International Journal of Financial Engineering

In this paper, we study the probability of default, the credit default swap (CDS) implied probability of default, and the estimated actual probability of default from the structural models. We first show that the conditional risk-neutral probability of default is totally different from the CDS implied probability of default, and the CDS implied probability of default provides biased estimation of a corporation’s actual probability of default. Hence, the common belief that the CDS implied probability of default gives unbiased (or reliable) estimations of the firm’s probability of default is false. Furthermore, we use the credit spread risk premium as the difference of the physical measure and the risk-neutral measure of the credit spread to estimate the actual bond spread, and relate the credit spread risk premium in terms of the market price of risk and the credit spread volatility. Using the credit spread volatility and the risk-neutral credit spread and the market price of risk in hybrid HPD model, we obtain the estimated actual probability of default in a structural model. The estimated actual probability of default would be useful for credit rating agencies, investors, credit risk managers and regulators.

Recent interest in financial technology (fintech) lending business has caused increasing challenges of credit scoring models using bank account activity information. Our work aims to develop a new credit scoring method based on bank account activity information. This method incorporates borrower firms’ segment-level heterogeneity, such as a segment of sales size and firm age. We employ Bayesian hierarchical modeling, which mitigates data sparsity issue due to data segmentation. We describe our modeling procedures, including data handling and variable selection. Empirical results show that our model outperforms the traditional logistic model for credit scoring in information criterion. Our model realizes advanced credit scoring based on bank account activity information in fintech lending businesses, taking segment-specific features into credit risk assessment.

The goal of this paper is to establish a general framework for the development of small- or medium-sized enterprises’ (SMEs) growth path by using star-coupled stochastic dynamic system approach. The dynamic behaviors are related to the stochastic resonance (SR) phenomenon subject to multiplicative fluctuation and periodic force which could be interpreted as uncertain environments faced by SMEs (enterprises) during their growth process. The multiplicative noise is modeled as dichotomous noise (uncertainty under the innovation and capital paradigm) and the memory of risk environments is characterized by using fractional kernel function. By using the mathematical derivation, the analytical expressions for the first moment of the steady state response, the stability in the long-time limit in terms of (enterprises) systems’ asymptotic stability is obtained. Theoretic and simulation results show the nonmonotonic dependence between the output gain and the input signal frequency, noise parameters for SMEs dynamic behaviors. Furthermore, the fluctuation noise, the number of related parties (partners) for SMEs, and the fractional-order work together, producing more complex dynamic phenomena compared with the traditional integral-order systems (for enterprises). Finally, theoretical analyses with corresponding numerical simulations results established in this paper would provide a possible fundamental mathematical framework for the study of Schumpeter’s theory on the development for SMEs’ growth under the “innovation and capital paradigm” and related disciplines. In particular, the framework allows us, for the first time, to logically conclude that “in general, the ratio for SMEs’ growth successfully is around less than one-third”, this is actually consistent with what the market has been observing commonly in general.

In this paper, we use the permutation entropy algorithm to derive the static and dynamic permutation entropy of commodity futures, and to evaluate the effectiveness of main products in China’s commodity futures market. The intraday data of six varieties belonging to six categories in China’s commodity futures market are taken as samples. We find the following: (1) The return distribution of the main varieties shows high peaks, fat tails and asymmetry, and follows the biased random walk distribution characteristics; (2) The permutation entropy of all varieties decreases significantly in the same time window, during which the price volatility of major commodity markets rises. And the time window coincides with the impact time of COVID-19 epidemic; (3) By comparing the distribution of permutation entropy of main varieties in different stages of event shock, we found that the mean value of permutation entropy decreases significantly during the process of event shock, and the price fluctuates greatly. Therefore, the significant decrease of permutation entropy is a valuable warning signal for regulators and investors.

This study investigates the effect of the board of directors on financial performance, either directly or indirectly through the existence of risk management in Indonesia.This study presents empirical investigation of 31 nonfinancial Indonesia listed companies from 2010 to 2016. This study utilizes the Structural Equation Modeling (SEM) model. The results of the SEM model find that there is a significant positive effect of the existence of risk management and the tenure-Chief Executive Officer (CEO) on financial performance. However, CEO duality has a significant negative effect on financial performance. The results also find that the effect of CEO duality and board size are significant positive on financial performance through the existence of risk management. It is one of the first papers to investigate the effect of board of directors and financial performance, either directly or indirectly through the existence of risk management in Indonesia.

In this paper, we consider the construction of a sales management strategy for a highly liquid asset trading at the market. The proposed strategy goal is to maximize the weighted average price of sales. It is assumed that the market price follows a geometric Brownian motion process in which drift and volatility coefficients are random functions of time. The important feature of the given management is that the volumes of assets in the succession of buy and sell executed bargains are calculated exclusively on the basis of the observed market prices rather than on the model coefficient values. In contrast to the management proposed earlier in this study, obligatory realization of some minimum volume of assets on the given time period is demanded. Examples of real-world markets trade demonstrating the imposed constraints effect on the weighted average price values obtained within the constructed management are given.

In this study, we study the price dynamics of cryptocurrencies using adaptive complementary ensemble empirical mode decomposition (ACE-EMD) and Hilbert spectral analysis. This is a multiscale noise-assisted approach that decomposes any time series into a number of intrinsic mode functions, along with the corresponding instantaneous amplitudes and instantaneous frequencies. The decomposition is adaptive to the time-varying volatility of each cryptocurrency price evolution. Different combinations of modes allow us to reconstruct the time series using components of different timescales. We then apply Hilbert spectral analysis to define and compute the instantaneous energy-frequency spectrum of each cryptocurrency to illustrate the properties of various timescales embedded in the original time series.

