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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
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

MQL5 code base

This short indicator note introduces William Blau’s double-smoothed stochastic, attributing it to a 1990 article. It identifies the calculation’s inputs as the current close, the lowest low and highest high over a lookback period, and exponential moving…

Tehniskie indikatoriCenas impulssStatistika
Kraken Learn

This beginner’s guide explains futures grid trading bots, which place long and short orders at preset price levels around a contract price. The approach aims to capture repeated movements within a range by systematically buying and selling, rather than…

KriptoaktīviNākotnes līgumiRežģa tirdzniecībaRiska pārvaldība
BigQuant

The document describes Temporal Routing Adaptor (TRA), a way to extend a stock prediction model so it can learn from different patterns in market data. It notes that momentum and reversal behavior may coexist, which challenges the assumption that…

AkcijasMašīnmācīšanāsStatistikaPortfeļa veidošana
BigQuant

The document answers how to allocate weights across strategies in a multi-strategy backtest. Its proposed workflow is to extract each strategy’s daily return series and use an optimization package to find portfolio weights. This frames the task as portfolio…

Portfeļa veidošanaVēsturisko datu pārbaudeStatistika
Qlib

Qlib separates forecasting signals from portfolio construction. A strategy turns prediction scores into trading decisions, while a weight-based base class lets users specify target holdings and delegates order generation to the framework. The documented…

Portfeļa veidošanaVēsturisko datu pārbaudeRīkojumu izpildeRiska pārvaldība
SuperMind

This Chinese-market stock screen combines three conditions: turnover between 3% and 12%, an opening price within 5% of the 10-day average closing price, and more than two limit-up days during the past 10 days. It is aimed at finding active stocks whose…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This post proposes screening stocks that have at least two limit-up sessions within 500 days and five moving averages described as overlapping. It interprets the moving-average condition as a possible sign of nearby support and resistance, and repeated…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This Chinese-language post outlines an equity screening rule that combines MACD above zero with a candlestick-pattern condition and a company characteristic. It presents the combination as a way to identify stocks with upward trend potential, while warning…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
Amberdata research

The article explains how leveraged perpetual futures positions can be liquidated when traders fail to meet maintenance margin requirements. It treats liquidation data as forced buy or sell order flow that may reveal short-term market pressure, and describes…

KriptoaktīviPerpetuālie nākotnes līgumiTirgus mikrostruktūraVēsturisko datu pārbaude
MQL5 code base

The document introduces a color-histogram implementation of William Blau’s Q-period Stochastic Index, an indicator described in his book on momentum, direction, and divergence. It identifies the indicator’s general form and points to a smoothing-algorithm…

Tehniskie indikatoriCenas impulss
MQL5 code base

This expert advisor monitors open positions across symbols and magic numbers. After a position has been open for a configurable number of seconds, it checks whether profit has reached a configured threshold in points. If the threshold is met, the advisor…

Rīkojumu izpildeRiska pārvaldībaPozīcijas apjoma noteikšana
ProRealCode

The document explains a trend indicator attributed to Andrew Abraham’s 1998 article. It defines trend direction using a trailing level built from a weighted average of true range. True range is the largest of the current high-low range and the gaps from the…

Sekošana tendenceiSvārstīgumsTehniskie indikatoriRiska pārvaldība
MQL5 code base

The expert advisor combines MACD divergence with stochastic confirmation and Bollinger Band trade exits. For buys, the stochastic main line must be above its signal line and remain within the configured oversold range for a specified candle period. The sell…

Tehniskie indikatoriValūtu tirgusRiska pārvaldība
MQL5 code base

This short listing describes XWAMI_HTF, a version of the XWAMI indicator with a selectable chart timeframe in its input settings. The example default is a four-hour period, indicating that users can choose the timeframe on which the indicator operates. It…

Tehniskie indikatori
Amberdata research

This article outlines factors to assess before depositing token pairs into a decentralized exchange liquidity pool. Liquidity providers receive a share of swap fees, generally represented by redeemable pool tokens, and some pools may also distribute…

DeFiRiska pārvaldībaSvārstīgumsVēsturisko datu pārbaude
Lumibot

This example describes a concentrated long-only stock portfolio built through a sequence of AI agents. A research agent ranks companies for understandable businesses, cash generation, and attractive prices. A second agent challenges each idea by examining…

AkcijasMašīnmācīšanāsPortfeļa veidošanaVēsturisko datu pārbaude
SuperMind

This proposed A-share stock screen combines market activity, company size, profitability, and recent price action. It selects stocks with turnover between 3% and 12%, market capitalization below 10 billion yuan, positive income, and at least one limit-up…

AkcijasCenas impulssCenas izrāviensĶīnas tirgi
Stratmill research code

This code excerpt implements three filters intended to support spread trading and risk adjustment. The correlation filter calculates rolling correlation between the first two series, rescales it to a zero-to-one range, and uses changes in that measure to…

Pāru tirdzniecībaSvārstīgumsRiska pārvaldībaVēsturisko datu pārbaude
SuperMind

This Chinese course listing outlines a study of A-share stocks that reach their daily upper price limit. Its stated sequence is to explain the limit-up mechanism, classify limit-up events, examine subsequent stock returns, and then apply a support vector…

AkcijasMašīnmācīšanāsCenas izrāviens
MQL5 code base

This document describes a chart indicator that displays trend direction and trade signals derived from the UltraWPR indicator on a selected bar. It uses a colored background: pale shades mark trend continuation, while brighter shades distinguish buy and sell…

Tehniskie indikatoriSekošana tendencei
SuperMind

This proposed stock screen combines amplitude above 1, institutional participation, and year-over-year growth in net profit attributable to parent-company shareholders above 20% and at most 100%. The final criteria specify institutional participation above…

AkcijasĶīnas tirgiSvārstīgumsCenas impulss
SuperMind

This post proposes screening A-share stocks for turnover between 3% and 12%, market value below 10 billion yuan, scale above 200 million yuan, and no losses. It presents the screen as a way to combine trading activity, company size, and profitability, then…

AkcijasĶīnas tirgiFaktoru ieguldīšanaVēsturisko datu pārbaude
MQL5 code base

This document outlines a proposed position-sizing engine for algorithmic trading. It combines Kelly sizing, which uses estimated win rate and payoff ratio, with volatility adjustment based on Average True Range and tick value. The stated goal is to reduce…

Riska pārvaldībaPozīcijas apjoma noteikšanaSvārstīgums