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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: 79,386

Hummingbot docs

This overview explains controllers as reusable, configurable components in Hummingbot Strategy V2. A controller receives market data such as order books, trades, and candles, then emits actions that direct a parent script to create or stop executors.…

Tirgus veidošanaArbitrāžaRežģa tirdzniecībaRīkojumu izpilde
SuperMind

This note proposes a short-term A-share screen requiring price amplitude above 1%, a daily decline between 4% and 5%, and a sequence of higher recent lows. The rising-low condition is intended to identify stocks whose short-term price floor is moving upward…

AkcijasĶīnas tirgiTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

This note outlines an A-share stock screen based on daily price amplitude above 1%, a share price of 18.5 yuan, and a rising K value from the KDJ stochastic indicator. It presents the amplitude threshold as a way to find stocks with notable price movement…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This note describes a daily A-share stock screen combining three filters: MACD above its zero line, a share price below 12 yuan, and previous-day trading value above 60 million yuan. It says the screen is run before the market opens and presents the turnover…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
MQL5 code base

This expert advisor combines a moving average with MACD to open trades and add to losing positions. It checks for signals or additions when a new bar appears. A sample buy setup requires MACD below zero, its main line above its signal line, and price above…

Valūtu tirgusTehniskie indikatoriPozīcijas apjoma noteikšanaRiska pārvaldība
BigQuant

This Chinese-language event listing outlines a dynamic trading approach for timing exchange-traded funds. It identifies three components: selecting a pool of highly liquid ETFs, ranking candidates with multiple momentum dimensions, and adjusting the approach…

AkcijasCenas impulssTehniskie indikatoriRīkojumu izpilde
Kraken Learn

Impermanent loss is the reduction in a liquidity provider’s pool value relative to simply holding the deposited assets. The document explains the setting: an automated market maker holds two assets in a smart-contract pool, and traders’ swaps change their…

KriptoaktīviDeFiTirgus mikrostruktūra
BigQuant

This Chinese equity market report summarizes sector performance, index and industry valuations, market breadth, fund positioning, and an intermediate-term trend model. It reports that building materials, agriculture and forestry, utilities, light…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
Qlib

This configuration describes a Qlib experiment using a graph attention model, GATs, with an LSTM base model to predict near-term returns for CSI 300 constituents. It sets Chinese market data, defines a close-to-close forward return label, normalizes features…

AkcijasĶīnas tirgiMašīnmācīšanāsVēsturisko datu pārbaude
SuperMind

This post presents a Chinese equity screen based on price amplitude above 1%, excluding Beijing-listed shares, and auction turnover above 0.26%. Its proposed refinement also filters for prices within 2% of a 60-day moving average and adds positive valuation…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This post outlines a Chinese stock screen using daily amplitude, a reversal-style candle condition, and a fixed closing price of 18.5 yuan. It provides both an indicator formula and Python example, with the latter also invoking candlestick pattern functions.…

AkcijasĶīnas tirgiTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

This post describes a Chinese equity screen combining daily price movement, trading activity, and valuation. It selects stocks with amplitude above 1%, current volume above 10,000 lots, a higher open, and Shenzhen main-board listing, while requiring…

AkcijasĶīnas tirgiSvārstīgumsFaktoru ieguldīšana
SuperMind

The document proposes screening equities for a daily high-to-low range above one percent, a reversal or engulfing-style pattern, and then sorting selected names by a popularity measure. It frames range as a way to find volatile stocks, the pattern as a…

AkcijasTehniskie indikatoriSvārstīgumsTirgus noskaņojums
MQL5 code base

This brief note describes a version of a modified optimum elliptic filter indicator that adds a user-selectable chart timeframe. The example default is a four-hour period, while the input is intended to let a trader choose another timeframe for the…

Tehniskie indikatori
SuperMind

The document describes a stock screen combining membership in the metaverse sector, a minimum circulating market capitalization, and weekly MACD above the zero line. Its stated rationale is to find larger companies in that sector whose trend indicator is…

AkcijasTehniskie indikatoriSekošana tendenceiĶīnas tirgi
MQL5 code base

The indicator measures each candle’s body relative to its full range, using the ratio to classify candles as strong, weak, or neutral. It presents the current candle’s body and wick proportions alongside a lookback summary of average body ratio and…

Tehniskie indikatoriCenas impulssStatistika
SuperMind

This equity screen looks for stocks with turnover in a specified range, a rising K value from the KDJ indicator, and greater displayed volume at the best bid than at the best ask. The article explains these as filters for trading activity, short-term…

AkcijasTehniskie indikatoriTirgus mikrostruktūra
SuperMind

This stock-screening idea combines daily range, a rising-bottom condition, and three consecutive declining closes. The article also gives a more specific indicator version using trend and Bollinger Band filters, then proposes selling when price or a candle…

AkcijasTehniskie indikatoriAtgriešanās pie vidējās vērtībasRiska pārvaldība
vn.py community

This forum question examines why changing the initialization length of a trading system’s ArrayManager can materially alter a backtest. The strategy uses RSI generated through TA-Lib, and the author suspects that the indicator’s path dependence makes its…

Vēsturisko datu pārbaudeTehniskie indikatoriRiska pārvaldībaStatistika
SuperMind

This post describes an A-share stock screen combining a daily price-amplitude threshold, a nonempty convertible-bond name field, and a company classification filter that can be configured for criteria such as industry or state ownership. It proposes ranking…

AkcijasĶīnas tirgiFaktoru ieguldīšanaTehniskie indikatori
BigQuant

This short Chinese-language note defines quantitative investing as using programs to invest based on collecting and analyzing substantial market data. It presents automation as a way to respond to market changes more quickly, follow a consistent process, and…

MašīnmācīšanāsStatistikaVēsturisko datu pārbaudeRiska pārvaldība
Amberdata research

The recap compares Bitcoin and Ethereum options markets through realized and implied volatility, term structures, skew, and relative gamma pricing. It describes BTC shifting into contango as front-end implied volatility falls more sharply than longer-dated…

KriptoaktīviOpcijasSvārstīgumsAtvasināto instrumentu cenu noteikšana
SuperMind

This stock-selection proposal combines three filters: RSI below 65, year-over-year growth in net profit attributable to parent-company shareholders above 20% and no greater than 100%, and exclusion of stocks that hit the daily limit-up on the prior day. It…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
MQL5 code base

This document describes a utility script for viewing open forex positions’ profit or loss in pips. It says the tool does not place or close trades, and reports four outputs: aggregate pip P&L across positions, the pip result for each position, the sum of…

Valūtu tirgusRiska pārvaldība