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Ieškoti bibliotekoje

3,481 dokumentų

BigQuant

This forum post raises a data-preparation problem in an LSTM trading strategy. The author reports that filtering rows before rolling sequence windows can remove observations that should remain part of the temporal context, causing later observations to shift…

Mašininis mokymasisAkcijosStatistikaIstorinis testavimas
BigQuant

The article compares two ways to build equity strategies: train a predictive model on chosen factors and a defined stock universe, or specify screening conditions directly. The AI approach can be quicker to assemble, but its behavior may be hard to diagnose…

AkcijosMašininis mokymasisInvestavimas pagal veiksniusIstorinis testavimas
BigQuant

The report reassesses valuation, growth, technical, and risk factors in Chinese A-shares after removing industry and style influences. Its core method is to adjust factor data for exposures such as industry, market capitalization, or beta, then test whether…

Kinijos rinkosAkcijosInvestavimas pagal veiksniusIstorinis testavimas
BigQuant

Fundamental quantitative investing applies statistical methods and algorithms to company accounts, industry information, and macroeconomic data to rank stocks by estimated value or quality. The document describes analyzing profitability, financial strength,…

AkcijosInvestavimas pagal veiksniusPortfelio konstravimasStatistika
BigQuant

The paper examines how five emotions expressed on Sina Weibo—anger, disgust, fear, joy, and sadness—relate to Chinese stock returns. It uses machine learning to classify posts and wavelet analysis to study how the relationship changes over time and across…

Kinijos rinkosAkcijosRinkos nuotaikosMašininis mokymasis
BigQuant

This competition entry modifies a Deep Alpha convolutional neural network by supplying five time slices for each of 98 factors, rather than using a single slice. The network structure and most parameters remain close to the original model because training…

AkcijosMašininis mokymasisInvestavimas pagal veiksniusIstorinis testavimas
BigQuant

This report examines changes in concentrated holdings among Chinese active equity funds using quarterly disclosures and a daily estimate of fund exposure to a core group of crowded stocks. It compares the core group’s holdings over time, separates changes in…

AkcijosKinijos rinkosStatistikaInvestavimas pagal veiksnius
BigQuant

This support exchange concerns an IndexError that occurs when a Chinese convertible bond data table is read during a backtest. The same table can be read outside the backtest, and comparable reads of other tables within the backtest reportedly succeed. That…

Istorinis testavimasStatistikaKinijos rinkos
BigQuant

This short BigQuant assignment describes a daily stock-ranking approach built from a combination of total equity and trailing-twelve-month average return on equity. Each day, the strategy holds stocks with comparatively high values of the combined factor. It…

Kinijos rinkosAkcijosInvestavimas pagal veiksniusPortfelio konstravimas
BigQuant

This overview introduces three types of company data associated with FactSet: a six-level product and service based industry classification, company-to-company supply-chain relationships, and geographic revenue exposure. The classification is presented as a…

AkcijosInvestavimas pagal veiksniusRenginiais pagrįsta prekybaPortfelio konstravimas
BigQuant

This forum exchange explains why a sell order can disappear in an event-driven backtest when the stock is suspended on the scheduled execution day. The order was generated on one day, but the attempted match on the next day failed because trading was halted;…

AkcijosIstorinis testavimasPavedimų vykdymas
BigQuant

This weekly report describes two quantitative equity approaches. The first builds on holdings of successful active funds, then applies quantitative selection to create an enhanced portfolio benchmarked against active equity funds rather than broad market…

AkcijosInvestavimas pagal veiksniusRenginiais pagrįsta prekybaTechniniai rodikliai
BigQuant

This note explains beta as a measure of an asset’s market risk exposure and introduces the Fama–French three-factor model as a way to capture size and value style exposures. It describes how to quantify style performance with long-short portfolios: small-cap…

AkcijosInvestavimas pagal veiksniusStatistikaKinijos rinkos
BigQuant

This research proposes a stock selection factor that estimates similarity between companies using ten financial measures spanning profitability, solvency, operating efficiency, and growth. After cross-sectional normalization, it uses cosine similarity to…

Kinijos rinkosAkcijosInvestavimas pagal veiksniusImpulsas
BigQuant

This post sketches an experimental model for identifying leading stocks, using gradient boosted regression to score shares within a rolling window. The proposed label gives higher scores to stocks that rise more, experience smaller drawdowns, and break out…

AkcijosMašininis mokymasisPramušimasRizikos valdymas
BigQuant

This China equity strategy ranks stocks cross-sectionally using circulating market capitalization and earnings per share, combining the rankings into a total score and sorting from low to high. It excludes special-treatment and suspended stocks, requires…

Kinijos rinkosAkcijosInvestavimas pagal veiksniusIstorinis testavimas
BigQuant

The article argues that retail traders often sell during fear and re-enter during excitement, while institutions may accumulate during declines and distribute into renewed demand. It recommends treating oneself as a follower, watching capital flows, and…

Rinkos nuotaikosRinkos mikrostruktūraRizikos valdymas
BigQuant

This review of research on equity factor investing explains why low unconditional correlations between factors may not provide protection when macroeconomic conditions deteriorate. It describes selecting fast-moving state variables that reflect expectations…

AkcijosInvestavimas pagal veiksniusPortfelio konstravimasRizikos valdymas
BigQuant

This report examines why investment portfolios turn over, how to manage that turnover, and how turnover control affects portfolio outcomes. It frames the drivers across the research and trading process: alpha changes influence target holdings, optimization…

Portfelio konstravimasPavedimų vykdymasRizikos valdymasAkcijos
BigQuant

The document describes a hybrid approach that combines ARMA-GARCH models with several neural network types to identify market patterns and predict the direction of shocks in defense equities and foreign exchange. ARMA-GARCH models capture linear time-series…

Mašininis mokymasisStatistikaKintamumasAkcijos
BigQuant

This note describes a daily liquidity signal built from intraday order book snapshots. It sums bid and ask volumes across the first five levels, then measures their normalized imbalance as the difference divided by the total. Separately, it calculates…

Investavimas pagal veiksniusRinkos mikrostruktūraStatistika
BigQuant

The document briefly introduces a multi-factor investment platform, focusing on how to estimate stock and portfolio factor exposures. Stock exposures are derived from database values such as price-to-earnings and price-to-book ratios, then cleaned and…

Investavimas pagal veiksniusPortfelio konstravimasStatistika