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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
Quantpedia
Dokumentu skaits: 86
TqSdk
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
Quantopian lekcijas
Dokumentu skaits: 45
Binance API docs
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: 79,386

SuperMind

The article explains return on invested capital (ROIC), return on equity (ROE), and weighted average cost of capital (WACC) as tools for judging whether a company’s growth creates value. ROIC relates after-tax operating profit to invested capital, while ROE…

AkcijasFaktoru ieguldīšanaRiska pārvaldībaStatistika
SuperMind

The document presents an intraday stock-selection screen for Chinese equities. It selects stocks with an amplitude above 1, a product of prior-day turnover and the ratio of current auction volume to prior-day volume between 0.5 and 2, and a price rise below…

AkcijasĶīnas tirgiTehniskie indikatoriRiska pārvaldība
MQL5 code base

The document describes a technical indicator built from three moving averages: a short-term average displaced forward by three periods, a medium-term average displaced by five, and a long-term average displaced by five. It identifies the periods as 3, 7, and…

Tehniskie indikatori
SuperMind

The post proposes a stock selection rule combining price amplitude above a stated threshold, progressively rising bottom levels, and a bullish weekly bar. It characterizes these as technical signals for price movement and buying interest, then suggests…

AkcijasTehniskie indikatoriCenas impulssRiska pārvaldība
BigQuant

The post reports a BigQuant backtest failure in which the data extraction stage returned zero rows, and the backtest then raised an IndexError while constructing its rebalance schedule. The logs show the sequence from feature processing to an empty extracted…

Vēsturisko datu pārbaudeAkcijas
SuperMind

The post describes a way to prompt a language model to produce backtest code for the SuperMind platform: provide platform-specific function documentation, spell out the desired trading logic, and warn against known invalid patterns. Its example requests a…

AkcijasTehniskie indikatoriVēsturisko datu pārbaudeRīkojumu izpilde
BigQuant

This brief BigQuant community post reflects on the challenge of improving a strategy’s Sharpe ratio while also controlling drawdowns. The author’s remarks suggest that judging a strategy by Sharpe alone can overlook the difficulty of managing losses. They…

StatistikaRiska pārvaldībaVēsturisko datu pārbaudeAkcijas
SuperMind

This short-term Chinese stock screen selects shares whose daily price amplitude exceeds 1, whose reported daily control measure has an absolute change above 21, and whose auction-period return lies between -2% and 5%. The post presents these filters as a…

Ķīnas tirgiAkcijasTehniskie indikatoriRiska pārvaldība
SuperMind

This Chinese equity screening proposal combines a ranking by capital strength with an exclusion for Beijing-listed A-shares and a revenue-growth condition. Capital strength is described broadly using measures such as trading volume, turnover, or order-side…

Ķīnas tirgiAkcijasFaktoru ieguldīšana
MQL5 code base

The Guppy Multiple Moving Average indicator groups two sets of moving averages to compare shorter-term price behavior with longer-term market direction. Its fast group uses six averages from 3 to 15 periods, while its slow group uses six averages from 30 to…

Valūtu tirgusTehniskie indikatoriSekošana tendencei
SuperMind

This Chinese equities screen combines three price conditions: daily amplitude above 1, a 9:25 price gain below 6%, and a closing price above the previous day's low. The stated intent is to find stocks with some volatility and strength while avoiding an…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This Chinese stock screen looks for companies in the metaverse industry that also have a robotics concept, recorded a limit-up day during the prior 25 days, and have a free-float market value below 10 billion yuan. The rationale is to combine a recent strong…

AkcijasĶīnas tirgiCenas izrāviensCenas impulss
MQL5 code base

This expert advisor trades after a chosen number of consecutive candles share the same direction: it buys after a bullish run and sells after a bearish run. Version 6 adds configurable exits when the next candle goes against the position, an event the…

Valūtu tirgusCenas izrāviensTehniskie indikatoriVēsturisko datu pārbaude
BigQuant

This Chinese research summary describes an equity index-enhancement approach using listed companies’ reported revenue by business line. It uses annual and interim report data, then applies Chinese-language keyword extraction and similarity analysis to…

AkcijasĶīnas tirgiFaktoru ieguldīšanaPortfeļa veidošana
ProRealCode

This note describes a way to rescale the Stochastic Momentum Index (SMI) against its recent volatility. It first computes the SMI, then forms upper and lower bands around a 24-period exponential moving average using two standard deviations. The current SMI’s…

Tehniskie indikatoriSvārstīgumsCenas impulss
vn.py community

This brief forum post advocates managing market data as files rather than relying solely on a database, particularly when handling large volumes of tick data. The author shares a personal approach using Parquet files and points readers to an implementation…

Tirgus mikrostruktūraRīkojumu izpilde
SuperMind

This A-share stock screen combines three filters: reported net buying above 5% for the day, three consecutive declining sessions, and a 20-day moving average above the 120-day moving average. The article interprets net buying as possible institutional…

AkcijasTehniskie indikatoriAtgriešanās pie vidējās vērtībasĶīnas tirgi
SuperMind

This stock-selection idea combines a daily turnover rate between 3% and 12%, a reversal pattern described as a price move that recovers after a decline, and a positive daily MACD reading. The article presents the combination as a way to find stocks showing…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This note describes a simple stock screen built around the 5-, 10-, 20-, 30-, and 60-day moving averages converging. It interprets convergence as a period of price balance that may precede a change in direction, and proposes using the signal to identify…

AkcijasTehniskie indikatoriSekošana tendencei
SuperMind

The post proposes a Chinese equity screen combining a positive MACD reading, positive price change and net large-order flow, and a positive but capped ten-day gain. It gives formulas for MACD, daily price change, large-order net volume, and the ten-day…

Ķīnas tirgiAkcijasCenas impulssTehniskie indikatori
FMZ guides

This guide surveys the languages and visual tools available for building trading strategies on FMZ, including JavaScript, TypeScript, Python, Rust, C++, My language, Pine, Blockly, and Workflow. It describes selected platform features: JavaScript…

Vēsturisko datu pārbaudeRīkojumu izpildeTehniskie indikatori
MQL5 code base

This indicator description explains a way to compare the movements of seven major currencies against the US dollar. Each series is rebased to a common starting point, allowing changes over the selected period to be viewed on a shared relative scale. An…

Valūtu tirgusTehniskie indikatori
vn.py community

The post asks why Alpha158 labels use different forward-return horizons in two implementations. It compares a label spanning the close at T+1 to the close at T+3 with a Qlib label spanning T+1 to T+2, then relates those choices to China’s T+1 stock-trading…

Ķīnas tirgiAkcijasVēsturisko datu pārbaudeMašīnmācīšanās