我国股份制商业银行薪酬激励有效性研究

我国股份制商业银行薪酬激励存在一些不足，原因在于薪酬激励的自身因素和薪酬环境因素两方面。自身因素主要包括忽视长期行为激励、缺乏同业竞争优势、轻视普通员工激励；环境因素主要有银行治理结构不完善、市场非充分有效、法规制度不健全等。本文通过对商业银行高管人员及普通员工的薪酬与业绩相关性进行实证检验，认为我国商业银行薪酬激励基本上是有效的，但是其有效性并不十分理想。据此，本文提出了提升我国商业银行薪酬激励有效性的具体建议：从微观层面看，优化薪酬激励机制：从中观层面看，强化商业银行治理结构；从宏观层面看，改善外部相关环境。     

The Effects of Attributes on the Repeat Sales Pattern of Residential Property in Hong Kong

There has been copious research work on the development of house price models and the construction of house price indices. However, results in some studies revealed that the accuracy of such indices could be subject to selection bias when using only information from a sample of sold properties to estimate value movements for the entire housing stock. In particular, estimated house price appreciation is usually systematically higher among properties that change hands more frequently. It therefore suggests that the determination of important factors affecting the transaction frequency or intensity of a housing unit should be a more fundamental research question. This paper examines the possible factors that determine the popularity of residential unit by means of a repeated sales pattern. The Poisson regression model and event history analysis techniques are employed to assess the effect of attributes on transaction frequency and intensity. The event history analyses technique can take account of transaction-specific as well as time-dependent covariates, and therefore is recommended for analyzing repeated sales data in a real estate market. All transaction records during the period 1993–2000 from the Land Registry of one of the most popular residential estates in Hong Kong were used to illustrate the method. Unlike a response to favorable transaction price, good quality units do not necessarily inherently display a high transaction frequency. Rather, units of average quality are more likely to be transactionally active.     

On the estimation of stock-market reaction to corporate layoff announcements

This study investigates the stock-market reaction to layoff announcements where more than 1000 workers are affected. We employ a dummy variable regression (DVR) version of the market model and compare the results obtained using ordinary least squares (OLS) versus exponential GARCH (EGARCH), and value-weighted (VW) versus equally weighted (EW) market index. We find that the stock market responds negatively to layoffs attributed to low demand. We also find that contrary to prior research, the market reacts positively to restructuring-related layoffs on the announcement date. This pattern of market reaction is observed regardless of the market index used or the parameter estimation methods employed, although the empirical results indicate that using EGARCH/VW market index tends to generate fewer statistically significant test results and smaller (in the absolute size of the cumulative) abnormal returns (ARs). Taken together, our study provides additional support for the claim that studies of stock-market reaction to corporate events must account for the time variation in return volatility. Ignoring these could result in erroneous inferences.     

U.S. Monetary Regimes and Optimal Monetary Policy in the Euro Area

Monetary policy in the United States has been documented to have switched from reacting weakly to inflation fluctuations during the 1970s, to fighting inflation aggressively from the early 1980s onward. In this paper, I analyze the impact of the U.S. monetary policy regime switches on the Eurozone. I construct a New Keynesian two‐country model where foreign (U.S.) monetary policy switches regimes over time. I estimate the model for the U.S. and the Euro Area using quarterly data and find that the United States has switched between those two regimes, in line with existing evidence. I show that foreign regime switches affect home (Eurozone) inflation and output volatility and their responses to shocks, substantially, as long as the home central bank commits to a time‐invariant interest rate rule reacting to domestic conditions only. Optimal policy in the home country instead requires that the home central bank reacts strongly to domestic producer‐price inflation and to international variables, such as imported goods relative prices. In fact, I show that currency misalignments and relative prices play a crucial role in the transmission of foreign monetary policy regime switches internationally. Interestingly, I show that only marginal gains arise for the Euro Area when the European Central Bank (ECB) adjusts its policy according to the monetary regime in the United States. Thus, a simple time‐invariant monetary policy rule with a strong reaction to Producer Price Index (PPI) inflation and relative prices is enough to counteract the effects of monetary policy switches in the United States.     

