VALUATION EFFECT OF CORPORATE NAME CHANGE IN CHINESE TECHNOLOGY STOCKS

Each year, hundreds of firms change names in China. A corporate name change is an expensive proposition. Hence, one may wonder whether investors truly reward such corporate actions. This study examines the short-term valuation effect of corporate name changes for China technology stocks. We classify the nature of name changes into the concept vs. non-concept related name changes and strategic vs. cosmetic name changes. In addition to the nature of name change, we also examine the effect of market sentiment on the name change of technology companies’ values. Our findings reveal that firms with concept-related name changes and strategic name changes generate significantly positive cumulative abnormal returns on the announcement date. However, the same outcome cannot be achieved in the pre- and post-event periods. Our results further show that investors of Chinese tech stocks are not influenced by their sentiment, suggesting that investors are bounded rational in China.


INTRODUCTION
Over the past few months of the COVID-19 pandemic crisis, companies are scrambling to file for a change of subsidiaries' names to include buzzwords related to the hottest market trend, such as "bio" or "biotech." A firm's name To link to this article: https://doi.org/10.21315/aamjaf2022.18.1.3 change is not uncommon in the corporate landscape. A firm's name is considered an intangible asset representing a firm's reputation and can be traded. The firm's name reflects its identity, which is used to transmit information about its prospects to investors or is viewed as a signal for its future development and plans (Karim, 2011). A corporate name change can be either structural, indicating the firm's change of ownership or matching the change of the firm's business lines, or a pure name change. Kashmiri and Mahajan (2015) document that name changes help firms improve their inherent and signaling values. A firm's name change is an expensive proposition. It can lead to hefty tangible and intangible costs, such as legal payment, advertisement spending, reputation, and goodwill. Therefore, we naturally expect firms to change names only when it leads to shareholder value creation.
The valuation effect of a name change is defined as a positive market reaction to the name change announcement. Ideally, managers take specific corporate actions only if it results in increased shareholder value. There are many legitimate reasons why a firm changes its name, including major asset restructuring, changes in controlling shareholders, leading business changes, and name changes compelled by regulation. However, there are also less common cases where managers change the corporate names to cope with the market conditions, such as attempting to associate the firm with the current hot industries. Since name change is an expensive corporate exercise, investigating how investors respond to firms' decisions to such a corporate action is worth investigating. Several studies have examined whether a relationship exists between a name change and its nature and the relationship between a name change's valuation effect and firms' past performance (Wu, 2010;Khorana et al., 2003;Kot, 2011).
However, few have focused on the relationship between name change's valuation effect and market sentiment. For example, Lin et al. (2016) compare the valuation effect of oil-related name change in the US and Canada and find that greater investor sentiment would result in more significant abnormal returns. Besides, most studies focus on the developed markets, but how investors in the emerging market respond to name change may differ from developed markets. This study aims to fill these gaps by examining whether a name change is associated with abnormal returns for the China A-share market and explore how the characteristics associated with name change affect the abnormal returns.
Name change of listed companies is a common phenomenon in the Chinese A-share market. However, studies in this area are scant for the market. We select the China market, and the technology industry in particular, for the following reasons. First, technology stocks have always been the investors' focal point due to the sector's accelerated growth in recent years. The increased attention in technology stocks is particularly evident during the current pandemic crisis as the Chinese government devotes much of its resources to developing the technology sector. He et al. (2020) study Chinese industries' responses towards the COVID-19 pandemic and report that information technology industries have been resilient to the pandemic.
Secondly, the ongoing intensified China-US trade war targets the technology industry, reshaping the worldwide suppliers of telecommunications networks, and directly affecting the sector's capital flow. Chi et al. (2020) suggest that a trade war would negatively impact global trade, investment, and economic growth. Given the backdrop that China and the US are imposing regulations and policies to protect their domestic technology sectors, the tech sector is pushed into the global spotlight. Thirdly, China's stock market is dominated by individual investors.
This market structure makes it more vulnerable to stock price manipulation when firms shore up share prices by taking corporate actions unrelated to the fundamentals. In such an environment, Baker and Wurgler (2007) argue that the demand for speculative securities would be higher, and speculative stocks are expected to have a higher return when investor sentiment ups. We are convinced that the China technology industry presents an ideal platform to investigate how investors respond to firms' decisions to change names for the above reasons.
This study adds to the limited evidence of emerging markets in several ways. First, it investigates whether investors of Chinese technology stock are subjected to market sentiment. Secondly, the study examines whether and how investor behaviors differ with different types of name changes. Third, whether firms can deceive investors through name change that is not also accompanied by structural change, that is, a pure name change.
Firms transmit valuable information, such as the reason for a name change, in and around the announcement date. The existing literature reported mixed evidence of the valuation effect of a name change. Typically, three scenarios are observed following a corporate name change announcement: positive impact (Kot, 2011;Karim, 2011;Berkman et al., 2011), adverse impacts (Asyngier, 2018), or an absence of a significant effect (Lin et al., 2016). Following the rationality perspective, the valuation effect should be positively significant on the event date. However, Baker and Wurgler (2007) argue that individual investors may under-or overreact to such corporate announcements due to psychological biases such as overconfidence, conservatism, and the like. Some studies focus on how the valuation effect differs for different types of name change. The different kinds of name change comprise a major name change, minor name change, addition name change, or deletion name change.
In this regard, a major name change denotes changing the entire firm name. For example, Shanghai Duolun Industry Co. Ltd, an architectural ceramics enterprise, changed its name to P2P Financial Information Service Co. Ltd during the internet boom in 2015. A minor name change, on the other hand, involves instances where a firm changes part of its name.
However, in the minor name change, the new name can still be identified in its original firm, as when Sichuan Troy Information Technology Co. Ltd. changed its name to Troy Information Technology Co. Ltd. It has been documented that a major name change results in a firm earning a higher abnormal return since it passes on stronger signals to investors. These finding contrasts that of a minor name change that does not report such abnormal returns (Khorana et al., 2003;Kot, 2011;Biktimirov & Durrani, 2017). In China, stocks are ubiquitously classified into various concepts based on a firm's business, and every concept class carries with it a particular connotation and is usually thematic. One such example is the Olympic theme stocks that refer to companies with business opportunities tied to the Olympic Games. Our study incorporates this unique concept-classification system in defining the types of firms' name change in this setting. We define hot concept stocks as the firm's stock that receives intense attention from investors and vice versa. We hypothesise that hot stocks stand a higher chance of being overvalued as compared to their peers. Due to investors' limited attention to securities, the firms whose names contain concept terms may be more likely to receive investors' attention (Jiang, 2016). It is likely that managers take advantage of this investor behavior and change the firm name in a grandstanding way to lure less-informed investors into buying the firm's shares.
A firm name is considered an intangible asset since the value represents the firm's future income. Several studies examine the relationship between the drivers of a name change and its associated cumulative abnormal returns. Kashmiri and Mahajan (2015) and Biktimirov and Durrani (2017) document that the perceived reasons for a firm name change affect the firm's value. Wu (2010) reports that firms that change names send signals about the imminent change of the firm's businesses. In addition to the concept classification, we also classify name change into either a strategic name change or a cosmetic name change. Our result reports the presence of significant positive abnormal returns only for strategic name changes.
Moreover, we examine the influence of market sentiment on investor behaviour using the turnover of the tech index as the proxy for market sentiment. We expect the valuation effect to be positive when the market sentiment is generally upbeat (Baker & Wurgler, 2007).
Many reasons were advanced to explain the drivers of a corporate name change. Two broad theories underlying the motivations are signaling theory and behavioural finance. The signaling perspective claims that a firm uses name change to transmit information to investors, such as changes in the company structure and leading businesses. Behavioural finance theorists contend that managers exploit investors' irrational behaviour to push up stock prices and attract investors' attention by changing names. This irrationality perspective may explain the valuation effect of a cosmetic name change. Since cosmetic change may influence investors' perceptions and views about the firm, managers purportedly time the firm's actions to take advantage of these investor behavioral biases (Gupta & Aggarwal, 2014;Khorana et al., 2003). Jiang (2016) suggests that if irrational investors are optimistic about a particular industry or stock trends before the name change, a name change announcement would further intensify their existing optimism and confidence. This causes investors to overreact to a firm's name change and results in abnormal share price increases.
This study contributes to the limited empirical literature by examining the effect of a name change within the Chinese stock market framework. The remaining of the paper is organised as follows. We discuss the sample selection process and methodology in the next section. Next, empirical results are discussed in the next section. We then present the discussion and implications of our findings, and the last section concludes.

