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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
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SuperMind
Dokumentu skaits: 12,226
OKX Learn
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Strategy library
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MQL5 code base
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BigQuant
Dokumentu skaits: 3,481
Bitget Academy
Dokumentu skaits: 3,298
MQL5 articles
Dokumentu skaits: 3,012
TradingView scripts
Dokumentu skaits: 1,976
ProRealCode
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Deribit Insights
Dokumentu skaits: 1,232
Machine Learning for Trading
Dokumentu skaits: 1,124
arXiv papers
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Amberdata research
Dokumentu skaits: 766
FMZ forum
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FMZ digest
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vn.py community
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QuantInsti blog
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Galaxy Research
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QuantStart
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Stratmill research code
Dokumentu skaits: 219
Robot Wealth
Dokumentu skaits: 195
NautilusTrader
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Hummingbot docs
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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
Quantpedia
Dokumentu skaits: 86
TqSdk
Dokumentu skaits: 86
Hyperliquid docs
Dokumentu skaits: 79
Freqtrade
Dokumentu skaits: 68
Hudson & Thames
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Awesome Systematic Trading
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backtrader
Dokumentu skaits: 54
vn.py
Dokumentu skaits: 50
Quantopian lekcijas
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Binance API docs
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FMZ guides
Dokumentu skaits: 38
pysystemtrade
Dokumentu skaits: 34
Freqtrade docs
Dokumentu skaits: 32
quant-trading
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FinRL
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Zipline
Dokumentu skaits: 22
FMZ live strategies
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Jesse
Dokumentu skaits: 17
pyfolio
Dokumentu skaits: 16
Alphalens
Dokumentu skaits: 14
WonderTrader
Dokumentu skaits: 14
backtesting.py
Dokumentu skaits: 11
Technical Analysis
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QTPyLib
Dokumentu skaits: 8
Lumibot strategies
Dokumentu skaits: 7
QuantRocket
Dokumentu skaits: 7
Awesome Quant
Dokumentu skaits: 1

Meklēt bibliotēkā

Dokumentu skaits: 3,481

BigQuant

This equity research summary describes high-frequency factors built from combinations of price and trading-volume information. It presents two examples: an illiquidity factor adjusted using changes in the price path, and a trading-behavior factor derived…

AkcijasĶīnas tirgiAugstas frekvences tirdzniecībaFaktoru ieguldīšana
BigQuant

This short learner response defines quantitative investing as using scientific inputs, such as mathematics, public opinion data, or financial information, together with software to make investment decisions partly or fully automatically. It identifies…

Vairāku aktīvu tirdzniecībaRiska pārvaldība
BigQuant

This research note proposes a way to study the microstructure behind equity reversal. For each stock, it examines the prior twenty trading days, calculates average transaction value per trade for each day, and separates days with relatively high and low…

AkcijasĶīnas tirgiAtgriešanās pie vidējās vērtībasFaktoru ieguldīšana
BigQuant

This preliminary example applies a functional LSTM network to Chinese equity data, using the CSI 300 as its prediction target. The sequence input contains six market features—closing, opening, high and low prices, amount, and volume—across 30 time steps. The…

AkcijasMašīnmācīšanāsĶīnas tirgi
BigQuant

This podcast recap explains how Pyth Network supplies blockchain applications with financial market prices. Its publisher-driven design obtains first-party data from exchanges, market makers, and trading firms, then aggregates publisher updates for use by…

KriptoaktīviDeFiTirgus mikrostruktūra
BigQuant

A BigQuant user reports that a group of order-size factors was missing during a scheduled factor task and remained unavailable during the first two dependent simulated-trading runs. The factors appeared in a later run that evening. The user says similar…

Rīkojumu izpildeRiska pārvaldība
BigQuant

This research roundup summarizes two studies. The first revisits the equity size effect, the long-standing claim that smaller-capitalization stocks earn higher average returns than larger ones. It describes the study as examining competing claims about the…

AkcijasFaktoru ieguldīšanaStatistika
BigQuant

This factor combines intraday price direction with trading volume concentration to estimate how effectively trading activity is associated with price movement. It separates volume-weighted returns during rising and falling minutes, then uses the balance…

Cenas impulssTehniskie indikatoriStatistikaAkcijas
BigQuant

This factor proposal estimates intraday active buying from minute bars: when a bar closes above its open, its traded amount is counted as active buying; bars closing below their open are assigned to passive buying. The daily active-buy ratio divides the…

