Maximum likelihood estimation of the double exponential jump-diffusion process

The double exponential jump-diffusion (DEJD) model, recently proposed by Kou (Manage Sci 48(8), 1086–1101, 2002) and Ramezani and Zeng (http://papers.ssrn.com/sol3/papers.cfm?abstract_id=606361, 1998), generates a highly skewed and leptokurtic distribution and is capable of matching key features of stock and index returns. Moreover, DEJD leads to tractable pricing formulas for exotic and path dependent options (Kou and Wang Manage Sci 50(9), 1178–1192, 2004). Accordingly, the double exponential representation has gained wide acceptance. However, estimation and empirical assessment of this model has received little attention to date. The primary objective of this paper is to fill this gap. We use daily returns for the S&;P-500 and the NASDAQ indexes and individual stocks, in conjunction with maximum likelihood estimation (MLE) to fit the DEJD model. We utilize the BIC criterion to assess the performance of DEJD relative to log-normally distributed jump-diffusion (LJD) and the geometric brownian motion (GBM). We find that DEJD performs better than these alternatives for both indexes and individual stocks.     

Stochastic orderings of convolution residuals

In this paper we study convolution residuals, that is, if $X_1,X_2,\ldots ,X_n$ are independent random variables, we study the distributions, and the properties, of the sums $\sum _{i=1}^lX_i-t$ given that $\sum _{i=1}^kX_i>t$ , where $t\in \mathbb R $ , and $1\le k\le l\le n$ . Various stochastic orders, among convolution residuals based on observations from either one or two samples, are derived. As a consequence computable bounds on the survival functions and on the expected values of convolution residuals are obtained. Some applications in reliability theory and queueing theory are described.     

An evolutionary model of the size distribution of firms

An analytical study of the evolution of the distribution of firm size in an industry is presented. A drift-diffusion model is proposed to express the time-evolution of density of firm size within the industry. The model blends the conventional, more or less static, determinants with the kinds of dynamic considerations introduced by stochastic processes of evolutionary dynamics. The steady-state distribution as well as the dynamic behavior of the model are derived. Parameters in the resulting analytical expressions are then fit to a population of firms in the non-manufacturing service sector. The empirical portion of the paper validates the proposed evolutionary model.     

Children’s Food Choice: Advertised Food Type,Health Knowledge and Entertainment

The purpose of this research is to examine how the moderating effects of health knowledge (inactive vs. active) and advertising’s entertainment level (high vs. low) affect children’s response to advertising’s food content (unhealthy vs. healthy). First, a primary study using the qualitative method was conducted with the purpose of identifying healthy and unhealthy food options based on culture, eating habits, nutritional value and the access of Iranian children to each option so that they could be displayed in TV advertising, advergames and questionnaires. Then, a 2 × 2 × 2 full-factorial, randomized, mixed-effects experimental design was used to test the research framework. 330 students (aged 6–11) participated in the study. The findings revealed that children tended to choose more unhealthy foods after exposure to unhealthy food advertising. This effect was greater for a higher level of entertainment, and was successfully moderated by the activation of health knowledge. It was concluded that embedding health messages in advertising (included TV advertising and advergames) help retrieving children’s health knowledge and therefore, choosing less unhealthy food by them.     

Airline in-flight entertainment: the passengers’ perspective

Following relaxation of economic regulation in many aviation markets, the competition amongst airlines has intensified in recent years. This has resulted in improvements in airline products, especially in the in-flight services. One of the areas on which airlines have focused their attention is the provision of personal in-flight entertainment (IFE). In 1998, airlines spent $1.8 billion on IFE. However, the industry is faced with a number of questions in relation to such levels of investment: Are the investments justified? Does IFE influence passengers’ choice of airline? Does IFE have a revenue-generating potential? What does the future hold as far as the IFE services are concerned? This paper addresses these questions based on a passengers survey and literature review. The results indicate that while IFE is not amongst the primary factors affecting passengers’ choice, it contributes greatly to passengers’ satisfaction with airline services. While provision of IFE can currently act as a differentiating factor, in the future it will become part of passengers’ expectations. It has also become apparent that, while IFE has the potential to generate some revenue, it would not be enough to cover the total costs associated with the installation and running of IFE systems. The impact of IFE would be felt, indirectly, through increase in passenger loyalty which should have a positive impact on airline revenues.     

