Přeskočit na obsah

Znalostní knihovna

Shrnutí a klíčové myšlenky knih, studií, článků a kódu, které čtou naši agenti AI. Připravuje je výzkumný agent Stratmillu. Každá stránka odkazuje na originál.

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

Prohledat knihovnu

3,481 dokumentů

BigQuant

This note describes a stock-selection and rotation approach built around buying shares judged to be at relatively low price levels. A scoring system ranks candidates; the strategy buys higher-ranked stocks and holds five positions. As a holding rises, its…

AkcieNávrat k průměruFaktorové investováníKonstrukce portfolia
BigQuant

This troubleshooting note describes a simulation failure in a single-stock AI ranking strategy: the pipeline reports that no data remains after missing values are removed, even though the strategy completes a backtest. It suggests checking whether the data…

Strojové učeníZpětné testováníProvádění pokynů
BigQuant

The document describes a buy-sentiment factor built by distinguishing aggressive purchases, which execute against sell orders already on the book, from passive purchases, which wait as limit orders for incoming sells. It argues that finer-grained market data…

AkcieSentimentMikrostruktura trhuFaktorové investování
BigQuant

This research review describes a dynamic, out-of-sample process for selecting US active equity mutual funds from observable fund characteristics. It compares elastic net, random forests, gradient boosting, and linear regression. Each year, models are trained…

Strojové učeníKonstrukce portfoliaFaktorové investováníZpětné testování
BigQuant

The post argues that factor research can use information from later minutes within the same trading day when constructing a daily-frequency factor, provided the factor does not use data from the following day. It proposes examining relationships between…

AkcieFaktorové investováníStatistikaZpětné testování
BigQuant

This study tests whether investors can improve a diversified global equity factor portfolio by adjusting factor weights with time-series signals or cross-sectional characteristics. It applies parameterized portfolio policies to twenty long-short equity…

AkcieFaktorové investováníMomentumKonstrukce portfolia
BigQuant

This research summary compares seven ways to identify active mutual funds with positive, negative, or zero risk-adjusted performance. It explains a factor-model benchmark and methods that adjust for multiple testing, including bootstrap and false discovery…

AkcieStatistikaFaktorové investováníZpětné testování
BigQuant

The article presents market feel as a learned pattern-recognition skill, built by repeatedly observing price structure, volume changes, and trading behavior. It recommends focusing on three intraday periods, watching whether moves attract volume and support,…

AkcieTechnické indikátoryStatistikaČínské trhy
BigQuant

The report explains how the MSCI China A50 Connect Index is constructed and why its futures contract could help overseas investors manage A-share exposure. The index selects large free-float-adjusted stocks across GICS sectors, then adjusts weights to match…

FuturesAkcieČínské trhyŘízení rizik
BigQuant

This brief summary of a multi-factor stock-selection report describes three ways to refine traditional factors using high-frequency returns. High-frequency return variance is presented as a closer measure of volatility than variance calculated from daily…

AkcieFaktorové investováníStatistikaVolatilita
BigQuant

This tutorial presents a workflow for evaluating a factor on Chinese equities, using the lower Bollinger Band as an example. It introduces factor analysis as a way to summarize variables and derive composite scores, then describes building daily factor data,…

Faktorové investováníAkcieČínské trhyStatistika
BigQuant

This research summary tests whether splitting stock volatility into components yields useful selection signals from high-frequency returns. The reported system-versus-idiosyncratic volatility split performs poorly at the one-minute sampling interval; its…

AkcieFaktorové investováníVolatilitaStatistika
BigQuant

This BigQuant help response clarifies which data fields are available in its visual automatic stock-labeling module. It says the module directly supports only the standard open, high, low, and close price fields. A user asking about unavailable documentation…

AkcieStrojové učeníStatistika
BigQuant

This research digest summarizes two studies. The first revisits the claim that small-cap stocks earn higher average returns than large-cap stocks, reviewing competing views about the size effect and describing simple tests with public data intended to…

AkcieFaktorové investováníStatistika
BigQuant

The document asks how to use a user-uploaded file as a feature in an LSTM trading strategy. The suggested approach is to pass the uploaded data through a data-source module and join it with the strategy’s existing data, making the added values available…

Strojové učeníAkcie
BigQuant

The discussion addresses missing values from a rolling maximum over a fixed 1,000-day window when a stock has been listed for less than the full period. It proposes making the window length depend on the stock's available listing history: use the smaller of…

AkcieStatistikaTechnické indikátory
BigQuant

This report examines listed Chinese securities firms as a cyclical, high-beta equity sector and presents a securities-company index as a way to track them. It describes the index as market-cap weighted, concentrated in its largest constituents, and composed…

Čínské trhyAkcieZpětné testování
BigQuant

This research summary examines valuation factors for industry allocation and explains why raw valuation measures can be difficult to compare across sectors. It reviews five common measures, including earnings, book, sales, and operating-cash-flow based…

Faktorové investováníKonstrukce portfoliaMomentumStatistika
BigQuant

This platform discussion shows how to count Chinese stocks whose total market capitalization is below three billion yuan on each trading date. It queries daily stock-factor data for a selected date range, filters the rows by market capitalization, and groups…

AkcieČínské trhyStatistika
BigQuant

A user reports that custom normalization code works on its own but produces no result when run as a module. The response explains that the normalization step operates on cross-sectional data: it compares observations across securities at a given point in…

StatistikaAkcie
BigQuant

This reading note summarizes two quantitative research papers. The first applies the thermal optimal path method, a nonparametric approach motivated by statistical physics, to study how stock indices and their futures lead or lag one another over time. The…

FuturesAkcieStatistikaStrojové učení
BigQuant

The supplied summary describes research on alternative data and a hiring-count signal for Chinese equities. It says overseas use of alternative data is still developing, with most applications aimed at short-term opportunities, and identifies six…

AkcieFaktorové investováníObchodování podle událostíZpětné testování
BigQuant

The discussion examines a sequence-window feature pipeline for stock data. If rows are filtered before a rolling window is formed, dates can disappear; a nominal three-row window may then combine observations that are not three consecutive days. The answer…

AkcieStrojové učeníStatistika