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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
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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
Dokumentu skaits: 766
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
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
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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
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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: 3,481

BigQuant

This note describes a stock risk factor based on the Sharpe ratio over a 20-day period. It defines the measure as annualized stock return minus a risk-free rate, divided by the stock return standard deviation. The stated risk-free rate is 0.04. The factor is…

AkcijasFaktoru ieguldīšanaRiska pārvaldībaStatistika
BigQuant

The document introduces the True Strength Index (TSI), a price momentum indicator calculated from closing prices. It first measures the close-to-close change and its absolute value, then applies two exponential moving average smooths to each series. The…

Tehniskie indikatoriCenas impulssAkcijas
BigQuant

This research explores whether intraday price and volume relationships can improve stock selection. It builds three signals from price–volume correlation: its average level, its stability over time, and its trend. The average signal adjusts conventional…

AkcijasĶīnas tirgiFaktoru ieguldīšanaTehniskie indikatori
BigQuant

This report examines institutional investors’ holdings and style preferences, focusing on Chinese equities and summarizing US institutional ownership for context. It outlines four possible data sources for monitoring institutions: macro indicators, trading…

AkcijasĶīnas tirgiFaktoru ieguldīšanaPortfeļa veidošana
BigQuant

This report describes ways to study institutional investors’ market footprint and preferences in Chinese equities. Because many institutions do not disclose complete holdings, it proposes classifying shareholder accounts from listed companies’ public…

AkcijasĶīnas tirgiFaktoru ieguldīšanaPortfeļa veidošana
BigQuant

This report explains how to isolate a desired equity style factor while controlling exposure to other factors. It contrasts full replication, which reproduces modeled pure-factor returns but does not control ex ante risk, with constrained mean-variance…

AkcijasFaktoru ieguldīšanaPortfeļa veidošanaRiska pārvaldība
BigQuant

This review summarizes research on whether anchoring to a stock’s 52-week high helps explain why prices respond slowly to news about economically connected firms. Its central hypothesis is that investors underreact to good news about a customer when a…

AkcijasCenas impulssFaktoru ieguldīšana
BigQuant

This article proposes a visual exit technique combining a moving average with a horizontal line drawn from a recent swing high or low. For a long position, the trader marks a visible high, extends a horizontal reference, and treats the bar vertically aligned…

AkcijasTehniskie indikatoriSekošana tendenceiRiska pārvaldība
BigQuant

This Chinese-language strategy note surveys ways to connect macro conditions, company fundamentals, valuation, and sector performance. It describes a credit and earnings framework for market regimes, a rolling stock-bond yield spread as a relative valuation…

AkcijasĶīnas tirgiFaktoru ieguldīšanaStatistika
BigQuant

This research summary presents factor timing as a risk-control problem rather than solely as a return-forecasting problem. It proposes adjusting the upper and lower bounds on factor exposures in a portfolio, with those limits informed by factor risk,…

Faktoru ieguldīšanaRiska pārvaldībaPortfeļa veidošanaVēsturisko datu pārbaude
BigQuant

This Chinese-language brokerage research summary examines advanced driver-assistance systems in China, focusing on adoption, technology requirements, supplier roles, and domestic competition. It describes ADAS as a chain of perception, planning, decision,…

AkcijasĶīnas tirgiMašīnmācīšanās
BigQuant

This platform guide describes two ways to organize data preparation and simulated trading. In one workflow, a separate task cleans and stores factors, then a trading task consumes its output. In the other, one task first prepares and saves the data and then…

Rīkojumu izpildeVēsturisko datu pārbaude
BigQuant

The article discusses three reported Chinese equity-market changes: wider daily price limits for risk-warning stocks, expanded after-hours fixed-price trading, and revised ChiNext listing standards that place more weight on growth and research investment. It…

Ķīnas tirgiAkcijasRīkojumu izpildeTirgus mikrostruktūra
BigQuant

This overview introduces the Fama-French five-factor asset pricing model as an extension of the three-factor model. It describes the market risk premium, size, value, profitability, and investment-style factors, and explains each as a return spread between…

AkcijasFaktoru ieguldīšanaStatistikaPortfeļa veidošana
BigQuant

This strategy selects stocks that open above the previous close and have a five-day closing-price average above the ten-day average. Among qualifying stocks, it ranks by price-to-earnings ratio in ascending order and chooses the first ten; purchases are…

AkcijasCenas impulssTehniskie indikatoriVēsturisko datu pārbaude
BigQuant

This document summarizes the SEC’s 2019 adoption of Rule 6c-11, which lets many ETFs operate under the Investment Company Act of 1940 and list without seeking an individual exemptive order. It frames the rule around regulatory exemptions, custom creation and…

AkcijasASV tirgiTirgus mikrostruktūra
BigQuant

This student submission translates a Chinese stock trading pattern into explicit screening and trading rules. The setup looks for a declining session after a limit-up day, with current volume twice the prior day’s volume. The stock is then watched, with…

AkcijasCenas izrāviensCenas impulssTehniskie indikatori
BigQuant

The document presents a SQL query for calculating a stock’s five-day price return and ranking that return against other stocks on the same date. It uses a window function to retrieve each instrument’s close from five trading rows earlier, then computes the…

AkcijasStatistikaĶīnas tirgi
BigQuant

The document explains how to restrict a Chinese stock machine-learning dataset to shares that closed at their daily price limit, or to shares that hit the limit on the previous trading day. It describes filtering factor data by limit-status value and using a…

AkcijasĶīnas tirgiMašīnmācīšanāsVēsturisko datu pārbaude
BigQuant

This guide explains how to monitor a StockRanker model’s validation performance during training. It recommends preparing a validation dataset, either from a separate data module or by reusing the training data, and connecting it to the model’s validation…

MašīnmācīšanāsStatistikaVēsturisko datu pārbaude
BigQuant

This short indicator reference defines a Keltner Channel using high, low, and close price data alongside three parameters: the moving-average period, the ATR period, and a multiplier. It first calculates an average of true range over the selected ATR period.…

Tehniskie indikatoriSvārstīgums
BigQuant

This document outlines a two-stock pairs strategy based on a presumed long-term cointegrating relationship. It fits a linear relationship between the stocks’ prices, calculates the residual, and standardizes that residual over a rolling history. When the…

AkcijasPāru tirdzniecībaAtgriešanās pie vidējās vērtībasVēsturisko datu pārbaude
BigQuant

This article outlines a workflow for adding intraday monitoring and automated execution to a BigQuant equity strategy. Its premise is that factor calculations may produce a next-day trading plan only after the market closes, leaving no mechanism to react to…

AkcijasRīkojumu izpildeTirgus mikrostruktūraĶīnas tirgi
BigQuant

This essay uses an unfinished introduction to a supposed futures reversal method to illustrate the appeal and danger of searching for secret signals. It does not describe a specific entry rule or demonstrate that any reversal strategy works. Instead, it…

Nākotnes līgumiRiska pārvaldībaPozīcijas apjoma noteikšana