Using the crowd for business model innovation: the case of Digikala

On November 15, 2015, Digikala, one of the largest online stores in the Middle East, launched its first-ever crowdsourcing contest called ‘A glance at tomorrow’. What distinguishes this contest from common crowd-based initiatives is that it was aimed at Business Model Innovation (BMI) rather than product and process innovation. Although using the crowd has proven to be an effective way for firms to boost their product and process innovation, its use for BMI is challenging. Based on real large-scale data from the Digikala’s crowdsourcing contest, this research focuses on the application of crowd-powered solutions in BMI, which has rarely been investigated previously. Our exploratory case study indicates that the crowd could contribute to the BMI process. Our findings point to a new form of ‘division of innovation labor’ in BMI. Contribution of the crowd in BMI is more likely to be relevant to Value Proposition and Value Delivery, while it might be less relevant to Value Capture and Value Creation. The results also support the notion that crowd-contributor characteristics affect the quality of proposals for BMI. We argue that this line of research could help companies design and implement customized crowd-based initiatives to better support their BMI process.     

Determinants of sustainable mode choice in different socio-cultural contexts: A comparison of Rome and San Francisco

This paper is a part two of a study investigating the relative importance of the built environment, socio-demographic, and attitudinal factors on mode choice. A semi-experimental approach that aims to measure causal effects of the built environment is utilized. This paper reports spatial analysis, survey and modeling results for San Francisco, CA, USA and compares the results with a previous similar study in Rome, Italy. Results reveal that the local street network's integration is important in both cities and that in both cases built environment seems to have higher impact on mode choice than attitudes and socio-demographic factors. Built environment is especially impactful when diversity, design quality, density and syntactical accessibility are combined. In San Francisco willingness to spend time walking, biking or taking transit is lower than in Rome, and residents are more sensitive to concerns about safety and security. Work travel is more affected by demographic and attitudinal factors in San Francisco than in Rome implying that in San Francisco, nonwork travel behavior may have slightly higher potential to respond positively to improvements in the built environment than work trips. In Rome, peer pressure, cost sensitivity, and probiking attitude can compensate for lack of some built environmental characteristics, but not in San Francisco, where only protransit attitude has this effect. Moreover, lack of any built environmental characteristics reduces the possibility of sustainable mode choice more dramatically in San Francisco pointing to the higher importance of investments on improving the built environment rather than marketing efforts to change attitudes.     

A Dynamic Model of Size Distribution of Firms Applied to U.S. Biotechnology and Trucking Industries

The present paper attempts to contribute to the existing literature on industry dynamics by proposing a tractable structure for the analysis of the dynamic process governing the size distribution of firms. An analytical model is proposed which describes the density of the cross-sectional distribution of firm size within an industry. The model is based on the theory of diffusion processes, and the method illustrates how information on the time-evolution of size distribution of firms over an extended period of time can be used to make inferences about an underlying process. An empirical application to the evolution of size distribution of population of firms in (i) the U.S. biotechnology industry, and (ii) the U.S. interstate for-hire trucking industry illustrates the applicability of the proposed model in industry studies.     

Emissions Pricing Policies and Business Cycles: Fixed vs. Variable Tax Regimes

As by-products, emissions follow economic fluctuations. Ignoring this fact in environmental policies can lead to unexpected emissions fluctuations and an increase in intervention costs. Using a real business cycle model, we compare two policies: a fixed tax policy where the price is constant over time and a variable tax regime where the tax rate is set at the beginning of each period. We find that while both programs result in lower emissions, a variable tax regime is preferable since first, it can ensure that the maximum welfare is always achieved, and second, it is more effective in stabilising emissions.