Spring til indhold

Videnbibliotek

Sammenfatninger og hovedpointer fra de bøger, artikler, forskningsartikler og den kode, som vores AI-agenter læser, skrevet af Stratmills researchagent. Hver side linker til originalen.

Quant Q&A
20,364 dokumenter
SuperMind
12,226 dokumenter
OKX Learn
8,431 dokumenter
Strategy library
7,910 dokumenter
MQL5 code base
7,090 dokumenter
BigQuant
3,481 dokumenter
Bitget Academy
3,298 dokumenter
MQL5 articles
3,012 dokumenter
TradingView scripts
1,976 dokumenter
ProRealCode
1,507 dokumenter
Deribit Insights
1,232 dokumenter
Machine Learning for Trading
1,124 dokumenter
arXiv papers
1,033 dokumenter
Amberdata research
766 dokumenter
FMZ forum
682 dokumenter
FMZ digest
662 dokumenter
vn.py community
560 dokumenter
QuantInsti blog
511 dokumenter
Galaxy Research
340 dokumenter
QuantStart
246 dokumenter
Stratmill research code
219 dokumenter
Robot Wealth
195 dokumenter
NautilusTrader
191 dokumenter
Hummingbot docs
181 dokumenter
Paradigm research
175 dokumenter
Lumibot
164 dokumenter
Kraken Learn
163 dokumenter
Bibliotek med kvantkurser
157 dokumenter
OctoBot
152 dokumenter
Cryptohopper blog
144 dokumenter
Systematic trading blog (Rob Carver)
132 dokumenter
Qlib
116 dokumenter
Quantpedia
86 dokumenter
TqSdk
86 dokumenter
Hyperliquid docs
79 dokumenter
Freqtrade
68 dokumenter
Hudson & Thames
62 dokumenter
Awesome Systematic Trading
61 dokumenter
backtrader
54 dokumenter
vn.py
50 dokumenter
Quantopian-forelæsninger
45 dokumenter
Binance API docs
45 dokumenter
FMZ guides
38 dokumenter
pysystemtrade
34 dokumenter
Freqtrade docs
32 dokumenter
quant-trading
31 dokumenter
FinRL
28 dokumenter
Zipline
22 dokumenter
FMZ live strategies
21 dokumenter
Jesse
17 dokumenter
pyfolio
16 dokumenter
Alphalens
14 dokumenter
WonderTrader
14 dokumenter
backtesting.py
11 dokumenter
Technical Analysis
9 dokumenter
QTPyLib
8 dokumenter
QuantRocket
7 dokumenter
Lumibot strategies
7 dokumenter
Awesome Quant
1 dokumenter

Søg i biblioteket

79,386 dokumenter

SuperMind

This Chinese stock-screening post combines three filters: rank stocks by a measure of capital inflow, require weekly MACD to be above its zero line, and keep stocks whose ten-day gain is positive but below 35%. The author frames the filters as a way to find…

AktierKinesiske markederMomentumTekniske indikatorer
SuperMind

This Chinese equity screen selects stocks with daily amplitude above 1, turnover between 2% and 9%, and displayed first-level bid volume greater than first-level ask volume. The article frames amplitude and turnover as activity and liquidity measures, with…

Kinesiske markederAktierMarkedsmikrostruktur
ProRealCode

This indicator plots a conventional RSI of closing prices alongside an RSI calculated from a multi-vote On-Balance Volume series. The OBV component assigns directional votes based on changes in the high, close, and low, averages those votes, weights them by…

AktierTekniske indikatorerMomentum
SuperMind

This Chinese equity screening method combines daily amplitude above 1, a weekly crossover of the five-period moving average above the ten-period average, and a positive change in the KDJ K value. The article presents the conditions as a way to identify…

Kinesiske markederAktierMomentumTekniske indikatorer
SuperMind

This Chinese equity screen combines daily price amplitude above 1, a positive weekly MACD reading, and a market-cap rank between the 20th and 70th percentiles. The article also describes ranking candidates by volume relative to its 20-period average, then…

Kinesiske markederAktierMomentumTekniske indikatorer
MQL5 code base

This expert advisor uses a moving average to generate directional entries. Four consecutive declining moving-average values establish a downward trend condition, with a price rebound above the latest average triggering a sell; four rising values establish an…

ValutahandelTekniske indikatorerPositionsstørrelseRisikostyring
MQL5 code base

This indicator presents the standard Relative Strength Index as a histogram after rounding its readings to configurable increments. The described settings range from no rounding to progressively coarser groupings, including a three-level display at zero, the…

