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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 brief indicator note defines Leadlag as a comparison between two exponential moving averages of closing prices. It takes closing price data and two period parameters, one for the lead line and one for the lag line. The supplied pseudocode calculates…

Tehniskie indikatoriAkcijas
BigQuant

The article investigates why XGBoost training took far longer in some Python process setups than with joblib’s loky backend. Its experiments compare direct execution and several multiprocessing approaches, then identify the OpenMP thread limit as the key…

MašīnmācīšanāsStatistikaVēsturisko datu pārbaude
BigQuant

This BigQuant backtest handler describes a daily portfolio process driven by a date-filtered prediction ranking. It allocates roughly one holding-period fraction of portfolio value to daily purchases during an initial staging phase; afterward, it can use up…

AkcijasMašīnmācīšanāsPortfeļa veidošanaRīkojumu izpilde
BigQuant

This report studies whether active-buying measures derived from high-frequency trading data can help rank industries for rotation. It constructs buy-share, buy-intensity, net-buy-share, and net-buy-intensity factors using volume and turnover data from the…

Ķīnas tirgiAkcijasFaktoru ieguldīšanaPortfeļa veidošana
BigQuant

This research note assesses China’s consumer recovery under normalized pandemic controls, using a combination of policy text analysis and indicators of aggregate spending, passenger flows, cinema attendance, and physical store counts. It argues that…

Ķīnas tirgiAkcijasUz notikumiem balstīta tirdzniecībaStatistika
BigQuant

This brief note identifies two errors in the conditions used by a stock strategy example. The first concerns a year-over-year net profit growth factor: the intended filter selects positive growth rather than negative growth. The second concerns position…

AkcijasFaktoru ieguldīšanaVēsturisko datu pārbaude
BigQuant

The article explains why investment teams need to understand how machine-learning models produce decisions, especially when those decisions affect clients, risk controls, or deployment choices. It contrasts inherently interpretable approaches, such as linear…

MašīnmācīšanāsStatistikaRiska pārvaldība
BigQuant

This 2020 research summary compares valuations and return drivers across large- and small-cap Chinese equity indexes. It reports that small-cap valuations were near historical medians while large-cap indexes, including the SSE 50 and CSI 100, were near…

AkcijasĶīnas tirgiFaktoru ieguldīšanaStatistika
BigQuant

The document is a user’s question about calculating three-day and five-day moving averages within a custom feature factor on a quantitative trading platform. It asks how to use lagged close-price fields such as the current-day close, how rolling mean…

AkcijasTehniskie indikatori
BigQuant

The document defines the Sharpe ratio as a way to assess a portfolio or strategy’s excess return relative to the variability of its returns. It gives the calculation: subtract the risk-free rate from average portfolio return, then divide by the standard…

StatistikaRiska pārvaldība
BigQuant

This research summary reviews academic momentum-factor development and reports empirical findings for China’s A-share market. It says traditional momentum measures there exhibit reversal, with stronger reversal over shorter formation windows, and that…

AkcijasĶīnas tirgiCenas impulssFaktoru ieguldīšana
BigQuant

This report excerpt discusses forecasting equity factor returns as commonly used stock-selection factors fluctuate. It proposes improving and simplifying an earlier conditional-expectation timing model by framing factor timing as a regression-based…

Faktoru ieguldīšanaAkcijasStatistikaPortfeļa veidošana
BigQuant

This research note studies post-earnings-announcement drift in Chinese A-shares: stocks reporting results above expectations may continue to earn positive abnormal returns, while those below expectations may lag. It estimates expected net profit and revenue…

AkcijasĶīnas tirgiUz notikumiem balstīta tirdzniecībaFaktoru ieguldīšana
BigQuant

This stock-selection proposal combines a daily price-range threshold, afternoon large-order inflows and a closing price between the Bollinger middle band and upper band. The document gives formulas for the range and band conditions, describes a…

AkcijasTehniskie indikatoriSvārstīgumsĶīnas tirgi
BigQuant

The document raises a modeling question about predicting whether a future price move is positive using a label that takes only two values. The label compares a later close with an earlier open and assigns one class for an increase and the other for a…

MašīnmācīšanāsStatistikaAkcijas
BigQuant

The document reports a discrepancy in a Chinese stock-status data table for one security on a specified historical date. A query against the table returned a status identifying the stock as *ST, while the author says the company was no longer classified that…

AkcijasĶīnas tirgiVēsturisko datu pārbaudeStatistika
BigQuant

The report adapts William O’Neil’s base-pattern and CANSLIM ideas to the Chinese A-share market. It combines price formations such as cup-with-handle and double bottoms with company growth measures, relative price strength, trading activity, and…

Ķīnas tirgiAkcijasCenas izrāviensCenas impulss
BigQuant

The document explains how performance attribution can reveal the sources of a portfolio’s returns, even when portfolios have similar styles and overall results. It outlines three approaches: style analysis, which uses portfolio and benchmark returns to infer…

Faktoru ieguldīšanaPortfeļa veidošanaRiska pārvaldība
BigQuant

This article presents a time-series momentum strategy that switches between a short lookback signal and a longer one according to market volatility. The short signal uses one month of returns and the slow signal uses twelve months; each takes a long or short…

Cenas impulssMašīnmācīšanāsSvārstīgumsVēsturisko datu pārbaude
BigQuant

This article outlines a systematic trend-following approach commonly called the Turtle method. It describes choosing liquid markets, using average true range (ATR) as a volatility measure for position sizing, and entering on Donchian channel breakouts. The…

Nākotnes līgumiSekošana tendenceiCenas izrāviensSvārstīgums
BigQuant

This research summary examines whether institutional trading before earnings announcements contributes to mispricing and post-earnings announcement drift (PEAD). It measures abnormal institutional demand before announcements and relates it to subsequent…

AkcijasUz notikumiem balstīta tirdzniecībaTirgus noskaņojumsStatistika
BigQuant

The document explains how to build trading agents within a strategy framework. It describes a workflow in which research agents gather market evidence and a dedicated trading agent can submit orders, while deterministic Python can enforce fixed execution and…

MašīnmācīšanāsVēsturisko datu pārbaudeRīkojumu izpildeRiska pārvaldība
BigQuant

This strategy ranks the mainland China A-share universe using company size and a price momentum measure. It removes suspended and specially treated shares, calculates a market-cap rank and the ratio of 20-day to 60-day average closing prices, and adds the…

AkcijasĶīnas tirgiFaktoru ieguldīšanaCenas impulss
BigQuant

This note describes using a forecast of the time-varying Sharpe ratio as a monthly signal for switching between cash and Chinese equity indices. It outlines two forecasting approaches: a regression model associated with Robert Whitelaw and an ARMA model. The…

AkcijasĶīnas tirgiStatistikaVēsturisko datu pārbaude