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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
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

FMZ forum

This beginner tutorial explains why a live trading system may need to collect its own candlestick history. Some exchanges provide candle data directly, while others may not. The author distinguishes live use from testing: the platform supplies historical…

Rīkojumu izpildeTirgus mikrostruktūraKriptoaktīvi
Amberdata research

This podcast recap discusses Rated’s work on Ethereum proof-of-stake infrastructure data. Validator assessment uses real-time and historical measures such as uptime, efficiency, and protocol adherence to give operators context for improving performance. The…

KriptoaktīviDeFiBlokķēdes datiStatistika
ProRealCode

The document describes a modified Aroon oscillator intended to react more quickly to trend changes while smoothing noise. It starts from the difference between Aroon Up and Aroon Down, applies an exponential moving average, and tests a range of gain values…

Tehniskie indikatoriSekošana tendenceiAtgriešanās pie vidējās vērtībasStatistika
SuperMind

This post describes a basic A-share momentum screen that excludes Beijing-listed stocks and selects for daily amplitude above 1% and a closing price at the two-day high. It frames amplitude and market location as filters and the recent price high as a…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This post presents a daily, end-of-session A-share selection rule: retain stocks with MACD above zero and turnover between 3% and 12%, then rank them by market heat. It describes positive MACD as a trend filter and heat as a way to identify stocks attracting…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
SuperMind

This document describes a short-term A-share screen combining turnover, recent price declines, and limit-up activity. It selects stocks with turnover between 3% and 12%, three consecutive falling sessions, and more than two limit-up days within the prior ten…

AkcijasĶīnas tirgiCenas impulssTehniskie indikatori
MQL5 code base

The document critiques trend lines built from DeMark pivot points or Bill Williams fractals when key points are identified using only a minimum-bar rule. It proposes removing that minimum and defining a point's dimension as the smallest count of bars on…

Tehniskie indikatoriSekošana tendenceiNākotnes līgumiVēsturisko datu pārbaude
SuperMind

The article proposes screening stocks for a daily price range above 1%, no limit-up close on the previous day, and a positive gain over the preceding ten days below 35%. It presents the range as a way to find more active shares and treats the prior-day…

AkcijasĶīnas tirgiCenas impulssSvārstīgums
SuperMind

This stock-selection screen combines turnover, order-book balance, and share price. It selects listed mainland Chinese stocks with turnover between 3% and 12%, first-level bid volume greater than first-level ask volume, and a latest price below 12 yuan. The…

AkcijasĶīnas tirgiTirgus mikrostruktūraTehniskie indikatori
ProRealCode

The document describes an indicator that compares recent volatility with a longer-term volatility baseline. It calculates standard deviations of close-to-close momentum over short and long lookback periods, then divides the short-period value by the…

SvārstīgumsTehniskie indikatoriStatistika
BigQuant

This brief platform support exchange addresses why a historical-data call for the CSI 300 index is not recognized. The response says the newer backtest engine retrieves data through SQL and suggests using the platform’s data interface to obtain index data…

AkcijasĶīnas tirgiVēsturisko datu pārbaude
FMZ forum

The essay cautions against treating a single factor as a reliable cause of an investment outcome. It uses stock reactions to restructuring announcements to show that the same news can be welcomed in a bull market and ignored or sold in a weak market. It also…

StatistikaRiska pārvaldībaAkcijas
SuperMind

This document outlines a Chinese-equity screen requiring a stock to belong to the metaverse theme, have positive net buying attributed to major participants during the auction, and show a KDJ K value below 20. The post interprets the KDJ threshold as a weak…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas impulss
SuperMind

This document describes an intraday screen for Chinese equities. Its stated filters are turnover between 3% and 12%, at least one limit-up event in the previous 25 days, and exclusion of special-treatment stocks. It aims to identify candidates before 10 a.m.…

Ķīnas tirgiAkcijasTehniskie indikatoriCenas izrāviens
SuperMind

This screen looks for metaverse-related stocks whose turnover is between 3% and 12% and whose candles have closed down for seven consecutive sessions. The document describes the setup as a way to find companies in the metaverse theme after a sustained…

AkcijasĶīnas tirgiAtgriešanās pie vidējās vērtībasTehniskie indikatori
MQL5 code base

The proposed screen selects stocks with turnover between 3% and 12%, a positive product of the daily price change and net volume attributed to very large orders, and a close above the Bollinger upper band. Its stated rationale is to combine active trading…

AkcijasTehniskie indikatoriCenas impulssTirgus mikrostruktūra
SuperMind

This system combines the direction of an X-day average of closing prices with price comparisons over two lookback intervals. A buy setup requires the average to be higher than it was Y days earlier, while the latest close is below its level Y days earlier…

AkcijasSekošana tendenceiAtgriešanās pie vidējās vērtībasTehniskie indikatori
SuperMind

This stock screen targets companies classified in the metaverse industry. It selects shares where the KDJ indicator has just crossed upward and turnover is between 2% and 9%, with eligible securities checked before 10 a.m. for that day's trading. The…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
SuperMind

This note proposes screening Chinese stocks for prior-day trading-list appearances with buy amounts greater than sell amounts, an amplitude threshold, and membership in a beverage or alcohol-related industry. It presents the combination as a way to capture…

AkcijasTirgus mikrostruktūraĶīnas tirgiTehniskie indikatori
SuperMind

This note describes a short-term Chinese stock screen using three conditions: amplitude above a stated threshold, a rising-bottom pattern, and more than two limit-up days within a ten-day window. Its stated rationale is to find shares with strong recent…

AkcijasCenas impulssTehniskie indikatoriĶīnas tirgi
SuperMind

This Chinese stock-screening note combines a 14-period RSI threshold below 65 with a recent candle pattern, then ranks qualifying shares by auction value and selects the top five. The stated rationale is to pair a technical condition described as oversold…

AkcijasTehniskie indikatoriĶīnas tirgiVēsturisko datu pārbaude
SuperMind

This article outlines a process for developing equity selection rules, from finding market examples and forming a hypothesis to implementing factors, running an initial backtest, reviewing losses, and deciding whether to adjust the logic. It proposes several…

AkcijasĶīnas tirgiTehniskie indikatoriVēsturisko datu pārbaude