Felizia Arni Rudiawarni

The research examines the role of discussion in investors’ decision in a step-by-step information setting. Several studies present that disclosure strategy stimulates order-effect bias, but simultaneous information decreases the impact of that bias. This bias makes people weigh more heavily to recent observations than they do to older ones. Using step-by-step information, a recency effect is expected to be found. This study uses an experimental method. The participants are the representation of non-professional investors in the stock market because of a lack of knowledge and experience. Participants are also a reflection of the customer easiness in registering to be stock traders. The role of discussion between participants is a new feature of this experiment. After evaluating participants’ decision in a discussion, the experiment shows that an individual’s choice after discussion produces more bias, although they already learn the information before the discussion. The research finds that (1) using the within-subject sample, group discussion produces overvaluation (undervaluation) in positive (negative) sequential information, (2) there is bigger price revision when negative sequential information is presented. This study suggests disclosure strategies for companies. Considering a recency bias, companies must present step-by-step information when they disclose good news, but they must avoid step-by-step disclosures when giving bad news. The second practical implication is for investors; they need to think about the benefits of joining an investor club, since the discussion exacerbates recency bias. These results are expected to contribute to finance literature.

Intellectual capital is widely recognized as one of the most important assets in modern businesses, but it is only reported in the financial statement in certain conditions. This study aims to evaluate the role of value-added intellectual capital (VAIC) in moderating the relationship between earnings management and financial performance. This research uses data from non-financial companies listed on the Singapore Exchange and Indonesia Stock Exchange covering the period of 2016–2021, with a total of 3,303 firm-year observations. VAIC is measured using Pulic’s intellectual capital model and earnings management using the Kasznik Model (1999). This study uses multiple linear regressions to examine the relationship between variables. The findings indicate that earnings management has no significant effect on the financial performance of Singapore, but it has a significant positive effect on the financial performance of Indonesia. Furthermore, this study discovers that intellectual capital moderates the relationship between earnings management and financial performance in both countries differently, that intellectual capital moderation is positive (negative) for the Singapore (Indonesia) sample. These findings suggest that the role of intellectual capital varies depending on stock exchanges; Singapore is considered a developed country in Southeast Asia, whilst Indonesia is considered a developing one. This study concludes that the role of intellectual capital in the relationship between earnings management and financial performance varies between market characteristics and across industries.

Given the growing significance of the capital market, investors tend to steer clear of stock price crashes. This study aims to examine how idiosyncratic risk affects the likelihood of a stock price crash and how discretionary income smoothing affects the relationship between them. This study uses a data panel to empirically examine the hypothesis. This study uses a data panel to empirically examine the hypothesis, using 1,203 firm-year observations from non-financial companies publicly traded on the Indonesia Stock Exchange from 2019 to 2021. The results show that firms with greater idiosyncratic risk do not significantly generate higher stock price crash risk. Nevertheless, this study also discovered that managing discretionary income smoothing is essential to increasing the risk of crashes. The test shows that the coefficient of discretionary income smoothing is 0.153 and significant with a t-value of 2.104. Moreover, the investigations also indicate that greater use of discretionary income smoothing can amplify the impact of idiosyncratic risk on the likelihood of stock price crashes. This is shown from the results where the moderation of the two variables has a positive coefficient of 0.087 and is significant at 10% with a t-value of 1.446. Based on the findings, this study concludes that the presence of idiosyncratic risk by itself may not substantially impact the probability of stock market crashes. However, combined with discretionary income smoothing, it can worsen the potential negative consequences. It implies that how a firm reports its income can affect its susceptibility to stock price crashes.

Type of the article: Research Article

Abstract
Intangible assets play a significant role in the New Economy period we currently live in, yet their capitalization remains challenging due to high failure rates in innovation. The purpose of this study is to investigate the circumstances under which businesses have the potential to raise the future value of using their intangible assets. This study used publicly listed firms on the Indonesia Stock Exchange (IDX) from 2019 to 2024. The final sample comprises 1,974 firm-years that satisfy the selection criteria. A multiple regression analysis was carried out for the assessments. The findings show that the sole possession of intangible assets is insufficient to raise the value of the companies and explicitly shows a negative effect (coefficient = –0.1443, t-value = –2.406). However, the interaction tests reveal that to boost future excess returns, businesses possessing intangible assets are required to demonstrate earnings growth (coefficient = 0.0142, t-value = 2.388) and a strong price-to-book ratio (coefficient = 0.0627, t-value = 7.441). Furthermore, a sector-specific analysis reveals that these results diverge for the technology and healthcare sectors, where intangible assets fail to explain future excess returns (F-statistics = 3.912 and 8.299, respectively). This investigation suggests that the impact of intangible assets on firm value is not uniform; rather, it is contingent upon specific corporate financial fundamentals and industry contexts, proving that investors require validation of innovation through profitability and market strength.