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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
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SuperMind
Dokumentu skaits: 12,226
OKX Learn
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Strategy library
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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
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Amberdata research
Dokumentu skaits: 766
FMZ forum
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FMZ digest
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vn.py community
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QuantInsti blog
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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
Quantpedia
Dokumentu skaits: 86
TqSdk
Dokumentu skaits: 86
Hyperliquid docs
Dokumentu skaits: 79
Freqtrade
Dokumentu skaits: 68
Hudson & Thames
Dokumentu skaits: 62
Awesome Systematic Trading
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backtrader
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vn.py
Dokumentu skaits: 50
Quantopian lekcijas
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Binance API docs
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FMZ guides
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pysystemtrade
Dokumentu skaits: 34
Freqtrade docs
Dokumentu skaits: 32
quant-trading
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FinRL
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Zipline
Dokumentu skaits: 22
FMZ live strategies
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Jesse
Dokumentu skaits: 17
pyfolio
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Alphalens
Dokumentu skaits: 14
WonderTrader
Dokumentu skaits: 14
backtesting.py
Dokumentu skaits: 11
Technical Analysis
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QTPyLib
Dokumentu skaits: 8
QuantRocket
Dokumentu skaits: 7
Lumibot strategies
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Awesome Quant
Dokumentu skaits: 1

Meklēt bibliotēkā

Dokumentu skaits: 3,481

BigQuant

This meetup note surveys several topics in equity quant work. It outlines reversal-factor ideas based on recent returns, technical indicators such as RSI and Bollinger Bands, and fundamental changes such as valuation or a return to profitability. It suggests…

AkcijasAtgriešanās pie vidējās vērtībasTehniskie indikatoriFaktoru ieguldīšana
BigQuant

This assignment outlines a style-rotation process built from three stock strategies: small-capitalization, below-book-value, and oversold-rebound approaches. After backtesting each strategy, it proposes saving the return and position series, then comparing…

Ķīnas tirgiAkcijasFaktoru ieguldīšanaAtgriešanās pie vidējās vērtības
BigQuant

This article proposes four warning signs to watch for during an equity boom: historically extreme valuation multiples, a high ratio of total stock-market capitalization to GDP, broad insider selling, and speculative surges in weak or distressed stocks. It…

AkcijasRiska pārvaldībaTirgus noskaņojumsĶīnas tirgi
BigQuant

This report examines how portfolio optimization settings affect a multi-factor equity strategy. It considers the interaction of active-weight limits with the lambda coefficient, the share of non-index constituents, industry and size exposures, turnover…

AkcijasFaktoru ieguldīšanaPortfeļa veidošanaRiska pārvaldība
BigQuant

This Chinese-language research summary examines analyst consensus estimates as a source of information beyond company financial statements and trading data. It cautions that analyst forecasts tend to be optimistic and that A-share consensus estimates often…

AkcijasFaktoru ieguldīšanaĶīnas tirgiVēsturisko datu pārbaude
BigQuant

The author describes a stock-selection approach intended for people who cannot monitor prices throughout the trading day. Signals are checked at 2:50 p.m.; the proposed routine is to buy a leading candidate scoring above 6 before the close, and to skip…

AkcijasĶīnas tirgiCenas impulssVēsturisko datu pārbaude
BigQuant

This short platform discussion distinguishes a backtest’s pre-market processing from live or simulated trading. In a backtest, the pre-market step may access the current day’s opening price, allowing a rule to use that price to decide on afternoon trading…

Vēsturisko datu pārbaudeRīkojumu izpilde
BigQuant

This note outlines a basic toolkit for constructing low-frequency factors from price and trading data. For each selected input, it proposes calculating rolling means, sums, standard deviations, and skewness over several lookback windows, ranging from short…

AkcijasFaktoru ieguldīšanaTehniskie indikatoriStatistika
BigQuant

The discussion addresses a user who sees a cloud task appear stopped after reopening a browser and asks for more detailed logs. The platform response says closing the browser does not stop the program running in the cloud, but output logs cannot be…

