Soft budget constraint refers to the situation where an economic entity expects to obtain economic assistance when in financial difficulties. During the past decade, a sizable literature has accumulated explaining the causes and consequences of the soft budget constraint. Many of the theories have traced soft budget constraint on enterprises to that on banks. However, why do banks often face soft budget constraint? How to mitigate the resulting problems? In this paper, we first show that owing to their special financial structure, banks as market institutions intrinsically face hard budget constraint and nevertheless remain stable and effective. Since banks’ finance mostly comes from deposits, it is very difficult for banks to be refinanced when their investment projects are unsuccessful due to the sequential service arrangement for bank deposits. This limitation hardens the budget constraint on banks and disciplines bankers’ investment decisions. However, the advent of instantaneous-social-welfareminded modern governments, which have both the resources and the incentives to bail out failing banks, gives rise to the soft budget constraint of banks. This causes bankers’ moral hazard problems. As an institutional solution to the resulting banking instabilities, banking regulation emerged in order to restrict banks’ investment decisions. We provide historical evidence on the genesis and symptoms of, and institutional solution to the soft budget constraint of banks over the past six hundred years to support our theory. We also conduct contemporary econometric analysis to show how the lack of government commitment to a hard budget constraint gives rise to a strict banking regulation. We further explore the predictions of our theory in the paper.

Technical traders base their analysis on the premise that the patterns in market prices are assumed to recur in the future, and thus, these patterns can be used for predictive purposes. This paper tests the simplest and most popular trading rules―moving average―in the Chinese stock market. Overall, our results are similar to the ones of Brock et al. (1992) and Lo et al. (2000), providing strong support for the technical strategies. In fact, technical indicators do provide incremental information, and buy signals consistently generate higher returns than sell signals. We also find that the asymmetric phenomenon between the buy and sell signals, and we attributed it to the investors’ behaviors.

Guilin Jiqi is a pharmaceutical company listed on Shenzhen Stock Exchange from 1997. Taking into account the special institutional background of China, we thoroughly analyze possible motives for her accounting fraud in 2000. Guilin Jiqi made up the accounting profit in the semi-annual report. Interestingly, the employee shares of Guilin Jiqi began to be tradable in the open market from June. After rejecting other possibilities, we find that the most probable motive for this earnings manipulation is to help her employees, except top managers, to sell their shares at a huge profit. Our case evidence tells an interesting story regarding another form of insider trading. The management might recognize the contribution of employees by helping them to take advantage of investors fooled by inflated accounting profit. The pressure from subordinates possibly played an important role in the decision making of the management.

Stock market liberalization is a decision to allow foreign investors to purchase domestic shares. This paper is an event study on market reactions around the announcement of the Qualified Foreign Institutional Investors (QFII) scheme in China. We find no significant abnormal returns in market indices in the short-term period leading up to the announcement, negative abnormal returns in the short-term period following the announcement, and no significant abnormal returns in the long-term period thereafter. The findings do not comply with the prediction of international asset pricing models. The QFII scheme may not help much in reducing the cost of equity capital and risk premium of China companies.

Based on Allen and Gale (1992), Aggarwal and Wu (2002), this article introduces dynamic transaction costs. So, we can comprehensively and theoretically discuss the major roles of government against stock market manipulation for the first time. First, the government should require all the related participants disseminate great and true information in time, in order to decrease the cost of intelligent investor. Second, the government should vigorously regulate the trading and discriminate the intelligent investor from manipulator to increase the manipulator’s cost. Last, in order to decrease the intelligent investor, the government also should increase the degree of investor education

Under the framework of Rational Expectation Equilibrium (REE), the paper analyzes the impacts of insider trading on the secondary market in the order-driven system. We show that when insider trading is allowed, the average price will not change and there is a positive correlation between the future price and the current price. The volatility and liquidity change without sure direction with insider trading. The price efficiency is a special case with and without insider trading. The insider is benefit by insider trading wherever the outsider and liquidity trader may be benefit or hurt by insider trading.

This paper contributes to the development of recent literature on the explanation power and calibration issue of heterogeneous asset pricing models by presenting a simple stochastic market fraction asset pricing model of two types of traders (fundamentalists and trend followers) under a market maker scenario. Statistical analysis based on Monte Carlo simulations shows that the long-run behaviour and convergence of the market prices, long (short)-run profitability of the fundamental (trend following) trading strategy, survivability of chartists, and various under and over-reaction autocorrelation patterns of returns can be characterized by the stability and bifurcations of the underlying deterministic system. Our analysis underpins mechanism on various market behaviour (such as under/over-reactions), market dominance and stylized facts in high frequency financial markets.

本文的目的是运用较为严密的实证方法来考察和比较东亚危机前韩国、印度尼西亚、泰国等新兴市场国家和东亚危机后中国这一世人瞩 目的转型经济国家在开放过程中，国内产出和货币、信贷水准及其波动受到外部影响的特征。 通过引入非对称 “时变波动”(asymmetric time-varying volatility) 特征的二元EGARCH-VAR实证模型，论文得到了以下三个主要的结论：第一、虽然为维持名义汇率的稳定，各国政府都积极地干预外汇市场，由此影响了当期内外利差的收敛，但从动态发展的角度上看，包括中国在内的4个国家其金融的实际开放程度都在不断加大。第二、除90年代国际资本移动的鼎盛阶段以外，各国发生的经济波动并不是由外部冲击直接带来的，更多的是在开放经济的环境下国内经济的不确定因素所导致。第三、通过各国经济波动特征的比较，可以发现汇率制度、金融市场的开放程度以及资本市场的发展状况对经济波动有很大的影响。

It is commonly argued that poorly designed banking system safety nets are largely to blame for the frequency and severity of modern banking crises. For example, “underpriced” deposit insurance and/or low reserve requirement are often viewed as factors that encourages risk-taking by banks. In this paper, we study the effects of three policy variables: deposit insurance premia, reserve requirement and the way in which the costs of bank bailouts are financed. We show that when deposit insurance premia are low, the monetization of bank bailout costs may not be more inflationary than financing these costs out of general revenue. This is because, while monetizing the costs increases the inflation tax rate, higher levels of general taxation reduce savings, deposits, bank reserves, and the inflation tax base. Increasing the inflation tax rate obviously raises inflation, but so does an erosion of the inflation tax base. We also find that low deposit insurance premia or low reserve requirements may not be associated with a high rate of bank failure.

Numerous studies have shown that the simple random walk model outperforms all structural and time series models in forecasting the conditional mean of exchange rate changes. However, in many important applications, such as risk management, forecasts of the probability distribution of exchange rate changes are often needed. In this paper, we develop a nonparametric portmanteau evaluation procedure for out-of-sample density forecast and provide a comprehensive empirical study on the out-of-sample performance of a wide variety of time series models in forecasting the intraday probability density of two major exchange rates－Euro/Dollar and Yen/Dollar. We find that some nonlinear time series models provide better density forecast than the simple random walk model, although they underperform in forecasting the conditional mean. For Euro/Dollar, it is important to model heavy tails through a Student-t innovation and asymmetric time-varying conditional volatility through a regime-switching GARCH model for both in-sample and out-of-sample performance; modeling conditional mean and serial dependence in higher order moments (e.g.,conditional skewness), although important for in-sample performance, does not help out-of-sample density forecast. For Yen/Dollar, it is also important to model heavy tails and volatility clustering, and the best density forecast model is a RiskMetrics model with a Student-t innovation. As a simple application, we Þnd that the models that provide good density forecast generally provide good forecast of Value-at-Risk.