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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
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
QuantRocket
7 dokumenter
Lumibot strategies
7 dokumenter
Awesome Quant
1 dokumenter

Søk i biblioteket

3,481 dokumenter

BigQuant

This overview surveys six ICLR 2022 studies: periodic time-series forecasting, model-based policy optimization, disentangled representations, Stein-based sampling, deployment-efficient reinforcement learning, and training with privileged observations. The…

MaskinlæringStatistikkMomentumHistorisk testing
BigQuant

This article explains why selecting useful input features matters in predictive modeling. Irrelevant variables can add training time, contribute to overfitting, and make it harder for a model to generalize. Feature selection is presented as a way to reduce…

MaskinlæringStatistikk
BigQuant

This forum post responds to a question about selling after a 10% gain or cutting a position after a 10% loss. The included example checks open equity positions against current prices, retrieves the highest price since purchase, and exits when price falls 7%…

AksjerRisikostyringOrdreutførelse
BigQuant

This article describes a daily process for building a watchlist of strong stocks. After the close, rank shares by traded value and keep the top 30. From that group, look for stocks rising more than 3% on increased volume, giving extra attention to volume…

AksjerMomentumKursbruddTekniske indikatorer
BigQuant

This Chinese-language article introduces a workflow for building custom stock-selection strategies on the older BigQuant platform. It contrasts platform-generated AI strategies, which learn from selected factors but may be difficult to interpret or tune,…

AksjerFaktorinvesteringHistorisk testingMaskinlæring
BigQuant

This study compares ways to hedge stock holdings, motivated by investors who hold equities as a base for IPO subscriptions and want to reduce exposure to price swings. It measures hedge costs using annualized futures discounts and compares those costs across…

FuturesOpsjonerAksjerRisikostyring
BigQuant

This article explains how to assess a systematic futures model through test design and several complementary performance measures. It recommends testing across multiple instruments and long historical periods, and including commissions and slippage. The…

FuturesHistorisk testingRisikostyringOrdreutførelse
BigQuant

This article proposes studying Chinese A-share stocks during days when the broader market falls sharply. It suggests identifying historical selloff days, then examining two setups: stocks that close at the daily upper price limit despite the market decline,…

AksjerKinesiske markederHistorisk testingTekniske indikatorer
BigQuant

This document summarizes two external research papers. The first concerns allocating capital among private fund strategies within a fund-of-funds portfolio, using multi-objective linear programming to derive allocation weights. The second examines the ratio…

PorteføljekonstruksjonOpsjonerMarkedsmikrostrukturStatistikk
BigQuant

This article explains random forests and decision trees, then applies a random forest regressor to short-horizon Chinese stock selection. It describes bootstrap sampling, random feature selection, averaging tree predictions, tree pruning, regression split…

AksjerMaskinlæringFaktorinvesteringHistorisk testing
BigQuant

The document describes why quantitative investors use machine learning to analyze large datasets, forecast market direction, and select portfolios. It highlights the ability of these methods to represent nonlinear relationships and process data efficiently,…

MaskinlæringHistorisk testingStatistikk
BigQuant

This overview presents basic ways to assess broad equity-market conditions and limit portfolio exposure during potential declines. It describes moving-average crossovers as timing signals, with a shorter average crossing above a longer one treated as bullish…

AksjerTekniske indikatorerRisikostyringPorteføljekonstruksjon
BigQuant

This opinion piece presents stock trading as a possible independent career, emphasizing schedule autonomy, reduced dependence on an employer, access to shares in public companies, and the ability to shift attention among sectors. It argues that market…

AksjerKinesiske markederRisikostyring
BigQuant

This commentary argues that oversight of quantitative trading should focus on predictable, transparent market rules and enforcement of misconduct, rather than suppressing algorithmic methods as a category. It frames the regulatory challenge as balancing…

Kinesiske markederMarkedsmikrostrukturHøyfrekvenshandelOrdreutførelse
BigQuant

Risk parity allocates portfolio weights so that assets contribute more evenly to total portfolio risk, rather than assigning capital according to expected returns or equal dollar amounts. The document outlines a workflow: estimate asset volatilities and…

PorteføljekonstruksjonRisikostyringFlere aktivaklasserStatistikk
BigQuant

This review surveys three directions in factor investing: refining established factor methods, incorporating new data and models, and using factors as a basis for asset allocation. It describes improving value signals with multiple valuation measures,…

FaktorinvesteringPorteføljekonstruksjonMaskinlæringRisikostyring
BigQuant

The document addresses a screening condition that combines a stock closing above a rolling maximum with a recent limit-up requirement. The questioner reports that the combined filters return no candidates even though individual conditions seem to identify…

Kinesiske markederAksjerKursbruddTekniske indikatorer
BigQuant

The article introduces trend following as buying when prices rise and selling when they weaken, then reviews five indicators that may inform such decisions: moving averages, Bollinger Bands, MACD, RSI, and On-Balance Volume. It describes using price relative…

AksjerTrendfølgende handelTekniske indikatorerMomentum
BigQuant

The report argues that ranking fund managers can reduce redundant information when one manager oversees several similar funds. It proposes tracking manager style across market capitalization, value versus growth, industry concentration, individual-stock…

AksjerKinesiske markederFaktorinvesteringPorteføljekonstruksjon
BigQuant

This research summary presents cash-flow duration as a framework for understanding why equity characteristics such as value, profitability, investment, low beta, and dividend payout are associated with returns. Duration measures the timing of a company’s…

AksjerFaktorinvesteringPorteføljekonstruksjonStatistikk
BigQuant

This brief review interprets the CSI 300’s movements through valuation bands tied to an assumed earnings growth rate. Using a 12-times valuation assumption and projected 2018 net profit growth, it describes an estimated index range and treats the July move…

AksjerKinesiske markederStatistikk
BigQuant

This article presents a multi-asset allocation framework that combines traditional asset selection with allocation to systematic factors. It maps macroeconomic variables and style factors to asset classes, estimates exposures with time-series regressions,…

Flere aktivaklasserFaktorinvesteringPorteføljekonstruksjonHistorisk testing
BigQuant

This research note discusses how to turn equity alpha signals into portfolio forecasts and combine multiple factors. It suggests converting factor z-scores into expected returns using average results from repeated cross-sectional regressions, and favors…

AksjerFaktorinvesteringStatistikkPorteføljekonstruksjon
BigQuant

This research summary describes a machine-learning approach to predicting very short-term price changes from futures order-book data. It proposes using support vector machines with features such as best bid and ask prices and sizes, order-book depth, slope…

FuturesMaskinlæringHøyfrekvenshandelMarkedsmikrostruktur