Vēsturisko datu pārbaudeRīkojumu izpilde
BigQuant

The document raises a question about reproducing a 60-day moving-average comparison in a Chinese quantitative research platform. The user’s feature flags observations when a close-price series is below a 60-day mean calculated from prices divided by an…

Tehniskie indikatoriStatistikaAkcijas
BigQuant

This note presents a simple crossover interpretation of Kaufman’s Adaptive Moving Average. It describes a possible entry when price has been below the indicator and a bullish candle moves above it. A downward cross, especially when the indicator changes…

Tehniskie indikatoriSekošana tendenceiAkcijas
BigQuant

This brief BigQuant discussion answers how to retrieve the MACD histogram value for the day on which the highest close occurred within a prior 30-day window. The suggested workflow is to use a time-series argmax function to locate the offset of the maximum…

Tehniskie indikatoriAkcijas
BigQuant

The document explains MACD as a trend and momentum indicator made up of a MACD line, a signal line, and a histogram. It describes bullish signals when the MACD line crosses above the signal line or rises while below zero, and bearish signals when it crosses…

Tehniskie indikatoriCenas impulssSekošana tendenceiAkcijas
BigQuant

This research summary describes adapting daily price-volume alpha research to intraday high-frequency data for stock selection. It examines relationships between price and volume, including ordinary and unusual activity, and reports constructing three…

AkcijasAugstas frekvences tirdzniecībaFaktoru ieguldīšanaStatistika
BigQuant

This brief Chinese-language forum post reports a data-quality issue discovered while debugging backtests: some runs returned no results, and inspection showed that certain factors were empty in many cases. The author notes that noticing the missing values…

Vēsturisko datu pārbaudeMašīnmācīšanāsStatistika
BigQuant

This technical note introduces the Money Flow Index (MFI) and outlines its calculation from high, low, close, and volume data over a chosen lookback period. It first computes typical price as the average of the day's high, low, and close. Volume-weighted…

Tehniskie indikatoriAkcijasStatistika
BigQuant

The post reports a BigQuant backtest failure with a KeyError for the start_date field. The example pipeline screens Chinese stocks, uses recent fund holdings and moving-average conditions to generate signals, ranks selected stocks by market capitalization,…

Ķīnas tirgiAkcijasTehniskie indikatoriVēsturisko datu pārbaude
BigQuant

This report excerpt reviews Chinese equity market performance and factor behavior for the week summarized in an early 2020 research note. It says major indices and most sectors fell during the week, while quality factor effectiveness improved and analyst…

AkcijasFaktoru ieguldīšanaCenas impulssAtgriešanās pie vidējās vērtības
BigQuant

This essay argues that experienced investors may communicate in a direct, plainspoken way because they have worked through complexity and learned to focus on what they understand. It frames simplicity as the result of discernment rather than lack of…

Riska pārvaldībaStatistika
BigQuant

This article explains how a rolling average smooths a time series and why longer lookback windows produce smoother but slower signals. It compares simple, exponential, linearly weighted, triangular, and volatility-adjusted moving averages, focusing on how…

Tehniskie indikatoriSekošana tendenceiCenas impulssNākotnes līgumi
BigQuant

This document summarizes lifecycle funds, which adjust their asset allocation as a target date approaches. The described approach gradually reduces portfolio risk over time, with the aim of matching investment risk to the holder’s changing capacity for risk…

Vairāku aktīvu tirdzniecībaPortfeļa veidošanaRiska pārvaldībaĶīnas tirgi
BigQuant

The note addresses a stock forecasting workflow that displayed an unexpected prediction date and failed when publishing a simulated trade. Its proposed fix is to make sure the training period and prediction period are not set to the same dates. This is a…

AkcijasMašīnmācīšanās
BigQuant

This document introduces a pivot indicator that uses high and low prices together with left- and right-strength parameters. It describes locating local lows and highs within a rolling window whose size depends on those settings, then comparing how recently…

Tehniskie indikatoriStatistika
BigQuant

This short exchange explains how to interpret a long-short portfolio return in factor analysis and how to select a chosen group from a factor-ranked universe. It describes the long-short spread as the return from buying the lowest-ranked group and selling…

Faktoru ieguldīšanaPortfeļa veidošanaĶīnas tirgi