Pāriet uz saturu

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

The document outlines a data mining workflow for investment research, moving through data collection, cleaning, feature extraction, structuring, storage, analysis, and evaluation of results. It frames this workflow as a way to turn growing volumes of market…

MašīnmācīšanāsStatistikaAkcijasĶīnas tirgi
BigQuant

This summary describes a style-neutral, multi-factor stock selection system for Chinese A-shares built from short-horizon price and volume behavior. The report develops nearly 200 trading-oriented alpha factors using daily stock data, aiming to capture the…

AkcijasĶīnas tirgiFaktoru ieguldīšanaTehniskie indikatori
BigQuant

This essay argues that traders can accelerate learning by studying experienced practitioners’ actual trade records and decision patterns instead of relying only on abstract explanations or repeated personal trial and error. It recommends choosing examples…

Riska pārvaldībaPozīcijas apjoma noteikšanaVēsturisko datu pārbaude
BigQuant

This overview introduces risk parity as an asset-allocation approach and places it alongside the classical mean-variance framework. Mean-variance optimization seeks portfolios that maximize expected return for a given risk level or minimize risk for a target…

Vairāku aktīvu tirdzniecībaPortfeļa veidošanaRiska pārvaldība
BigQuant

The report examines how fundamental factors predict stock returns differently across groups defined by market capitalization, profitability, and volatility. It argues that factor weights should vary by group rather than applying one set of weights across the…

AkcijasFaktoru ieguldīšanaPortfeļa veidošanaVēsturisko datu pārbaude
BigQuant

This article presents the volume clock as an event-based way to measure market activity, in contrast with fixed calendar time. Sampling equal-volume intervals can reduce intraday seasonal effects and may produce observations better suited to conventional…

Nākotnes līgumiAugstas frekvences tirdzniecībaTirgus mikrostruktūraRīkojumu izpilde
BigQuant

This research review studies whether stocks with unusually high trading volume earn a premium that reflects information about the real economy. It constructs high-volume premiums from stocks ranked by recent abnormal volume, then tests whether the premiums…

AkcijasTirgus mikrostruktūraStatistikaFaktoru ieguldīšana
BigQuant

The article explains a method for separating a mutual fund’s total alpha into selection alpha and weighting alpha. Selection alpha is estimated by replacing reported portfolio weights with market-cap weights, isolating the contribution of choosing stocks;…

AkcijasFaktoru ieguldīšanaPortfeļa veidošanaStatistika
BigQuant

This overview discusses two research approaches to using deep learning for equity factor discovery. The first builds stock embeddings from co-investment patterns in fund portfolios: random walks on a stock-fund graph produce sequences for skip-gram training.…

AkcijasMašīnmācīšanāsFaktoru ieguldīšanaTehniskie indikatori
BigQuant

This brief forum exchange addresses whether the minus-one term in a short-term stock factor formula removes shares trading below one currency unit. The reply says it does not: the subtraction applies to the value produced by a maximum operation. The…

AkcijasTehniskie indikatoriStatistika
BigQuant

This research summary describes a study of price spillovers from homes in Hong Kong identified as haunted. It reports progressively smaller average price declines across nearby properties: the affected unit, other units on the same floor, homes in the same…

Statistika
BigQuant

This report examines whether changes in economic growth, inflation, interest rates, and risk premiums can help guide allocation among value and growth stocks and among large-, mid-, and small-cap Chinese equities. It uses GDP growth, CPI, the ten-year…

AkcijasFaktoru ieguldīšanaĶīnas tirgiStatistika
BigQuant

This Chinese-language research summary examines how differences between reported macroeconomic data and consensus forecasts may relate to returns in Chinese equities, bonds, and commodities. It compares forecast data sources, noting that Bloomberg records…

Vairāku aktīvu tirdzniecībaUz notikumiem balstīta tirdzniecībaStatistikaVēsturisko datu pārbaude
BigQuant

This report reviews U.S. mutual fund and ETF expense ratios through 2017, comparing equity, balanced, bond, money market, target date, active, and index products. It describes broad fee declines over time and relates them to investor demand for low cost…

Vairāku aktīvu tirdzniecībaASV tirgiStatistika
BigQuant

This short introductory note describes quantitative investing as the use of mathematical models to turn investment ideas into measurable criteria. Those criteria can be used to identify opportunities, place trades, and manage risk. It highlights potential…

StatistikaMašīnmācīšanāsRiska pārvaldība
BigQuant

This platform update describes additions to an expression engine for quantitative analysis. The new rolling functions calculate sums, means, standard deviations, variances, skewness, and kurtosis over a specified lookback while handling missing values. It…

StatistikaNākotnes līgumiCenas impulssTehniskie indikatori
BigQuant

This article explains beta as an asset or portfolio’s sensitivity to a market benchmark, estimated through linear regression. It situates beta within a factor-model view, where returns are described as a combination of exposures to other assets or factors…

AkcijasĶīnas tirgiRiska pārvaldībaPortfeļa veidošana
BigQuant

The document explains Bayesian optimization as a way to search expensive black-box objectives, such as portfolio return or risk-adjusted performance. It describes using a Gaussian process as a probabilistic model: observations update the model’s posterior,…

MašīnmācīšanāsStatistikaVēsturisko datu pārbaude
BigQuant

This article collects practical advice for building and debugging deep learning models, using a generative adversarial network for manga coloring as its motivating example. It recommends beginning with a small working baseline, visualizing predictions and…

MašīnmācīšanāsStatistikaVēsturisko datu pārbaude
BigQuant

This document describes John Ehlers’ Adaptive Relative Strength Index, an oscillator whose lookback changes with an estimated market cycle. It first smooths the midpoint of each bar, then applies digital filters to derive in-phase and quadrature components.…

Tehniskie indikatoriStatistika
BigQuant

The study examines timing the basis between Chinese equity indices and their futures, motivated by persistent futures discounts and uncertainty for market-neutral funds. To reduce the influence of carry components such as rates, dividends, and time to…

Nākotnes līgumiAkcijasAtgriešanās pie vidējās vērtībasCenas impulss
BigQuant

The document introduces the correlation coefficient as a measure of the direction and strength of a linear relationship between two variables. It defines the coefficient using covariance and the variables’ standard deviations, and explains that its values…

StatistikaPortfeļa veidošanaVairāku aktīvu tirdzniecība
BigQuant

This research note studies whether stocks featured on China’s daily price-change leaderboards attract investor attention and how that attention relates to later returns. Using Sogou search index data as an attention proxy, it reports a U-shaped relationship…

AkcijasĶīnas tirgiCenas impulssFaktoru ieguldīšana
BigQuant

The document answers a brief question about counting stocks within each industry group in a quantitative data expression. Its example groups records by the first-level Shenwan industry field and sums a conditional value: one for rows whose amount is…

AkcijasStatistikaĶīnas tirgi