Evaluation of forecasting methods from selected stock market returns

Mallikarjuna, M.; Rao, R. Prabhakara

doi:10.1186/s40854-019-0157-x

Cited by 64 publications

(60 citation statements)

References 67 publications

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“…Besides predictors, forecasting techniques also play an important role in determining forecast accuracy. According to Mallikarjuna and Rao ( 2019 ), traditional regression techniques generally outperform others including artificial intelligence and frequency domain models in providing accurate forecasts.…”

Section: Literature Reviewmentioning

confidence: 99%

COVID-19 and instability of stock market performance: evidence from the U.S.

2021

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The effect of COVID-19 on stock market performance has important implications for both financial theory and practice. This paper examines the relationship between COVID-19 and the instability of both stock return predictability and price volatility in the U.S over the period January 1st, 2019 to June 30th, 2020 by using the methodologies of Bai and Perron (Econometrica 66:47–78, 1998. 10.2307/2998540; J Appl Econo 18:1–22, 2003. 10.1002/jae.659), Elliot and Muller (Optimal testing general breaking processes in linear time series models. University of California at San Diego Economic Working Paper, 2004), and Xu (J Econ 173:126–142, 2013. 10.1016/j.jeconom.2012.11.001). The results highlight a single break in return predictability and price volatility of both S&P 500 and DJIA. The timing of the break is consistent with the COVID-19 outbreak, or more specifically the stock selling-offs by the U.S. senate committee members before COVID-19 crashed the market. Furthermore, return predictability and price volatility significantly increased following the derived break. The findings suggest that the pandemic crisis was associated with market inefficiency, creating profitable opportunities for traders and speculators. Furthermore, it also induced income and wealth inequality between market participants with plenty of liquidity at hand and those short of funds.

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Section: Literature Reviewmentioning

confidence: 99%

COVID-19 and instability of stock market performance: evidence from the U.S.

2021

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“…Theoretical and empirical studies have revealed that the relation between stock markets and economic growth is positive (Kim et al 2011;Guptha and Rao 2018;Mallikarjuna and Rao 2019). Investment decision plays a significant role in attaining the desired returns through stock market forecasts.…”

Section: Introductionmentioning

confidence: 99%

S&P BSE Sensex and S&P BSE IT return forecasting using ARIMA

2020

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This study forecasts the return and volatility dynamics of S&P BSE Sensex and S&P BSE IT indices of the Bombay Stock Exchange. To achieve the objectives, the study uses descriptive statistics; tests including variance ratio, Augmented Dickey-Fuller, Phillips-Perron, and Kwiatkowski Phillips Schmidt and Shin; and Autoregressive Integrated Moving Average (ARIMA). The analysis forecasts daily stock returns for the S&P BSE Sensex and S&P BSE IT time series, using the ARIMA model. The results reveal that the mean returns of both indices are positive but near zero. This is indicative of a regressive tendency in the long-term. The forecasted values of S&P BSE Sensex and S&P BSE IT are almost equal to their actual values, with few deviations. Hence, the ARIMA model is capable of predicting medium- or long-term horizons using historical values of S&P BSE Sensex and S&P BSE IT.

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“…It has been found that emerging markets usually have high stock returns as compared to developed markets due to noise, less transparent information, and expected market liquidity (Paddrik and Tompaidis 2019). Mallikarjuna & Rao (2019) explains that the forecastability enhances the real value of the stock and if significant, the investors buy the stocks to get a high return. Therefore, forecasting of the stock returns using market ratios is considered significant for investment decisions.…”

Section: Introductionmentioning

confidence: 99%

“…Conclusively, the Forecasting Error Statistics of the Emerging Market Level Return outperformed the Market Level Return based on in-sample fit forecastability. The forecast error statistics are found to be dynamically efficient forecast errors to predict the stock returns(Mallikarjuna and Rao, 2019; Caldeira et.al., 2020;Clark et. al., 2020)…”

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confidence: 99%

Analysis and Forecastability of Market Model: Evidence From Pakistani Market Index and Emerging Market Index

Mubarik

Saeed

Shahab

2021

HSSR

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Purpose of the Study: This study examines and analyzes the influence of the Market Model on the Market Level Return (KSE-100 index) and the Emerging Market Level Return (MSCI Index). Methodology: The study has employed the sample data of the companies’ representatives of the Oil and Gas Sector of Pakistan from July 2001 to June 2018 respectively. For estimation, the Panel Regression techniques are employed followed by the Forecast Error Statistics for the in-sample forecast ability of the variables under study. Main Findings: The results of the study depict that the Market Model comprising of the Market Value Financial Ratios strongly influences the returns of the Emerging Market Index relative to the Market Level Return respectively. Similarly, the predictive power of the Market Model is more influential at the Emerging Market Level Return but not less at Market Level Return. Application of the Study: The findings of the study suggest that the domestic and foreign investors may consider the Market Value Financial Ratios for the valuation and estimation of asset prices. Moreover, the local authorities may take robust steps to continuously reforms in the Energy Mix policy to enhance local as well as foreign investment. Novelty/Originality of this study: The prime novelty of the study is to analyze the market model based on Market Value Financial Ratios to forecast the Market Level Return and Emerging Market Index Returns using three standard symmetric measures; root mean square error (RMSE), the mean absolute error (MAE), the mean absolute percentage error (MAPE) and the Theil inequality coefficient (TIC) respectively.

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Evaluation of forecasting methods from selected stock market returns

Cited by 64 publications

References 67 publications

COVID-19 and instability of stock market performance: evidence from the U.S.

COVID-19 and instability of stock market performance: evidence from the U.S.

S&P BSE Sensex and S&P BSE IT return forecasting using ARIMA

Analysis and Forecastability of Market Model: Evidence From Pakistani Market Index and Emerging Market Index

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