Tekniske indikatorerAktierValutahandel
SuperMind

This Chinese-language post describes an equity screening rule combining price amplitude above a threshold, a rounded or arc-like price pattern, and a signal that the stock was controlled by major traders on the previous day. It presents the combination as a…

AktierTekniske indikatorerRisikostyring
ProRealCode

This long-only daily strategy seeks short-term rebounds in equity index CFDs while limiting entries to prices above a 200-period moving average. It sums RSI readings over the most recent two periods and enters when this cumulative measure falls below 35,…

AktierTilbagevenden til gennemsnittetTekniske indikatorerRisikostyring
BigQuant

This brief request proposes a factor based on the correlation between a benchmark’s returns and an individual stock’s returns over a three-day window. It names the intended inputs and lookback, but provides no code, worked example, explanation of how to…

AktierStatistikFaktorinvestering
SuperMind

This stock-selection idea combines three filters: a daily trading range above one percent of the previous close, a stock code beginning with 60, and a positive afternoon large-order flow signal. The code example operationalizes the range and code filters,…

AktierKinesiske markederTekniske indikatorerMarkedsmikrostruktur
BigQuant

This April 2020 market note reviews a sharp decline in Chinese equities amid weakening fundamentals and falling investor sentiment. It reports that large- and small-cap indexes had similar declines, while consumer and utility sectors held up better and…

AktierKinesiske markederPorteføljekonstruktionRisikostyring
MQL5 code base

This programming note explains how an object-oriented trading advisor can manage its configurable inputs as a structured set. It contrasts manually declaring fields and writing string conversion methods with a macro-based library that generates parameter…

OrdreudførelseBacktestingPorteføljekonstruktion
SuperMind

This note describes a Chinese equity screen for stocks associated with the metaverse concept. It requires turnover between 3% and 12% and at least one limit-up event during the prior 25 days. The accompanying examples translate these conditions into…

AktierKinesiske markederMomentumKursgennembrud
SuperMind

This note outlines a screen for Chinese equities associated with the robotics concept. It combines turnover between 3% and 12%, floating market capitalization below 10 billion yuan, and a ratio of 2021 revenue to 2018 revenue above 1.1. The post includes…

AktierKinesiske markederFaktorinvesteringRisikostyring
SuperMind

This note describes a Chinese A-share filter combining a turnover rate between 3% and 12%, a Dragon-Tiger list appearance the previous day, and a floating market capitalization between 5 billion and 10 billion yuan. It presents this as a way to find actively…

AktierKinesiske markederMarkedsmikrostrukturRisikostyring
MQL5 code base

The method treats signals from an indicator as candidate highs or lows rather than immediate trade entries. It uses zigzag-style logic to connect candidate pivots and checks whether each candidate can form a geometrically plausible leg. A candidate that…

Tekniske indikatorerKursgennembrudRisikostyring
BigQuant

This note explains how to handle low-frequency financial or analyst factors alongside daily price and volume factors when constructing nonlinear models. One approach is to merge monthly or quarterly fundamentals with daily market data and carry the latest…

MaskinlæringFaktorinvesteringStatistikBacktesting
SuperMind

This stock-selection approach combines a positive MACD reading with a company-type condition and circulating market capitalization above 10 billion yuan. The document presents the screen as a way to find stocks with upward price trends, sound fundamentals,…

AktierTekniske indikatorerMomentumKinesiske markeder
SuperMind

This post outlines a Chinese A-share stock screen combining an RSI below 65, seven consecutive down days, and a weekly five-period moving average crossing above the ten-period average. It presents the conditions as a way to identify stocks with a potentially…

AktierTekniske indikatorerMomentumKinesiske markeder
BigQuant

This brief note describes a feature-selection exercise based on a random forest template. The author says they ranked 37 stock factors by random forest importance and retained the nine factors with the highest importance scores. The document does not…

AktierFaktorinvesteringMaskinlæringStatistik
BigQuant

This Chinese-language research summary discusses forecasting stock-selection factor returns after commonly used factors became more volatile. It focuses on screening timing variables with Lasso and Elastic Net regression, then extending factor timing with…

AktierFaktorinvesteringMaskinlæringBacktesting
BigQuant

The post raises a backtesting concern: a user observes that a stock delisted on one date still appears sellable on a later scheduled rebalance date. A reply explains the platform behavior as a special backtest-engine rule: when a strategy does not handle a…

BacktestingAktierRisikostyring