Mispricing and Investor Preference with Six Indicators of Blue-Chip Stocks’ Future Returns

Abstract

This research involves three variables: future returns, mispricing, and investor preference. The issue is that future returns in the markets are difficult to understand, especially for beginner, amateur investors. They are advised to focus on blue-chip stocks due to their safety in the market. The objective of this research is to find a connection from mispricing and investor preference to the future anomalies as indicators of mispricing and ten measurements as indicators of investor preference leading to three anomalies of mispricing and three measurements of investor preference. The three anomalies are asset growth, net operating assets, and total returns of blue-chip stocks. The methods used are descriptive statistics and associative statistics. In this research, we adopted eleven liabilities to total assets, while the three investor preferences are beta synchronous trading, book equity to market equity, and size. The descriptive statistics show that the asset growth, net operating asset, and size of eight companies are above the mean and the others are below it. Blue-chip stocks have excellent growth in assets, high operating assets, and high market capitalization. In addition, they have low liabilities (solvable), book value to market value (high return), and beta (low market sensitivity). The associative statistics used the multiple-regression cross-section Newey–West method and conducted the examination three times; that is, it tested mispricing with three indicators, investor preference with three indicators, and additional indicators between mispricing and investor preference. The result is not significant for the investor preference and mispricing index for the future returns of blue-chip stocks. The policy implication is that there is no divergence between fundamental and price security in the types of blue-chip stocks for future returns. Moreover, the institutional or individual investor does not impact future return’s stocks.

Predictability of Asset Returns on Blue Chip Stocks

“…This indicates that the stocks in the KFX index face higher demand or more attention than the stocks outside the index. Iman, Syamruddin, Irwansyah (2020) suggested that the result is not significant for the investor preference and mispricing index for the future returns of blue-chip stocks [3]. However, this study still has some limitations, because this study only includes three U.S. indexes, and it does not rule out that the indexes of other countries and regions will have different changes.…”

Kurtosis and Skewness on Lagged Market Risk Premium in Indonesian Market During Covid 19 Pandemic

“…From US listed firms, the firms with top brands have higher stock returns, lower sytematic risk and lower idiosyncratic risk than others (Huang et al, 2021). It might be also similar to Blue Chips in Indonesia (Lubis et al, 2020).…”

“…Indonesia Capital Market or IHSG is the lowest risk market among Southeast Asian Countries (Lubis, 2018a). Thus, From many indexes, there are several indexes that are market stability such as development board index, the miscellaneous industry index, the Indonesian FTSE indeks, the LQ-45 index, the 30 stock index , and the sharia index (Lubis, 2018b) From the previous explanation on researches, I could see that during COVID-19 pandemic, almost stock market returns in all of the world found in bear phase except Japanese Market. This fact motivate me to explore the stock market returns which called aset pricing.…”

“…From the previous theoretical learning there is a link between asset pricing and skewness where the systematic risk of skewness also carries a premium risk (Rubinstein, 1973) (Kraus & Litzenberger, 1976) (Harvey & Siddique, 2000) and a model that states total skewness of both systematic and idiosyncratic is important in securities valuation (Brunnermeier et al, 2007); (Barberis et al, 2008); (Mitton & Vorkink, 2007). At Langlois (2019) there are differences with research beforehand regarding their assumptions with investors' choices.…”

“…Recent research measures the depth of the market crash (Cerrato et al, 2017); adding to adding to portfolio performance (Jondeau & Rockinger, 2012); (Martellini & Ziemann, 2010); the best predictor of market returns (Jondeau et al, 2019); specifying downside beta market (Harris et al, 2019); strengthening skewness and kurtosis with the GJR-GARCH method (1,1) (Alexander et al, 2021); and until the future third-moment absolute company returns have a negative relationship with institutional ownership and market capitalization, different from that in the US (Zhen, 2020). From the explanation above, I would like to have an empirical perspective on kurtosis in the Indonesian capital market, whether it is a systematic risk, not a corporate risk.…”