasingly used approach in quantitative investing. It describes two applications: forecasting market movements and selecting portfolios. It also points to potential benefits, including handling nonlinear…

MašīnmācīšanāsPortfeļa veidošana
BigQuant

This guide explains how to obtain and read monthly partitioned stock bar data at four intraday frequencies, then align the local compressed tables with corresponding cloud tables used for prediction. It describes the Feather file layout, recommends loading…

AkcijasMašīnmācīšanāsTirgus mikrostruktūraStatistika
BigQuant

This report proposes identifying Chinese quantitative private funds through exchange-disclosed trading-seat data. It matches stocks held by four funds among the largest tradable shareholders at quarter-end with the broker seats that appeared on those stocks’…

Ķīnas tirgiAkcijasTirgus mikrostruktūraCenas impulss
BigQuant

This report reviews factor performance across the broad market, sectors, industries, and indices during the first half of 2018, then examines factor selection in a market with sharply different outcomes across stocks and sectors. It reports that most factors…

AkcijasFaktoru ieguldīšanaPortfeļa veidošanaVēsturisko datu pārbaude
BigQuant

This summary describes a market-timing approach that uses a convolutional neural network to extract patterns from lower-dimensional index features, including technical indicators, and classify expected returns. Predicted return classes are then used to drive…

Ķīnas tirgiAkcijasMašīnmācīšanāsTehniskie indikatori
BigQuant

The document answers how to identify when a strategy’s maximum drawdown occurred in a backtest. It recommends adding a strategy risk overview module after the backtest module, which reports the drawdown and its associated date. The example reports a maximum…

Vēsturisko datu pārbaudeRiska pārvaldība