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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

The article explains a four-part decomposition of market beta based on whether market and individual stock returns are positive or negative together. The components distinguish joint losses, joint gains, and the two mixed-sign cases. Using realized…

AkcijasStatistikaRiska pārvaldībaPortfeļa veidošana
BigQuant

This summary of a 2018 brokerage study examines whether capital-flow measures can help anticipate shifts among equity investment styles. It argues that raw fund-flow observations may add little beyond price and volume because those variables move together,…

AkcijasFaktoru ieguldīšanaPortfeļa veidošanaStatistika
BigQuant

This article warns retail equity traders that fast algorithms may exploit order-flow speed differences, bursts of retail enthusiasm, and clustered stop levels. It illustrates possible behaviors: entering ahead of slower orders, buying into a sentiment-driven…

AkcijasĶīnas tirgiTirgus mikrostruktūraRīkojumu izpilde
BigQuant

This study examines whether futures-curve shape can rank commodity markets. It explains backwardation, where deferred contracts are cheaper than nearer ones, and contango, where they are more expensive. The article connects these patterns to supply, demand,…

IzejvielasNākotnes līgumiPārneseFaktoru ieguldīšana
BigQuant

This platform support thread discusses how to preserve a model after rolling training and whether the final saved artifact represents the intended result. The replies characterize rolling training as a research-stage feature rather than a direct route to…

MašīnmācīšanāsVēsturisko datu pārbaude
BigQuant

The post contains a proposed monthly China A-share industry-rotation backtest. It ranks second-level industries by where current price-to-earnings ratios sit within their own rolling 60-session ranges, then selects six industries with the lowest relative…

Ķīnas tirgiAkcijasFaktoru ieguldīšanaVēsturisko datu pārbaude
BigQuant

The article describes turning rolling OHLC windows into sparse, binary candlestick images for a convolutional neural network. Each sample uses 32 time steps, normalized and mapped onto a 128-by-128 grid; three columns represent each candle’s open, high-low…

AkcijasMašīnmācīšanāsVēsturisko datu pārbaudeTehniskie indikatori
BigQuant

The article presents a speculative outlook for China’s A-share market in 2026. It anticipates a gradual upward market with a spring positioning period, a stronger phase from May through September, and a sharp interim pullback that it interprets as a possible…

Ķīnas tirgiAkcijasPortfeļa veidošanaRiska pārvaldība
BigQuant

This research digest summarizes two distinct topics. For multi-factor index construction, it contrasts a top-down approach, which combines single-factor indexes using assigned proportions, with a bottom-up approach, which optimizes holdings to increase…

Faktoru ieguldīšanaPortfeļa veidošanaAkcijasTirgus mikrostruktūra
BigQuant

This forum post describes an exploratory factor-construction exercise in the Chinese A-share market. The author says a small modification to a factor combination produced strong short-side results, then describes a revised version that removed the short…

Ķīnas tirgiAkcijasFaktoru ieguldīšanaStatistika
BigQuant

The document outlines three ways to explain portfolio results: style analysis using return regressions, benchmark-relative return decomposition, and multi-factor attribution. It describes the data each approach needs, including portfolio and benchmark…

Faktoru ieguldīšanaPortfeļa veidošanaRiska pārvaldībaStatistika
BigQuant

This opinion article argues that quantitative trading has different effects across market structures. It contrasts a US market it characterizes as institutionally dominated with China’s A-share market, which it portrays as retail-heavy and more driven by…

Ķīnas tirgiAkcijasTirgus mikrostruktūraTirgus noskaņojums
BigQuant

This review summarizes research on whether skilled active U.S. equity fund managers add more value when prices are noisier. It measures skill mainly through portfolio selectivity, proxied by one minus a fund’s return-model R-squared, and also uses a…

AkcijasTirgus noskaņojumsStatistikaRiska pārvaldība
BigQuant

This report summary describes revisions to AlphaNet, a neural network that learns stock-selection factors directly from raw price and volume data. AlphaNet v2 adds six ratio features, replaces pooling and dense layers with an LSTM to capture temporal…

AkcijasĶīnas tirgiMašīnmācīšanāsFaktoru ieguldīšana
BigQuant

The document summarizes a study of four MSCI smart beta equity indexes—value weighted, equal weighted, momentum, and minimum volatility—against a market-cap-weighted benchmark. Using monthly returns over 1999–2014, the study applies principal component…

AkcijasFaktoru ieguldīšanaStatistikaPortfeļa veidošana
BigQuant

The document explains a cost-concentration measure for the estimated purchase costs of a selected share of investors’ holdings. It defines the measure as the difference between the upper and lower bounds of that cost interval divided by their sum. A narrower…

AkcijasStatistikaFaktoru ieguldīšana
BigQuant

This article outlines an event-driven strategy for Chinese equities, using quarterly reports as the trigger. It treats a published year-over-year increase of more than 30% in attributable net income as a positive event, buys qualifying stocks when reported,…

Ķīnas tirgiAkcijasUz notikumiem balstīta tirdzniecībaVēsturisko datu pārbaude
BigQuant

This essay focuses on how fear can affect trading decisions, including hesitation after losses, reluctance to buy near highs, and difficulty acting during market weakness. Its central idea is that traders need not eliminate fear to act consistently; they can…

AkcijasRīkojumu izpildeRiska pārvaldībaStatistika
BigQuant

The report reviews the development of Smart Beta index funds in China and compares single-factor strategies in A-shares with counterparts in the US. It describes a Chinese market where offerings are relatively early-stage, commonly single-factor, and held…

AkcijasFaktoru ieguldīšanaPortfeļa veidošanaĶīnas tirgi
BigQuant

This report summary describes a Chinese equity ETF rotation approach built from industry indices with matching exchange-traded funds. It selects 14 industries from the broader industry classification and rotates exposure among their ETFs. The strategy is…

AkcijasĶīnas tirgiSekošana tendenceiNākotnes līgumi
BigQuant

This strategy ranks stocks across mainland China’s A-share market using a small-cap factor and a five-period momentum measure. It combines the market-cap rank with momentum into a composite score, selects the top 50 names, and assigns equal weights. The…

Ķīnas tirgiAkcijasCenas impulssFaktoru ieguldīšana
BigQuant

The article argues that quantitative trading is an execution method, not a source of returns by itself. A trading system can automate orders and support consistent discipline, but it cannot make a weak or faulty strategy profitable. It also questions the…

Rīkojumu izpildeRiska pārvaldībaVēsturisko datu pārbaudeAkcijas
BigQuant

The document reviews tactical and dynamic asset allocation, then focuses on predicting short-term movements in Chinese equity indices. It compares logistic regression, artificial neural networks, and support vector machines across different inputs and…

AkcijasĶīnas tirgiMašīnmācīšanāsSekošana tendencei