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Kunnskapsbibliotek

Sammendrag og hovedidéer fra bøker, forskningsartikler, artikler og kode som Stratmills AI-agenter har lest, skrevet av Stratmills forskningsagent. Hver side lenker 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 for kvantkurs
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-forelesninger
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
Lumibot strategies
7 dokumenter
QuantRocket
7 dokumenter
Awesome Quant
1 dokumenter

Søk i biblioteket

3,481 dokumenter

BigQuant

This note reports results for five related quantitative factors. The starting signal standardizes the ratio of trading volume to turnover. Variants combine it with 20-period close-price variability, a momentum-style calculation based on recent price changes,…

FaktorinvesteringStatistikkHistorisk testing
BigQuant

The document summarizes a report comparing the historical performance and future prospects of index funds and actively managed funds. Its stated takeaway is that their past performance showed no clear overall winner. A slight historical advantage for active…

AksjerFaktorinvesteringPorteføljekonstruksjon
BigQuant

The document poses a model validation question rather than giving a complete answer: after training a multi-factor model on historical data and evaluating it on a later year, should a trader deploy that fitted model or retrain it on a newer rolling window?…

MaskinlæringFaktorinvesteringHistorisk testingStatistikk
BigQuant

The document outlines a framework that combines monetary and credit conditions to time Chinese equities and bonds, then adds momentum, oil, or inflation signals for commodities, equities, and bonds. It argues that monetary policy can lead markets because of…

Flere aktivaklasserFaktorinvesteringMomentumPorteføljekonstruksjon
BigQuant

The document explains softmax as a transformation from a vector of scores to nonnegative values that sum to one, making them interpretable as a probability distribution. It describes its role in the continuous bag-of-words model in Word2Vec, where model…

MaskinlæringStatistikk
BigQuant

This literature summary reviews evidence that stocks with greater left-tail risk, measured using value at risk or expected shortfall, subsequently earn lower returns. The underlying study sorts stocks by tail-risk measures, compares portfolio returns and…

AksjerRisikostyringMomentumStatistikk
BigQuant

This research summary examines whether detrended cumulative equity factor returns show cyclical behavior and whether macroeconomic cycles can help explain it. The proposed framework represents three cycles associated with Kitchin, Juglar, and Kuznets…

FaktorinvesteringStatistikkHistorisk testing
BigQuant

This opinion article argues that many retail investors lose through overtrading, chasing short-term leaders, and expecting rapid gains. It recommends accepting limits in prediction and focusing instead on patiently waiting for a market, sector, or stock to…

AksjerTrendfølgende handelRisikostyringKinesiske markeder
BigQuant

The document summarizes research applying Wasserstein generative adversarial networks (WGANs) to financial return series and comparing them with standard GANs. WGANs replace the original GAN’s distribution-distance measure with Wasserstein distance, which…

MaskinlæringStatistikkAksjerKinesiske markeder
BigQuant

This platform-support exchange concerns a pair-trading strategy that failed to run in simulation. The suggested fix is to leave the data-extraction module’s start-date option unbound to live-trading parameters. The explanation is that the strategy’s…

ParhandelStatistikkHistorisk testing
BigQuant

This Chinese-language post discusses a small-cap equity strategy whose apparent style changed from small-cap exposure to liquidity exposure over a short period. It argues that factor premia are time-varying and that a strategy labeled as small-cap may earn…

Kinesiske markederAksjerFaktorinvesteringStatistikk
BigQuant

The article challenges the claim that Chinese stock index futures expiry reliably causes equity market declines. It argues that these contracts settle in cash, so settlement itself does not require buying or selling ETFs or underlying shares. Hedgers can…

FuturesAksjerStatistikkMarkedssentiment
BigQuant

The document examines why ESG ratings from different providers can disagree, citing differences in factor definitions, data sources, weighting, and treatment of missing disclosures. It warns that ratings may reward companies with greater reporting resources…

AksjerFaktorinvesteringStatistikkRisikostyring
BigQuant

This report surveys gold’s supply and demand, major trading venues, and common investment instruments. It notes that investment demand and central bank purchases are especially relevant to prices, and describes the roles of London spot trading, U.S. futures,…

RåvarerFuturesMarkedssentimentHistorisk testing
BigQuant

This document describes an A-share strategy that rotates among industries according to a market-regime indicator, then selects stocks within chosen industries using four factors emphasizing short-term reversal and low attention. The regime indicator is used…

AksjerKinesiske markederMomentumTilbakevending mot gjennomsnittet
BigQuant

The post describes troubleshooting a strategy that behaved correctly in backtests but produced missing or intermittent signals in simulated trading. After checking other strategies and revisiting the selection conditions, the author found that including the…

Historisk testingOrdreutførelseStatistikk
BigQuant

The report discusses using the Black–Litterman (B-L) framework to incorporate an investment manager’s judgments into a quantitative factor portfolio. It frames factor information coefficients as the return inputs and their covariance matrix as a…

Kinesiske markederFaktorinvesteringPorteføljekonstruksjonMomentum
BigQuant

This Chinese-language summary outlines an equity market-timing approach based on a long short-term memory (LSTM) neural network. The model is described as learning dependencies across time-series observations and adapting to sharp changes in trends. It…

AksjerMaskinlæringHistorisk testingKinesiske markeder
BigQuant

This brief summary outlines several approaches to rotating among equity industries. It discusses adapting the investment clock framework from asset allocation to sector selection, while noting that macroeconomic data may be delayed or unreliable and that…

AksjerKinesiske markederFaktorinvesteringTekniske indikatorer
BigQuant

The document describes an equity strategy that combines broad-market timing with multiple pre-entry checks on each stock. It uses a dynamic portfolio of five holdings, with risk controls managed independently for each position. The stated rules include an 8%…

AksjerRisikostyringPosisjonsstørrelseHistorisk testing
BigQuant

This Chinese-language post describes a method for turning raw futures tick updates into real-time minute bars for traders using lower- and medium-frequency strategies. Its design aims to align bar timestamps with common market-data conventions: ticks during…

FuturesMarkedsmikrostrukturOrdreutførelseStatistikk
BigQuant

The document summarizes research using account-level Shenzhen Stock Exchange data from 2012 to 2015 to examine whether daily price limits shape trading behavior. It separates individual investors by account size and compares them with institutions, focusing…

Kinesiske markederAksjerMarkedsmikrostrukturTilbakevending mot gjennomsnittet
BigQuant

This research summary explains why monthly and year-over-year macroeconomic readings can mislead when economic series contain seasonal and calendar effects. It describes X-13-ARIMA-SEATS as a widely used adjustment approach and emphasizes that seasonal…

Flere aktivaklasserStatistikkKinesiske markederFaktorinvestering
BigQuant

The document outlines a beginner workflow for creating an AI-assisted stock selection strategy on a quantitative platform. It starts with defining a trading style, translating that idea into candidate features, expressing those features for model training,…

AksjerMaskinlæringHistorisk testingPosisjonsstørrelse