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Hae kirjastosta

3,481 dokumenttia

BigQuant

This report introduces an early-stage study of market microstructure signals in the IF equity index futures contract. It proposes examining the difference between midpoint and trade-price log returns, quoted depth, large trades, and signed volume. The…

FutuuritMarkkinoiden mikrorakenneTilastotiedeKorkean taajuuden kaupankäynti
BigQuant

This document reviews an empirical comparison of machine learning approaches for forecasting monthly returns in China’s A-share market. The described process trains models on prior data, uses a validation period for tuning, and tests predictions out of…

Kiinan markkinatOsakkeetKoneoppiminenFaktoripohjainen sijoittaminen
BigQuant

This research summary reviews tests of eight proprietary price-volume factors in Chinese equities, comparing monthly, weekly, and biweekly rebalancing. The factors include active buying and selling, smart money, ideal amplitude, APM, ideal reversal, large-…

OsakkeetKiinan markkinatHintamomentumTekniset indikaattorit
BigQuant

The document outlines the Chaikin oscillator, a technical indicator built from price and volume data. It first weights volume by the relationship between the close and open relative to the day's high-low range, cumulatively sums that measure, and then takes…

Tekniset indikaattoritTilastotiedeOsakkeet
BigQuant

This tutorial describes a Python workflow for comparing two subfunds with the China Securities 1000 Index using weekly net asset values. It calculates rolling correlations over a 20-day window and plots how those relationships change, then compares period…

Kiinan markkinatTilastotiedeRiskienhallintaSalkun muodostaminen
BigQuant

This example describes a daily, long-only futures strategy using a 10-period average crossing a 30-period average to generate entry and exit signals. A 120-period moving average acts as a trend filter: the strategy opens a position after an upward crossover…

FutuuritTrendin seuraaminenTekniset indikaattoritHistoriatestaus
BigQuant

The document outlines a workflow for building equity strategies that adapt their stock-selection logic to market conditions. It proposes measuring market sentiment with signals such as the number of limit-up stocks and average returns, then adding industry…

OsakkeetFaktoripohjainen sijoittaminenTilastotiedeHistoriatestaus
BigQuant

This post is a satirical warning about trusting impressive quantitative strategy claims and backtest curves. It points readers toward shared deep-learning strategy code, but supplies no description of the model, training data, signals, or validation process.…

HistoriatestausRiskienhallintaPosition koon määrittäminen
BigQuant

This Chinese market-timing report reviews sector strength, valuation, breadth, moving-average structure, and equity-fund positioning around July 2020. Its summary highlights stronger recent breadth: the share of stocks reaching 60-day highs and the balance…

OsakkeetKiinan markkinatHintamomentumTekniset indikaattorit
BigQuant

The article presents a robust version of equal risk contribution (risk parity) portfolio construction. It treats the estimated covariance matrix as uncertain and builds a bounded uncertainty set around the estimate. The optimization then accounts for…

Salkun muodostaminenRiskienhallintaTilastotiedeHistoriatestaus
BigQuant

This research note describes an enhancement strategy for China’s CSI 1000 small-cap equity index. It combines factors representing valuation, growth, trading behavior, capital flows, and network relationships within index constituents. After neutralizing for…

OsakkeetFaktoripohjainen sijoittaminenSalkun muodostaminenHistoriatestaus
BigQuant

This research summary describes how to build and compare active and passive portfolios of Chinese healthcare-themed funds. For active funds, it argues that screening should use actual underlying holdings, since a fund's label may not reflect a concentrated…

OsakkeetKiinan markkinatSalkun muodostaminenHistoriatestaus
BigQuant

The document discusses whether stochastic-process mathematics, including Brownian motion, still matters as machine learning becomes more common in quantitative finance. It presents several practitioner views: stochastic calculus has a stronger role in…

KoneoppiminenTilastotiedeJohdannaisten hinnoitteluToimeksiantojen toteutus
BigQuant

This 2018 research summary forecasts changes to the FTSE China A50, an index of large Chinese mainland stocks selected with free-float and liquidity considerations. It describes quarterly reviews in March, June, September, and December, and identifies index…

OsakkeetKiinan markkinatTapahtumapohjainen kaupankäyntiSalkun muodostaminen
BigQuant

This commentary examines sharp style swings in China’s A-share market, using recent surges and reversals in the nonferrous metals sector as its main example. It argues that a rapid rise concentrated in a small number of stocks can pull liquidity from other…

Kiinan markkinatOsakkeetMarkkinoiden mikrorakenneMarkkinatunnelma
BigQuant

This overview distinguishes language generation from financial prediction, arguing that strong text generation does not by itself solve markets’ low signal-to-noise ratios, changing patterns, and limited data. It explains GPT’s development and instruction…

KoneoppiminenTilastotiedeHistoriatestausJohdannaisten hinnoittelu
BigQuant

The document outlines a daily trend-following strategy for commodity futures based on Bollinger bands. It enters long when price breaks above the upper band and short when price breaks below the lower band, then exits when price crosses back through the…

FutuuritRaaka-aineetTrendin seuraaminenLäpimurto
BigQuant

This weekly review compares style-factor performance across Chinese equity universes and summarizes quantitative public-fund returns against broader stock and equity-oriented funds. It reports that price and trading activity related factors—including…

OsakkeetKiinan markkinatFaktoripohjainen sijoittaminenPalautuminen keskiarvoon
BigQuant

The article describes a method for estimating consensus net profit from analyst forecasts and using that estimate to build equity selection signals. It weights forecasts by report recency and by each analyst’s prior adjusted forecast error, giving greater…

OsakkeetFaktoripohjainen sijoittaminenTilastotiedeHistoriatestaus
BigQuant

This opinion article argues that retail traders face a structural disadvantage in short-term equity trading because quantitative firms can use fast systems and direct market connectivity. It attributes the gap to execution speed and claims that automated…

OsakkeetToimeksiantojen toteutusMarkkinoiden mikrorakenneRiskienhallinta
BigQuant

The article describes REDD-COPS, a dynamic allocation method designed to constrain rolling portfolio drawdown while pursuing long-term growth. It replaces a lifetime peak-to-trough reference with a rolling economic maximum, then adjusts exposure to risky…

Usean omaisuuslajin sijoittaminenSalkun muodostaminenRiskienhallintaVolatiliteetti
BigQuant

This short forum exchange addresses how to adapt a BigQuant strategy to rebalance on a five-day schedule. The reply recommends defining the holding-period setting in the backtest module’s initialization function, then using the K-line processing function to…

OsakkeetHistoriatestausSalkun muodostaminen
BigQuant

This article explains why high-frequency trading firms invest heavily in reducing the time it takes to receive market information and send orders. It describes an earnings-news episode in which an automated firm traded before financial news terminals…

Korkean taajuuden kaupankäyntiToimeksiantojen toteutusMarkkinoiden mikrorakenne
BigQuant

The document introduces an MQL4 library that ports regular-expression functionality from the .NET Framework. It outlines the library’s components for patterns, matches, capture groups, options, and Unicode character categories. It also lists options such as…

Toimeksiantojen toteutus