Microstructure-based manipulation: Strategic behavior and performance of spoofing traders

We examine how investors strategically spoof the stock market by placing orders with little chance of being executed, but which mislead other traders into thinking there is an imbalance in the order book. Using the complete intraday order and trade data of the Korea Exchange (KRX) in a custom data set identifying individual accounts, we find that investors strategically placed spoofing orders which, given the KRX's order-disclosure rule at the time, created the impression of a substantial order book imbalance, with the intent to manipulate subsequent prices. This manipulation, which made use of specific features of the market microstructure, differs from previously studied forms of manipulation based on information or transactions. Roughly half of the spoofing orders were placed in conjunction with day trading. Stocks targeted for manipulation had higher return volatility, lower market capitalization, lower price level, and lower managerial transparency. We also find that spoofing traders achieved substantial extra profits. The frequency of spoofing orders decreased drastically after the KRX altered its order-disclosure rule.     

Community-based tourism (TourDure) experience program: a theoretical approach

This research tested the Theory of Planned Behavior model to reveal the formation of tourists’ intention to experience a tour program organized by a local community (i.e. TourDure) by taking the moderating effect of gender and age into account. TourDure is an excellent case of the community-based tourism initiatives in Korea. A field survey was carried out for data collection. Our findings indicated that attitude and subjective norm had a significant impact on intention. Also, destination attachment showed a positive influence on the intention. In addition, subjective norm and attitude was found to be significant across the gender group.     

Failure Prediction: Evidence from Korea

This study is an attempt to construct and test a distress classification model for Korean companies. Utilizing a sample of 34 distressed firms from the recent 1990-1993 period and a matched (by industry and year) sample of non-failed firms, we observe the classification accuracy of two models. Both models utilize measures of firm size, asset turnover, solvency and leverage with one model available for testing only on publicly traded companies and one model applicable to all public and private entities. We observe excellent classification accuracy based on data from the first two years prior to distress. And, although the accuracy drops off after t -2, the models still provide effective early warnings of distress in many cases. The results of this study are of particular relevance in the current financial market scenario of increased deregulation and greater individual financial institution decision making. It is somewhat ironic for us to be proposing the use of a financial distress early-warning model given the current robust economic growth and low bankruptcy rate in Korea. But, the financial problems in Japan are a sobering reminder that high growth can be followed by financial excesses, increased business failures and large loan losses.