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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
Quantopian lekcijas
Dokumentu skaits: 45
Binance API docs
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 article describes a Chinese-equity factor that looks for unusually large intraday increases in trading amount, then aggregates information around those moments into daily observations. Its rationale is that a volume surge accompanying modest, orderly…

AkcijasFaktoru ieguldīšanaAugstas frekvences tirdzniecībaSvārstīgums
BigQuant

The strategy turns conventional stock-selection rules into Boolean features for a CNN classifier. Its inputs include returns and return ranks, turnover, valuation and profitability measures, money-flow signals, volatility, technical indicators, and recent…

Ķīnas tirgiAkcijasMašīnmācīšanāsCenas impulss
BigQuant

This strategy combines machine-learning stock ranking with trend-based entry filters for a manually selected pool of China Securities 150 constituents. The pool emphasizes larger, liquid companies, often described as core or sector leaders. A model scores…

Ķīnas tirgiAkcijasMašīnmācīšanāsCenas impulss
BigQuant

This report tests thirteen momentum and modified-momentum signals in China’s A-share market. The signals include returns over several lookback periods, turnover-weighted returns, exponentially weighted turnover-adjusted returns, and a long-horizon regression…

AkcijasĶīnas tirgiCenas impulssFaktoru ieguldīšana
BigQuant

This account describes extending a backtest of a Chinese small-cap strategy and finding that returns before 2024 were negative. It attributes the later high returns largely to growth in the Beijing Stock Exchange, whose smaller companies strongly affected a…

Ķīnas tirgiAkcijasFaktoru ieguldīšanaVēsturisko datu pārbaude
BigQuant

The document introduces multi-task learning (MTL), in which one model addresses several related tasks and uses shared patterns and task-specific differences. It suggests that this can improve learning efficiency and predictive accuracy compared with training…

MašīnmācīšanāsStatistikaVairāku aktīvu tirdzniecība
BigQuant

This research summary explores whether statistics computed from intraday stock data can add new signals to established multi-factor selection approaches in China’s A-share market. It evaluates realized volatility, realized skewness, and realized kurtosis as…

AkcijasFaktoru ieguldīšanaStatistikaAugstas frekvences tirdzniecība
BigQuant

The article outlines a Monte Carlo approach to pricing European calls on the China 50 ETF under the Black-Scholes-Merton framework. It divides the life of the option into time steps, simulates the underlying price with normally distributed shocks, calculates…

OpcijasAtvasināto instrumentu cenu noteikšanaStatistikaĶīnas tirgi
BigQuant

The document explains alpha as the return remaining after comparing a portfolio’s actual return with the return predicted by the Capital Asset Pricing Model. It gives the formula using portfolio return, the risk-free rate, portfolio beta, and benchmark…

Faktoru ieguldīšanaStatistikaPortfeļa veidošana
BigQuant

This document outlines a forecast of constituent changes for four major mainland Chinese equity indices: the CSI 300, CSI 100, SSE 180, and SSE 50. It explains the potential trading relevance of index rebalancing: when funds tracking an index must adjust…

AkcijasUz notikumiem balstīta tirdzniecībaĶīnas tirgiPortfeļa veidošana
BigQuant

This short assignment defines quantitative investing as making trading decisions with data-supported methods instead of relying on intuition. It frames the approach as a way to turn an investment idea into explicit rules and encode those rules in a strategy,…

StatistikaVēsturisko datu pārbaudeRiska pārvaldība
BigQuant

This meetup listing raises two quantitative research questions: why factors with strong information coefficients and information ratios may produce weaker Sharpe ratios, and why combining individually strong Sharpe-ratio factors can reduce portfolio…

Faktoru ieguldīšanaPortfeļa veidošanaTehniskie indikatoriStatistika
BigQuant

This research summary examines whether macroeconomic and market indicators can predict returns to equity factors, with particular attention to the size and reversal factors in Chinese stocks. It uses IVX regression, presented as a response to endogeneity and…

AkcijasFaktoru ieguldīšanaStatistikaĶīnas tirgi
BigQuant

This summary of a Chinese securities research presentation describes several equity research approaches. It outlines an event-driven system intended to assess whether market events have an effective price impact, alongside a multi-factor risk framework and…

AkcijasĶīnas tirgiUz notikumiem balstīta tirdzniecībaFaktoru ieguldīšana
BigQuant

The article contrasts three approaches to Chinese A-share trading. The first focuses on leading, popular stocks in the strongest sectors, holding briefly and using the five-day moving average as a reference for exiting after consecutive closes below it. The…

Ķīnas tirgiAkcijasCenas impulssSekošana tendencei
BigQuant

The document presents factor analysis as a core research step for multi-factor, index-enhancement, and market-neutral strategies. It frames the analyst’s work as evaluating candidate factors before strategy researchers use them, with the quality of that…

Faktoru ieguldīšanaStatistikaVēsturisko datu pārbaude
BigQuant

The report proposes refining the book-to-price (BP) valuation factor by splitting book value into retained earnings and invested capital. It forms two market-value ratios: REP for retained earnings and CCP for invested capital. The stated motivation is that…

AkcijasFaktoru ieguldīšanaĶīnas tirgiVēsturisko datu pārbaude
BigQuant

This research summary introduces price-impact bias, derived from five-minute stock order-flow and market data. It compares how similar proportions of aggressive buying and selling move prices. Stocks with stronger upward impact are described as easier to…

AkcijasTirgus mikrostruktūraAtgriešanās pie vidējās vērtībasFaktoru ieguldīšana
BigQuant

This Chinese-language document summarizes the development and adoption of algorithmic trading, describing early automated portfolio trading in the United States, later growth alongside computing, and broader access through commercial trading platforms. It…

Rīkojumu izpildeTirgus mikrostruktūraArbitrāža
BigQuant

The document answers a strategy implementation question: how to prevent a stock from being bought again for a specified period after a prior trade. Its proposed approach is to record the relevant date when a position is sold, then compare that stored date…

AkcijasRīkojumu izpildeVēsturisko datu pārbaude
BigQuant

This forum post describes a BigQuant backtest that raises a pandas KeyError for the column named buy_signal. The strategy code queries daily stock data and creates a factor field, then the trading handler filters context data using buy_signal equal to one.…

AkcijasVēsturisko datu pārbaude
BigQuant

This exchange asks how to make a deep-learning model produce two predictions for futures trading, one for a long view and one for a short view. The response explains that producing multiple outputs for a regression or classification model may require a…

MašīnmācīšanāsNākotnes līgumiStatistika
BigQuant

This forum post documents a BigQuant workflow in which LightGBM finishes running, but the subsequent score-to-position step fails because its query orders predictions by a column named score that is absent from the input dataset. The error identifies the…

MašīnmācīšanāsRīkojumu izpildePortfeļa veidošanaĶīnas tirgi
BigQuant

This forum post describes a historical data extraction discrepancy between BigQuant versions 1.0 and 3.0. The author reports calculating a 60-period regression slope relating stock returns to a benchmark return series over January 2010. In the stated…

Ķīnas tirgiStatistikaVēsturisko datu pārbaude