Review of Pacific Basin Financial Markets and Policies

This study highlights how banking regulation in Indonesia can be improved with a view to enhancing the cost-effectiveness of banking regulation and social welfare, and preventing future financial instability. We employ the Fries, Mella-Barral, and Perraudin (FMP) model (1997) and analyze the model under a robust regulatory regime concept to provide a new framework for banking regulation. Maximum likelihood estimates in VAR and GARCH are applied to monthly data on the market returns and deposit values for relatively-large banks. The results show how the authorities in Indonesia can establish optimal closure rules for each bank, levy "fair" deposit insurance premiums, estimate optimal subsidies (for different deposit insurance premiums) and identify the banks' "imminence to bankruptcy".

This paper attempts to pioneer a discussion on the exit and maintenance costs of the Currency Board System (CBS) in Hong Kong, and hopes to invite more debate on the issue. It suggests that the exit costs will depend on the timing of an exit, whether there are supplementary packages to mitigate the exit costs, and the choice of an alternative exchange rate system. In particular, it suggests that the monitoring band system favored by Williamson (2000) could help to reduce the exit costs. In addition, the paper points out that there are ways to reduce both the exit and maintenance costs. It then proposes a reform that could benefit the economy regardless of whether the policy maker eventually chooses to continue with or abandon the peg. The study is not only crucial to Hong Kong, but also important to other economies with a CBS as well as to the debate on the choice of exchange rate system.

This paper examines whether overconfidence can explain the relationship between performance and behavior of investors in Taiwan. Different from prior research that used a specific sample of individuals trading records, this work focuses on aggregate investor behavior to know whether overconfidence is a market-wide phenomenon. It is found that overconfident investors will trade more aggressively, and the excessive trading of overconfident investors results in the observed excessive market volatility. However, overconfidence effect exists only following bull markets. After a period of stock gains, overconfident traders tend to title their investment toward smaller-cap and growth stocks, consistent with the prediction of overconfident hypothesis that as investors become overconfident, they underestimate risk and thereby trade in riskier stocks.

This paper examines the effect of the degree of internationalization on capital structure for multinational corporations (MNCs) in Taiwan during the Asian financial crisis in 1997 by using dummy variables in a multiple regression analysis. The results show that: (1) For the IT industry, the higher the internationalization is, the higher the leverage will be, but it is the reverse for the NIT industry. (2) There is an industry effect on tangible assets, sales size, return on total assets, current ratio, and the times of interest earned, while the collateral value of assets is more significant for the NIT industry than the IT industry when MNCs make capital structure decisions. (3) There is an internationalization effect on the collateral value of assets, profitability, and liability payment ability. For low-internationalized MNCs, firm size and profitability are the important capital structure determinants, but for high-internationalized MNCs, the collateral value of assets is a key element of leverage decisions. (4) The liquidity risk caused by the Asian financial crisis allows the collateral value of assets and liability payment ability be the important determinants when MNCs make capital structure decisions. Finally, the results also express that international outsourcing and international financing play a somewhat important role for the IT industry during successive industry development.

We extend the feedback trader model by including a cross-market feedback trader. Our analysis of eighteen emerging markets suggests that there exists both positive and negative feedback traders in the markets and their activity is related to stock index return volatility. For cross-market feedback traders however, we show that, although cross-market autocorrelation among emerging markets is high and variable, the hypothesized negative relationship between cross-market autocorrelation and volatility is much weaker than its domestic counterpart.

We generalize the standard lattice approach of Cox, Ross, and Rubinstein (1976) from a fixed sum to a random sum in a subordinated process framework to accommodate pricing of derivatives with random-sum characteristics. The asset price change now is determined by two independent Bernoulli trials on information arrival/non-arrival and price up/down, respectively. The subordination leads to a nonstationary trinomial tree in calendar-time, while a time change to information-time restores the simpler binomial tree that now grows with the intensity of information arrival irrespective of the passage of calendar-time. We apply the model to price the CBOT catastrophe futures call spreads as a binomial sum of binomial prices, which illuminates the information conveyed by the randomness of catastrophe arrival. Numerical results demonstrate that the standard binomial formula that ignores random claim arrival produces largest undervaluation error for out-of-money short-maturity options when a small number of significant catastrophes may strike during the option's maturity.

This paper discusses the time-series cross-sectional (TSCS) regression and the prediction ability of the artificial neural network (ANN) by examining the panel data of debt ratios of the high tech industry in Taiwan. We build models with these two methods and eight determinants of debt ratio and compare the forecast performances of five models, two ANN nonlinear models and three traditional TSCS linear models. The results show that the sign of each determinant in linear models is the same as that in ANN models. In addition, the insignificant determinants in linear models have low relative sensitivities in ANN models. It seems that these two methods show consistent results for the capital structure determinants. Researchers and practitioners can employ either ANN or traditional statistical model to analyze the important determinants of the capital structure of their firms. The results of comparing the out-of-sample forecasting capabilities of the two methods indicate that: (1) the proposed ANN with 1-year lag model shows better forecast performance than the other three linear models in spite of high or low debt ratio; (2) the debt ratios of the present year are highly related to those of the previous year; and (3) the ANN model is capable of catching sophisticated nonlinear integration effects. Consequently, the ANN method is the more appropriate one between the two methods to be applied to build a forecasting model for the high tech industry in Taiwan.

Convertible bond (CB) issuers have been required to include financial forecasts in prospectuses filed with the Taiwan Securities and Futures Commission (TSFC) since 1991. This study examines the association between CB issuance terms and the extent of optimistic initial earnings forecasts and earnings management, as well as the association between CB issuance terms and the extent of reported (post-managed) earnings forecasts. Empirical results indicate that: (1) the likelihood of the issuing company making an optimistic initial earnings forecast (positive initial forecast error) increases with conversion price, issuance amount, and issuance period, but decreases with an increasing conversion period and reselling premium; (2) earnings management was pervasive in the year of issue of the CB; and (3) a substitutive relation exists between earnings management and issuance terms in CB issuing.