Data
This study's sample consists of all technology companies listed in the Shenzhen stock exchange and Shanghai stock exchange that have changed names between 1 January 2014 and 31 December 2018. Since the technology industry is a general term for several industries related to science and technology, which contain more than one industry, we selected several industries based on a technology-related index. For instance, since CSI Technology Top Index contains the computing industry, the computing industry is included in this study.
Thus, the technology industry consists of the following sub-industries: electronic component industry, computing industry, communication industry, pharmaceutical industry, and aerospace industry. To construct the sample, we first use the RESSET database to identify the technology industry companies that have changed names between 2014 and 2018. Our initial dataset comprises 196 name-change announcements. Next, we use Eastmoney Choice Database to collect firms' former names and data for other variables. We also scrutinise each firm's official announcement documents to determine the reasons for the firm's name change.
Less confauding events (72) Less missing data and outliers (17) Final sample 33 Table 1 summarises the sample selection process of this study. We first filtered out name changes required by the government (denote as passive name change hereafter). Next, we removed the firms that have publicly announced some confounding events five days before and five days after (−5, +5) the announcement date t. The confounding events referred to herein include earnings and dividend announcements, mergers or acquisitions, and operational and capital restructuring that have shown to impact a firm's value. The announcement date t is taken as when shareholders vote on the proposed name change or the meeting date at which shareholders approved the name change. If the event dates fall on a weekend, the next trading day would be used as the announcement date. Furthermore, firms that did not trade from t-1 to t+1 relative to the announcement date are omitted from our sample. Lastly, we exclude 17 firms with missing data from the sample pool. Our final sample set consists of 33 firms.

