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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

A user asks why backtest results change when the number of historical days fetched before a test is increased, even when the strategy calculates a moving average such as a ten-period average. The question assumes that fetching at least the indicator’s…

Vēsturisko datu pārbaudeAkcijasStatistika
BigQuant

This post describes a simple stock-selection screen for Chinese equities. It seeks stocks with a daily trading range above a threshold, upward movement in short-term moving averages, and circulating market capitalization above a stated floor. The…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
BigQuant

This article explains Reflex and Trendflex, two price indicators attributed to John Ehlers. Both first smooth prices with a SuperSmoother low-pass filter, then measure average distance between the smoothed price path and a reference line. The distance is…

Nākotnes līgumiKriptoaktīviSekošana tendenceiTehniskie indikatori
BigQuant

This research report develops equity-selection factors from four types of intraday information: price behavior, price-volume relationships, pre-open auction data, and selected trading periods such as the close or high-volume intervals. It evaluates 46…

AkcijasĶīnas tirgiTehniskie indikatoriTirgus mikrostruktūra
BigQuant

This article compares neural networks, decision trees, random forests, support vector machines, and a stock-ranking algorithm for equity selection. It describes broad trade-offs: neural networks can model nonlinear relationships and varied data structures,…

AkcijasMašīnmācīšanāsVēsturisko datu pārbaudeĶīnas tirgi
BigQuant

This report examines corporate tax burdens in China at the economy, industry, and listed-company levels. It distinguishes taxes from mandatory non-tax charges, describes differences across industries, and notes that the shift from business tax to value-added…

AkcijasĶīnas tirgiStatistika
BigQuant

This overview explains how factor models can identify portfolio risk drivers and how factor strategies can target their associated return premia. It describes equity factors such as value, size, momentum, volatility, quality, yield, growth, and liquidity,…

Faktoru ieguldīšanaVairāku aktīvu tirdzniecībaRiska pārvaldībaPortfeļa veidošana
BigQuant

This educational-session overview introduces machine-learning and deep-learning approaches to quantitative stock selection. It lists core workflow topics: defining prediction labels, engineering features, separating training, validation, and test sets, and…

MašīnmācīšanāsAkcijasStatistikaVēsturisko datu pārbaude
BigQuant

The document answers a programming question about applying a per-stock price-pattern test to stocks first selected by daily market filters. The suggested workflow reads hourly bars for the candidate instruments in one batch, then passes the shared data frame…

AkcijasTehniskie indikatoriRīkojumu izpilde
BigQuant

The document explains the price-to-earnings ratio (P/E) as a way to relate a stock’s price to the company’s earnings per share. Comparing two stocks at the same price but with different earnings shows how the ratio distinguishes their valuations: the stock…

AkcijasFaktoru ieguldīšanaStatistika
BigQuant

The report explains how option prices can be used to construct volatility and skew measures for the Chinese equity market. VIX represents expected volatility over a forward period, while SKEW captures the market’s pricing of asymmetric returns and tail risk.…

OpcijasSvārstīgumsAtvasināto instrumentu cenu noteikšanaĶīnas tirgi
BigQuant

The article presents a discretionary momentum setup for Chinese equities that avoids chasing rapid advances and instead looks for a shift from prior weakness to renewed strength. It characterizes a previous session with heavy trading and a contested limit-up…

Ķīnas tirgiAkcijasCenas impulssCenas izrāviens
BigQuant

This short post introduces a template for monitoring a personally selected stock universe, aimed at individual investors who may trade manually rather than buy many stocks in batches. The stated use is to track dozens or hundreds of shares and view their…

AkcijasĶīnas tirgi
BigQuant

This summary of a Haitong Securities study examines whether the cyclically adjusted price-to-earnings ratio can predict long-run US equity returns. Historically, high CAPE readings tended to accompany weaker subsequent ten-year returns, and low readings…

AkcijasASV tirgiAtgriešanās pie vidējās vērtībasStatistika
BigQuant

This study compares loss functions for neural models that forecast five-day cumulative returns for selected Chinese A-shares. It uses a DeepAlpha DNN as the main model and compares mean squared error with absolute error, Pseudo-Huber, negative information…

MašīnmācīšanāsAkcijasĶīnas tirgiVēsturisko datu pārbaude
BigQuant

This research summary explains why predictive machine-learning models can mistake unstable associations for causal relationships, especially when selection bias or confounding drives observed patterns. It presents propensity-score analysis as a way to make…

AkcijasMašīnmācīšanāsStatistikaĶīnas tirgi
BigQuant

This lesson explains binary classification through logistic regression, using the example of predicting whether a stock will rise. It describes encoding outcomes as zero and one, interpreting the model output as a probability, and applying a 0.5 cutoff to…

MašīnmācīšanāsStatistikaAkcijas
BigQuant

The document introduces a video about applying “做T” trading—buying and selling within a trading period—to a value stock, using China Yangtze Power as its example. Its stated aim is to explore whether this approach can generate returns beyond simply holding…

AkcijasĶīnas tirgi
BigQuant

The article argues that algorithmic trading can exploit retail investors’ predictable reactions to price action and news in China’s A-share market. It illustrates this with two anecdotal patterns: a sharp late-session reversal in high-flying consumer stocks…

AkcijasĶīnas tirgiTirgus mikrostruktūraTirgus noskaņojums
BigQuant

This research update describes two A-share stock-selection approaches. The product-price strategy tracks changes in listed companies’ main product prices and highlights cases where prices have risen but share prices may not yet reflect the development. The…

AkcijasĶīnas tirgiUz notikumiem balstīta tirdzniecībaTirgus noskaņojums
BigQuant

The report builds a composite trading-heat signal from stock-specificity and market-cap-adjusted turnover, using these trading-behavior measures as proxies for speculative activity. It argues that the two inputs capture most of the useful information in a…

AkcijasFaktoru ieguldīšanaĶīnas tirgiVēsturisko datu pārbaude
BigQuant

The document explains how members access BigQuant market data through its Python SDK. It outlines installation and login, describes checking table permissions, and demonstrates querying selected daily stock fields over a date range. It also shows how to…

Ķīnas tirgiAkcijasTehniskie indikatoriStatistika
BigQuant

This overview explains how quantitative strategies use factors to express hypotheses about future returns. It describes candidate signal sources such as prices, fundamentals, macroeconomic data, and text, then outlines a research process: translate an…

Faktoru ieguldīšanaStatistikaVēsturisko datu pārbaudeRiska pārvaldība
BigQuant

A BigQuant support discussion addresses a user’s difficulty training a StockRanker model for individual-stock prediction. The replies recommend moving to the newer StockRanker template because the older module is no longer actively maintained. A second…

AkcijasMašīnmācīšanāsĶīnas tirgi