Likelihood-based specification analysis of continuous-time models of the short-term interest rate

An extensive collection of continuous-time models of the short-term interest rate is evaluated over data sets that have appeared previously in the literature. The analysis, which uses the simulated maximum likelihood procedure proposed by Durham and Gallant (2002), provides new insights regarding several previously unresolved questions. For single factor models, I find that the volatility, not the drift, is the critical component in model specification. Allowing for additional flexibility beyond a constant term in the drift provides negligible benefit. While constant drift would appear to imply that the short rate is nonstationary, in fact, stationarity is volatility-induced. The simple constant elasticity of volatility model fits weekly observations of the three-month Treasury bill rate remarkably well but is easily rejected when compared with more flexible volatility specifications over daily data. The methodology of Durham and Gallant can also be used to estimate stochastic volatility models. While adding the latent volatility component provides a large improvement in the likelihood for the physical process, it does little to improve bond-pricing performance.     

An Economic Analysis of Requirements to Prevent Handheld Hair Dryer Water Immersion Electrocutions in the USA

Before 1987, when handheld hair dryers were not required to protect against water immersion electrocutions, there were almost 16 such electrocutions annually in the USA. This article presents a retrospective evaluation of the benefits and costs of the 1987 and 1991 immersion protection requirements of the voluntary hair dryer safety standard in the USA. The benefits are based on estimates of the reduced risk of electrocution resulting from the requirements, and the valuation of the reduced risk derived from willingness to pay studies of the “value of statistical life” found in the economics literature. The costs were defined as the incremental costs associated with incorporating the immersion protection technology into handheld hair dryers. The study found that the requirements were highly effective and may have reduced the immersion-related mortality rate by almost 97%. The expected present value of the estimated benefits of the requirements amounted to about $4.56 per dryer in 2014 dollars and substantially exceeded the costs of about $2 per dryer. The primary outcome measure, the expected net benefits (i.e., benefits minus costs) of the requirements, amounted to an average of about $2.56 per hair dryer, over the hair dryer’s expected product life. Given sales of about 23 million handheld hair dryers annually, the present value of the expected net benefits associated with 1 year’s production would have amounted to about $58.9 million. A sensitivity analysis showed that the major findings were robust with respect to changes in the underlying parameters of the analysis. The study also discusses the factors leading to a high rate of effectiveness estimated for the immersion protection requirements.     

Monte Carlo methods for estimating,smoothing, and filtering one- and two-factor stochastic volatility models

One- and two-factor stochastic volatility models are assessed over three sets of stock returns data: S&P 500, DJIA, and Nasdaq. Estimation is done by simulated maximum likelihood using techniques that are computationally efficient, robust, straightforward to implement, and easy to adapt to different models. The models are evaluated using standard, easily interpretable time-series tools. The results are broadly similar across the three data sets. The tests provide no evidence that even the simple single-factor models are unable to capture the dynamics of volatility adequately; the problem is to get the shape of the conditional returns distribution right. None of the models come close to matching the tails of this distribution. Including a second factor provides only a relatively small improvement over the single-factor models. Fitting this aspect of the data is important for option pricing and risk management.     

The adoption of strategic marketing practices： A comparison between New Zealand and Chinese manufacturers

This article compares the extent to which ten basic ＂textbook＂ strategic marketing practices are being used among manufacturing firms in New Zealand and China. Data was collected via questionnaire and a total of 145 and 89 usable responses were received from firms employing more than 50 people in each country respectively. The results indicate that many of the basic strategic marketing practices which are typically advocated in the mainstream academic literature have been similarly and quite widely adopted by manufacturers in both countries. However, the results also suggest that, albeit in different areas, there is still scope for manufacturers in both New Zealand and China to embrace strategic marketing more fully.     

Impact of Wal-Mart on Market Share in a Rural Grocery Market: An Application of the Markov Chain Model

With Americans spending up to 13% of their income on grocery shopping, smart shopping can help a typical family save. Many scholars have studied the effects on market share and profits from changing market share using the Markov model, and also studied the competitive strategies of grocery retailers under these conditions. While the forecast of the steady state is highly useful, examining the transition periods before the steady state is reached is also useful. In these transition periods, a retailer may opt for a new competitive strategy; therefore, the transition periods may provide greater insight into the dynamics of the competitive response. More attention should be paid to the revenues for groceries in transition periods before a steady state is reached—especially in markets dominated by retail giants, such as Wal-Mart. This study attempts to model that phenomenon and to explore appropriate competitive strategies.     

Share of wallet's role in customer profitability

Understanding the financial contribution customers make to their organisations is an initial step in customer relationship management. Set in the banking industry, this paper examines the strength of ‘share of wallet’ as a proxy variable for measuring customer profitability. Data from a study of 1,100 personal retail banking customers of a New Zealand regional bank were used in combination with the bank's own customer contribution data for each of those respondents. Results indicate that although share of wallet might be used as a proxy for customer contribution at a macro level of customer classification, details of specific financial relationships customers have with their main bank are still necessary. Nevertheless, share of wallet ought to become a standard entry in a bank's customer database.