Praleisti ir pereiti prie turinio

Žinių biblioteka

Stratmill tyrimų agento parengtos knygų, straipsnių, mokslinių darbų ir kodo, kuriuos skaito mūsų DI agentai, santraukos ir pagrindinės mintys. Kiekviename puslapyje pateikiama nuoroda į originalą.

Quant Q&A
20,364 dokumentų
SuperMind
12,226 dokumentų
OKX Learn
8,431 dokumentų
Strategy library
7,910 dokumentų
MQL5 code base
7,090 dokumentų
BigQuant
3,481 dokumentų
Bitget Academy
3,298 dokumentų
MQL5 articles
3,012 dokumentų
TradingView scripts
1,976 dokumentų
ProRealCode
1,507 dokumentų
Deribit Insights
1,232 dokumentų
Machine Learning for Trading
1,124 dokumentų
arXiv papers
1,033 dokumentų
Amberdata research
766 dokumentų
FMZ forum
682 dokumentų
FMZ digest
662 dokumentų
vn.py community
560 dokumentų
QuantInsti blog
511 dokumentų
Galaxy Research
340 dokumentų
QuantStart
246 dokumentų
Stratmill research code
219 dokumentų
Robot Wealth
195 dokumentų
NautilusTrader
191 dokumentų
Hummingbot docs
181 dokumentų
Paradigm research
175 dokumentų
Lumibot
164 dokumentų
Kraken Learn
163 dokumentų
Kiekybinės prekybos kursų biblioteka
157 dokumentų
OctoBot
152 dokumentų
Cryptohopper blog
144 dokumentų
Systematic trading blog (Rob Carver)
132 dokumentų
Qlib
116 dokumentų
TqSdk
86 dokumentų
Quantpedia
86 dokumentų
Hyperliquid docs
79 dokumentų
Freqtrade
68 dokumentų
Hudson & Thames
62 dokumentų
Awesome Systematic Trading
61 dokumentų
backtrader
54 dokumentų
vn.py
50 dokumentų
Binance API docs
45 dokumentų
Quantopian paskaitos
45 dokumentų
FMZ guides
38 dokumentų
pysystemtrade
34 dokumentų
Freqtrade docs
32 dokumentų
quant-trading
31 dokumentų
FinRL
28 dokumentų
Zipline
22 dokumentų
FMZ live strategies
21 dokumentų
Jesse
17 dokumentų
pyfolio
16 dokumentų
Alphalens
14 dokumentų
WonderTrader
14 dokumentų
backtesting.py
11 dokumentų
Technical Analysis
9 dokumentų
QTPyLib
8 dokumentų
QuantRocket
7 dokumentų
Lumibot strategies
7 dokumentų
Awesome Quant
1 dokumentų

Ieškoti bibliotekoje

3,481 dokumentų

BigQuant

This report introduces environmental, social, and governance investing and outlines six approaches, including exclusions, positive screening, ESG integration, thematic investing, and shareholder engagement. It compares MSCI and Thomson Reuters rating methods…

AkcijosInvestavimas pagal veiksniusPortfelio konstravimasKinijos rinkos
BigQuant

This report overview describes how artificial intelligence may be applied across investment management, including portfolio research, investment decisions, trading, risk control, product development, and client marketing. It highlights information…

Mašininis mokymasisKelių turto klasiųRizikos valdymasPavedimų vykdymas
BigQuant

This weekly report surveys Chinese equity-selection factors built from intraday trading behavior. Examples include return skewness, downside-volatility share, buying interest and large-order net buying after the open, late-session trading share, average…

AkcijosKinijos rinkosDidelio dažnio prekybaInvestavimas pagal veiksnius
BigQuant

This document describes an Expert Advisor built around the Adaptive Cyber Cycle indicator. It generates a signal when the indicator crosses its signal line at a bar close. The inputs also allow use of related Adaptive CG Oscillator, CyberCycle, or Adaptive…

Valiutų rinkaTechniniai rodikliaiIstorinis testavimas
BigQuant

This article explains how to simplify factor research by converting many distinct raw values into a smaller number of bins. Its example is a daily return factor across thousands of stocks, where nearby values may be treated as equivalent for exploratory…

AkcijosKinijos rinkosStatistikaInvestavimas pagal veiksnius
BigQuant

This research summary reviews the 2021 commodity futures market and examines whether exchange increases in trading fees affect commodity prices and CTA strategies. It describes a year of broad price gains followed by sharp reversals amid market…

Ateities sandoriaiŽaliavosPrekyba pagal tendencijąRinkos mikrostruktūra
BigQuant

The article explains how a backtest can look convincing while relying on conditions that may not hold in live markets. It examines three assumptions: orders fill immediately at the signal price, market data forms a continuous sequence, and prices from a…

Istorinis testavimasPavedimų vykdymasRinkos mikrostruktūraRizikos valdymas
BigQuant

