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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 explains a supervised learning workflow for ranking stocks by their expected future returns. It introduces features, a fitted function, model parameters, and a loss function, then describes labeling return targets, splitting observations into…

AkcijasMašīnmācīšanāsStatistikaVēsturisko datu pārbaude
BigQuant

The article explains play-to-earn games as blockchain-based games that reward activity with tokens or NFTs that may be traded beyond the game. It outlines how a game built on a blockchain can assign digital identities to items, enabling players to hold,…

KriptoaktīviDeFi
BigQuant

This forum entry shows a BigQuant initialization example for setting futures commissions through a per-contract commission object. The configuration maps an instrument to separate rates for opening, closing, and same-day closing trades, then passes the…

Nākotnes līgumiVēsturisko datu pārbaudeRiska pārvaldībaRīkojumu izpilde
BigQuant

This BigQuant assignment submission describes a stock strategy with two adjustable parameters and a target of holding 50 stocks. The author says the implementation adds filters for non-ST stocks, non-suspended shares, and excludes Beijing Stock Exchange…

AkcijasĶīnas tirgiVēsturisko datu pārbaudePortfeļa veidošana
BigQuant

This strategy applies a 20-day channel to a fixed basket of five Chinese stocks. It defines the upper and lower limits as the rolling mean of closing prices plus or minus two standard deviations. A stock is bought when its close exceeds the upper limit and…

Ķīnas tirgiAkcijasCenas izrāviensSvārstīgums
BigQuant

The article describes a framework for identifying crowded sectors and estimating whether crowding may be building or unwinding. It measures asset clustering from principal components of sector return covariances, using the concentration of explained variance…

AkcijasFaktoru ieguldīšanaPortfeļa veidošanaStatistika
BigQuant

This research note examines how stock trading volume changes across the trading day and how the timing of that volume relates to subsequent returns. It describes a W-shaped intraday pattern in China, with activity rising around the morning and afternoon…

AkcijasĶīnas tirgiAugstas frekvences tirdzniecībaFaktoru ieguldīšana
BigQuant

This Chinese-language forum post asks how BigQuant’s StockRanker model works and whether its gradient-boosted decision tree component could be replaced with another ensemble method, such as XGBoost, while retaining a similar ranking strategy. It describes…

AkcijasMašīnmācīšanāsPortfeļa veidošana
BigQuant

This report summary introduces over-the-counter options as customized, non-standardized contracts negotiated between counterparties or arranged through an intermediary. It focuses on binary, or digital, options, whose payoff is discontinuous: at expiry the…

OpcijasAtvasināto instrumentu cenu noteikšanaFiksēta ienākuma instrumentiStatistika
BigQuant

The document describes a Chinese equity screening rule that combines a 14-period RSI below 65, the product of daily percentage change and super-large-order net inflow, and large-order net inflow above 0.05 over three consecutive days. Its stated aim is to…

AkcijasTehniskie indikatoriMašīnmācīšanāsĶīnas tirgi
BigQuant

This research examines how crude oil returns relate to the Chinese equity market and industry returns, then applies estimated oil sensitivity to stock timing, industry rotation, and portfolio risk control. It describes a changing economic relationship:…

IzejvielasAkcijasFaktoru ieguldīšanaPortfeļa veidošana
BigQuant

This study examines whether company news sentiment can help select Chinese stocks. It describes a news score where higher values generally indicate more positive coverage, then measures changes in the average score over a rolling lookback period. The…

AkcijasTirgus noskaņojumsFaktoru ieguldīšanaVēsturisko datu pārbaude
BigQuant

This short forum post recommends adding the Amihud factor to a high-frequency factor table associated with a multi-factor alpha research series. The author says the factor was omitted from the table and characterizes it as a strong long-side factor. The…

Faktoru ieguldīšanaAugstas frekvences tirdzniecībaTirgus mikrostruktūra
BigQuant

The document presents a process for identifying stocks linked to an investment theme using company business classifications and supplier relationships. It starts with leading firms tied to the theme, finds their shared business activities and common…

AkcijasĶīnas tirgiPortfeļa veidošanaCenas impulss
BigQuant

This introduction explains NumPy’s homogeneous multidimensional arrays and highlights broadcasting, vectorized operations, and mathematical functions as tools for working efficiently with numerical data. It applies these ideas to a short series of…

AkcijasStatistikaSvārstīgums
BigQuant

The report proposes measuring a company’s short-term debt capacity by comparing cash and cash equivalents plus net operating cash flow with interest-bearing debt due within a year. It then builds a related stability factor and discusses two uses: ranking…

AkcijasĶīnas tirgiFaktoru ieguldīšanaRiska pārvaldība
BigQuant

The document describes how to combine custom buy and sell conditions with a stock-ranking strategy. Its example selects stocks when the current open is above the prior close and the five-day closing-price average is above the ten-day average. It then ranks…

AkcijasTehniskie indikatoriFaktoru ieguldīšanaRīkojumu izpilde
BigQuant

This report uses a cycle model to assess global markets in 2018. It identifies recurring short, medium, and long cycles in year-over-year financial and economic indicators, and says regression analysis supports their role in asset-price movements. The…

Vairāku aktīvu tirdzniecībaStatistikaAkcijasFiksēta ienākuma instrumenti
BigQuant

This study reproduces high-frequency stock-selection factors from brokerage research using one-minute OHLCVA data and a sample of roughly 350 constituents of the CSI 300 over a historical period ending in 2022. It focuses on five daily factors formed from…

Ķīnas tirgiAkcijasAugstas frekvences tirdzniecībaFaktoru ieguldīšana
BigQuant

The author investigates whether the highest-ranked stocks from a convolutional neural network strategy deliver the best results. The experiments apply a model trained on a small number of stocks to broader selections, then backtest separate groups of ranked…

Ķīnas tirgiAkcijasMašīnmācīšanāsFaktoru ieguldīšana
BigQuant

This strategy-sharing article describes an active China A-share approach that blends model-based stock ranking with technical timing. It starts from a manually selected China Securities 150-related universe, described as roughly 100–300 larger, liquid…

AkcijasĶīnas tirgiMašīnmācīšanāsCenas impulss
BigQuant

This Chinese research note presents a June 2022 outlook for equity style factors and a framework for combining short-term signals with longer-term cycle analysis. It favors valuation, volatility, and turnover factors overall. Its internal indicators are…

Faktoru ieguldīšanaStatistikaCenas impulssSvārstīgums
BigQuant

This Chinese-language post describes an optimization of a machine-learning strategy template for the BigQuant platform. The author reports reducing a two-year backtest from 65 minutes to 26 seconds by using parallel computation and delayed execution. The…

MašīnmācīšanāsVēsturisko datu pārbaudeAkcijasStatistika
BigQuant

This learning note outlines a stock-price forecasting pipeline that uses an LSTM as a sequence generator and a CNN as a discriminator in a generative adversarial network. It describes a broad feature set: related assets and rates, technical indicators, news…

AkcijasMašīnmācīšanāsStatistikaVēsturisko datu pārbaude