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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 market commentary considers whether foreign investor outflows and a rise in shares becoming tradable would materially affect Chinese equities. It distinguishes short-term trading flows from longer-term institutional allocations, including new mutual…

Ķīnas tirgiAkcijasTirgus noskaņojumsUz notikumiem balstīta tirdzniecība
BigQuant

This meetup summary covers several practical quant trading questions. It suggests examining order book behavior with Level 2 data when developing capital-flow signals, and describes using a Plotly heatmap to inspect correlations among factors. It also points…

Tirgus mikrostruktūraFaktoru ieguldīšanaStatistikaRiska pārvaldība
BigQuant

This review describes machine-learning approaches to predicting stock returns from accounting data and company characteristics. It compares linear methods, including ordinary least squares, LASSO, and ridge regression, with nonlinear models such as random…

AkcijasĶīnas tirgiMašīnmācīšanāsFaktoru ieguldīšana
BigQuant

This submission reflects on a quantitative strategy test whose results changed substantially when the author replaced its default factors or broadened the stock universe to include main-board and ChiNext shares. The observation highlights two practical…

Faktoru ieguldīšanaMašīnmācīšanāsVēsturisko datu pārbaudeĶīnas tirgi
BigQuant

The article reviews research on whether individual commitment within US equity mutual fund management teams affects performance. It classifies managers as committed when they work only for one fund, and noncommitted when they also manage other funds. The…

AkcijasFaktoru ieguldīšanaStatistikaPortfeļa veidošana
BigQuant

The report studies whether intraday return distributions contain stock selection information beyond conventional daily factors. Using one-minute stock prices, it constructs factors from intraday return variance, skewness, and kurtosis, then examines…

AkcijasFaktoru ieguldīšanaAugstas frekvences tirdzniecībaStatistika
BigQuant

This guide describes a workflow for training an end-to-end stock model locally on compressed minute and multi-minute bar data, then submitting its weights and training code for cloud prediction. It explains that local files store prices and amounts as scaled…

AkcijasMašīnmācīšanāsVēsturisko datu pārbaudeRīkojumu izpilde
BigQuant

This note tests an A-share stock screen inspired by a “Beautiful 50” concept. It selects companies using three annual-report criteria: net profit growth above 15%, return on equity above 15% for three consecutive years, and a price-to-earnings ratio below…

AkcijasFaktoru ieguldīšanaVēsturisko datu pārbaudeĶīnas tirgi
BigQuant

This article argues that a high percentage of winning trades does not guarantee profits. It emphasizes the relationship between win rate and the relative size of gains and losses, using examples to illustrate how a strategy with fewer winning trades may…

Riska pārvaldībaPozīcijas apjoma noteikšanaTirgus noskaņojumsAkcijas
BigQuant

This overview introduces artificial intelligence and machine learning as tools for analyzing financial data and supporting investment decisions or trading operations. It groups methods by task: supervised learning for prediction and classification,…

MašīnmācīšanāsStatistikaRiska pārvaldībaPortfeļa veidošana
BigQuant

This note addresses a mismatch in factor analysis: a prediction set has been restricted by strategy conditions, so only a small number of stocks receive scores, while the analysis module still expects broad market coverage. The suggested response is to skip…

AkcijasFaktoru ieguldīšanaVēsturisko datu pārbaude
BigQuant

This community post describes a discrepancy between a CNN-based stock strategy's backtest and simulated-trading signals. With a rolling window of five, both reportedly signal the same stock on January 4. With a window of ten, the simulation notification…

AkcijasMašīnmācīšanāsVēsturisko datu pārbaudeRīkojumu izpilde
BigQuant

The article argues that unusually high trading volume after a stock advance is an ambiguous event rather than an automatic sell signal. Every trade has both a buyer and a seller, so volume alone cannot reveal whether existing holders are distributing shares…

AkcijasTehniskie indikatoriCenas impulss
BigQuant

This educational overview introduces common inputs for quantitative stock selection, beginning with simple and exponential moving averages, RSI, Bollinger Bands, MACD, moving-average crossovers, VWAP, and historical volatility. It describes their usual…

AkcijasTehniskie indikatoriMašīnmācīšanāsStatistika
BigQuant

This research summary revisits the capital asset pricing model by splitting daily stock returns into open-to-close intraday returns and close-to-open overnight returns. It reports that, in the US sample, beta is negatively related to intraday returns but…

AkcijasStatistikaFaktoru ieguldīšanaASV tirgi
BigQuant

The document outlines a Chinese stock screening and trading strategy that targets shares which closed at the daily limit-up on each of the previous two days. Candidates must trade above their five-day moving average, have a price-to-earnings ratio of roughly…

AkcijasĶīnas tirgiCenas impulssCenas izrāviens
BigQuant

This article describes a modification to random forest models that lets an investor express factor preferences directly in the tree-building process. Selected factors are forced to drive splits near the top of each decision tree, increasing their influence.…

MašīnmācīšanāsFaktoru ieguldīšanaAkcijasĶīnas tirgi
BigQuant

The strategy selects Chinese stocks on the day they lose ST designation, buys qualifying names at the open, and holds them for three days. It describes closing trades at the end of the holding period and applying the rule to every stock that meets the event…

AkcijasUz notikumiem balstīta tirdzniecībaĶīnas tirgi
BigQuant

This research explores whether online search interest can serve as a timely measure of investor sentiment and help identify shifts between large-cap and small-cap Chinese equities. It treats search activity related to each style as a sentiment proxy,…

AkcijasTirgus noskaņojumsĶīnas tirgiVēsturisko datu pārbaude
BigQuant

This exchange asks whether MACD components and a short-window swing-volatility feature used in model training and prediction contain future information. The response says these factors are calculated from historical data, implying that the indicators…

Tehniskie indikatoriMašīnmācīšanāsVēsturisko datu pārbaudeStatistika
BigQuant

This research note proposes an equity factor based on how each stock’s intraday volume pattern differs from the market’s. It starts from the common U-shaped market volume profile and argues that a stock with unusually concentrated or uneven trading may have…

AkcijasFaktoru ieguldīšanaStatistikaTirgus mikrostruktūra
BigQuant

The document introduces stationarity and cointegration as the basis for pairs trading. It describes a stationary series as having a stable mean and variance, and presents a pair as cointegrated when the difference between their prices is stationary. Under…

Nākotnes līgumiPāru tirdzniecībaAtgriešanās pie vidējās vērtībasStatistika
BigQuant

This brief support note answers when a newly purchased position’s cost information appears in BigQuant. It distinguishes three operating modes: backtests and simulated trading update the value after the market close on the trade date, while live trading…

Vēsturisko datu pārbaudeAkcijas