International Journal of Business and Development Studies
Volume:8 Issue: 1, Autumn 2016

Futures contract is one of the most important derivatives that is used in financial markets in all over the world to buy or sell an asset or commodity in the future. Pricing of this tool depends on expected price of asset or commodity at the maturity date. According to this, theoretical futures pricing models try to find this expected price in order to use in the futures contract. So in this article, three futures pricing models have been considered. In the first model, one-factor pricing model without spot price jump has been presented. In this model futures price of commodity is a function of spot price and remaining time to maturity. In the others, the models have been expanded by using jump-diffusion processes and stochastic jump in spot price. Then, to empirically study the models, NYMEX WTI crude oil futures price data has been used and parameters have been estimated with Kalman filter algorithm. The empirical results show that the one factor model with uniform jump is suitable to explain the crude oil spot price behavior and its futures price. This model and estimated parameters provide the useful tool to predict NYMEX WTI oil future prices.

The literature show evidence that small manufacturing enterprises (SMEs) are understood as main source of technology development and employment creation. At the same time they are vulnerable to a number of restrictions such as access to finances, skilled labor and public support, while are exposed to high competition and suffer from low survival rate. This research aims to shed lights on the role that education play in the process of industrial and economic development of Iranian provinces. This research is conducted in a number of ways. First, a comprehensive literature review is conducted to gain experience from the national and international literature to identify the state-of-art research and important theories, methods and empirical results to shape the structure of this research and identify key data requirements. Second, the status of industrial infrastructure and distribution of firms by important characteristic of education is investigated. Comparison is made at the aggregate national level. Third, based on the literature findings and analysis of the industry structure, assemble a data set at the province level that is representative with good coverage of the industry sector. Also a composite Development Infrastructure Index for provinces with available ranks in mentioned component is calculated. Based on the findings, appropriate policy recommendations to improve the conditions of SMEs infrastructure and performance will purposed.

During the recent decades, neural network models have been focused upon by researchers due to their more real performance and on this basis, different types of these models have been used in forecasting. Now, there is a question that which kind of these models has more explanatory power in forecasting the future processes of the stock. In line with this, the present paper made a comparison between static and dynamic neural network models in forecasting (uninvariable) the return of Tehran Stock Exchange (TSE) index in order to find the best model to be used for forecasting this series. The data were collected daily from 26/11/2009 to 17/10/2014. The models examined in this study included two static models (Adaptive Neuro-Fuzzy Inference Systems «ANFIS» and Multilayer Feed-forward Neural Network «MFNN») and a dynamic model (nonlinear neural network autoregressive model «NNAR»). The findings showed that based on the Mean Square Error and Root Mean Square Error criteria, ANFIS model had a much higher forecasting ability compared to other models.

This paper investigates the nature of volatility characteristics of stock returns in the Bangladesh stock markets employing daily all share price index return data of Dhaka Stock Exchange (DSE) and Chittagong Stock Exchange (CSE) from 02 January 1993 to 27 January 2013 and 01 January 2004 to 20 August 2015 respectively. Furthermore, the study explores the adequate volatility model for the stock markets in Bangladesh. Results of the estimated MA(1)-GARCH(1,1) model for DSE and GARCH(1,1) model for CSE reveal that the stock markets of Bangladesh capture volatility clustering, while volatility is moderately persistent in DSE and highly persistent in CSE. Estimated MA(1)EGARCH(1,1) model shows that effect of bad news on stock market volatility is greater than effect induced by good news in DSE, while EGARCH(1,1) model displays that volatility spill over mechanism is not asymmetric in CSE. Therefore, it is concluded that return series of DSE show evidence of three common events, namely volatility clustering, leptokurtosis and the leverage effect, while return series of CSE contains leptokurtosis, volatility clustering and long memory. Finally, this study explores that MA(1)-GARCH(1,1) is the best model for modeling volatility of Dhaka stock market returns, while GARCH models are inadequate for volatility modeling of CSE returns.

There are various causes for inflation in macroeconomics. One of the important channels of experiencing inflation is through the international economy caused by external shocks. In this context, the impact of exchange rate volatilities on domestic prices known as Exchange Rate Pass-Through (ERPT) plays a vital role. The present paper deals with the impact of Exchange Rate Pass-Through on inflation in Iran. To do so, using a monthly time series data for the period 1983: 1-2014: 9, a Threshold Regression has been applied to estimate the relevant model. The results indicate a growth rate of monthly nominal exchange rate of 9.1 percent acts as a threshold rate. In other words, ERPT to domestic prices above the threshold is statistically significant whereas below the threshold, is not statistically significant. Therefore, due to the fact that one of the main functions of the central bank is to maintain a stable currency value it is very important to pay attention to the impact of Exchange Rate Pass-Through and its threshold effects in implementation monetary policies to curb inflation.

Digital and Information technologies are fundamental factors for all organizations which carry out organizational and social activities levels and it causes to change the nature of business. Create what is a type of entrepreneurship that is extracted from the concept of entrepreneurship. Digital and information technology is one of electronic style of this creation. Therefore, it can be said that an organization utilizes digital entrepreneurship providing that it employs the Internet, Information and Communication Technology as devices for producing and developing in their business and trend opportunities. Present paper is planning to be identified the major structural and content factors of digital entrepreneurship. Additionally, it is programmed to study the quality constructing the digital Entrepreneurship. To achieve to hinted subjects, it has been used different theories, application survey and questionnaire of digital entrepreneurship. The sample size consists of 137 experts of entrepreneurship which were voted from Science and Technology Park in East Azerbaijan-Iran in 2013. Data analysis was carried out by using Factor Analysis, Structural Equation, Freidman Mean Ranking Test, AHP Rankin Analysis. It can be concluded that the consequences of present study illustrates that there is significant relationship between content and structural factors together. Moreover, it is existence meaningful results in AHP.

This study seeks to investigate the impact of job characteristics on counterproductive work behaviour (CWB). Three forms of CWB are identified: interpersonal CWB, production CWB, and property CWB. The regression analysis carried out on a sample of 355 employees showed mixed results. Job significant demonstrated a significant and negative relationship with production CWB. The relationship between job feedback, interpersonal CWB and property CWB was as postulated. In similar not, job identity demonstrated a significant and negative relationship with organizational CWB. However, job autonomy does not show any significant relationship. Implications, limitations, and suggestions for future research are discussed.