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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
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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 example outlines a China A-share stock selection and portfolio backtest workflow. It screens for eligible, non-suspended stocks, calculates 30-day and 90-day returns, and ranks those returns cross-sectionally. The illustrated filter favors stocks in the…

Ķīnas tirgiAkcijasCenas impulssFaktoru ieguldīšana
BigQuant

The study groups fifty Wind order-flow measures into eight categories, including inflows, outflows, net active buying, and large-order flows. It evaluates these signals as stock-selection factors using portfolio sorts, cross-sectional regressions, and…

AkcijasFaktoru ieguldīšanaStatistikaVēsturisko datu pārbaude
BigQuant

This brief Q&A explains how to change the scoring function used during hyperparameter search. The question asks how to include annualized return, win rate, and maximum drawdown alongside a Sharpe-based score. The response says the score function can read…

MašīnmācīšanāsVēsturisko datu pārbaudeRiska pārvaldība
BigQuant

This speech transcript outlines a research framework spanning short, intermediate, and long horizons. It associates short-term work with factor models and machine-learning stock selection, intermediate work with industry and style rotation, and long-horizon…

Vairāku aktīvu tirdzniecībaAkcijasMašīnmācīšanāsFaktoru ieguldīšana
BigQuant

This note describes a daily stock factor that combines weighted order book pressure with the closing price’s deviation from intraday VWAP. It weights the five visible book levels by proximity, giving the nearest level the greatest weight, then uses trading…

AkcijasTirgus mikrostruktūraCenas impulssTehniskie indikatori
BigQuant

This article explains how to measure whether active mutual fund managers adjust holdings in stocks with different downside market sensitivity ahead of market moves. It defines relative downside beta as the portfolio weighted downside beta minus conventional…

AkcijasRiska pārvaldībaPortfeļa veidošanaStatistika
BigQuant

The document explains net income compound annual growth rate (CAGR) as an annualized measure of change between an initial and a later profit value. It distinguishes CAGR, which represents compounding across multiple periods, from a simple endpoint growth…

AkcijasĶīnas tirgiFaktoru ieguldīšanaVēsturisko datu pārbaude
BigQuant

This installment of a quantitative investing research review introduces two overseas studies relevant to stock selection. The first examines how interest rates affect stock pricing and is described as offering a new analytical framework and empirical testing…

AkcijasFaktoru ieguldīšanaStatistikaSvārstīgums
BigQuant

This support exchange diagnoses why a futures Bollinger Band strategy produced no backtest results. The reported cause is a mismatch between the date ranges: the data extraction module supplied data from 2021, while the backtest was set to run in 2024. Since…

Nākotnes līgumiTehniskie indikatoriVēsturisko datu pārbaude
BigQuant

This tutorial explains how to build and install a reusable BigQuant module that reads a named data table, selects a date range, and rounds chosen floating-point fields to a requested number of decimal places. It describes defining required and optional…

AkcijasStatistikaRīkojumu izpilde
BigQuant

This platform support note addresses why an order query may return no information in a pre-market handler even though it can return information after the market session. The question concerns using existing orders to build a process that cancels orders at…

Rīkojumu izpilde
BigQuant

This research note presents investor mood as a possible explanation for seasonal patterns in both market returns and the relative performance of stocks. It hypothesizes that assets that perform well in historically upbeat periods will tend to do so again in…

AkcijasTirgus noskaņojumsFaktoru ieguldīšanaStatistika
BigQuant

The document explains turnover as the number of shares traded during a period divided by the average number of shares available to trade, expressed as a percentage. It illustrates the calculation with a quarterly example in which traded volume is twice the…

AkcijasStatistikaRīkojumu izpildeTirgus mikrostruktūra
BigQuant

The document describes a China A-share index enhancement approach that adds industry rotation to a CSI 300 stock-selection portfolio. Its motivation is that the benchmark has uneven industry weights, making active industry exposure a meaningful part of…

Ķīnas tirgiAkcijasFaktoru ieguldīšanaPortfeļa veidošana
BigQuant

This research summary extends a framework for selecting functional equity funds for fund-of-funds portfolios. It distinguishes sectors where active stock selection may add value from those better served by sector ETFs. For consumer and growth exposures, it…

AkcijasFaktoru ieguldīšanaPortfeļa veidošanaRiska pārvaldība
BigQuant

The article contrasts quantitative trading, which it describes as using statistical models and systematic execution to exploit price deviations linked to investor emotion, with discretionary investing, where patience, independent judgment, and resilience may…

StatistikaTirgus noskaņojumsRiska pārvaldība
BigQuant

This 2018 report revisits whether the investment clock can guide asset allocation amid trade tensions and political shocks. Its traditional mapping assigns equities to recovery, commodities to overheating, bonds to recession, and cash to stagflation. It…

Vairāku aktīvu tirdzniecībaPortfeļa veidošanaFaktoru ieguldīšanaStatistika
BigQuant

This Chinese equity strategy selects stocks whose opening price is above the previous close and whose five-day closing-price average is above the ten-day average. It ranks qualifying stocks by price-to-earnings ratio in ascending order, selects up to ten,…

AkcijasĶīnas tirgiCenas impulssFaktoru ieguldīšana
BigQuant

This strategy combines model-based stock ranking with trend-following entry filters to seek short- and medium-term gains in Chinese equities. It starts from a manually selected pool of China Securities 150 constituents, narrowed to roughly 100–300 large,…

AkcijasMašīnmācīšanāsSekošana tendenceiCenas impulss
BigQuant

The script describes a spread-trading approach linking methanol futures with polyethylene and polypropylene futures. It estimates an MTO production margin by valuing the two polymer contracts together and subtracting the methanol input cost, adjusted for…

Nākotnes līgumiIzejvielasAtgriešanās pie vidējās vērtībasPāru tirdzniecība
BigQuant

The document raises a practical trading question: how to enforce a minimum holding period using trading days rather than calendar days. Its example calculates elapsed time by subtracting the last rebalance date from the current date, which counts weekends…

Rīkojumu izpildeStatistikaVēsturisko datu pārbaude
BigQuant

This short support discussion concerns a simulated trading run that reportedly failed or stopped before reaching its intended endpoint, even though the available logs showed no clear error. Replies suggest two different observations: one participant saw a…

AkcijasVēsturisko datu pārbaudeRiska pārvaldība
BigQuant

This article explains how the Fama-French model extends CAPM first with size and value factors, then with profitability and investment factors. It describes double sorts by size and book-to-market, return on equity, or asset growth, and forms RMW from…

AkcijasFaktoru ieguldīšanaStatistikaĶīnas tirgi
BigQuant

The document explains how combinatorially symmetric cross-validation (CSCV) can estimate the probability of backtest overfitting (PBO). It distinguishes training overfitting, where a model performs poorly on held-out data, from backtest overfitting, where a…

Vēsturisko datu pārbaudeStatistikaMašīnmācīšanāsFaktoru ieguldīšana