AkcijasTirgus mikrostruktūraStatistikaFaktoru ieguldīšana
BigQuant

The report summary presents a Campisi-style performance attribution model for bond funds using net asset value returns, an approach intended for cases where timely holdings data are scarce, especially for private funds. It describes five explanatory factors:…

Fiksēta ienākuma instrumentiFaktoru ieguldīšanaPortfeļa veidošanaStatistika
BigQuant

This short forum entry concerns an error in a data-merging function used for rolling backtests. The shown approach reads a DataFrame from each datasource, selects rows whose date is on or after a supplied cutoff, resets the index, and then combines the…

Vēsturisko datu pārbaudeStatistika
BigQuant

This research summary describes a model for estimating the probability that large-cap stocks will outperform small caps over the coming month. It uses changes in short-term interest rates and broad-market volatility as leading inputs, with the aim of…

AkcijasĶīnas tirgiFaktoru ieguldīšanaStatistika
BigQuant

This research summary describes using market microstructure data to estimate the share of individual stocks held by public mutual funds. It reports that a model trained across the full stock universe has some out-of-sample predictive ability, and that…

AkcijasAugstas frekvences tirdzniecībaTirgus mikrostruktūraStatistika
BigQuant

This report compares ways to construct and standardize equity factors from analyst consensus forecasts for expected return on equity, net profit, profit growth, and two-year compound growth. It recommends time-series standardization to create…

AkcijasFaktoru ieguldīšanaStatistikaVēsturisko datu pārbaude
BigQuant

The document explains how genetic programming can evolve formulas from stock price and volume inputs to discover candidate equity selection factors. It outlines the evolutionary cycle of selection, crossover, and mutations, and describes adapting a genetic…

AkcijasMašīnmācīšanāsFaktoru ieguldīšanaVēsturisko datu pārbaude
BigQuant

The report describes a stock-selection approach that forecasts the coming information coefficient of seven style factors, then adjusts their weights according to expected effectiveness. Its features include each factor’s historical information coefficient…

AkcijasFaktoru ieguldīšanaMašīnmācīšanāsVēsturisko datu pārbaude
BigQuant

This example describes an event-driven stock selection strategy that evaluates companies on the day their financial reports are announced. It selects stocks with year-over-year net profit growth below 1 and ranks candidates by that growth measure. The screen…

Ķīnas tirgiAkcijasUz notikumiem balstīta tirdzniecībaVēsturisko datu pārbaude
BigQuant

This document explains a simple trend-following rule using five-day and ten-day moving averages of closing prices. It buys at the next session's open when the shorter average is above the longer average, then sells at the next open when the shorter average…

AkcijasSekošana tendenceiTehniskie indikatoriVēsturisko datu pārbaude
BigQuant

This report describes a Probit model for predicting Chinese listed companies likely to announce high stock dividends or share splits. It groups predictors into company characteristics such as share price, total share capital, and listing age; growth measures…

Ķīnas tirgiAkcijasStatistikaFaktoru ieguldīšana
BigQuant

This article compares active and index approaches to high-yield bonds, focusing on costs, liquidity, market-value weighting, and pricing inefficiencies. Its central case for active management is that thin trading can make index rebalancing costly and…

Fiksēta ienākuma instrumentiRiska pārvaldībaTirgus mikrostruktūra
BigQuant

This brief BigQuant troubleshooting note addresses an HDF5 error encountered when using the Chinese stock filter component. Its practical guidance is to avoid placing the filter directly after a code-list component; instead, connect the data first and apply…

AkcijasĶīnas tirgi
BigQuant

This support thread describes a BigQuant stock-ranking workflow that backtests successfully but fails when launched as simulated trading. The logs show that feature extraction runs, but later extraction steps return empty datasets; the ranker then receives…

MašīnmācīšanāsAkcijasVēsturisko datu pārbaude
BigQuant

This event description outlines a defensive quantitative fund of funds approach built around diversification across asset classes. It proposes combining macroeconomic conditions—growth, interest rates, inflation, and credit—with market-level measures such as…

Vairāku aktīvu tirdzniecībaPortfeļa veidošanaCenas impulssSvārstīgums
BigQuant

This analysis studies the predicted 2018 midyear constituent changes for the SSE 50, CSI 300, and CSI 500 indices. It estimates potential price pressure with an impact coefficient and reviews historical rebalancing effects. The report finds that removal…

AkcijasĶīnas tirgiUz notikumiem balstīta tirdzniecībaTirgus mikrostruktūra