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

This document introduces two self-balancing binary search trees and explains how their balancing rules support efficient lookup, insertion, and deletion. For AVL trees, it defines node height and balance factor, then describes single and double rotations and…

Statistika
BigQuant

The article describes an architecture that combines iTick market feeds, other economic and alternative data, and DeepSeek-R1 to support quantitative research workflows. It proposes attention-based data fusion, automated strategy variant generation,…

MašīnmācīšanāsStatistikaRiska pārvaldībaVairāku aktīvu tirdzniecība
BigQuant

The document summarizes U.S. retirement accounts, especially 401(k) plans and IRAs, as flexible account structures that offer a broad range of investments. It reports that mutual funds represent about half of assets and describes equity funds as the largest…

Vairāku aktīvu tirdzniecībaPortfeļa veidošanaRiska pārvaldībaASV tirgi
BigQuant

The document considers whether quantitative trading in China has a durable future as the field becomes more crowded. It argues that more participants using similar strategies can compress the limited excess returns available in an A-share market that is not…

AkcijasĶīnas tirgiRiska pārvaldība
BigQuant

This strategy ranks constituents of the CSI Dividend Index using a combined score based on dividend yield and return on equity (ROE). Dividend yield represents distributions relative to share price, while ROE is used as a measure of how effectively a company…

AkcijasĶīnas tirgiFaktoru ieguldīšanaPortfeļa veidošana
BigQuant

This report introduces intraday high-frequency trading in the Chinese securities market, framing it as an attempt to capture short-lived market inefficiencies caused by investor behavior or delayed reactions to information. It defines the strategies under…

Augstas frekvences tirdzniecībaTirgus mikrostruktūraRīkojumu izpildeRiska pārvaldība
BigQuant

This report studies whether rotating among industry and thematic exchange-traded funds can support an absolute-return portfolio. It selects 14 industries with matching funds from a broader set of Chinese industry groups, then compares a rotation portfolio…

AkcijasĶīnas tirgiCenas impulssPortfeļa veidošana
BigQuant

This research report explains reinforcement learning concepts, including Markov decision processes, state and action values, reward design, and value-based and policy-based algorithms. Its applied example uses a deep Q-network to time long positions in the…

MašīnmācīšanāsAkcijasTehniskie indikatoriVēsturisko datu pārbaude
BigQuant

This broad practical guide introduces machine learning in quantitative investing, covering supervised, unsupervised, and reinforcement learning. It explains data preparation, missing values, categorical features, scaling, train and test splits,…

MašīnmācīšanāsAkcijasCenas impulssSekošana tendencei
BigQuant

This brief indicator note defines the moving average, abbreviated MA, as a calculation using closing prices and a lag or lookback parameter. It gives a compact formula reference for producing an MA value from those inputs. The entry identifies the indicator…

Tehniskie indikatoriStatistika
BigQuant

The document describes a Chinese stock-selection example that represents daily buy signals as a factor value of one and sell signals as zero. It proposes processing those values and using them to filter and rank stocks. The stated data source is daily stock…

AkcijasFaktoru ieguldīšanaUz notikumiem balstīta tirdzniecībaVēsturisko datu pārbaude
BigQuant

This assignment outlines a workflow for creating a visual machine learning stock strategy using BigQuant’s StockRanker course and strategy template. The participant is asked to modify the model’s input features by adding personal factors, then backtest the…

MašīnmācīšanāsAkcijasVēsturisko datu pārbaudeFaktoru ieguldīšana
BigQuant

The post describes a feature-data issue in a quantitative research workflow. A request failed with an error indicating that no observations remained after missing values were removed. Changing the feature lookback period, as suggested by common…

AkcijasStatistikaVēsturisko datu pārbaude
BigQuant

The document introduces convex functions through their geometric shape and explains a first-order characterization for differentiable convex functions on an open convex domain. At any point, the function’s value at another point is at least as large as the…

StatistikaMašīnmācīšanās
BigQuant

The document examines how benchmark choice affects mutual fund performance estimates. It contrasts return-based evaluation, which is sensitive to benchmark selection, with holdings-based evaluation, which can be more precise but depends on infrequently…

AkcijasStatistikaFaktoru ieguldīšanaRiska pārvaldība
BigQuant

This discretionary trend-following framework aims to join an established advance rather than predict a market bottom. It lists three possible entry cues: a bullish engulfing candle after a pullback to support, a retest near the short moving-average cluster…

AkcijasSekošana tendenceiTehniskie indikatoriRiska pārvaldība
BigQuant

This report outlines the first step in a multi-factor model research process: selecting which factors to combine. It proposes using a hedging perspective and benchmark factor exposures as part of the screening criteria, with the stated aim of reducing the…

Faktoru ieguldīšanaPortfeļa veidošanaAkcijasStatistika
BigQuant

This brief platform report describes a suspected stock-price data problem in a backtest using TWAP-based adjustment prices. A newly added position in Ping An Bank appeared to generate a sudden large profit because its recorded average holding price was…

Vēsturisko datu pārbaudeRīkojumu izpildeAkcijasĶīnas tirgi
BigQuant

This research summary presents labor leverage as a company characteristic that may help explain differences in expected stock returns. It defines labor leverage through the relative size and rigidity of labor expenses, which shape how operating profits…

AkcijasFaktoru ieguldīšanaStatistikaASV tirgi
BigQuant

This report summary presents an investment case for Chinese technology equities and the China Securities Technology 50 Strategy Index. It argues that sharp market declines may offer opportunities to add exposure, based on a claimed review of 13 major…

AkcijasĶīnas tirgiFaktoru ieguldīšanaPortfeļa veidošana
BigQuant

This tutorial outlines a workflow for modeling Chinese steel futures using high frequency market data. It starts with tick snapshots for the RB2305 contract, explains that futures may trade during night sessions, and resamples the raw observations into ten…

Nākotnes līgumiIzejvielasAugstas frekvences tirdzniecībaMašīnmācīšanās
BigQuant

This introductory assignment defines quantitative investing as using computer programs and historical market data to identify assets and apply predefined buying and selling rules. It highlights the ability to scan a broad universe more quickly than a human…

Vēsturisko datu pārbaudeMašīnmācīšanāsRiska pārvaldība
BigQuant

This study examines whether active U.S. equity mutual funds that increase portfolio concentration subsequently achieve better risk-adjusted performance. Its rationale is a tradeoff: concentrating holdings can give greater weight to the manager’s strongest…

AkcijasPortfeļa veidošanaRiska pārvaldībaStatistika
BigQuant

This document describes a competition built around Deep Alpha-CNN, an equity prediction model using a seven-layer one-dimensional convolutional neural network with residual connections. The report’s stated findings favor the deeper network over a two-layer…

AkcijasMašīnmācīšanāsVēsturisko datu pārbaudeStatistika