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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

SuperMind

This document explains the Simple Harmonic Oscillator (SHO), a bounded indicator intended to estimate market-cycle periods over short and intermediate horizons. It describes a centerline as a balance between bullish and bearish periods, with outer levels…

Tehniskie indikatoriSekošana tendenceiAtgriešanās pie vidējās vērtībasVēsturisko datu pārbaude
SuperMind

This post describes a Chinese equity screen combining recent large-order net buying, a high current-day position increase, and a historical dividend ratio threshold. It presents the flow conditions as signs of investor interest and the dividend filter as a…

AkcijasĶīnas tirgiTirgus noskaņojumsTehniskie indikatori
BigQuant

The document describes a basic workflow for evaluating a trained quantitative model. After fitting the model on training data, apply it to a validation set, then compare its predictions with the observed values to assess performance. This separates model…

MašīnmācīšanāsVēsturisko datu pārbaudeStatistika
Amberdata research

This podcast recap discusses how AI agents may interact with crypto assets and decentralized applications, alongside a vision for regulated DeFi that connects conventional banking with self-custodied digital assets. The guest describes agents as systems that…

KriptoaktīviDeFiMašīnmācīšanāsAtvasināto instrumentu cenu noteikšana
MQL5 code base

This expert-advisor design turns four RSI readings into a single weighted perceptron score. It uses RSI periods of 12, 36, 108, and 324, rescales each indicator around zero, and combines them with weights selected through optimization. The trading threshold…

Valūtu tirgusMašīnmācīšanāsTehniskie indikatoriSekošana tendencei
BigQuant

This research summary explains how to build a machine-learning stock-selection process using historical factor values to predict subsequent returns. In the training stage, a supervised model learns the relationship between inputs and returns; in the testing…

AkcijasMašīnmācīšanāsFaktoru ieguldīšanaVēsturisko datu pārbaude
SuperMind

This Chinese-language post describes a daily stock screen combining turnover, recent price direction, prior-day trading value, and limit-up status. It selects stocks with turnover between 3% and 12%, three consecutive declining sessions, and prior-day…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This stock-selection idea combines three technical conditions: at least five moving averages clustered together, positive returns, and more than two limit-up sessions within a ten-day window. The post interprets clustered averages as possible evidence of…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
MQL5 code base

This MQL5 demonstration illustrates supervised classification with a support vector machine (SVM), using a fictional animal-recognition task to explain labeled examples and learned decision boundaries. It generates seven-feature observations with rule-based…

MašīnmācīšanāsStatistikaVēsturisko datu pārbaude
SuperMind

This stock-selection proposal combines three filters: daily amplitude above one percent, a proxy for afternoon large-order net inflow, and a gain below six percent at the 9:25 observation. The stated aim is to find shares with notable movement and buying…

AkcijasĶīnas tirgiTehniskie indikatoriTirgus mikrostruktūra
SuperMind

The post outlines a Chinese equity screening rule combining three conditions: prior-session price amplitude above one percent, tradable share float no greater than 5.5 billion shares, and a positive prior-session main-fund control reading. It frames these…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
pysystemtrade

The document explains an exponentially weighted moving average crossover (EWMAC) forecast. It subtracts a slower exponential moving average of price from a faster one, then divides that difference by daily price volatility. A positive or negative result…

Nākotnes līgumiSekošana tendenceiCenas impulssSvārstīgums
MQL5 code base

The document describes a trend oscillator that estimates the dominant direction of candlestick closing prices over a selected period. It identifies two user settings: the lookback period and a calculation method. This positions the indicator as a way to…

Tehniskie indikatoriSekošana tendencei
MQL5 code base

The note describes a way to smooth a relative strength index: apply Jurik-style smoothing to prices before calculating RSI. The stated motivation is to reduce false signals while keeping the result responsive to market changes. It presents the smoothed RSI…

Tehniskie indikatoriCenas impulss
SuperMind

The proposed stock screen selects shares whose turnover rate is between 3% and 12%, that were listed in the current year, and whose actual turnover on the referenced prior day is between 3% and 28%. The article frames these conditions as a way to find…

AkcijasTehniskie indikatoriRīkojumu izpildeRiska pārvaldība
SuperMind

This stock screen combines three technical conditions: overlap among the 5-, 10-, 20-, 60-, and 120-day moving averages; a concentration measure subject to a stated threshold; and shortening green bars in the 15-minute MACD histogram. The document describes…

AkcijasTehniskie indikatoriCenas impulssSekošana tendencei
MQL5 code base

The document describes a price gap indicator that displays gaps as a histogram. It assigns red bars to upward gaps, which it suggests may fill downward, and blue bars to downward gaps, which it suggests may fill upward. The proposed gap-filling direction is…

Tehniskie indikatoriAtgriešanās pie vidējās vērtībasVēsturisko datu pārbaude
ProRealCode

The SSL Hybrid combines several moving average channels with ATR bands to show trend direction, possible continuation entries, exits, and volatility. SSL1 acts as the baseline trend signal: its color indicates bullish or bearish conditions, while a neutral…

Tehniskie indikatoriSekošana tendenceiSvārstīgumsRiska pārvaldība
MQL5 code base

This indicator defines a modified Detrended Price Oscillator as the closing price minus a moving average. Users can adjust the moving average period, calculation method, and applied price, allowing them to change the resulting curve. The description says…

Tehniskie indikatoriAtgriešanās pie vidējās vērtībasSekošana tendencei
MQL5 code base

This document describes a configurable chart indicator for identifying bullish and bearish divergence between price and an oscillator. It also includes hidden divergence, support and resistance lines, and optional channel displays. Users can select from a…

Tehniskie indikatoriCenas impulssCenas izrāviens
Stratmill research code

This helper prepares spread changes and their lagged values as inputs for a regression model. It can expand the lag features with pairwise products, split a chosen in-sample period into ordered training and test sets, and keep a separate out-of-sample…

MašīnmācīšanāsStatistikaVēsturisko datu pārbaudePāru tirdzniecība
SuperMind

This Chinese A-share screening proposal filters for stocks with an intraday range above 1% during 2021, then keeps observations where price change multiplied by an estimate of very large order flow is positive. The intended interpretation is that volatility…

AkcijasĶīnas tirgiTirgus mikrostruktūraSvārstīgums
ProRealCode

This indicator method turns a stair-step moving average into the center of an oscillator. It updates the trend center when a triangular moving average moves beyond a configurable percentage threshold; otherwise, the prior center is retained. A short simple…

Nākotnes līgumiTehniskie indikatoriAugstas frekvences tirdzniecībaSekošana tendencei