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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 note proposes adding a 20-period average true range (ATR) volatility factor to a trading strategy, with the aim of improving its Sharpe ratio. It describes a regime-dependent relationship: higher ATR is associated with stronger returns in bull markets,…

SvārstīgumsRiska pārvaldībaVēsturisko datu pārbaude
BigQuant

This A-share stock selection strategy buys the ten smallest companies by market capitalization each day and rebalances daily. Its universe is drawn from the CSI 1000 and excludes ST and delisted stocks. Additional filters require a positive trailing…

AkcijasĶīnas tirgiFaktoru ieguldīšanaTehniskie indikatori
BigQuant

This BigQuant community post reports that applying a lagged value in a query that joins stock prefactors directly to an index-component table can produce zero-filled results. The example calculates a two-period stock return using a lagged close price, then…

Ķīnas tirgiAkcijasStatistika
BigQuant

This short forum answer addresses how to aggregate price-to-earnings data across stocks in an industry. It suggests using a grouped sum operation keyed by an industry classification and applying it to trailing-twelve-month P/E values in a stock-factor…

AkcijasĶīnas tirgiStatistika
BigQuant

This article proposes interpreting value, momentum, quality, and low-volatility returns through a recurring factor cycle inferred from factor performance itself. It describes normal periods, episodes when value suffers a major drawdown due to growth stocks…

AkcijasFaktoru ieguldīšanaCenas impulssAtgriešanās pie vidējās vērtības
BigQuant

This Chinese-language summary reviews a quantitative research team’s 2017 results across four areas: multi-asset allocation, index enhancement, factor timing, and commodity trading adviser strategies. It reports that an equity-and-bond active risk-parity…

Ķīnas tirgiVairāku aktīvu tirdzniecībaFaktoru ieguldīšanaSekošana tendencei
BigQuant

The document describes preparing supervised-learning labels from Chinese daily stock bars. It calculates a forward price ratio using lead values, clips observations to the cross-sectional 1st and 99th percentile boundaries, and assigns the result as the…

AkcijasĶīnas tirgiMašīnmācīšanāsStatistika
BigQuant

This report frames next-day direction in China’s Wind All A-share index as a binary classification task. It trains a decision-tree-based AdaBoost model on 51 daily features drawn from several markets and asset classes, including repo rates, credit spreads,…

Ķīnas tirgiAkcijasMašīnmācīšanāsVēsturisko datu pārbaude
BigQuant

This event page outlines a presentation on moving from discovering individual factors to designing their portfolio weights. It identifies linear and nonlinear combinations and ICIR-based weighting as methods, with attention to their underlying rationale and…

Faktoru ieguldīšanaPortfeļa veidošanaVēsturisko datu pārbaude
BigQuant

This shared open-source example builds a daily classifier for Chinese stocks using price and volume data, technical indicators, and three supervised models: a random forest, logistic regression, and a linear support vector classifier. Features include…

Ķīnas tirgiAkcijasMašīnmācīšanāsTehniskie indikatori
BigQuant

This summary compares two research reports on protecting portfolios during market stress: one published before a major volatility episode and another written afterward. It frames their comparison around how investors assess defensive strategies before a…

Riska pārvaldībaOpcijasCenas impulssFaktoru ieguldīšana
BigQuant

The report describes applying OpenFE, an enumerate-and-filter framework, to discover interpretable fundamental factors from Chinese companies’ balance sheets, income statements, and cash-flow statements. It first removes fields with substantial missing data,…

AkcijasFaktoru ieguldīšanaMašīnmācīšanāsStatistika
BigQuant

This research summary describes a monthly sector-rotation framework for Chinese equities. It groups 29 CITIC first-level industries into financial, cyclical, consumer, and growth sectors, builds market-cap-weighted sector indices, and proposes selecting…

AkcijasĶīnas tirgiPortfeļa veidošanaStatistika
BigQuant

This research summary describes a multi-factor approach to selecting Chinese convertible bonds. It treats each bond’s value as a combination of straight-bond value and embedded option value, and examines how bond returns relate to the underlying stock. The…

Fiksēta ienākuma instrumentiOpcijasFaktoru ieguldīšanaPortfeļa veidošana
BigQuant

This study proposes a market mechanism for trading data products by separating data ownership from the right to use the data. Ownership is divided into tradable units to support liquidity, while use rights remain indivisible and go to an end user. The…

Tirgus mikrostruktūraMašīnmācīšanāsStatistikaRīkojumu izpilde
BigQuant

This overview defines factors as common drivers of security returns and distinguishes systematic factor exposure from asset-specific risk. It traces the move from the market-only CAPM to multi-factor explanations such as the Fama–French market, size, and…

AkcijasFaktoru ieguldīšanaPortfeļa veidošanaStatistika
BigQuant

The article argues that Rust can suit quantitative trading infrastructure where large data workloads, dense computation, concurrency, and low latency matter. It attributes this fit to Rust’s performance, memory and thread safety guarantees, and lack of…

Rīkojumu izpildeAugstas frekvences tirdzniecībaAkcijasNākotnes līgumi
BigQuant

The document defines the Mass indicator using the high-low range. It first applies an exponential moving average to that range, then smooths the result with a second exponential moving average of the same length. The ratio of the first smoothed range to the…

Tehniskie indikatoriSvārstīgumsStatistika
BigQuant

This forum post compares backtest results for a 20-day and 110-day moving-average strategy on Vanke A shares across two platforms. The strategy buys when the shorter average exceeds the longer one and exits when it falls below, using full portfolio…

AkcijasĶīnas tirgiSekošana tendenceiTehniskie indikatori
BigQuant

This research summary describes an A-share market-impact model intended to narrow the gap between simulated strategy returns and realized portfolio returns. It argues that applying one fixed slippage rate cannot reflect how impact varies across stocks,…

AkcijasRīkojumu izpildeTirgus mikrostruktūraPortfeļa veidošana
BigQuant

This forum post presents a DAI query for filtering Chinese A-share records and asks how to save a large result table as an XLS spreadsheet for separate analysis. Its SQL selects dates, instruments, and derived indicators for price-limit events, including…

AkcijasĶīnas tirgiTehniskie indikatoriStatistika
BigQuant

This Chinese research summary examines the turn-of-month calendar effect, described as stronger returns in the first half of a month than in the second. It reports that a simple strategy of buying during the first half and shorting during the second…

Ķīnas tirgiAkcijas
BigQuant

This research summary examines whether inventory cycle phases can help time broad sectors and the Shanghai Composite. It describes four phases—active restocking, passive restocking, active destocking, and passive destocking—and compares qualitative phase…

Ķīnas tirgiAkcijasFaktoru ieguldīšanaVēsturisko datu pārbaude
BigQuant

The document raises a data-timing question about China’s Dragon-Tiger List, a report of stocks with notable trading activity. It names fields for returns one, two, and five days after a stock appears on the list, and says the five-day return is unavailable…

Ķīnas tirgiAkcijasVēsturisko datu pārbaudeRiska pārvaldība