An analysis of all intraday trades in the Jakarta Stock Exchange during 2003–2004 indicates that more than half of them are “manipulated” by principal stockbrokers. Consequently, they can earn between 59% and 92% more annually than intermediary stockbrokers, which depend heavily on their investment patterns as well as firm’s characteristics. Specifically, our regression results suggest that with increases in their degree of principalness (PRIN), stockbrokers with a greater trade imbalance earn more at the expense of outside investors, even though this effect diminishes as PRIN increases. Moreover, firms that suffer the most from stockbrokers’ inappropriate behavior have large market capitalization or high stock liquidity.

Capex guidance disclosed by a firm’s peers provides useful information about their peers’ investment plans. In this study, we find a positive association between peers’ capex guidance and managerial learning about investment opportunities from stock prices as captured by the sensitivity of investment to Tobin’s Q, which is consistent with peers’ disclosure of investment plans encouraging investors’ information processing and thereby providing stock price–based feedback to managers. In cross-sectional analyses, we find this relationship is more pronounced when peer guidance is more informative, when managers have a greater incentive to learn from stock prices, and when the market can aggregate more information. We also find that investment corresponding to peer-capex-guidance–affected Tobin’s Q correlates with higher future performance, suggesting that improvement in managerial learning leads to better performance. Overall, our results offer insights into how peers’ disclosure of their investment plans influences information feedback from the market to the focal firm. JEL Classification : G31; M4; M41

We investigate the accuracy of several corporate failure prediction models, namely the original Altman's Z-score and Z˝-score, discriminant analysis, logistic regression and artificial neural network (ANN) by studying Indonesian firms. Using hand-collected data of forced delisting and healthy listed firms in Indonesia stock exchange, our results show that our ANN model has the highest accuracy among other models, respectively, followed by Z˝-score, logistic regression model, discriminant analysis model and the original Z-score. In addition, among these models, we also find that the original Z-score has the smallest type I error, or it is the most sensitive model, whereas Z˝-score has the smallest type II error, or it is the most specific model. Thus, in the view of efficiency, even though those models are very simple and were developed more than 30 years ago, the predictive ability of their combination is still pertinent to predict corporate failure in Indonesia.

The performance of foreign investors relative to domestic investors has been a subject of mixed evidence. While foreign investors are often perceived to underperform due to an information disadvantage, they are also known for their aggressive trading and superior performance in initiated orders. We provide further clarity on this issue. Specifically, by analyzing over five million transactions on the Jakarta Stock Exchange, our findings reveal that foreign investors consistently outperform domestic investors in terms of both annualized returns and profit amounts. Further investigation attributes this outperformance to the higher sophistication of foreign investors, who demonstrate superior stock-picking abilities and effective growth investing strategies.