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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 document presents a framework for testing stock-selection factors. It evaluates each trading day’s stock factor values against returns over subsequent holding periods, aiming to show how predictive information changes as the holding period grows. Daily…

AkcijasFaktoru ieguldīšanaStatistikaVēsturisko datu pārbaude
BigQuant

The post asks how to adapt a portfolio-selling routine so that, when the equity allocation exceeds 60% of total portfolio value, the excess exposure is sold from the lowest-ranked holdings. The supplied routine builds a set of currently held securities,…

AkcijasPortfeļa veidošanaPozīcijas apjoma noteikšanaRīkojumu izpilde
BigQuant

The post reports an observation from more than six months of intraday modeling in Chinese equities using five-minute bars. At each time point, the author independently tuned parameters with tree-structured Parzen estimation. The reported optimization…

AkcijasĶīnas tirgiMašīnmācīšanāsStatistika
BigQuant

This research summary examines where mutual fund excess returns may come from, separating security-selection skill from timing skill. Timing is framed as adjusting a fund's market beta, with stronger exposure during rising markets and reduced exposure during…

AkcijasFaktoru ieguldīšanaStatistikaPortfeļa veidošana
BigQuant

The document introduces quantitative investing as an approach that uses numerical models to build an investment process, contrasting it with methods that rely more on qualitative judgment. It describes how quantitative methods can combine computing with…

Vairāku aktīvu tirdzniecībaAkcijasStatistikaPortfeļa veidošana
BigQuant

This short assignment response defines quantitative investing as turning recurring patterns observed through statistical analysis of financial markets into structured methods for future trading. It mentions stocks, futures, and digital assets, and describes…

Vairāku aktīvu tirdzniecībaStatistikaMašīnmācīšanāsRiska pārvaldība
BigQuant

The note explains how a Chinese stock daily bar series relates to adjusted and unadjusted prices. It identifies the cited index daily data as back-adjusted and shows that dividing the close by its adjustment factor can recover an unadjusted price. The…

AkcijasĶīnas tirgi
BigQuant

This guide explains how to carry training data for a StockRanker model from BigQuant’s 1.0 environment into version 3.0. In the older environment, it exports the training dataset with date, instrument, label, and the selected feature columns. The file is…

MašīnmācīšanāsAkcijas
BigQuant

This weekly market report organizes several indicators of Chinese equity liquidity by sector: ETF subscriptions and redemptions, northbound investor flows, estimated allocations from pending and newly raised equity funds, company buybacks, and…

AkcijasĶīnas tirgiStatistikaTirgus noskaņojums
BigQuant

The document examines how trend following could address the equity risk concentration in conventional target-date funds. Their glide paths reduce stock allocations as retirement approaches, yet the portfolio may remain dominated by equity risk, leaving…

Sekošana tendenceiVairāku aktīvu tirdzniecībaRiska pārvaldībaPortfeļa veidošana
BigQuant

This BigQuant support exchange explains a possible source of confusion in backtests: the platform’s `hold_days` setting defines a build-up period during which the strategy can buy, and does not itself require each purchased stock to remain in the portfolio…

Vēsturisko datu pārbaudePortfeļa veidošanaRīkojumu izpilde
BigQuant

The document explains a two-stage model that uses gradient-boosted decision trees to create features for logistic regression. The trees split and combine the original inputs; each sample is then represented by a binary vector marking the leaf it reaches in…

MašīnmācīšanāsStatistikaVēsturisko datu pārbaude
BigQuant

This tutorial demonstrates extracting minute-level stock data for a selected date range with a distributed query platform, then calculating features through SQL-style operators. The examples cover a five-period moving average of closing prices, a…

AkcijasTehniskie indikatoriStatistikaMašīnmācīšanās
BigQuant

The document presents an individual-investor approach inspired by Peter Lynch: use familiar products and services to generate company ideas, then assess business quality, growth, debt, and valuation. Its suggested checks include sustained profit growth,…

AkcijasPozīcijas apjoma noteikšanaPortfeļa veidošanaRiska pārvaldība
BigQuant

This research summary examines why stocks can earn excess returns before earnings announcements. It proposes that investors and analysts resolve some uncertainty ahead of the report, supporting price gains before the announcement itself. The study measures…

AkcijasOpcijasUz notikumiem balstīta tirdzniecībaSvārstīgums
BigQuant

The document reports a single-factor study of operating-efficiency and growth measures. For six operating factors, it says the analysis used grouped portfolio net values, long-short group returns, information coefficients, and Fama–MacBeth methods. Four…

AkcijasFaktoru ieguldīšanaStatistikaVēsturisko datu pārbaude
BigQuant

This research overview presents a workflow for building stock-selection signals from daily price and volume data. Genetic programming generates candidate factors, using rank information coefficients to target linear relationships or mutual information to…

AkcijasĶīnas tirgiMašīnmācīšanāsFaktoru ieguldīšana
BigQuant

The study summary examines whether active stock selection that increases a mutual fund portfolio’s technological similarity predicts subsequent performance. Company patent distributions are compared using cosine similarity, and a fund’s active technological…

AkcijasFaktoru ieguldīšanaStatistikaPortfeļa veidošana
BigQuant

This Chinese-language forum post raises practical questions about what factor weights from a labeling or training process represent. It distinguishes possible interpretations, including neural-network parameters, regression coefficients, and tree-based…

Faktoru ieguldīšanaMašīnmācīšanāsStatistika
BigQuant

This summary of an equity research report explains portfolio optimization as a framework for managing risk exposures, holdings, weights, turnover, and market impact while incorporating investor views. It argues that simple portfolio construction may perform…

AkcijasPortfeļa veidošanaRiska pārvaldībaStatistika
BigQuant

This brief report summarizes a quantitative market-timing view of Chinese A-shares as of early April 2020. It describes the market as being in a bottoming phase with limited downside, and lists sector strength, index and industry valuations, stock-market…

AkcijasĶīnas tirgiTehniskie indikatoriStatistika
BigQuant

The document presents Wyckoff analysis as a way to interpret market supply and demand through price and volume. It describes three guiding principles: compare demand with supply, treat trading ranges as potential causes of later moves, and assess whether…

AkcijasĶīnas tirgiTehniskie indikatoriCenas izrāviens
BigQuant

The article argues that quantitative trading depends on market understanding as well as technical implementation. It contrasts trend-following and mean-reversion approaches as examples of strategies grounded in different views of market behavior, and…

Faktoru ieguldīšanaSekošana tendenceiAtgriešanās pie vidējās vērtībasRiska pārvaldība
BigQuant

The article describes a supervised learning approach that classifies whether a stock’s closing price will be higher or lower after a chosen horizon. It smooths historical prices with exponential weighting, then uses six technical indicators—including RSI,…

AkcijasMašīnmācīšanāsTehniskie indikatoriVēsturisko datu pārbaude