Using a real option approach, this paper models an arbitrary real life investment, which typically has a long maturity date, as a perpetual American call option in a Levy market. Expressions for the moments, characteristic function and infinitesimal generator of the associated jump-diffusion Levy process, defined by two independent compound Poisson processes and two correlated standard Brownian motions, are derived and these fundamental results are employed to determine the optimal time for investment. An application of the results to a Build Operate and Transfer investment is furnished.

A risk-neutral-density (RND) function plays a key role in determining option prices accurately. The RND function is useful in understanding the negative skewness and the excess kurtosis of the stock returns. RND models bases on the log-normal distribution (for example, Black–Scholes (BS) model (Black, F and M Scholes (1973). The pricing of options and corporate liabilities, The Journal of Political Economy 3, 637–654)) are less accurate to capture the negative skewness and the excess kurtosis of stock returns (Markose, S and A Alentorn (2011). The generalized extreme value distribution, implied tail index, and option pricing, The Journal of Derivatives 18(3), 35–60). The Extreme Value Theory (EVT) is useful in addressing the tail behavior of stock returns. The tail shape parameter in a Generalized Extreme Value (GEV) distribution class helps control tails’ size and shape. This paper model, the RND function in pricing the European call option, is modeled using a GEV distribution class, namely, a Gumbel distribution. It then compares GEV distribution option values with the BS values. It observes that the BS model underprices the call option values near maturity compared to those obtained by the GEV model. The Gumbel distribution for stock returns is useful in reducing the pricing bias of the BS model.

This paper investigates the dynamic links between renewable energy, commodities, and financial stock markets and analyzes the performance of renewable energy investment in an international portfolio diversification strategy across different financial market conditions. By using the dynamic spillover approach, the empirical results show that the renewable energy and oil markets are net emitters of shocks to stock markets. By applying the nonparametric stochastic dominance approach and comparing the optimal maximum Sharpe ratio (MSR) diversified portfolios, the results suggest that the renewable energy index can be a good substitute for traditional diversification, especially during tranquil periods.

In this paper, we analyze Sovereign Bond-Backed Securities in the Euro area, concentrating our attention on the return of the different tranches and on their riskiness. We show that as the correlation level among States increases, the yield rate of senior tranches increases while the yield rate of junior tranches decreases. A similar effect is observed when introducing a block dependence structure with high correlation among States belonging to the same block. Introducing a nonzero recovery rate, as opposed to a null recovery rate, decreases the yield rate of senior tranches and increases the yield rate of junior tranches. We compute the loss distribution and the Value at Risk (VaR) associated with the market risk of retaining the different tranches of the bond. We also analyze the possibility of reaching a safe asset through pooling tranches of government bonds of different States. In summary, we show that the issue in reaching a comprehensive and safe offering through the securitization of government bonds is not the safety of senior tranches but the risk of the junior ones.

In this paper, we consider the upper and lower variances under model uncertainty and propose the corresponding algorithm. We then focus on the linear combination of maximally distributed and $G$-normally distributed random variables, and obtain the explicit formula to calculate Value-at-Risk (VaR) where the underlying risk is captured by such combination with mean-uncertainty and variance-uncertainty simultaneously. As an application in finance, the general $G$-VaR prediction with model uncertainty is also discussed.

Purpose: This research was administered to investigate the influence of spiritual leadership on organizational commitment and organizational commitment on organizational performance seen through multidimensions where spiritual leadership is in three dimensions namely vision, faith/hope, and altruistic love; organizational commitment in three dimensions namely affective, normative, and continuity, while organizational performance is in two dimensions which are financial and nonfinancial performance. Design/Method: The population selected in this study included 1,422 members of Village Credit Institution (LPD) in Bali Province including the chairman, secretary, and treasurer. Samples were selected by using the probability sampling technique which is a simple random sampling in which the sample size $n$ was drawn from a population of magnitude $N$, allowing each unit to have the same chance of being selected. The obtained data were then analyzed using a Structural Equation Modeling based on analysis of moment structure (AMOS), with multidimensions in each research variable. Findings: The results of the analysis show that vision, faith/hope, and altruistic love have a significant influence on affective commitment, normative commitment, and continuity commitment. On the other hand, affective, normative, and continuity commitment share a certain influence on financial performance. However, it is only the normative commitment that influences nonfinancial performance. Originality: The novelty of this research is in the effort to reconstruct the previous research model to obtain a new one that combines two research models; the spiritual leadership model and the A-Three Component Model of Organizational Commitment. The new model is expected to solve the inconsistencies of previous research results and solve various problems related to leadership and organizational commitment as variables that influence LPD performance.

The purpose of this research is to examine the relationship between corporate governance and risk management of Indonesian banks. Bank risk managements are measured by market risk, credit risk, and liquidity risk. The samples used in this study were all banks registered in Indonesia during the 2010–2016 period. The data sources were obtained from the annual reports and bank financial reports. The results show that corporate governance implementation in Indonesia was able to affect credit risk and liquidity risk. There were differences in credit risk and liquidity risk in banks with different governance ratings, but not at market risk.