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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 example outlines a China A-share stock selection and portfolio backtest workflow. It screens for eligible, non-suspended stocks, calculates 30-day and 90-day returns, and ranks those returns cross-sectionally. The illustrated filter favors stocks in the…

Kinesiske markederAksjerMomentumFaktorinvestering
BigQuant

The study groups fifty Wind order-flow measures into eight categories, including inflows, outflows, net active buying, and large-order flows. It evaluates these signals as stock-selection factors using portfolio sorts, cross-sectional regressions, and…

AksjerFaktorinvesteringStatistikkHistorisk testing
BigQuant

This brief Q&A explains how to change the scoring function used during hyperparameter search. The question asks how to include annualized return, win rate, and maximum drawdown alongside a Sharpe-based score. The response says the score function can read…

MaskinlæringHistorisk testingRisikostyring
BigQuant

This note describes a daily stock factor that combines weighted order book pressure with the closing price’s deviation from intraday VWAP. It weights the five visible book levels by proximity, giving the nearest level the greatest weight, then uses trading…

AksjerMarkedsmikrostrukturMomentumTekniske indikatorer
BigQuant

This article explains how to measure whether active mutual fund managers adjust holdings in stocks with different downside market sensitivity ahead of market moves. It defines relative downside beta as the portfolio weighted downside beta minus conventional…

AksjerRisikostyringPorteføljekonstruksjonStatistikk
BigQuant

The document explains net income compound annual growth rate (CAGR) as an annualized measure of change between an initial and a later profit value. It distinguishes CAGR, which represents compounding across multiple periods, from a simple endpoint growth…

AksjerKinesiske markederFaktorinvesteringHistorisk testing
BigQuant

This installment of a quantitative investing research review introduces two overseas studies relevant to stock selection. The first examines how interest rates affect stock pricing and is described as offering a new analytical framework and empirical testing…

AksjerFaktorinvesteringStatistikkVolatilitet
BigQuant

This support exchange diagnoses why a futures Bollinger Band strategy produced no backtest results. The reported cause is a mismatch between the date ranges: the data extraction module supplied data from 2021, while the backtest was set to run in 2024. Since…

FuturesTekniske indikatorerHistorisk testing
BigQuant

This tutorial explains how to build and install a reusable BigQuant module that reads a named data table, selects a date range, and rounds chosen floating-point fields to a requested number of decimal places. It describes defining required and optional…

AksjerStatistikkOrdreutførelse
BigQuant

This platform support note addresses why an order query may return no information in a pre-market handler even though it can return information after the market session. The question concerns using existing orders to build a process that cancels orders at…

Ordreutførelse
BigQuant

This research note presents investor mood as a possible explanation for seasonal patterns in both market returns and the relative performance of stocks. It hypothesizes that assets that perform well in historically upbeat periods will tend to do so again in…

AksjerMarkedssentimentFaktorinvesteringStatistikk
BigQuant

The document explains turnover as the number of shares traded during a period divided by the average number of shares available to trade, expressed as a percentage. It illustrates the calculation with a quarterly example in which traded volume is twice the…

AksjerStatistikkOrdreutførelseMarkedsmikrostruktur
BigQuant

The document describes a China A-share index enhancement approach that adds industry rotation to a CSI 300 stock-selection portfolio. Its motivation is that the benchmark has uneven industry weights, making active industry exposure a meaningful part of…

Kinesiske markederAksjerFaktorinvesteringPorteføljekonstruksjon
BigQuant

This research summary extends a framework for selecting functional equity funds for fund-of-funds portfolios. It distinguishes sectors where active stock selection may add value from those better served by sector ETFs. For consumer and growth exposures, it…

AksjerFaktorinvesteringPorteføljekonstruksjonRisikostyring
BigQuant

The article contrasts quantitative trading, which it describes as using statistical models and systematic execution to exploit price deviations linked to investor emotion, with discretionary investing, where patience, independent judgment, and resilience may…

StatistikkMarkedssentimentRisikostyring
BigQuant

This 2018 report revisits whether the investment clock can guide asset allocation amid trade tensions and political shocks. Its traditional mapping assigns equities to recovery, commodities to overheating, bonds to recession, and cash to stagflation. It…

Flere aktivaklasserPorteføljekonstruksjonFaktorinvesteringStatistikk
BigQuant

This Chinese equity strategy selects stocks whose opening price is above the previous close and whose five-day closing-price average is above the ten-day average. It ranks qualifying stocks by price-to-earnings ratio in ascending order, selects up to ten,…

AksjerKinesiske markederMomentumFaktorinvestering
BigQuant

This strategy combines model-based stock ranking with trend-following entry filters to seek short- and medium-term gains in Chinese equities. It starts from a manually selected pool of China Securities 150 constituents, narrowed to roughly 100–300 large,…

AksjerMaskinlæringTrendfølgende handelMomentum
BigQuant

The script describes a spread-trading approach linking methanol futures with polyethylene and polypropylene futures. It estimates an MTO production margin by valuing the two polymer contracts together and subtracting the methanol input cost, adjusted for…

FuturesRåvarerTilbakevending mot gjennomsnittetParhandel
BigQuant

The document raises a practical trading question: how to enforce a minimum holding period using trading days rather than calendar days. Its example calculates elapsed time by subtracting the last rebalance date from the current date, which counts weekends…

OrdreutførelseStatistikkHistorisk testing
BigQuant

This short support discussion concerns a simulated trading run that reportedly failed or stopped before reaching its intended endpoint, even though the available logs showed no clear error. Replies suggest two different observations: one participant saw a…

AksjerHistorisk testingRisikostyring
BigQuant

This article explains how the Fama-French model extends CAPM first with size and value factors, then with profitability and investment factors. It describes double sorts by size and book-to-market, return on equity, or asset growth, and forms RMW from…

AksjerFaktorinvesteringStatistikkKinesiske markeder
BigQuant

The document explains how combinatorially symmetric cross-validation (CSCV) can estimate the probability of backtest overfitting (PBO). It distinguishes training overfitting, where a model performs poorly on held-out data, from backtest overfitting, where a…

Historisk testingStatistikkMaskinlæringFaktorinvestering