International Journal of Financial Engineering

The purpose of this study is to investigate the impact of behavioral biases on investment decision, and the interaction effect of socio-demographic characteristics. Data were collected from a sample of 179 individual investors in the Pakistan Stock Exchange (PSX). The authors conducted a hierarchical regression analysis to test the moderating effect of socio-demographic variables on behavioral biases. The results show that behavioral biases have a significant impact on investors’ decision-making. Moreover, socio-demographic variables (education, occupation and marital status) moderate the relationship between emotional biases and investors’ decision-making. This study provides a new addition to prior literature by investigating the impact of behavioral biases on investors’ decision-making, and the interaction effect of socio-demographic characteristics.

In the top-down approach of intensity-based credit risk modeling, a procedure called “random thinning” is needed to obtain credit event intensities for sub-portfolios. This paper presents a random thinning model incorporating a risk factor called the credit quality vulnerability factor (CQVF) to capture time-series variation in credit event occurrence in a target sub-portfolio. In particular, we propose a type of CQVF that follows truncated normal distributions specified by macroeconomic variables. Using credit event samples of Japanese firms, our empirical analysis aims to clarify the applicability and effectiveness of the proposed model to practical credit risk management. Since macroeconomic variables are included in our model, it is applicable to the macro-stress testing of portfolio credit risk management within a top-down-type framework.

This study proposes a mathematical optimization model for simultaneously forecasting plausible market scenarios and portfolio losses. Interest rates, volatilities and correlation coefficients can be modeled by the DCC-GARCH. A constraint condition is set by the Mahalanobis distance for deciding an acceptable range of change in interest rates. An objective function is set as a hypothetical market portfolio loss from delta, gamma and vega. The mathematical optimization model becomes a nonlinear programming problem for which it is difficult to find appropriate solutions. Therefore, the study introduces an original heuristic approach for preventing the signs of solutions from unintentionally becoming inverse. The study finds that, compared to a stressful scenario in Japan, the forecasting scenarios and losses are plausible.

The key area of this research is to analyze the total factor productivity of mutual funds by using Data Envelopment Analysis (DEA) and also to identify the components which play a significant role in the growth of productivity. Malmquist productivity index approach is a nonparametric method that decomposes the index into components of productivity. The process of decomposition also helps in identifying the contribution of technology and efficiency in the growth of mutual funds in Pakistan. Empirical results suggest that efficiency growth in mutual funds is presenting the upward trend. The individual results of mutual funds showed the divergent trend. The component of pure efficiency change has a great influence on productivity growth except for all others components, and technical change has a smaller number of contributions in productivity growth.

Leveraged exchange-traded funds (LETF) are newly introduced ETFs that have become increasingly popular. It closely tracks the value of an underlying index while allowing for additional leverage. In this paper, we consider the valuation of options written on LETF under two popular affine GARCH models, the Heston–Nandi model and the inverse Gaussian GARCH model. We also calibrate the two models using market data, and demonstrate the superior pricing performance.

The implied volatility of an option contract is the value of the volatility of the underlying instrument which equates the theoretical option value from an option pricing model (typically, the Black–Scholes$-$Merton model) to the current market price of the option. The concept of implied volatility has gained in importance over historical volatility as a forward-looking measure, reflecting expectations of volatility (Dumas et al., 1998). Several studies have shown that the volatilities implied by observed market prices exhibit a pattern very different from that assumed by the Black–Scholes$-$Merton model, varying with strike price and time to expiration. This variation of implied volatilities across strike price and time to expiration is referred to as the volatility surface. Empirically, volatility surfaces for global indices have been characterized by the volatility skew. For a given expiration date, options far out-of-the-money are found to have higher implied volatility than those with an exercise price at-the-money. For short-dated expirations, the cross-section of implied volatilities as a function of strike is roughly V-shaped, but has a rounded vertex and is slightly tilted. Generally, this V-shape softens and becomes flatter for longer dated expirations, but the vertex itself may rise or fall depending on whether the term structure of at-the-money volatility is upward or downward sloping. The objective of this study is to model the implied volatility surfaces of index options on the National Stock Exchange (NSE), India. The study employs the parametric models presented in Dumas et al. (1998); Peña et al. (1999), and several subsequent studies to model the volatility surfaces across moneyness and time to expiration. The present study contributes to the literature by studying the nature of the stationary point of the implied volatility surface and by separating the in-the-money and out-of-the-money components of the implied volatility surface. The results of the study suggest that an important difference between the implied volatility surface of index call and put options: the implied volatility surface of index call options was found to have a minimum point, while that of index put options was found to have a saddlepoint. The results of the study also indicate the presence of a “volatility smile” across strike prices, with a minimum point in the range of 2.3–9.0% in-the-money for index call options and of 10.7–29.3% in-the-money for index put options; further, there was a jump in implied volatility in the transition from out-of-the-moneyness to in-the-moneyness, by 10.0% for index call options and about 1.9% for index put options.

This study has attempted to calculate the actual cost of the fund of SMEs by considering the fund from institutional and non-institutional sources. For this study, some financial tools, techniques, two samples mean comparison test and ANOVA test have been used to analyze the cross-sectional primary data. The study has found that the average actual cost of the fund from institutional sources, non-institutional sources (without trade credit) and trade credit are 15.52%, 32.11% and 40%, respectively. The cost of the external financing of small enterprises is higher than the medium enterprises and this cost in manufacturing sectors is higher than the service/trade sectors. Again, this cost in rural region is higher than the urban region but it is not statistically significant. The average cost of external financing of SMEs is about 29% which is really high to conduct a business properly.

Daily and weekly market index returns were analyzed to examine market efficiency in emerging and frontier markets in MENA region. Based on a set of tests, autocorrelation, runs, unit root and multiple variance report tests, over a period of 7 years, our results show mixed results for different indices. However, emerging and frontier market and yield series indicate the lack of market efficiency. We find that daily and weekly market index returns do not follow random markets. We can conclude that investors can obtain the flow of arbitrage profits due to the inefficiency of the market belonging to these countries.