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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
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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
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Amberdata research
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FMZ forum
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FMZ digest
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vn.py community
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QuantInsti blog
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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
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Binance API docs
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FMZ guides
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pysystemtrade
Dokumentu skaits: 34
Freqtrade docs
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quant-trading
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FinRL
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Zipline
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FMZ live strategies
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Jesse
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pyfolio
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Alphalens
Dokumentu skaits: 14
WonderTrader
Dokumentu skaits: 14
backtesting.py
Dokumentu skaits: 11
Technical Analysis
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QTPyLib
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QuantRocket
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Lumibot strategies
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Awesome Quant
Dokumentu skaits: 1

Meklēt bibliotēkā

Dokumentu skaits: 79,386

MQL5 code base

This Expert Advisor uses the Kolier SuperTrend indicator with moving-average crossings to generate trade entries. A signal is acted on when the bar closes and a square of the corresponding color appears. The description specifies that the EA relies on the…

Valūtu tirgusTehniskie indikatoriSekošana tendenceiVēsturisko datu pārbaude
SuperMind

This Chinese stock-screening proposal combines an amplitude filter, simultaneous bullish crosses among three moving averages, and a condition that the prior close be above its 250-day moving average. It presents the setup as a way to find stocks with recent…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
MQL5 code base

This document describes a basic MetaTrader 4 Expert Advisor that trades using the Stochastic oscillator. Its indicator parameters can be changed through the EA inputs, letting learners explore how different settings affect its signals. The text frames the…

Valūtu tirgusTehniskie indikatoriVēsturisko datu pārbaude
SuperMind

This Chinese equity screen looks for stocks in the metaverse sector that closed above their 250-day moving average on the previous day and had at least one limit-up event during the prior month. The long moving average acts as a price-trend filter, while the…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
MQL5 code base

The document describes the Oracle trading indicator as a forecasting tool that redraws its values four bars ahead. It notes that the indicator’s strong promotional description is disputed, and that redrawing makes its apparent past signals difficult to…

Tehniskie indikatoriValūtu tirgus
SuperMind

This stock screen combines three filters: a daily high-to-low range above 1% of the previous close, a ticker beginning with 60, and a prior-day main-fund flow condition. The accompanying indicator formula and Python example express the flow condition as a…

AkcijasĶīnas tirgiSvārstīgums
SuperMind

This Chinese equity screening rule selects stocks from 2021 with a 9:25 a.m. price rise below 6%, then ranks them by capital strength from highest to lowest. The stated goal is to favor the highest-ranked names after applying those two filters. The document…

AkcijasĶīnas tirgi
vn.py community

This VeighNa forum exchange discusses how to obtain current account funds through the CTP trading interface. A user asks whether account balances can be retrieved synchronously, like an HTTP request, rather than through asynchronous updates. A reply points…

Nākotnes līgumiRīkojumu izpildeTirgus mikrostruktūra
SuperMind

This Chinese-language post outlines an equity screen requiring price amplitude above 1, a high equal to the highest high of the current and previous day, and at least one limit-up event during the prior 25 days. It frames the conditions as a way to find…

AkcijasSvārstīgumsCenas impulssCenas izrāviens
SuperMind

This Chinese-language post describes an equity screen combining a volatility condition, at least one daily gain of 10% or more in the prior 25 trading days, and a stock concentration measure below 20%. It also proposes adding fundamental and valuation…

AkcijasCenas impulssSvārstīgumsTehniskie indikatori
MQL5 code base

This short description presents a Fast Stochastic oscillator variant that aims to reduce noise and lets users select the indicator timeframe through an input parameter. The example timeframe is four hours. It also notes that the indicator depends on a…

Tehniskie indikatoriNākotnes līgumi
backtesting.py

This tutorial shows how to build a long-only moving average crossover strategy by combining reusable strategy components from a Python backtesting library. It turns the relationship between a short and a longer moving average into entry signals, allocates…

AkcijasSekošana tendenceiTehniskie indikatoriRiska pārvaldība
SuperMind

This stock selection rule combines a turnover range of 3% to 12%, three consecutive declining sessions, and a reported control ratio above 21%. The article frames the high control ratio as a sign of concentrated holdings or buying by large investors, while…

AkcijasĶīnas tirgiTehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

This document proposes a stock screen requiring a daily price amplitude above a stated threshold, MACD above its zero line, and membership in the metaverse concept group. It presents the concept theme as an additional selection dimension and gives indicator…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
TqSdk

This reference explains advanced order instructions for futures and options trading through TqSDK. It compares ordinary limit orders, FAK orders that cancel any unfilled remainder, and FOK orders that cancel unless the full quantity can execute immediately.…

Rīkojumu izpildeNākotnes līgumiOpcijasTirgus mikrostruktūra
SuperMind

This document outlines an equity screen combining a metaverse industry classification, an arc-shaped price pattern, and shortening green bars in a 15-minute MACD histogram. Its accompanying formula also applies price-range and moving-average conditions,…

AkcijasTehniskie indikatoriĶīnas tirgiRiska pārvaldība
SuperMind

This note describes an A-share screening approach that combines a daily high-low range greater than one percent, at least one limit-up session during the previous 25 days, and current volume above its 21-day average. The accompanying Python example adds a…

AkcijasTehniskie indikatoriCenas impulssSvārstīgums
BigQuant

This meetup page collects questions about quantitative trading on the BigQuant platform. Topics include searching for holding-period parameters in a default stock-ranking template, defining reusable Python modules, and building a workflow for developing…

AkcijasMašīnmācīšanāsVēsturisko datu pārbaudeStatistika
SuperMind

This note presents an A-share stock screen combining a daily trading-range threshold, at least one limit-up session in the prior 25 days, and current volume above its 21-day average. Its sample formulas also add a condition that the current low is close to…

AkcijasTehniskie indikatoriCenas impulssSvārstīgums
SuperMind

This A-share stock-selection rule looks for daily amplitude above one, large-order net volume above 0.05 for at least three consecutive days, current volume above 10,000 lots, and an opening price higher than the previous close. The document frames these…

AkcijasTehniskie indikatoriTirgus mikrostruktūraĶīnas tirgi
Qlib

This configuration describes a Qlib machine-learning workflow that trains a CatBoost regression model on Alpha158 features for CSI 300 instruments. It defines separate training, validation, and test periods, then records signal analysis and portfolio…

AkcijasMašīnmācīšanāsVēsturisko datu pārbaudePortfeļa veidošana
SuperMind

This A-share stock screen combines a positive MACD reading, positive price-to-earnings ratio, and an opening gap between -2% and 5% relative to the previous close. The document presents MACD above zero as a trend filter, positive P/E as a basic valuation…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This stock-screening proposal selects companies assigned to the metaverse industry, displaying a rounded price pattern, with the opening price less than 6% above the previous close. It frames the price-shape condition as a custom indicator and uses the…

AkcijasTehniskie indikatoriĶīnas tirgiCenas impulss
BigQuant

This article proposes a defensive equity strategy that seeks oversold rebounds or bounces after a pullback. It draws inspiration from research on money-flow factors, including inflow, outflow, net institutional flow, and opening net flow, and proposes…

AkcijasAtgriešanās pie vidējās vērtībasFaktoru ieguldīšanaMašīnmācīšanās