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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 article discusses recruiting and interviewing in China’s quantitative trading industry. It argues that candidates need not come from finance: people trained in fields such as chemistry, mathematics, statistics, and computer science may bring useful…

Riska pārvaldībaStatistika
BigQuant

The post outlines a proposed equity workflow that links market breadth, sector selection, stock screening, and portfolio exposure. It would compare broad-market indices with industry or concept indices using beta, select sectors with higher beta, then choose…

Ķīnas tirgiAkcijasFaktoru ieguldīšanaPozīcijas apjoma noteikšana
BigQuant

The note answers how to prevent a backtest from buying stocks that cannot realistically be traded because they are suspended or locked at a one-price limit. It says BigQuant's backtesting module handles these cases by automatically canceling an order when…

Vēsturisko datu pārbaudeAkcijasRīkojumu izpildeĶīnas tirgi
BigQuant

This daily report summarizes an RSRS-based market timing model for major Chinese equity indices on April 7, 2020. The model retained bullish views on the Shanghai Composite, CSI 500, and ChiNext, while taking a more cautious stance on the SSE 50 and CSI 300.…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
BigQuant

This brokerage report reviews Chinese equity style behavior during the week of April 13–17, 2020, then outlines a style outlook using macroeconomic conditions, historical calendar patterns, cross-sectional dispersion, fund flows, valuations, and macro event…

AkcijasFaktoru ieguldīšanaStatistikaĶīnas tirgi
BigQuant

The article describes inferring a fund’s constituents and weights from its total value time series. It compares Extended Linear Cloning (ELC), which uses regression coefficients as asset importance scores and retains the highest scoring candidates, with…

MašīnmācīšanāsPortfeļa veidošanaStatistikaAkcijas
BigQuant

This brief BigQuant support note explains a common cause of a “no data left after dropna” error when backtesting a strategy on the SSE 50 universe. The error can occur because the strategy’s filters leave no eligible stocks, rather than because the backtest…

AkcijasĶīnas tirgiVēsturisko datu pārbaude
BigQuant

This study constructs equity selection factors from trade by trade data to measure aggressive buying. It aggregates transactions into minute level buying and selling amounts, then derives buying share and buying intensity measures. The proposed factors can…

AkcijasFaktoru ieguldīšanaTirgus mikrostruktūraVēsturisko datu pārbaude
BigQuant

This overview explains how AI quantitative investment platforms combine machine learning, deep learning, and natural language processing with financial data analysis. It describes a general workflow in which platforms collect and process market and financial…

MašīnmācīšanāsRiska pārvaldībaPortfeļa veidošanaRīkojumu izpilde
BigQuant

The document briefly explains a variation of the Schaff Trend Cycle indicator. It says the indicator is calculated from the difference between two RSI oscillators that use different lookback periods, and identifies the item as a colored version of that…

Tehniskie indikatoriCenas impulss
BigQuant

This study proposes a passive index that selects between the A-share and H-share of the same company according to which listing is cheaper after currency adjustment. It examines price gaps across dual-listed Chinese companies, using panel regression to…

Ķīnas tirgiAkcijasAtgriešanās pie vidējās vērtībasVēsturisko datu pārbaude
BigQuant

This report examines shifts in China’s A-share market and argues that both industry fundamentals and market style help explain relative sector returns. It describes a stepwise regression that attributes sector performance to beta, company size, cyclicality,…

Ķīnas tirgiAkcijasFaktoru ieguldīšanaStatistika
BigQuant

This research note evaluates 31 quality factors for stock selection in Hong Kong equities and compares their effectiveness with results in mainland A-shares. Twelve factors are reported as notably effective, particularly measures tied to operating cash flow…

AkcijasFaktoru ieguldīšanaStatistikaVēsturisko datu pārbaude
BigQuant

This Chinese-language weekly report presents a cautious near-term market view after large-weight industries weakened relative to smaller industries. It describes an industry allocation signal favoring market-cap-weighted exposure, which would reduce exposure…

AkcijasCenas impulssSvārstīgumsFaktoru ieguldīšana
BigQuant

This report is presented as the opening installment in a series on fundamental quantitative stock selection, focused on the lithium battery industry chain. Its stated aim is to combine fundamental information with traditional multi-factor selection,…

AkcijasĶīnas tirgiFaktoru ieguldīšana
BigQuant

This overview introduces statistical learning methods for prediction and data analysis. It covers linear and logistic regression, linear and quadratic discriminant analysis, resampling, predictor selection, regularization, dimension reduction, nonlinear…

StatistikaMašīnmācīšanāsVēsturisko datu pārbaude
BigQuant

This forum post describes a long-short stock routine that first attempts to close existing positions, then buys the three highest-ranked stocks and sells short the three lowest-ranked. It checks whether each security can be traded before sending an order,…

AkcijasRīkojumu izpildeTirgus mikrostruktūraPozīcijas apjoma noteikšana
BigQuant

The document introduces Altman's Z-score as a composite financial-risk measure built from five ratios: working capital, retained earnings, earnings before interest and taxes, market equity relative to liabilities, and sales, each scaled against assets except…

AkcijasĶīnas tirgiFaktoru ieguldīšanaVēsturisko datu pārbaude
BigQuant

This research review examines momentum in China’s A-share market as institutional ownership and analyst attention have grown. It compares traditional lookback returns with measures that account for price paths, remove limit-up days, use earnings announcement…

AkcijasĶīnas tirgiCenas impulssFaktoru ieguldīšana
BigQuant

This research summary examines how earnings forecasts can improve equity valuation and stock selection in China’s A-share market. It argues that historical return on equity alone has limited selection value there, while substituting forecast earnings for…

AkcijasĶīnas tirgiFaktoru ieguldīšanaStatistika
BigQuant

This research note describes extending mean-variance portfolio allocation with higher-moment information, especially co-skewness and co-kurtosis among assets. Mean and covariance alone can miss differences in joint tail behavior: portfolios with similar…

Portfeļa veidošanaStatistikaRiska pārvaldībaVēsturisko datu pārbaude
BigQuant

This article presents six proposed bullish chart setups: a pullback that holds above a limit-up level and a moving average, rising volume after a contraction, a two-stage expansion from a price low, a large down day on reduced volume, a sequence of pullbacks…

AkcijasTehniskie indikatoriCenas impulssCenas izrāviens
BigQuant

This report summary lays out a framework for analyzing government interest-rate bonds through supply and demand, return decomposition, duration timing, and portfolio allocation. It attributes supply partly to fiscal conditions and economic pressure, and…

Fiksēta ienākuma instrumentiNākotnes līgumiSekošana tendenceiAtgriešanās pie vidējās vērtības
BigQuant

This submission describes a composite stock factor combining three ranked measures: three-year net profit growth, the inverse of summed turnover over five periods, and the inverse of five-period trading-amount variability. The intended profile is high growth…

AkcijasFaktoru ieguldīšanaStatistikaRiska pārvaldība