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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 report proposes a cross-sectional stock-selection framework that combines choices of factor subspaces, model families, and ensemble rules. Its base learners include boosted trees, ExtraTrees, random forests, Ridge regression, and Lasso regression,…

AkcijasĶīnas tirgiMašīnmācīšanāsFaktoru ieguldīšana
BigQuant

This report explores whether stock selection factors built from Level 2 transaction records can predict returns over a monthly horizon. It derives measures from trade size categories and trade direction, including the shares of trading represented by…

AkcijasTirgus mikrostruktūraFaktoru ieguldīšanaVēsturisko datu pārbaude
BigQuant

This short question-and-answer thread addresses how to obtain a list of stocks underlying convertible bonds in the BigQuant data environment. A reply suggests reading the `stk_instrument` field from the `basic_info_CN_BOND` table. The questioner then asks…

AkcijasĶīnas tirgi
BigQuant

This guide explains the workflow for a BigQuant contest focused on constructing 15-minute factors from three-second stock snapshot data. Participants are asked to write factor logic without using model-generated factor synthesis. The platform provides…

AkcijasAugstas frekvences tirdzniecībaFaktoru ieguldīšanaVēsturisko datu pārbaude
BigQuant

This research digest summarizes two finance topics. The first reviews competing claims about the size effect, the long-discussed idea that smaller companies have higher average returns than larger ones. It says the underlying study uses simple tests and…

AkcijasFaktoru ieguldīšanaStatistikaPortfeļa veidošana
BigQuant

This overview describes a practical Python workflow spanning data collection, database access, and machine-learning, deep-learning, and natural-language-processing tools. Its investing example uses traditional factors measured over rolling 12-month windows…

Ķīnas tirgiAkcijasMašīnmācīšanāsFaktoru ieguldīšana
BigQuant

This report examines domestic Chinese fund products that provide exposure to Hong Kong equities and their role in broader asset allocation. It reviews access routes and fund types, including actively managed products and index funds, then compares the…

Ķīnas tirgiAkcijasVairāku aktīvu tirdzniecībaPortfeļa veidošana
BigQuant

This overview explains the Kuramoto model, which represents interacting oscillators through phase dynamics. Each oscillator’s motion depends on its natural frequency, coupling strength, and phase differences with the others. Positive coupling draws phases…

Vairāku aktīvu tirdzniecībaStatistika
BigQuant

This research summary treats the assignment of special treatment (ST) status as a proxy for financial distress among Chinese A-share companies. It describes using Fisher discriminant analysis and regression-based models to predict company financial…

AkcijasĶīnas tirgiStatistikaRiska pārvaldība
BigQuant

This document outlines the development of US investment advisory services across four historical phases and describes the industry’s current structure. It proposes examining market scale, concentration, client types, service models, and fee arrangements, but…

Vairāku aktīvu tirdzniecība
BigQuant

This document connects prospect theory and the disposition effect to potential changes in stock supply. It describes a behavioral asymmetry: investors tend to realize gains quickly, while holding losing positions longer and sometimes accepting more risk in…

AkcijasTirgus mikrostruktūra
BigQuant

The document reviews thematic funds, which target long-term narratives such as artificial intelligence or alternative energy. It describes a surge in US thematic-fund assets and inflows through early 2021, then frames investment as a difficult selection…

AkcijasPortfeļa veidošanaRiska pārvaldībaRīkojumu izpilde
BigQuant

The document outlines how sequence learning can fit into a conventional quantitative investment process: feature extraction, individual asset return prediction, portfolio construction, and trade execution. It describes using price and volume measures,…

MašīnmācīšanāsFaktoru ieguldīšanaPortfeļa veidošanaRīkojumu izpilde
BigQuant

The article offers three discretionary rules for stock traders: favor stocks that have previously produced gains for the trader, concentrate research on a small number of names, and use price trends to guide holding and exit decisions. Its most explicit…

AkcijasSekošana tendenceiTehniskie indikatoriRiska pārvaldība
BigQuant

This weekly factor report describes two forms of diagnostics for the ten highest-ranked anonymous ModelScore factors: average style exposures estimated through daily multivariate regressions, and average industry-level Rank ICs measuring the cross-sectional…

AkcijasĶīnas tirgiFaktoru ieguldīšanaStatistika
BigQuant

The study applies the CCK approach to detect herding among the constituents of Chinese equity indices. It treats herding as a period when constituent returns move more alike: their co-movement increases while the dispersion of returns falls. The authors also…

AkcijasĶīnas tirgiStatistikaCenas impulss
BigQuant

This research summary examines what drives convergence in the basis of stock index futures and how those drivers can inform cash-and-futures hedging. After accounting for dividend effects, it identifies the current contract’s annualized basis, the index’s…

Nākotnes līgumiAkcijasStatistikaAtvasināto instrumentu cenu noteikšana
BigQuant

The document outlines a daily stock rotation schedule: buy ten stocks at the open, hold each cohort for five days, and sell it at the close on its fifth day. It allocates capital in five equal portions, investing one portion in each day’s new cohort. From…

AkcijasPozīcijas apjoma noteikšanaVēsturisko datu pārbaudePortfeļa veidošana
BigQuant

This document poses a model-design question: whether the number of input factors in a StockRank model relates to the number of leaves per tree or the total number of trees, and whether there are useful rules of thumb for choosing these quantities. It…

MašīnmācīšanāsFaktoru ieguldīšanaStatistikaVēsturisko datu pārbaude
BigQuant

This note introduces the Average Directional Index (ADX), an indicator calculated from high, low, and close prices over a chosen lookback length. It outlines the intermediate calculations: true range, positive and negative directional movement, and the…

Tehniskie indikatoriSekošana tendenceiStatistika
BigQuant

This summary reports tests of 19 factors derived from sell-side analyst consensus data, covering forecast financial measures and analyst attention. For financial factors, it compares raw values with industry-relative rankings and quarter-over-quarter…

AkcijasFaktoru ieguldīšanaStatistikaVēsturisko datu pārbaude
BigQuant

The article discusses Chinese stocks that close at the daily limit and then open sharply lower. It offers two possible explanations: short selling followed by repurchasing at a lower price, and conventional large traders either distributing shares near a…

AkcijasĶīnas tirgiTirgus mikrostruktūraTirgus noskaņojums
BigQuant

This article reviews Word2Vec as an efficient method for learning word vectors from context, and compares it with matrix-based and clustering approaches to distributed representations. It discusses CBOW and Skip-Gram, emphasizing their different update…

MašīnmācīšanāsStatistika
BigQuant

This document outlines a machine learning workflow built around feature engineering, model training, and model combination. Feature engineering includes creating, extracting, and selecting variables. It contrasts linear models, which capture linear…

MašīnmācīšanāsAkcijasFaktoru ieguldīšanaPortfeļa veidošana