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Ieškoti bibliotekoje

3,481 dokumentų

BigQuant

The document presents price resiliency (RES), a covariance-based measure intended to capture both the price impact of liquidity shocks and how long those shocks persist. It compares returns in the first half-hour of trading with returns over the rest of the…

AkcijosStatistikaRinkos mikrostruktūraInvestavimas pagal veiksnius
BigQuant

This brief project note reports a modification to an existing quantitative strategy: market capitalization was added to the scoring process and return on equity was removed. The author says the backtest improved after the change, but provides no performance…

AkcijosInvestavimas pagal veiksniusPortfelio konstravimasIstorinis testavimas
BigQuant

The document explains how to choose between regression and classification when building machine-learning models for stock research. A regression task predicts a continuous quantity, illustrated by forecasting a stock’s five-day return. It introduces fitting…

Mašininis mokymasisAkcijosStatistikaKinijos rinkos
BigQuant

The report introduces a Barra-style multi-factor risk and return attribution model for Chinese equities. Its central idea is to explain the returns and risks of many stocks through a smaller set of style factors, making portfolio exposures easier to analyze.…

AkcijosKinijos rinkosInvestavimas pagal veiksniusRizikos valdymas
BigQuant

This short BigQuant discussion asks whether factor analysis of a custom stock universe requires manually importing a data table. The response says custom feature data can instead be passed into the factor-analysis module, enabling analysis for a user-defined…

AkcijosInvestavimas pagal veiksniusStatistikaKinijos rinkos
BigQuant

This BigQuant example attempts to close a stock position after its price falls more than 10% below cost, then exclude that instrument from target holdings until a cooldown expires. It tracks expiration dates in a pool, removes expired entries each day,…

AkcijosRizikos valdymasIstorinis testavimas
BigQuant

This guide explains how BigTrader turns simulated strategy signals into live orders through a desktop trading terminal. Users connect an account and access credential, load a simulation task, review the resulting plans, adjust order sizes and times, then…

Pavedimų vykdymasPozicijos dydžio nustatymasAkcijosKinijos rinkos
BigQuant

The document summarizes a report that uses a random forest model to identify rising and falling market patterns from macroeconomic indicators and market data. It describes two applications: timing exposure to the CSI 300 index and rotating among industry…

Mašininis mokymasisAkcijosKinijos rinkosPrekyba pagal tendenciją
BigQuant

This explanation defines an asset’s exposure to a factor as its sensitivity to that factor’s returns. It illustrates the idea with a value factor: filter a broad A-share universe, sort stocks by price-to-earnings ratio, and form a long-short portfolio from…

AkcijosInvestavimas pagal veiksniusStatistikaPortfelio konstravimas
BigQuant

This BigQuant help exchange explains how to select a fixed number of records after ranking a stock universe. The question concerns approximating a CSI 1000 universe when a direct index-membership filter is unavailable and usable daily constituent data is…

AkcijosKinijos rinkosPortfelio konstravimas
BigQuant

The report compares ordinary K-fold cross-validation with time-series cross-validation for tuning machine-learning models on sequential data. Random folds can place later observations in training while earlier ones are used for validation, creating leakage…

Mašininis mokymasisStatistikaIstorinis testavimasKinijos rinkos
BigQuant

This short support discussion explains why HFTrade applies a volume limit during high-frequency backtests and why that setting can prevent an order from filling completely. The discussion says volume caps may be poorly suited to minute and tick data, where…

Didelio dažnio prekybaIstorinis testavimasPavedimų vykdymasRinkos mikrostruktūra
BigQuant

This research summary outlines a strategic allocation model that maps Chinese equities and bonds to underlying macroeconomic risks. It uses principal component analysis to define five factors: economic growth, interest rates, credit, term spread, and…

Kelių turto klasiųAkcijosFiksuoto pajamingumo priemonėsInvestavimas pagal veiksnius
BigQuant

The document summarizes research on the disposition effect among actively managed U.S. equity mutual funds: managers may sell winning stocks too readily while holding losing stocks. It describes a measurement based on quarterly changes in reported holdings…

AkcijosStatistikaInvestavimas pagal veiksnius
BigQuant

The document distinguishes temporary factor decay from permanent factor failure. It attributes much of the decline in a signal’s excess returns to competition: as more capital uses a factor, its alpha can shrink, while changing market styles may later…

Investavimas pagal veiksniusDidelio dažnio prekybaPavedimų vykdymas
BigQuant

This essay presents a set of survival rules for trading Chinese equities during overheated bull markets, using the 2007 and 2015 market peaks as cautionary examples. It describes a recurring pattern of shakeouts, rapid speculative advances, and liquidity…

Kinijos rinkosAkcijosRizikos valdymasPozicijos dydžio nustatymas
BigQuant

This brief presents a market review for Chinese A-shares during March 23–27, 2020, alongside a report title stating that the strategic long stance remained unchanged. It lists the strongest and weakest industry groups for the week and tracks several breadth…

AkcijosKinijos rinkosTechniniai rodikliaiPortfelio konstravimas
BigQuant

This Chinese equity research note proposes unexpected profitability as a source of stock-selection alpha. It measures operating profitability with return on net operating assets (RNOA), which separates operating activity from financing and is presented as…

AkcijosInvestavimas pagal veiksniusStatistikaKinijos rinkos
BigQuant

This article presents a critical account of quantitative trading’s possible effects on Chinese equity markets. It argues that rapid order placement and cancellation can make displayed depth incomplete, that some funds combine stock baskets with short index…

AkcijosKinijos rinkosDidelio dažnio prekybaRinkos mikrostruktūra
BigQuant

This document outlines a recurring BigQuant program for people developing quantitative trading skills. It has three stages: an online selection round in which participants submit factor models built from a provided template; training for selected entrants;…

Investavimas pagal veiksniusIstorinis testavimasMašininis mokymasisDidelio dažnio prekyba
BigQuant

This project note describes iterative construction and evaluation of equity factors using amount, turnover, price, market capitalization, and price-to-book data. Candidate expressions combine standardized ratios and rolling statistics, including volatility,…

AkcijosInvestavimas pagal veiksniusIstorinis testavimasMašininis mokymasis
BigQuant

This post outlines a Chinese equity screening rule combining turnover, a rising DEA condition, and a cap on tradable share count. It selects stocks with turnover between 3% and 12%, a rising signal derived from moving-average differences, and a circulating…

AkcijosTechniniai rodikliaiKinijos rinkosRizikos valdymas
BigQuant

This article describes a reproduction of residual network experiments on CIFAR-10, focusing on two changes from an earlier run: image augmentation and shortcut design. It pads training images by four pixels on each edge and randomly crops them back to the…

Mašininis mokymasisIstorinis testavimasStatistika
BigQuant

This document outlines a simple Chinese A-share strategy that ranks stocks by return on equity and selects the ten highest-scoring candidates. It describes filtering out special-treatment stocks, suspended shares, recently listed companies, and Beijing Stock…

AkcijosInvestavimas pagal veiksniusPortfelio konstravimasIstorinis testavimas