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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 report studies trend-based allocation across CITIC Securities’ first-level industry indexes. It frames the process as choosing assets, measuring momentum, selecting industries, assigning weights, and managing portfolio tracking. The analysis describes…

AkcijasSekošana tendenceiCenas impulssPortfeļa veidošana
BigQuant

This brief exchange explains an apparent one-day mismatch between backtest output logs and the trade details table. The stated cause is the difference between a signal and its execution: the log records when a price bar arrives and triggers the signal, while…

Vēsturisko datu pārbaudeRīkojumu izpilde
BigQuant

The document asks why a historical price-to-earnings series for China’s pharmaceutical industry differs from a series calculated in code. The example selects constituents classified under the 2021 Shenwan industry scheme, joins them to daily stock valuation…

AkcijasĶīnas tirgiStatistika
BigQuant

The document summarizes a strategy that combines the relative strength index, exponential moving average, volume-weighted average price, and moving average convergence divergence to generate trading signals. It describes this as a “Weapon Candle” approach…

AkcijasTehniskie indikatoriCenas impulssVēsturisko datu pārbaude
BigQuant

The article describes a discretionary review process for short-term stock theme trading. It begins by scanning the ten highest-turnover names, then compares sectors by the number of stocks advancing from a first limit-up day to a second. Next, it checks the…

AkcijasCenas impulssCenas izrāviensTirgus mikrostruktūra
BigQuant

The article argues that widely used price-based stop rules can cluster orders around obvious levels, where sudden moves may trigger many exits. It recommends shifting attention from a fixed loss percentage on each position to a preset total loss budget, with…

Riska pārvaldībaPozīcijas apjoma noteikšanaAkcijas
BigQuant

This short forum exchange reports a TypeError encountered when opening a backtesting module. The response attributes it to a strategy parameter-name list containing an item that is not a string, which prevents the framework from using that item as an…

Vēsturisko datu pārbaude
BigQuant

This review summarizes research on U.S. actively managed equity mutual funds during the acute COVID-19 market crisis. The study compares net fund returns with broad-market, style-matched, prospectus, and factor-model benchmarks, and examines investor flows…

AkcijasASV tirgiFaktoru ieguldīšanaStatistika
BigQuant

A user reports that a price-ratio buy condition never triggers during a year-long backtest, although the sell condition does. The response attributes the training error to StockRanker receiving only two factors, with a Boolean factor causing the model to…

AkcijasMašīnmācīšanāsVēsturisko datu pārbaude
BigQuant

The document explains abnormal idiosyncratic volatility (AIV), a price based measure of information risk around earnings announcements. It compares each stock’s residual volatility during the five trading days before earnings announcements with its residual…

AkcijasSvārstīgumsFaktoru ieguldīšanaUz notikumiem balstīta tirdzniecība
BigQuant

The document describes pure factor portfolios as a way to test whether a given equity factor has explanatory or investment value while controlling exposure to other factors. A pure portfolio is constructed to have unit exposure to the factor under…

Faktoru ieguldīšanaPortfeļa veidošanaStatistikaAkcijas
BigQuant

The document introduces the Commodity Selection Index (CSI), specifying high, low, close, and a lookback length as inputs. Its pseudocode builds an average true range measure from intraday range and gaps relative to the previous close. It also estimates…

IzejvielasNākotnes līgumiTehniskie indikatoriSekošana tendencei
BigQuant

This short project note outlines a workflow for preparing data and fitting a predictive model. It divides SQL data construction into a base dataset, a normalized dataset, and a final feature-and-label stage. The note mentions cross-sectional factor ranking…

MašīnmācīšanāsStatistikaVēsturisko datu pārbaude
BigQuant

This weekly report compares three Huatai fundamental stock-selection portfolios during a market pullback: a high-dividend-yield model, a low price-to-sales model, and a relative price-to-earnings model. It reports absolute returns, benchmark-relative…

AkcijasFaktoru ieguldīšanaPortfeļa veidošanaVēsturisko datu pārbaude
BigQuant

The article offers four proposed reasons Chinese quantitative funds may find A-shares attractive relative to US equities: a large listed universe and volatile small-cap stocks, lower trading costs, a higher retail share of trading that may create mispricing,…

Ķīnas tirgiASV tirgiAkcijasTirgus mikrostruktūra
BigQuant

This excerpt argues that risk control and position sizing deserve priority alongside stock selection and timing. Its proposed framework smooths risk decisions with a moving-average tracking system and calculates a daily score from market or stock…

Riska pārvaldībaPozīcijas apjoma noteikšanaSekošana tendenceiTehniskie indikatori
BigQuant

This report applies the Fama-French three-factor framework to China’s A-share market, examining monthly evidence from April 2010 through October 2022. It describes the market excess return factor, SMB for company size, and HML for book-to-market, with SMB…

AkcijasFaktoru ieguldīšanaStatistikaĶīnas tirgi
BigQuant

This monthly allocation report describes a strategic portfolio framework that maps broad asset holdings to underlying macroeconomic risks. It uses principal component analysis to define five factors—economic growth, interest rates, credit, term spread, and…

Vairāku aktīvu tirdzniecībaAkcijasFiksēta ienākuma instrumentiFaktoru ieguldīšana
BigQuant

This Chinese-language strategy note combines two China A-share stock-selection approaches: a small-cap, low-turnover portfolio and a dividend-focused portfolio that excludes the smallest stocks. The first ranks eligible stocks using market capitalization and…

AkcijasĶīnas tirgiFaktoru ieguldīšanaPortfeļa veidošana
BigQuant

This report summary describes a growth-stock selection approach for Chinese equities that pairs an earnings-surprise signal with the next-day price gap after an earnings announcement. Rather than comparing reported earnings with a numeric consensus estimate,…

Ķīnas tirgiAkcijasUz notikumiem balstīta tirdzniecībaCenas impulss
BigQuant

The document explains how to calculate a 14-period Relative Strength Index from closing prices. It separates price changes into gains and losses, averages the first period simply, then smooths later averages by carrying forward the prior value. The ratio of…

AkcijasTehniskie indikatoriCenas impulssSekošana tendencei
BigQuant

This document presents the China Securities Innovative Drug Industry Index as a way to track listed companies whose main businesses involve innovative drug research and development. It describes the index’s exposure to pharmaceutical subsectors, company…

AkcijasĶīnas tirgiPortfeļa veidošana
BigQuant

This report introduces gcForest, or multi-grained cascade forest, as a tree-based deep learning model proposed as an alternative to deep neural networks. It argues that the method may suit financial data because it is described as more robust to…

MašīnmācīšanāsVēsturisko datu pārbaudeStatistikaPortfeļa veidošana
BigQuant

This report evaluates risk parity, an asset allocation approach that aims to equalize the risk contributions of assets in a portfolio. It tests the approach using two historical data window designs: rolling windows and expanding recursive windows. For each…

Vairāku aktīvu tirdzniecībaPortfeļa veidošanaRiska pārvaldībaVēsturisko datu pārbaude