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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.

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20,364 dokumenter
SuperMind
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OKX Learn
8,431 dokumenter
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MQL5 code base
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Bitget Academy
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MQL5 articles
3,012 dokumenter
TradingView scripts
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ProRealCode
1,507 dokumenter
Deribit Insights
1,232 dokumenter
Machine Learning for Trading
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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 review surveys momentum investing across equities, funds, commodities, bonds, currencies, and cryptocurrencies. It explains cross-sectional momentum, which buys past winners and sells losers, and time-series momentum, which takes positions based on each…

MomentumTrendfølgende handelFaktorinvesteringFlere aktivaklasser
BigQuant

This document is a short summary of a report about constructing a fund-of-funds portfolio that can consistently outperform the median actively managed equity fund. It highlights the difficulty of selecting funds that remain above that benchmark across…

Flere aktivaklasserPorteføljekonstruksjonStatistikk
BigQuant

The document considers why a developer might share or commercialize a quantitative trading system instead of trading it privately. Its central explanation is that developers may struggle to follow their own rules: watching short-term price moves can trigger…

OrdreutførelseRisikostyringStatistikk
BigQuant

The document summarizes an analysis of the China Strategic Emerging Industries Index and its associated ETF. The index selects 100 listed companies from areas such as environmental technology, information technology, biotechnology, advanced manufacturing,…

AksjerKinesiske markederFaktorinvesteringPorteføljekonstruksjon
BigQuant

This tutorial introduces Pandas as a toolkit for working with financial data, focusing on its Series and DataFrame structures. It demonstrates creating indexed data, inspecting rows, columns, values, and types, sorting, transposing, selecting columns and…

AksjerStatistikkTekniske indikatorer
BigQuant

The document explains the expected input, initial state, and output shapes for PyTorch’s LSTM layer. With the default layout, inputs are arranged as sequence length, batch size, and feature count; the hidden and cell states also include layer and direction…

MaskinlæringStatistikkKinesiske markeder
BigQuant

This report summary examines gold supply and demand, macroeconomic influences, and ways to combine fundamental signals with short-term trend trading. It argues that supply changes relatively little, while shifts in investment demand help explain price…

RåvarerFaktorinvesteringTrendfølgende handelHistorisk testing
BigQuant

This summary of a brokerage research report discusses the research workflow for multi-factor equity selection. It highlights source-data issues such as delayed or unreliable financial disclosures, corporate restructurings that disrupt historical…

AksjerKinesiske markederFaktorinvesteringStatistikk
BigQuant

The document surveys ways to revise investment strategies, including changing asset allocations, rebalancing, diversifying across assets, adding quantitative signals, and strengthening risk controls. It mentions tools such as value-at-risk, risk budgeting,…

PorteføljekonstruksjonRisikostyringFaktorinvesteringHistorisk testing
BigQuant

The document introduces Bollinger Bands as a technical indicator calculated from closing prices. It names a moving-average window, another window for the lower band, and a standard-deviation multiplier as inputs. Its pseudocode describes an upper band based…

Tekniske indikatorerVolatilitet
BigQuant

The document explains quantile regression as an alternative to ordinary least squares for modeling stock returns. Because it estimates relationships at different points in the return distribution, it can reveal effects that an average-based model may hide,…

AksjerFaktorinvesteringStatistikkKinesiske markeder
BigQuant

The report summary describes a study of Chinese equities covered by broker buy-rating reports. Cross-sectional regressions reportedly find a significant return premium for covered stocks after controlling for common stock-selection factors. The premium is…

AksjerHendelsesdrevet handelMarkedssentimentStatistikk
BigQuant

The document outlines an equity factor research workflow: define a hypothesis from investment or behavioral theory, gather and clean data, calculate factor values, evaluate each factor, combine factors, and backtest and refine the result. It highlights…

AksjerFaktorinvesteringHistorisk testingStatistikk
BigQuant

This study examines whether stock-selection factors earn premiums from choosing stocks within industries, allocating across industries, or both. It tests 21 definitions spanning value, quality, momentum, low volatility, and size, using global…

AksjerFaktorinvesteringPorteføljekonstruksjonRisikostyring
BigQuant

The article evaluates a deep-learning stock-ranking model across broad-market and filtered Chinese equity universes. It uses rolling windows of three years for training and one year for evaluation, then compares portfolio sizes, rebalance intervals,…

AksjerMaskinlæringHistorisk testingPorteføljekonstruksjon
BigQuant

This research outline proposes constructing an A-share stock portfolio that seeks exposure to alpha while limiting unstable style exposures. Its motivation is concern that alpha-hedging returns may track market style rotations and that strategies experienced…

AksjerFaktorinvesteringPorteføljekonstruksjonRisikostyring
BigQuant

The document introduces the Psychological Line, abbreviated PSY, as a price-based indicator. Its stated calculation counts the days in a chosen lookback period when the close exceeds the previous close, divides that count by the period length, and expresses…

Tekniske indikatorerStatistikkMomentum
BigQuant

This report summary describes a study of capital-structure and solvency factors. It says nine capital-structure measures were assessed using grouped portfolio returns, long-short rankings, information coefficients, and Fama–MacBeth analysis. Four ratios were…

AksjerFaktorinvesteringStatistikk
BigQuant

The document compares machine-learning approaches to strategy development with more subjective manual parameter tuning. It recommends measuring overfitting by comparing performance on training and test data, using cross-validation where appropriate. For…

MaskinlæringStatistikkHistorisk testing
BigQuant

The article argues that individual traders are unlikely to beat quantitative funds at speed and disciplined execution. It challenges the idea that simply refusing to sell is a reliable defense, pointing to the difficulty of holding through sharp price moves…

AksjerTrendfølgende handelRisikostyring
BigQuant

This introductory article defines quantitative investing as using numerical models and systematic rules to guide investment decisions. It contrasts model-based methods with more discretionary approaches, then describes claimed benefits: disciplined…

Flere aktivaklasserStatistikkHistorisk testingPorteføljekonstruksjon
BigQuant

This document introduces a study of stock-selection factors based on herding behavior among individual Chinese equities. Its brief abstract places the work in the context of widely used domestic multi-factor strategies and says that such strategies had…

AksjerKinesiske markederFaktorinvesteringTilbakevending mot gjennomsnittet
BigQuant

This note defines the Momentum Index, abbreviated Mtm, as the current closing price minus the closing price a specified number of days earlier. The lookback interval is a parameter, so the resulting value depends on the chosen period. The measure expresses…

Tekniske indikatorerMomentumAksjer
BigQuant

A brief troubleshooting note explains a model training error in a stock ranking workflow. The stated cause is that all input factor values were either zero or one. Since the ranking model needs variation in its inputs to distinguish and order securities, a…

MaskinlæringStatistikkAksjer