Using Market Expectations to Test for Speculative Bubbles in the Crude Oil Market

The wide fluctuations of oil prices from 2003 to 2008 have attracted the interest of academics and policymakers. A popular view is that these fluctuations were caused by speculative bubbles due to the increased financialization of oil futures markets. This hypothesis, however, is difficult to examine since the fundamental price of oil is unobservable and, therefore, econometric evidence in favor of bubbles may actually be due to misspecified market fundamentals. In this paper, we extend two recently proposed methodologies for bubble detection that alleviate this problem by using market expectations of future prices. Both methodologies provide no evidence of speculative bubbles.     

Machine learning in individual claims reserving

Machine learning techniques make it feasible to calculate claims reserves on individual claims data. This paper illustrates how these techniques can be used by providing an explicit example in individual claims reserving.     

Pricing mortgage insurance contracts under housing price cycles with jump risk: evidence from the U.K. housing market

Previous studies have investigated the determinants of housing price cycles in the housing market; however, we observed the phenomenon of housing price jumps in the 2007 subprime crisis. This paper presents a discussion on the housing price cycle and abnormal price jumps to describe the behavior of housing prices in the United Kingdom. The empirical results show that the impact factors of housing cycles are market risk and the switching factor. Furthermore, the impact factors of jump risks include the bursting of the housing bubble and financial crises. Therefore, in this paper, we employ the Markov switching model with jump risks to value the MI contracts and analyze the influences of housing price cycles, jump risks, risks of market interest rate, and the prepayment risks on MI premiums. The results of sensitivity analysis show that more volatile housing price index returns, as well as longer periods of higher volatility in housing prices, raise MI premiums. Moreover, the MI premium is positively related to the absolute value of the average jump amplitude and the shock frequency of abnormal events. There is the tradeoff between the market interest rate and the prepayment risk. The influences of market interest rate are different on MI premium with/without prepayment risks.     

A logistic regression point of view toward loss given default distribution estimation

We propose a new procedure to estimate the loss given default (LGD) distribution. Owing to the complicated shape of the LGD distribution, using a smooth density function as a driver to estimate it may result in a decline in model fit. To overcome this problem, we first apply the logistic regression to estimate the LGD cumulative distribution function. Then, we convert the result into the LGD distribution estimate. To implement the newly proposed estimation procedure, we collect a sample of 5269 defaulted debts from Moody’s Default and Recovery Database. A performance study is performed using 2000 pairs of in-sample and out-of-sample data-sets with different sizes that are randomly selected from the entire sample. Our results show that the newly proposed procedure has better and more robust performance than its alternatives, in the sense of yielding more accurate in-sample and out-of-sample LGD distribution estimates. Thus, it is useful for studying the LGD distribution.     

Optimal pair-trading strategy over long/short/square positions—empirical study

Suzuki [Automatica, 2016, 67, 33–45] solves the optimal, finitely iterative, three-regime switching problem for investing in a mean-reverting asset that follows an Ornstein–Uhlenbeck price process and find explicit solutions. The remarkable feature of this model is that the investor can explicitly take either a long, short or square position and can switch the position, with transaction costs, during the investment period. We run empirical simulations of such multiple-regime switching models. There are very few such attempts in the existing literature because it is difficult to find, first, an explicit solution to the problem and second, appropriate financial assets that follow the artificial stochastic process required by the mathematical model. According to the Monte Carlo simulations of the optimal pair-trading strategy, the mean daily Sharp ratio is more than 2.3, whereas the mean Sharp ratio for the historical simulation of the ‘stub’ pairs (combinations of parent/subsidiary companies) is 0.6886. We believe that the results obtained from performing the empirical simulations are remarkable and consider that the optimal switching strategy of the rigorous mathematical model is applicable to businesses in the real world. For the reference many pseudo-program codes are added, which can help to replicate the optimal trading strategies.     

Dynamic Currency Linkages and Their Determinants: An Empirical Study for East Asian Economic Community Region

In this article, Copula GARCH models have been employed to study the inter-temporal process of currency market co-movements between ASEAN+6 countries (referred to in this study as East Asian Economic Community) and ASEAN+6 currency market index. Empirical results show that the sample countries of the region exhibit varying levels of currency co-movements with the Asian benchmark. Markov regime switching results show that many of the countries which had high dependences with the regional currency index as was found in copula estimations had also overlapping currency market cycles. Using Principal Component Analysis, we find that three statistical factors explain exchange rate co-movements which came out to be trade linkages, economic risk, and currency market openness in our dynamic panel data estimation.