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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

This overview describes eight groups it presents as influential in China’s A-share market: foreign investors, short-term speculative funds, social security and insurance funds, securities firms’ proprietary desks, corporate insiders, public funds, and…

AkcijasĶīnas tirgiTirgus noskaņojumsTirgus mikrostruktūra
BigQuant

This forum post reports a disagreement in 24-period and 72-period moving averages for a market series on a specified date. The author compares values from two retail charting sources with results from a quantitative platform, noting that the two external…

Tehniskie indikatoriStatistika
BigQuant

A user reports that every label in a trading demo appears to be zero. The response explains that the platform’s visualization shows only a subset of the data, and the displayed rows may all happen to carry the zero label. It recommends inspecting the full…

MašīnmācīšanāsStatistika
BigQuant

The document outlines why quantitative investors use machine learning to analyze growing financial datasets, forecast market movements, and help select portfolios. It describes machine learning's capacity to represent nonlinear relationships and process data…

MašīnmācīšanāsVēsturisko datu pārbaudeStatistika
BigQuant

This overview describes Chan theory as a chart-analysis framework built from nested price structures. It moves from processed candlestick fractals to strokes, segments, and overlapping consolidation zones, then classifies larger moves as advances, declines,…

Tehniskie indikatoriSekošana tendenceiCenas impulssVairāku aktīvu tirdzniecība
BigQuant

This meetup Q&A covers several practical quantitative trading topics. It explains rolling training as repeatedly updating a model using a moving or expanding historical window, and distinguishes incremental updates from retraining on the full dataset. It…

MašīnmācīšanāsFaktoru ieguldīšanaVēsturisko datu pārbaudePortfeļa veidošana
BigQuant

The document summarizes a research paper that uses a neural network to produce portfolio weights for exchange-traded funds. Instead of forecasting expected returns and then feeding those forecasts into a conventional optimizer, the approach directly tunes…

Vairāku aktīvu tirdzniecībaPortfeļa veidošanaMašīnmācīšanāsRiska pārvaldība
BigQuant

This Chinese-language seminar summary frames AI adoption as a response to falling asset-management margins despite growing assets under management. It sketches a progression from adjusting active portfolios using factor analysis, to building long-short…

Vairāku aktīvu tirdzniecībaFaktoru ieguldīšanaCenas impulssMašīnmācīšanās
BigQuant

This study outlines a Deep Q Network approach to timing trades in one stock. Instead of storing action values for every possible market state in a table, a neural network estimates values for available actions. The agent stores state, action, reward, and…

AkcijasMašīnmācīšanāsVēsturisko datu pārbaudeRiska pārvaldība
BigQuant

This report proposes diversifying portfolios across market, style, and strategy risk premia rather than allocating only among broad asset classes. It uses representative global equity, bond, and commodity indices to construct long-only strategies reflecting…

Vairāku aktīvu tirdzniecībaFaktoru ieguldīšanaCenas impulssSvārstīgums
BigQuant

This introduction explains the Skip-gram model as a method for predicting nearby context words from a chosen center word. It uses a short example sentence and a window extending two words to either side. The explanation defines one-hot representations, dense…

MašīnmācīšanāsStatistika
BigQuant

This article presents volume as a way to assess the force behind price movements. It argues that record volume alone should not be treated as proof of a market top, since trading activity can continue to set new highs. Instead, it singles out expanding…

AkcijasTehniskie indikatoriSekošana tendenceiCenas izrāviens
BigQuant

This review summarizes historical evidence on how assets and active strategies performed during periods of high and rising inflation in the United States, United Kingdom, and Japan. It defines inflation episodes using accelerating year-over-year inflation…

Vairāku aktīvu tirdzniecībaIzejvielasSekošana tendenceiCenas impulss
BigQuant

This analyst note reviews a Chinese bank IT provider’s 2019 results and argues that its business is shifting toward financial technology software and services. It reports revenue growth, a sharp increase in net profit, and software and technology services…

AkcijasĶīnas tirgiUz notikumiem balstīta tirdzniecība
BigQuant

This study examines whether a third-party platform’s rapid redistribution of sell-side analyst upgrades and downgrades changes price discovery and the value brokers provide to clients. Using US recommendation data from 2009–2013, leak timestamps, intraday…

AkcijasTirgus mikrostruktūraRīkojumu izpildeASV tirgi
BigQuant

This article introduces one-dimensional convolutional neural networks as a way to process financial sequences. A convolution applies shared filters across local time windows, allowing the model to learn patterns that can appear at different points in a…

AkcijasMašīnmācīšanāsStatistikaVēsturisko datu pārbaude
BigQuant

The document offers a brief allocation recommendation for bond funds in a period of increasing credit risk. It advises favoring funds with higher credit scores and specifies a threshold of 2.7 or above according to the authors’ credit scoring table. The…

Fiksēta ienākuma instrumentiRiska pārvaldībaPortfeļa veidošana
BigQuant

This document is available here only as a Chinese-language title and outline, with the body represented by a link to a PDF. The outline describes a quantitative approach to asset allocation that separates strategic allocation from tactical allocation. It…

Vairāku aktīvu tirdzniecībaPortfeļa veidošanaRiska pārvaldībaStatistika
BigQuant

This document outlines an asset-allocation approach that separates asset selection from portfolio weighting and market timing. It explains a hidden Markov model as a way to infer unobserved market regimes from observable data, represent complex observations…

AkcijasĶīnas tirgiMašīnmācīšanāsStatistika
BigQuant

This article explains how to configure an older BigQuant workflow to analyze alpha expressions in a manner modeled on WorldQuant’s WebSim. Users specify a factor expression and set the stock universe, data delay, linear decay, market or industry…

AkcijasFaktoru ieguldīšanaVēsturisko datu pārbaudePortfeļa veidošana
BigQuant

This brief troubleshooting exchange addresses a quant model that fails when configured with a single factor, even though the factor values appear normal. The proposed fix is to assign the factor a shorter alias; the author reports that using a very brief…

MašīnmācīšanāsStatistikaVēsturisko datu pārbaude
BigQuant

This BigQuant support note addresses a strategy that can read an uploaded CSV during development but fails to access it after being launched in simulated trading. It recommends storing the data as a platform data source and loading it within the trading…

Rīkojumu izpildeVēsturisko datu pārbaude
BigQuant

This brief BigQuant support note explains why a cloned strategy can work in backtesting yet fail in simulated trading. The example strategy was designed only for backtests, so its date range and instrument reference need changes before simulation: bind the…

Nākotnes līgumiVēsturisko datu pārbaudeRīkojumu izpilde
BigQuant

This research summary argues that standard single-factor information coefficient tests may not reflect index-enhancement practice. A factor’s performance in a broad shared universe may not transfer to a benchmark’s eligible stocks, and simple tests may omit…

AkcijasFaktoru ieguldīšanaPortfeļa veidošanaVēsturisko datu pārbaude