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Hae kirjastosta

3,481 dokumenttia

BigQuant

The document presents a framework for deciding whether a candidate multifactor strategy adds value beyond a small set of investable reference factors, called elementary smart betas. It models each candidate through its exposures to those factors and its…

Faktoripohjainen sijoittaminenSalkun muodostaminenRiskienhallintaUsean omaisuuslajin sijoittaminen
BigQuant

This commentary reviews the Chinese quantitative-investing environment in 2022 and presents a private manager’s expectations for 2023. It attributes a difficult path to excess returns to weak trading activity and rapid shifts in market style, alongside a…

Kiinan markkinatUsean omaisuuslajin sijoittaminenKoneoppiminenRiskienhallinta
BigQuant

This weekly report compares artificial intelligence stock-selection portfolios across broad A-share universes, industry-neutral portfolios, and portfolios restricted to the CSI 300 or CSI 500. It names XGBoost, support vector machines, random forests,…

Kiinan markkinatOsakkeetKoneoppiminenHistoriatestaus
BigQuant

The document presents a Chinese A-share backtest question: after selling a holding at the open, a daily-frequency strategy places a purchase near the close but buys only a small amount. The author wonders whether the simulator updates available cash only on…

OsakkeetHistoriatestausToimeksiantojen toteutusPosition koon määrittäminen
BigQuant

The study defines an earnings surprise by comparing reported results from forecasts, flash reports, or periodic filings with analyst consensus net profit estimates from the day before the announcement. For nonannual reports, it estimates full-period…

OsakkeetTapahtumapohjainen kaupankäyntiTilastotiedeHistoriatestaus
BigQuant

This brief literature note introduces a VaR-augmented Black-Litterman approach for constructing an absolute-return fund-of-funds portfolio with market-risk controls. The described formulation incorporates value-at-risk alongside practical trading…

Usean omaisuuslajin sijoittaminenSalkun muodostaminenRiskienhallintaTilastotiede
BigQuant

This research review examines whether mutual-fund outflows provide a clean measure of nonfundamental pressure on stock prices. It decomposes the MFFlow measure into components tied to the inverse of returns, the inverse of turnover, and relative fund selling…

OsakkeetTilastotiedeMarkkinoiden mikrorakenneRiskienhallinta
BigQuant

The document explains that exchange-traded funds cannot be processed with the platform’s basic feature extraction module. The reported run shows the extractor failing to find a close-price field for the selected instruments, producing no feature rows and…

OsakkeetKiinan markkinat
BigQuant

This Chinese-language report summary reviews the history and practice of machine learning in quantitative investing. It says that machine learning was used in the field during the early-1990s boom and that its applications continued in algorithmic trading…

KoneoppiminenTilastotiedeHistoriatestausToimeksiantojen toteutus
BigQuant

This roundtable transcript gathers views from Chinese investment managers, researchers, and futures professionals on the development of quantitative investing. Participants discuss the tension among scale, returns, and risk; the challenge of declining or…

Usean omaisuuslajin sijoittaminenFaktoripohjainen sijoittaminenKoneoppiminenMarkkinoiden mikrorakenne
BigQuant

This study develops two equity factors from the relationship between intraday volatility and the return-to-volatility ratio. The “rebuilding” factor uses the daily covariance between that ratio and volatility to represent cases where volatility rises without…

OsakkeetVolatiliteettiFaktoripohjainen sijoittaminenTekniset indikaattorit
BigQuant

This note discusses market style and public mutual fund positioning in Chinese equities. It compares the share of CSI 300 constituents within the broader CSI 800 universe, reporting that the share was 81% at the time of the note. It also cites two recent…

OsakkeetKiinan markkinatSalkun muodostaminen
BigQuant

The document introduces multiple linear regression as a model relating one dependent variable to several explanatory variables, contrasting it with simple regression. It connects the method’s broad use in quantitative finance with the progression from the…

TilastotiedeFaktoripohjainen sijoittaminenUsean omaisuuslajin sijoittaminen
BigQuant

This brief request proposes a factor based on the correlation between a benchmark’s returns and an individual stock’s returns over a three-day window. It names the intended inputs and lookback, but provides no code, worked example, explanation of how to…

OsakkeetTilastotiedeFaktoripohjainen sijoittaminen
BigQuant

This April 2020 market note reviews a sharp decline in Chinese equities amid weakening fundamentals and falling investor sentiment. It reports that large- and small-cap indexes had similar declines, while consumer and utility sectors held up better and…

OsakkeetKiinan markkinatSalkun muodostaminenRiskienhallinta
BigQuant

This note explains how to handle low-frequency financial or analyst factors alongside daily price and volume factors when constructing nonlinear models. One approach is to merge monthly or quarterly fundamentals with daily market data and carry the latest…

KoneoppiminenFaktoripohjainen sijoittaminenTilastotiedeHistoriatestaus
BigQuant

This brief note describes a feature-selection exercise based on a random forest template. The author says they ranked 37 stock factors by random forest importance and retained the nine factors with the highest importance scores. The document does not…

OsakkeetFaktoripohjainen sijoittaminenKoneoppiminenTilastotiede
BigQuant

This Chinese-language research summary discusses forecasting stock-selection factor returns after commonly used factors became more volatile. It focuses on screening timing variables with Lasso and Elastic Net regression, then extending factor timing with…

OsakkeetFaktoripohjainen sijoittaminenKoneoppiminenHistoriatestaus
BigQuant

The post raises a backtesting concern: a user observes that a stock delisted on one date still appears sellable on a later scheduled rebalance date. A reply explains the platform behavior as a special backtest-engine rule: when a strategy does not handle a…

HistoriatestausOsakkeetRiskienhallinta
BigQuant

The document explains how to find the highest and lowest closing prices over roughly two years using rolling time-series maximum and minimum functions. It treats two years as about 400 trading days and applies those functions to the closing-price series,…

OsakkeetTekniset indikaattoritTilastotiede
BigQuant

This research summary proposes measuring capital flows between large-cap and small-cap styles to identify when style investors are shifting allocations. It treats flow intensity as a signal of changing conviction and risk: when intensity is high, investors…

OsakkeetFaktoripohjainen sijoittaminenTilastotiedeRiskienhallinta
BigQuant

This short weekly report summarizes a divided Chinese equity market, with major indices moving in different directions. It compares the reported changes in the Shanghai Composite, CSI 500, ChiNext, and CSI 300, then notes that most of the covered long…

OsakkeetKiinan markkinatHintamomentumSalkun muodostaminen
BigQuant

This brief market note reviews Chinese 50ETF options conditions for the week ending November 2. It reports that the ETF closed at 2.594 after gaining 3.1% for the week, while the trading-value put-call ratio fell from 0.754 on October 26 to 0.575. The note…

OptiotVolatiliteettiMarkkinatunnelmaKiinan markkinat
BigQuant

This weekly market commentary reviews Chinese equity index moves and sector themes for August 8–14, 2022. It highlights Chiplet-related stocks and financial firms, linking the former to semiconductor packaging developments and the latter to expectations…

OsakkeetKiinan markkinatTapahtumapohjainen kaupankäyntiRaaka-aineet