Event Study Methodology
In this study, short-term cumulative abnormal return (CAR) is computed using event study methodology. Following Lin et al. (2016), we estimate i and i from the capital asset pricing model (CAPM) given the market return R m,t and stock return R i,t at time t: where R i,t denotes the return for security i on day t. Referring to Armitage (1995) that suggests that estimation periods can range from anything between 100 to 300 days for daily observations, and following thw model of Lin et al. (2016), we calculate R mt as the market return using SZSE Tech Index with an estimation period of (−120, −16). Next, we compute the abnormal return (AR) for security I using Equation 2.
where α i − β i R m,t represents the stock's expected return. We then calculate the mean of CAR i for security i for the event windows from t = j to t = k, as shown in Equation 3.
Next, we conduct a multivariate regression analysis and use a student t-test to examine the hypotheses. Three event periods are employed for our investigations. These include the pre-event period from t-5 to t-1, event day from t-1 to t+1, and post-event period from t+1 to t+5. The [-5, -1] window is included to investigate information leakage before announcement day. The [-1, 1] window is designed to examine if investors react immediately to the announcement, and the [1, 5] window is imposed on accessing the investor's short-run reaction after the announcement. Karim (2011) document that CAR for the post-event period could be positive due to investors' delayed response to collect more information regarding the firms' economic potential or need time to make a complex analysis.

Regression Model
This section examines the effect of the name change's nature and turnover on CAR. The name change natures are either classified as a concept-versus non-concept name change or a strategic versus cosmetic name change.

Explanations of variables
Concept: Concept is a generic term for a class of stocks with common characteristics. This stock classification is unique in China. For illustration, network concept stocks refer to the companies involved in the information network industry. Hot concepts will change based on the market and societal developments over time. Investors can easily and quickly locate different kinds of concept stocks grouped under various specific categories in apps. Besides, investors usually choose stocks from the preferred concept group, and concept stocks always enjoy favourable advertising effects. A stock in itself may not be too attractive, but investors will closely follow it once it is categorised into a particular concept. As a result, investors may overreact to the firm name change under the irrationality perspective when the new name contains a concept term. We divide our sample name changes into those that contain concept terms and those that do not. The concept variable is labeled as 1 for a concept-related name change and 0 if otherwise.
Turnover: Turnover as a measure of liquidity is used to proxy market sentiment (Baker & Stein, 2004). Turnover is the SZSE Tech Index's average turnover in a firm's trading period [-35, -6].
Strategic: This control variable differentiates the strategic name change from the cosmetic name change. We looked for and determined the reasons for a name change for each firm from its name change announcement. When name changes were accompanied by strategic reasons such as a change of business model, restructuring, mergers or acquisitions, diversification or expansion, or change to the more popular brand of the firm's businesses, it is treated as a strategic change.
When there were no such reasons associated with the name change, it is taken as a cosmetic change. For a strategic name change, the dummy variable is marked as 1 and 0 if otherwise.
It is well documented that information asymmetry leads to abnormal stock prices. As more pronounced information asymmetry denotes greater firm-specific risk, the effect must be eliminated. Chae (2002) uses firm size to measure information asymmetry and finds that the smaller the firm size, the greater the asymmetry. Wu (2010) measures information asymmetry using firms' age since IPO, documenting more significant asymmetry for younger firms. Following the prior studies, we use the firm's age and size to measure information asymmetry. In addition to information asymmetry, we also control for a firm's prior performance, as firms with poor past performance are more likely to outperform, resulting in higher abnormal returns. Moreover, ROA and Tobin's Q were used to proxy past performances.

Control variables
Information Asymmetry: Following Chae (2002) and Wu (2010), we account for information asymmetry using the age and firm size measurement. We denote age as the number of days between the firm's public debut on the stock exchange and name change announcement date, and size as the natural logarithm of the firm's total assets in the year prior to a name change.
Past Performance: Past performance is measured using ROA and Tobin's Q. ROA is the ratio of firm return to total asset in year period to name change. Tobin's Q is the firm's market value to total asset ratio in the year before the name change.

