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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
TqSdk
86 dokumenter
Quantpedia
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
Binance API docs
45 dokumenter
Quantopian-forelesninger
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

Søk i biblioteket

3,481 dokumenter

BigQuant

This article examines how often an investor should make decisions when each decision reflects some degree of skill and incurs trading costs. It models repeated independent outcomes and argues that expected compounded return depends nonlinearly on skill,…

Flere aktivaklasserFuturesAksjerRentepapirer
BigQuant

A user questions why a reported monthly return is negative when most of the month appeared positive. The reply explains that the earlier portion of the equity curve was above its zero reference, but losses in the final days brought the curve below zero. It…

StatistikkHistorisk testing
BigQuant

This event announcement describes a session on using Cowork to build a quantitative market-timing process and apply it to a small-cap stock strategy. The proposed approach uses macroeconomic indices as timing inputs and presents a multi-factor timing…

Kinesiske markederAksjerFaktorinvesteringHistorisk testing
BigQuant

This report explains a value-versus-growth rotation strategy built around the idea that returns can come from deliberate exposure to style factors as well as broad market risk. It links shifts in style leadership to investor sentiment and risk appetite,…

FaktorinvesteringPorteføljekonstruksjonHistorisk testingKinesiske markeder
BigQuant

This review describes a Bayesian dynamic panel model for evaluating US mutual fund performance and its persistence. The model allows fund returns to have time-varying variance and covariance, cross-fund dependence, serial correlation, latent volatility, and…

StatistikkMaskinlæringFaktorinvesteringRisikostyring
BigQuant

This document summarizes Zhongtai’s annual outlook for 2022, presenting views on Chinese and U.S. markets, policy, liquidity, and sector opportunities. It anticipates gradual easing in China’s property stance without a full housing-cycle restart, a…

AksjerKinesiske markederAmerikanske markederFaktorinvestering
BigQuant

The report combines risk parity with the Black-Litterman framework to build stock-and-bond and broader multi-asset portfolios. It uses risk-parity weights as the prior allocation, short-term momentum as an investment view, and Black-Litterman to estimate…

Flere aktivaklasserPorteføljekonstruksjonMomentumRisikostyring
BigQuant

This article argues that during Chinese sector rallies, a highly visible limit-up leader may serve as an attention and sentiment anchor while larger positions are accumulated or exited across less prominent related stocks. It describes a sequence in which…

AksjerKinesiske markederMarkedssentimentMarkedsmikrostruktur
BigQuant

This document summarizes several modeling choices for quantitative trading. It argues that machine learning may be easier to apply in high frequency strategies than in lower frequency settings, and that nonlinear models can capture more from data than linear…

MaskinlæringHøyfrekvenshandelHistorisk testingStatistikk
BigQuant

The report frames asset allocation as exposure to underlying risk factors rather than simply to asset categories. It distinguishes macro factors, which represent shared risks across asset classes, from investable style factors, which explain risk premia…

FaktorinvesteringPorteføljekonstruksjonAksjerKinesiske markeder
BigQuant

This tutorial introduces Matplotlib as a Python library for visualizing data and walks through common chart types and layout tools. Examples show how to plot one or more series, customize line colors and markers, create scatter plots with variable point size…

Statistikk
BigQuant

This Chinese equity strategy applies a simple Turtle-inspired rule to five named stocks. It defines a recent high using the highest closing price over 20 sessions and a recent low using the lowest close over 10 sessions. The stated rule buys when the high…

AksjerTrendfølgende handelTekniske indikatorerHistorisk testing
BigQuant

This report consolidates tests of 78 factors across eight categories, comparing grouped portfolio returns, statistical independence measures, single-period and cumulative returns, t-statistics, and measures of return variability. It also examines…

AksjerFaktorinvesteringStatistikkPorteføljekonstruksjon
BigQuant

This research summary examines whether announcements of institutional investor visits to A-share companies contain information about subsequent stock returns. It describes the events as usually involving specific-company visits, a small number of…

AksjerKinesiske markederHendelsesdrevet handelStatistikk
BigQuant

This event description frames index enhancement as tracking a benchmark while seeking excess returns. It outlines a workflow involving single-factor screening, backtest construction, and parameter tuning, and presents a live demonstration that purportedly…

AksjerFaktorinvesteringHistorisk testingPorteføljekonstruksjon
BigQuant

The report examines how index-enhancement funds generate returns above their benchmarks. It separates active returns into industry selection, stock selection within industries, and their interaction, then compares stock selection within index constituents…

AksjerFaktorinvesteringPorteføljekonstruksjonStatistikk
BigQuant

The document discusses how to evaluate a stock factor using portfolios formed by sorting stocks on factor values. In a long–short comparison, the return spread is calculated between the group ranked highest by the factor and the group ranked lowest by the…

AksjerFaktorinvesteringHistorisk testing
BigQuant

This discussion concerns adapting a stock-ranking template to use financial factors in a machine-learning strategy. The author describes a forward-return label based on buying at the next day’s open and selling at the close five trading days later, then asks…

AksjerMaskinlæringFaktorinvesteringStatistikk
BigQuant

This proposed short-term A-share strategy selects ordinary shares that have closed at the daily limit for two consecutive sessions and belong to concepts ranking near the top by both recent three-session and fifteen-session returns. It excludes specified…

AksjerKinesiske markederMomentumKursbrudd
BigQuant

The document describes a proposed equity screen that starts with executive share-change announcements and then ranks eligible stocks using multiple factors. At each rebalance, the investor would look for relevant announcements published between the current…

AksjerHendelsesdrevet handelFaktorinvestering
BigQuant

The document explains what a useful volatility model should capture: volatility clustering and persistence, eventual mean reversion, asymmetric responses to positive and negative return shocks, effects from external variables and scheduled events, and…

VolatilitetStatistikkRisikostyringAksjer
BigQuant

This document introduces convertible bonds as instruments combining debt with an option to convert into the issuer’s shares. It outlines core contract features: face value, conversion price and period, coupon, conditional early redemption, and investor put…

RentepapirerOpsjonerVolatilitetKinesiske markeder
BigQuant

This document introduces convertible bonds as instruments combining debt with an option to convert into the issuer’s shares. It outlines core contract features: face value, conversion price and period, coupon, conditional early redemption, and investor put…

RentepapirerOpsjonerVolatilitetKinesiske markeder
BigQuant

This note recommends two research papers on behavioral finance and equity anomalies. The first examines how journalists’ experience, education, and industry knowledge relate to the accuracy of merger news when rumors circulate. It reports that vague wording…

Aksjer