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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 stock-selection method screens Chinese equities using three filters: a 14-period RSI below 65, a ten-day price gain above zero but below 35%, and a ranking by individual-stock popularity. The accompanying Python example additionally considers stocks…

AkcijasTehniskie indikatoriCenas impulssĶīnas tirgi
BigQuant

This analysis compares analyst forecast data from two Chinese financial data providers, examining report coverage, forecast accuracy, and the usefulness of forecast-related factors in stock selection. One provider is described as covering more stocks, while…

AkcijasFaktoru ieguldīšanaStatistikaĶīnas tirgi
SuperMind

A forum post asks how to retrieve popular industry indices through iWencai and pass them into a variable. The author describes a query combining industry indices with weekly KDJ conditions and recent main-fund-flow filters, then reports that a Python query…

Ķīnas tirgiAkcijasVēsturisko datu pārbaude
ProRealCode

This indicator marks upward and downward breakout signals by comparing the Force Index, calculated from closing prices, with Bollinger Bands applied to that index. A reading at or above the upper band produces a positive signal shown in green; a reading at…

Tehniskie indikatoriCenas izrāviensCenas impulss
MQL5 code base

ColorBears presents Bears Power as a colored histogram, with an option to choose Open, Close, High, or Low prices for its calculation. It also smooths the resulting indicator, allowing users to view a less jagged series. The document describes the…

Tehniskie indikatori
BigQuant

This article introduces support vector machines for classification and regression, then applies them to A-share stock selection. It explains the maximum-margin principle for linear SVMs, slack variables for imperfectly separable observations, and kernel…

AkcijasMašīnmācīšanāsStatistikaVēsturisko datu pārbaude
SuperMind

This tutorial explains how support vector machines classify data by finding a boundary with a wide margin, and how slack variables allow some classification errors in noisy data. It introduces kernel methods as a way to handle nonlinear boundaries by…

AkcijasMašīnmācīšanāsStatistikaVēsturisko datu pārbaude
MQL5 code base

This expert advisor is built on the idea that price crossing a moving average and traveling a specified distance may continue in that direction. It places Buy Stop and Sell Stop pending orders, then updates their distance from a long-period moving average at…

Valūtu tirgusSekošana tendenceiCenas izrāviensRīkojumu izpilde
SuperMind

This note describes a daily stock screen combining MACD above zero, a share price below 12 yuan, and three consecutive declines in closing price. It interprets the MACD condition as a positive trend context and the recent losses as a possible short-term…

AkcijasTehniskie indikatoriAtgriešanās pie vidējās vērtības
Hyperliquid docs

The document explains manual borrowing of USDC or USDT against supplied HYPE or BTC collateral for supported Hyperliquid account types. Borrow capacity is calculated from collateral quantity, oracle price, and the asset's loan-to-value ratio, with…

KriptoaktīviRiska pārvaldībaAtvasināto instrumentu cenu noteikšana
BigQuant

The document outlines a factor attribution framework for evaluating active equity funds within a fund of funds (FOF). It separates returns into broad risk exposures, such as market, style, and industry effects; alpha-factor contributions from technical and…

Faktoru ieguldīšanaAkcijasPortfeļa veidošana
MQL5 code base

The document describes an indicator that identifies a flat market from the horizontal position of a rounded moving average. It uses that condition to draw a channel, marking possible support and resistance levels for price. The concept is to use a smoothed…

Tehniskie indikatoriAtgriešanās pie vidējās vērtības
SuperMind

This stock-selection rule combines three filters: daily price range greater than 1%, closing price below 20, and prior-day trading value above 60 million. The article interprets the range as a sign of price movement and the trading-value threshold as a…

AkcijasĶīnas tirgiTehniskie indikatoriRiska pārvaldība
SuperMind

This Chinese equity screen looks for stocks in the metaverse sector whose prior-day price is above the 250-day moving average while MACD was below zero two days earlier. The intended combination is sector exposure, a long-term price trend filter, and a…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

This stock screen combines a turnover range of 3% to 12%, appearance on the prior day’s market leaderboard, and a stated intraday drawdown between 4% and 5%. The article frames turnover as a liquidity filter, leaderboard presence as a sign of market…

AkcijasĶīnas tirgiTehniskie indikatoriRiska pārvaldība
MQL5 code base

This document describes an indicator built from a single simple moving average that displays a channel on a chart. Users can choose between two plot styles: lines or bars. The indicator is presented as a visual way to classify the prevailing direction of a…

Tehniskie indikatoriSekošana tendencei
SuperMind

This note proposes a short-term Chinese equity screen using three conditions: a price-range measure above 1, a 9:25 price rise below 6%, and a previous-day 9:15 matched price associated with a limit-down event. It frames the filters as a combination of…

AkcijasTehniskie indikatoriTirgus noskaņojumsĶīnas tirgi
TqSdk

This documentation explains how to run a TqSdk strategy over historical data without changing its core logic, and how to retrieve trade logs and account statistics when the simulation ends. It describes catching a backtest-finished event, accessing summary…

Vēsturisko datu pārbaudeNākotnes līgumiAkcijasRīkojumu izpilde
SuperMind

This note describes a Chinese stock selection screen that combines a daily price-range condition, five consecutive years of return on equity above 15%, and a limit on tradable share count. It presents the range condition as a measure of volatility, the ROE…

AkcijasFaktoru ieguldīšanaSvārstīgumsĶīnas tirgi
BigQuant

This Chinese-language note estimates potential market upside across four equity groups: the CSI Bank sector, SSE 50, CSI 500, and ChiNext. Its framework considers fundamental trends, whether expected earnings growth supports current valuation, and the risk…

AkcijasĶīnas tirgiFaktoru ieguldīšanaStatistika
ProRealCode

The document presents a four-hour forex system: a breakout approach for NZD/USD and a reversal variant for AUD/NZD, described as using the same code with long and short orders reversed. The sample rules combine the direction of recent daily closes, a…

Valūtu tirgusCenas izrāviensAtgriešanās pie vidējās vērtībasTehniskie indikatori
MQL5 code base

This indicator displays the current Relative Strength Index alongside RSI calculated on a second, user-selected timeframe. Its period parameter controls the RSI calculation length, while a separate timeframe parameter selects the additional interval. The…

Tehniskie indikatoriCenas impulss
SuperMind

This Chinese equity screen combines three conditions: daily high-low range relative to the opening price above 1%, a ten-day return above zero and below 35%, and bullish technical filters. The accompanying Python example calculates moving averages of the…

AkcijasĶīnas tirgiTehniskie indikatoriCenas impulss
SuperMind

The document introduces a 2017 Guotai Junan research report that constructed 191 short-cycle alpha factors from price and volume characteristics and combined them in a stock-selection system. It notes that the factor expressions resemble those in…

AkcijasĶīnas tirgiFaktoru ieguldīšanaVēsturisko datu pārbaude