The document outlines a financial forum presentation on the use of artificial intelligence in quantitative investing. Its listed examples include a random forest approach to market timing and hedging, a pattern matching method for industry rotation, and a…

Mašininis mokymasisPortfelio konstravimasIšvestinių finansinių priemonių kainodara
BigQuant

This introductory tutorial explains machine learning concepts before focusing on linear regression. It defines features and labels, distinguishes supervised from unsupervised learning, and outlines classification, regression, clustering, and parameterized…

Mašininis mokymasisStatistikaInvestavimas pagal veiksniusIstorinis testavimas
BigQuant

This research summary examines whether analyst earnings forecast errors can help select stocks. It reports that realized forecast errors are strongly negatively associated with subsequent returns: stocks with smaller errors performed better in the described…

AkcijosInvestavimas pagal veiksniusStatistika
BigQuant

This document summarizes a documentary series on the development of money and financial systems. Its topics include the origins and social role of credit and debt, the rise of securities markets and sovereign borrowing, insurance and the welfare state,…

Kelių turto klasiųFiksuoto pajamingumo priemonėsAkcijosRizikos valdymas
BigQuant

This weekly report presents diagnostics for the ten highest-ranked anonymous factors in a Chinese quantitative research competition. It describes average style exposures estimated with daily multivariate regressions and average industry-level Rank ICs, the…

AkcijosKinijos rinkosInvestavimas pagal veiksniusPortfelio konstravimas
BigQuant

StockRanker is a tree-based learning-to-rank tool for ordering stocks from supplied features. Its listwise approach optimizes the quality of a stock list’s ranking, and the guide connects the method to the RankNet, LambdaRank, and LambdaMART line of work.…

AkcijosMašininis mokymasisStatistikaIstorinis testavimas
BigQuant

The document addresses a backtest or trading-log puzzle: a buy order is calculated by rounding available cash down to a whole multiple of 100 shares, yet the recorded final purchase quantity is not a multiple of 100. The explanation given is that the system…

AkcijosPavedimų vykdymasIstorinis testavimas
BigQuant

The document explains two differences between backtests and simulated or live trading in a notebook-based platform. In the described live modes, the initialization function runs during each trading period, whereas a backtest runs it once. It also says…

Istorinis testavimasPavedimų vykdymasRizikos valdymas
BigQuant

This update log describes changes to a Chinese equity screening expression. The initial filters included a trailing price-to-earnings ceiling and a minimum listing age. The author then replaces a fixed floating-market-capitalization threshold with a…

AkcijosInvestavimas pagal veiksniusIstorinis testavimasKinijos rinkos
BigQuant

This literature digest covers two topics. The first evaluates asset-pricing factor models using the maximum squared Sharpe ratio. It describes comparisons among nested models, from CAPM through three-, five-, and six-factor specifications, and non-nested…

Investavimas pagal veiksniusPortfelio konstravimasRizikos valdymasAkcijos
BigQuant

This report summarizes tests of equity factors across industries, covering cash flow, valuation, company size, momentum, liquidity, volatility, beta, and alpha. It compares factor performance using portfolio net value and ranking differences, and discusses…

AkcijosInvestavimas pagal veiksniusStatistika
BigQuant

This review describes a model in which equity factors move through normal conditions, periods of value weakness, and subsequent reversals. The value drawdown may reflect a rally in growth stocks or a collapse in value stocks; reversals then differ according…

Investavimas pagal veiksniusAkcijosImpulsasStatistika
BigQuant

The document discusses the rapid growth of China’s quantitative private fund industry since 2019. It attributes that expansion to growing volumes of data, better data processing, and market inefficiencies that may offer more alpha opportunities than mature…

Kinijos rinkosAkcijosKelių turto klasiųRizikos valdymas
BigQuant

This research summary explains a model in which product-market competition and expected asset returns influence one another. Competition can reduce profit margins, increasing firms’ operating leverage and exposure to systematic shocks. Threats from new…

AkcijosStatistikaInvestavimas pagal veiksniusJAV rinkos
BigQuant

This Chinese-language research summary describes a top-down framework for institutional fund allocation that connects macro asset views with strategy and product selection. It argues that asset allocation recommendations need to flow through to specific…

Kelių turto klasiųInvestavimas pagal veiksniusPortfelio konstravimasRizikos valdymas
BigQuant

The document introduces the Alligator technical indicator as three moving-average lines calculated from the midpoint of each bar's high and low. It names the lines Lips, Teeth, and Jaw, and describes each as a moving exponential average with a separate fast,…

Techniniai rodikliaiAkcijos
BigQuant

This summary of a May 2020 China A-share market-timing report combines sector performance, valuation, market breadth, fund positioning, and an intermediate-term model. It lists the strongest and weakest sectors, notes that valuations fell across several…

Kinijos rinkosAkcijosTechniniai rodikliaiStatistika