This study conducts multivariate regression analyses to test all hypotheses.
We control for the potential effects of information asymmetry and past performance using firms' ROA, Tobin's Q, size and age. The SZSE Tech Index's turnover is used to proxy for technology-related market sentiment. The higher the investor sentiment, the greater the turnover. Table 2 shows the descriptive statistics and correlation coefficients for all standard measures in the regression model. Excluding the correlations between size and Tobin's Q, and between concept and CAR[-5, -1], all pair-wise correlations are lower than the benchmark of 0.5. For the three models examined, all of the variance inflation factors are less than the benchmark of 10. Table 3 presents the CAR values for event day from t-5 to t+5 for the four categories of name changes. Figures 1 and 2 depict Table 3 graphically for ease of reading. Table 2 Descriptive statistics Notes: ***, ** and * indicate the coefficient is significant at 1%, 5%, and 10% levels, respectively.    Notes: t statistics are reported in parentheses. ***, ** and * indicate the coefficient is significant at 1%, 5%, and 10% levels, respectively, using a two-tail test. Table 4 depicts multivariate regression results with CAR on three event periods as dependent variables. We find that the abnormal returns are not significant for the firms' name changes with the higher turnover on both the event date and post-event periods but negatively significant in the pre-event period.
According to the efficient market perspective, this result suggests that investors in the Chinese technology market are not influenced by sentiment. Instead, they behave rationally. In other words, tech firms cannot generate positive abnormal returns through timing name changes when investor sentiment is high.
Also, containing concept term in new names produce significant CARs on the event day. However, non-significant CARs are observed for the preevent and the post-event periods. Our result is consistent with Jiang (2016), where the author finds positively significant CAR for firm name changes that involve concept terms in their new names.
Hence, we posit that investors are more likely to be attracted to and overprice firms that contain concept terms in their names. The finding suggests that managers can associate firms with hot industries to attract investors' attention by including a concept term in the new names, causing a positive valuation effect. This finding lends support to the investors' limited attention conjecture, implicating that investors pay attention to the more obvious information, resulting in share mispricings.
Finally, we find that the CAR for firms with the strategic name change is positively significant on the event day, negatively significant in the pre-event period, but not significant in the post-event period. In other words, investors react immediately and positively to a strategic name change. We interpret this as China investors are rational and react to information efficiently. The finding has come across as somewhat unexpected. Moreover, significant abnormal return for strategic name changes indicates that firms enjoy a signaling effect. Firms that experienced structural changes successfully transmit valuable information to investors through a name change. Finally, our findings support the proposition that a firm's valuation and thus price are influenced by the motivation behind the name change (Kashmiri & Mahajan, 2015).
In summary, our results implicate that investors of China stock market weigh the reasons behind a firm's name change rationally, and their sentiment does not influence their behaviors in a significant way. However, investors are more likely to be attracted by stocks related to hot industries, tech stocks in this case, and overprice firms whose new names involve a concept term.

IMPLICATIONS FOR STAKEHOLDERS
By shedding light on the investors' reactions to name change, this study has important implications for policymakers, corporations contemplating a name change, and investors. First, the Chinese government can impose stricter rules on a corporate name change to protect investors' interests. Second, the government can curb unscrupulous name change aiming to lure investors into trading their stocks. This action can help screen out inappropriate name change behavior, thus protecting investors' interests.
This study also benefits managers from a decision-making perspective. Our findings show that investors in the Chinese technology stock industry are rational, and firms can generate positive cumulative returns through a structural name change. Therefore, firms can change names when they have a strategic reason to do so but not change names for cosmetic reasons. Moreover, our results show that investors are more likely to be drawn to a concept-related name change and overreact to those corporate events. Therefore, firms that wish to be associated with a hot industry and thus receive investors' increased attention may strategically change their name to include a hot concept term.

CONCLUSION
We examine the short-term valuation effect of corporate name change based on the name change announcements made by the technology firms listed in the Shanghai Stock Exchange and Shenzhen Stock Exchange during the 2014-2018 period. Our results show that investors in the Chinese technology stock market are not swayed by sentiment, which is somewhat unexpected due to the country's unique market structure and investor profile. Furthermore, we find evidence that the concept-related name change has a stronger appeal to investors than the non-concept-related name change as investors pay more attention to the former. This finding is somewhat expected since concept stocks are usually the hot spot of the market. Moreover, we find that firms with strategic name change experience significantly positive valuation effects on the event day, implying that investors react positively and efficiently to strategic name changes.
There are several limitations to our study. First, the sample size is unavoidably small after the filtering procedures. Second, this study focuses on the Chinese technology industry and may not reflect the characteristics of the entire Chinese stock market. Hence, future research can include a broader sample coverage and examine the valuation effect of the corporate event of a name change for a more extended period.