Impact of Divergent Consumer Confidence on Option Prices

This paper investigates the impact of divergent consumer confidence on option prices. To model this, we assume that consumers disagree on the expected growth rate of aggregate consumption. With other conditions unchanged in the discrete-time Black–Scholes option-pricing model, we show that the representative consumer will have declining relative risk aversion instead of the assumed constant relative risk aversion. In this case all options will be underpriced by the Black–Scholes model under the assumption of bivariate lognormality. This revised version was published online in June 2006 with corrections to the Cover Date.     

金融期货价格波动限制机制探讨

金融期货价格稳定机制延缓了价格发现过程，并造成了流动性干扰，但从降低期货、现货交易总成本来讲，它还是利大于弊，因此设置价格波动限制是一种可行的政策，而且在期货、现货市场同时设定的效果最好。此外，从不同价格波动限制方式的影响来看，选择弹性涨跌幅限制可较好地发挥价格限制的好处，减小价格限制的不利影响。     

Inference with Dependent Data in Accounting and Finance Applications

We review developments in conducting inference for model parameters in the presence of intertemporal and cross‐sectional dependence with an emphasis on panel data applications. We review the use of heteroskedasticity and autocorrelation consistent (HAC) standard error estimators, which include the standard clustered and multiway clustered estimators, and discuss alternative sample‐splitting inference procedures, such as the Fama–Macbeth procedure, within this context. We outline pros and cons of the different procedures. We then illustrate the properties of the discussed procedures within a simulation experiment designed to mimic the type of firm‐level panel data that might be encountered in accounting and finance applications. Our conclusion, based on theoretical properties and simulation performance, is that sample‐splitting procedures with suitably chosen splits are the most likely to deliver robust inferential statements with approximately correct coverage properties in the types of large, heterogeneous panels many researchers are likely to face.     

Forecasting U.S. money growth using economic uncertainty measures and regularisation techniques

This paper examines the out-of-sample forecasting properties of six different economic uncertainty variables for the growth of the real M2 and real M4 Divisia money series for the U.S. using monthly data. The core contention is that information on economic uncertainty improves the forecasting accuracy. We estimate vector autoregressive models using the iterated rolling-window forecasting scheme, in combination with modern regularisation techniques from the field of machine learning. Applying the Hansen-Lunde-Nason model confidence set approach under two different loss functions reveals strong evidence that uncertainty variables that are related to financial markets, the state of the macroeconomy or economic policy provide additional informational content when forecasting monetary dynamics. The use of regularisation techniques improves the forecast accuracy substantially.     

Limit theorems for reflected Ornstein–Uhlenbeck processes

This paper studies one‐dimensional Ornstein–Uhlenbeck (OU) processes, with the distinguishing feature that they are reflected on a single boundary (put at level 0) or two boundaries (put at levels 0 and d > 0). In the literature, they are referred to as reflected OU (ROU) and doubly reflected OU (DROU), respectively. For both cases, we explicitly determine the decay rates of the (transient) probability to reach a given extreme level. The methodology relies on sample‐path large deviations, so that we also identify the associated most likely paths. For DROU, we also consider the ‘idleness process’ L_t and the ‘loss process’ U_t, which are the minimal non‐decreasing processes, which make the OU process remain ≥ 0 and ≤ d, respectively. We derive central limit theorems (CLTs) for U_t and L_t, using techniques from stochastic integration and the martingale CLT.     

Experts,firms, consumers or even hard data? Forecasting employment in Germany

In this article, we forecast employment growth for Germany with data for the period from November 2008 to November 2015. Hutter and Weber (2015) introduced an innovative unemployment indicator and evaluated the performance of several leading indicators, including the Ifo Employment Barometer (IEB), to predict unemployment changes. Since the IEB focuses on employment growth instead of unemployment developments, we mirror the study by Hutter and Weber (2015). It turns out that in our case, and in contrast to their article, the IEB outperforms their newly developed indicator. Additionally, consumers’ unemployment expectations and hard data such as new orders exhibit a high forecasting accuracy.     

Restoring tourist confidence and travel intentions after disasters: some insights from a rejoinder to a series of unfortunate events in Malaysian tourism

Many countries face a decline in tourist confidence and reduced travel intentions after disasters. However, Malaysia – a country that experienced a series of aviation tragedies throughout 2014 – encountered an overall increase in inbound tourists and monetary receipts. This article more closely examines the effects of these unfortunate events on Malaysian tourism and identifies several strategic avenues that can contribute to restoring tourist confidence and reigniting tourist interest in travelling to disaster-stricken countries.     

Consumer confidence and consumption expenditure in Indonesia

We estimate several competing regressions and find that confidence predicts consumption expenditure in Indonesia. Our estimations employ data on two measures of confidence, namely consumer and business confidence indexes, consumption and three standard predictors of consumption, namely labour income, stock price, and interest rate. We show that there are economic and statistical gains from consumption growth frameworks that account for consumer and business sentiments. Specifically, we show that policymakers can improve their forecast accuracy by between 4% and 13% by incorporating consumer and business sentiments into their forecasting frameworks.     

基于GIS的边坡三维极限平衡模型研究

自然界中发生的滑坡绝大多数呈三维形态,边坡稳定性分析应从三维的角度进行处理。在实际边坡工程作业中,科学地计算边坡受到边界条件约束、荷载作用、土体性质在空间上变异等实际形态的影响,同样需要进行三维稳定性分析。目前边坡稳定性分析仍以二维极限平衡法为主。当滑动面已经确定时,使用三维分析可以恰当地考虑滑坡的三维形态对安全系数的影响,同时可以避免二维分析时如何选择代表性横截面,计算结果是否合理等问题。     

凿井水下底卸式自动卸料吊桶

吊桶是立井井筒开凿时期提升矸石和运送材料及升降人员的主要容器,吊桶的卸矸目前多采用挂钩式或座钩式卸料方式;但是随着矿井的开凿深度不断延伸,在过透水层时,由于探放水不及时或涌出水比较大,超出了井筒的排水量,或者是由于冷冻井在解冻后,井筒的井筒质量不过关,各别井壁也会发生透水事故;这就会出现淹井事故,有时淹井深度达二三百米。对于处理这种淹井事故,往往只有一个办法,那就是用沙或混凝土对井筒回填;这就需要吊桶在下到几百米下的水底自动把料卸掉,但现在矿井常用的挂钩式吊桶和座钩式吊桶已经不能满足这个需要了。