Whether profitability and investment factors have additional explanatory power comparing with Fama-French Three-Factor Model: empirical evidence on Chinese A-share stock market

Jiao, Wenting; Lilti, Jean-Jacques

doi:10.1186/s40589-017-0051-5

Cited by 22 publications

(12 citation statements)

References 18 publications

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“…The improvement for FF 6-Factor Model and 3-Factor Model was marginal. The same results could also be found in the paper by the team of Kubota et al, Jiao et al and the team of Guo et al based on the stock market of Japan and China [30][31][32]. The additional two factors of investment and profitability were statistically insignificant for most portfolios.…”

Section: Ff Factor Literature Reviewsupporting

confidence: 82%

A Comparative Analysis of the Application of Machine Learning Algorithms and Econometric Models in Stock Market Prediction

Ni¹,

Chen²

2022

BCPBM

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Forecasting the future price trend of a stock traded on a financial exchange is the aim of stock market prediction. In recent decades, stock market prediction has been a fascinating topic in the domain of Data Science and Finance. In reality, the stock movement is ambiguous and chaotic due to various influencing factors such as government policy, current events, interest rates Etc. At the same time, accurate enough forecasting of stock price movement leads to substantial benefits for investors. This paper provides a comprehensive review of the application and comparison of Machine Learning (ML) algorithms and Econometric Models in stock market prediction. The mentioned models are categorized into (i) ML algorithms, including Linear Regression (LR), K-nearest neighbors (KNN), Support Vector Machine (SVM), and Long Short-Term Memory (LSTM). (ii) Econometric Models, including Autoregressive Integrated Moving Average (ARIMA) Model, Capital Asset Pricing Model (CAPM), and Fama-French (FF) Factor Model.

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Section: Ff Factor Literature Reviewsupporting

confidence: 82%

A Comparative Analysis of the Application of Machine Learning Algorithms and Econometric Models in Stock Market Prediction

Ni¹,

Chen²

2022

BCPBM

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“…Sutrisno and Ekaputra (2016) compared the Fama-French threefactor (FF3F) and five-factor (FF5F) effects on the Indonesia Stock Exchange (IDX). Conversely, Jiao and Lilti (2017) conducted a similar study in the Chinese A-share stock market and obtained a similar result. In Indonesia, FF5F was discovered to be slightly better than FF3F in explaining the excess return of stock portfolios.…”

Section: Introductionmentioning

confidence: 63%

Implementation of Capm, Fama-French Three-Factor, and Five-Factor in Indonesia Stock Exchange and Cement Industry Sector

Wedagama

Hakim

Juanda

et al. 2022

IJEFI

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Weighting Average Cost of Capital (WACC) plays a critical role as a discounting factor of the corporate valuation process's estimated future free cash flow by highly influencing the valuation process. It consists of three components, namely cost of debt, cost of equity, and proportion of capital structure. Costs of debt and capital structure are easily calculated due to data stability and less volatility. Meanwhile, the cost of equity is difficult to determine due to assumption, the period taken, the method applied, and complexity. Many assets pricing methods are used to determine the required rate of return in equity, namely CAPM, Fama French Three-Factor (FF3F), and Fama French Five-Factor (FF5F). These three asset pricing models are used to determine the models with strong explanatory factors on equity return to portfolios developed from sorting FF5F factors and individual equity of four cement companies publicly listed in the Indonesia Stock Exchange (IDX).

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“…Recently, Jiao (2017) found in china the applicability of the FF5F model, the model outperforms, on the other hand, Kubota and Takehara, (2018) found the FF5F model was insufficient in describing variance to the previous literature of the asset returns. This evidence leads to the conclusion that the effect of some anomalies remains unexplained.…”

Section: Introductionmentioning

confidence: 98%

Testing Liquidity Augmented Fama-French Five-Factor Model in Pakistan Stock Exchange

Haqqani

Aleem

2020

GER

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This study examines the empirical evaluation of the six-factor asset pricing model that augments the Fama-French (2015) five-factor asset pricing model with liquidity factor. Using data from July 2010 to June 2017 of non-financial firms listed on PSX, a 2x3 sort approach is used to construct six left-hand side portfolios, and a 2x2 approach is used to construct right-hand side factors namely, SMB, HML, RMW, CMA, and IML. Time series regression is used to analyze the data to obtained results. The empirical evidence illustrates that in PSX the six-factor model has efficient and better outcomes. Furthermore, the liquidity factor has a strong role in improving the performance of the asset pricing model.

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Whether profitability and investment factors have additional explanatory power comparing with Fama-French Three-Factor Model: empirical evidence on Chinese A-share stock market

Cited by 22 publications

References 18 publications

A Comparative Analysis of the Application of Machine Learning Algorithms and Econometric Models in Stock Market Prediction

A Comparative Analysis of the Application of Machine Learning Algorithms and Econometric Models in Stock Market Prediction

Implementation of Capm, Fama-French Three-Factor, and Five-Factor in Indonesia Stock Exchange and Cement Industry Sector

Testing Liquidity Augmented Fama-French Five-Factor Model in Pakistan Stock Exchange

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