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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 Chinese-language post describes a stock-selection screen that ranks shares by a measure called capital strength, interpreted in the post as trading volume, and applies a condition on float concentration plus a limit on the price gain observed at 9:25.…

Ķīnas tirgiAkcijasCenas impulssTehniskie indikatori
BigQuant

This short homework response defines quantitative investing as using scientific methods to seek profitable predictions. It identifies systematic analysis and statistical reasoning as strengths, then cautions that simulated results can create a false sense of…

StatistikaVēsturisko datu pārbaudeMašīnmācīšanās
BigQuant

The article presents five principles for trading: build decisions around one coherent set of rules, practice execution until it becomes habitual, judge performance over many trades, wait when conditions are noisy, and accept that strategies can fail. It…

Riska pārvaldībaStatistikaRīkojumu izpildeĶīnas tirgi
BigQuant

This retrospective examines US exchange traded products and China’s ETF market during 2020, covering fund flows, product launches, fees, providers, regulation, and investor preferences. In the United States, bond ETF inflows were strong amid Federal Reserve…

Vairāku aktīvu tirdzniecībaAkcijasFiksēta ienākuma instrumentiĶīnas tirgi
BigQuant

This short note highlights that feature importance can differ across predictive models, naming StockRanker and XGBoost as examples. It also points to changing the number of leaf nodes and the learning rate as model-tuning choices. These observations can help…

MašīnmācīšanāsAkcijasStatistikaVēsturisko datu pārbaude
BigQuant

This report describes a high-frequency futures CTA approach that uses the relationship between traded prices and adjusted intraday open interest. It argues that open interest can provide information beyond trading volume, and derives directional signals from…

Nākotnes līgumiAugstas frekvences tirdzniecībaTehniskie indikatoriVēsturisko datu pārbaude
BigQuant

The document addresses a timing problem when using weekly indicators in a daily trading strategy. A weekly calculation may be absent or incomplete during the current week if the data pipeline only forms values after the week closes. Its example asks how to…

AkcijasTehniskie indikatoriStatistikaVēsturisko datu pārbaude
BigQuant

This essay groups chart-centered approaches such as candlestick analysis, Dow Theory, Elliott waves, Wyckoff methods, and Gann techniques under a broad category of pattern-based trading theories. It proposes examining whether any of their components have…

Tehniskie indikatoriStatistikaRiska pārvaldībaAkcijas
BigQuant

A platform user reports that a backtest transaction record can misstate realized profit and loss when a stock position passes through an ex-rights corporate action. The example compares transactions in Chinese equities before and after such an adjustment and…

AkcijasVēsturisko datu pārbaudeStatistika
BigQuant

The post outlines an intended Chinese equity strategy that buys stocks when their price-to-earnings ratio ranks near the low end of its rolling history and sells when it reaches the high end, while restricting the universe to companies above a large…

AkcijasĶīnas tirgiAtgriešanās pie vidējās vērtībasVēsturisko datu pārbaude
BigQuant

This article explains a GBDT-plus-logistic-regression method for classifying stock direction. Gradient-boosted decision trees capture nonlinear feature relationships; each tree maps observations to leaf nodes, which are encoded as indicator variables.…

MašīnmācīšanāsAkcijasStatistikaVēsturisko datu pārbaude
BigQuant

This Chinese-language community post outlines a stock screening rule combining three technical conditions: daily amplitude above one percent, a newly formed KDJ golden cross, and three consecutive sessions in which the close is below the open. It frames high…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
BigQuant

A user reports that a template stock strategy fails during model training after replacing its full A-share universe with a manually chosen set of only a few stocks. The response recommends expanding the sample pool, explaining that the template is designed…

AkcijasMašīnmācīšanāsĶīnas tirgi
BigQuant

This report introduces machine learning as data-driven learning and outlines its three broad forms: supervised, unsupervised, and reinforcement learning. It describes how computing advances, larger datasets, and accessible software libraries have helped make…

MašīnmācīšanāsStatistikaĶīnas tirgiVēsturisko datu pārbaude
BigQuant

This report reviews the weekly returns and directional changes of 16 equity factors. For the week covered, a three-month price momentum or reversal measure led with a reported return of 1.45%, while the 24-day Relative Strength Index returned 0.43%. All…

AkcijasFaktoru ieguldīšanaCenas impulssTehniskie indikatori
BigQuant

This research summary investigates the A-share small-cap premium, comparing its strength across market-cap segments, industries, and global markets. It reports a pronounced size effect across the broader A-share market and within CSI 500 constituents, but a…

AkcijasĶīnas tirgiFaktoru ieguldīšanaStatistika
BigQuant

This research summary examines whether internet search attention can help anticipate rotations between Chinese large-cap and small-cap equity indices. It treats search-index changes related to the two market styles as a proxy for investor sentiment,…

AkcijasĶīnas tirgiTirgus noskaņojumsPortfeļa veidošana
BigQuant

This brief overview introduces genetic programming as an evolutionary approach to generating quantitative investment factors. It describes starting with basic data inputs and mathematical operators, then iteratively evolving candidate expressions through…

MašīnmācīšanāsFaktoru ieguldīšanaStatistikaAkcijas
BigQuant

The article discusses translating plain-language trading rules into Python strategies for the QMT platform. Its example is a moving-average crossover on a named Chinese equity, with an all-in position rule and adjusted price data. The author reports that an…

MašīnmācīšanāsAkcijasSekošana tendenceiVēsturisko datu pārbaude
BigQuant

This article advocates using the 20-day moving average as a simple guide to intermediate stock trends. It defines the line as the average closing price over the preceding 20 trading sessions, roughly a month of trading. The proposed reading combines the…

AkcijasTehniskie indikatoriSekošana tendencei
BigQuant

The document outlines an end-to-end portfolio construction framework that embeds a differentiable convex optimization layer within a neural network. Raw asset data passes through the network for feature extraction and combination, then an optimization layer…

MašīnmācīšanāsPortfeļa veidošanaVēsturisko datu pārbaudeStatistika
BigQuant

The document answers a data-preparation question: how to retain the time of day from a timestamp column while omitting its calendar date. It describes applying a datetime formatting operation to each value in a pandas column, creating a separate time field,…

Nākotnes līgumiStatistikaĶīnas tirgi
BigQuant

This short forum exchange addresses how to use a custom benchmark for a strategy such as pair trading, where a portfolio of two stocks may be a more relevant comparison than a broad market index. The suggested approach is to construct an index from the two…

AkcijasPāru tirdzniecībaPortfeļa veidošana