We examine the execution quality of electronic stock traders who are geographically dispersed throughout the U.S. Traders who are located near market central computers in the New York City area experience faster order execution. Moreover, the time to execute orders rises as a trader’s actual distance (mileage) to NYC widens. In electronic market settings, data transfer limitations and transmission slowdowns result in geographically dispersed electronic traders having different access to trading speed. We find that speed advantaged traders experience lower transaction costs and engage in strategies that are more conducive to speed.

The cost of trading in securities markets is often estimated on the basis of: 1) a trade execution rather than an original order; and 2) a quote midpoint at the time of trade execution rather than at the time of order submission. In our paper, we obtain data from a U.S. brokerage firm to examine the severity of these two problems. We find that the quote midpoint and order size at submission differ from that at execution approximately 40% of the time. These differences are economically important and are more likely to occur when the market is less liquid. Our results highlight the need for caution when inferring trading costs from market center data sources.

We examine the determinants of U.S. equity traders’ choice of electronic versus intermediated execution. While traders exhibit a strong overall preference for automation, when the market is less liquid at order submission time, traders seek market maker automated and human order-matching services more often. Traders overall tendency to choose intermediaries is highly correlated with their demand for liquidity. Market maker participation rates are higher for more active and larger size traders. Traders who choose intermediaries more often trade more stocks, execute orders quicker, price orders more aggressively, and disperse their trading over longer periods of time. Although U.S. stock intermediaries continue to lose market share, our results highlight the important niche role these firms can play in an increasingly automated, electronically-driven marketplace.

企业风险管理（ERM）作为风险管理学科的一个重要领域，在五十多年的发展过程中实现了从多个领域的分散研究向全面风险管理（ERM）一体化框架的演进，其中风险管理理论和内部审计与控制理论是两大理论来源，风险管理理论经历了从传统风险管理、财务波动性风险管理向ERM的发展，而内部审计与控制理论也经历了内部会计控制、内部控制整体框架向企业风险管理的演进，上述两大理论的发展都指向了ERM的方向，企业风险管理理论最终实现了集成发展，成为企业管理不可或缺的重要组成部分。

ABSTRACT：As an important derivative instrument, CDO is playing a crucial role in the financial crisis. With complicated structure, we have developed many pricing models, which all relay on complicated mathematical model. The paper, firstly, introduces the mainstream pricing model----structural model and reduced form model. Then we introduced the Hybrid Models based on two formal models, by discussing the parameter of pricing i.e. default probability, default free risk and default correlation. In this paper, we give the hybrid model by Monte Carlo simulation based on copula function. Finally, we consider the pricing sensitivity on various parameters. According to the result of simulation, the relationship between the tranches price and pricing parameters is various. For the equity tranche and mezzanine tranche, the price and recovery rate have a positive correlation, while the case is inverse for the senior tranche. We also can conclude that, higher default correlation can lower the price of equity tranche, and have an opposite effect on the senior tranche. The influence on the mezzanine tranche isn’t certain. Furthermore, by comparing two different copula function model, we can get that marginal distribution has different effect on the tranches price.

本文提出了一种新的马尔可夫机制转换 EGARCH模型（MRS-EGARCH），与传统的 波动率建模方法不同的是，我们在 MRS-EGARCH 中分别假定了收益残差序列可以服从高 斯、学生 t 以及广义误差分布，并进一步允许其分布的自由度与所处机制（Regime）有关， 以便刻画金融收益可能随时间变化的峰度（厚尾）特征。以能反映我国 A 股市场整体走势 的沪深 300指数为例，本文对比了 MRS-EGARCH模型和单机制 EGARCH模型的样本内和 样本外波动率预测结果。主要实证结果显示：沪深 300 指数确实存在不同的波动强弱机制区 间，而我们提出的 MRS-EGARCH 模型能够清晰区分出隐藏在收益序列中的不同机制。同 时，无论从样本内还是样本外的波动率预测结果来看，设定收益残差序列服从厚尾分布的 MRS-EGARCH都是预测精度更好的波动率模型。

Policy actions by the Federal Reserve during the recent financial crisis often involve recapitalization of banks. This paper offers a theory of the non-neutrality of money for policy actions taking the form of injecting capital into banks via nominal transfers, in an environment where banking frictions are present in the sense that there exists an agency cost problem between banks and their private-sector creditors. The analysis is conducted within a general equilibrium setting with two-sided financial contracting. We first show that even with perfect nominal flexibility, the recapitalization policy can have real effects on the economy. We then study the design of the optimal long-run recapitalization policy as well as the optimal short-run policy responses to banking riskiness shocks.

This paper examines the causes and consequences of venture capital (VC) stage financing. Using information about the geographic location of an entrepreneurial firm and the distance between the VC investor and the firm, I distinguish between three different hypotheses: the monitoring hypothesis, which argues that the VC staging and monitoring of entrepreneurial firms are substitutes; the hold-up hypothesis, which argues that staging is a mechanism for mitigating the hold-up problem between the entrepreneur and the VC investor; and the learning hypothesis, which argues that staging creates value through the real options generated by learning by VC investors. My analysis of the causes of stage financing suggests that VC investors located farther away from an entrepreneurial firm tend to finance the firm using a larger number of financing rounds, shorter durations between successive rounds, and investing a smaller amount in each round; however, VC investors’ propensity to stage is independent of whether or not the firm is located in a close-knit community. My analysis of the consequences of stage financing suggests that VC staging positively affects the entrepreneurial firm’s propensity to have a successful exit, operating performance in the IPO year, and post-IPO survival rate, but only if the firm is located far away from the VC investor; however, the entrepreneurial firm’s performance is independent of whether or not it is located in a close-knit community. Overall, the evidence supports the monitoring hypothesis, but does not provide any support for the hold-up or learning hypotheses.

In this paper, we derive the corresponding implied VIX formulas under the locally riskneutral valuation relationship proposed by Duan (1995) when various forms of GARCH model are proposed for S&P 500 index. The empirical study shows that the GARCH implied VIX is consistently and significantly lower than the CBOE VIX for all kinds of GARCH model investigated. Moreover, the magnitude of the difference suggests that the GARCH option pricing model is not capable of capturing the variance premium, which indicates the incompleteness of the GARCH option pricing under the locally risk-neutral valuation relationship. The source of this kind of incompleteness is then theoretically analyzed. It is shown that the framework of GARCH option pricing model fails to incorporate the price of volatility risk or variance premium.

This paper mainly finds that there is return predictability across equity-link firms in China’s stock market. By grouping the shareholder firms according to the shocks translated from their equity-link firms, we construct long-short momentum strategy to capture abnormal return of 2.01% per month, which we call “equity-link momentum”. After an array of adjustments based on risky factors and firm characteristics, the excess returns are still significant. However, the significance of equity-link momentum returns are sensitive to various attention proxies, such as firm size, past performance, turn over and mutual funds’ joint holding measurement, which is consistent with the hypothesis of limited attention.