Optimal Asset Allocation for CRRA and CARA Insurers under the Vasicek Interest Rate Model

This paper considers the reinsurance-investment problem with interest rate risks under constant relative risk aversion and constant absolute risk aversion preferences, respectively. Stochastic control theory and dynamic programming principle are applied to investigate the optimal proportional reinsurance-investment strategy for an insurer under the Vasicek stochastic interest rate model. Solving the corresponding Hamilton-Jacobi-Bellman equation via the Legendre transform approach, the optimal premium allocation strategies maximizing the expected utilities of terminal wealth are derived. In addition, several sensitivity analyses and numerical illustrations are given to analyze the impacts of different risk preferences and interest rate fluctuation on the optimal strategies. We find that the asset allocation and reinsurance ratio of the insurer are correlated with risk preference coefficient and interest rate fluctuation, and the insurance company may adjust the reinsurance-investment strategy to deal with interest rate risk.

Similarity Changes Analysis for Heart Rate Fluctuation Regularity as a New Screening Method for Congestive Heart Failure

Congestive heart failure (CHF) is a chronic cardiovascular condition associated with dysfunction of the autonomic nervous system (ANS). Heart rate variability (HRV) has been widely used to assess ANS. This paper proposes a new HRV analysis method, which uses information-based similarity (IBS) transformation and fuzzy approximate entropy (fApEn) algorithm to obtain the fApEn_IBS index, which is used to observe the complexity of autonomic fluctuations in CHF within 24 h. We used 98 ECG records (54 health records and 44 CHF records) from the PhysioNet database. The fApEn_IBS index was statistically significant between the control and CHF groups (p < 0.001). Compared with the classical indices low-to-high frequency power ratio (LF/HF) and IBS, the fApEn_IBS index further utilizes the changes in the rhythm of heart rate (HR) fluctuations between RR intervals to fully extract relevant information between adjacent time intervals and significantly improves the performance of CHF screening. The CHF classification accuracy of fApEn_IBS was 84.69%, higher than LF/HF (77.55%) and IBS (83.67%). Moreover, the combination of IBS, fApEn_IBS, and LF/HF reached the highest CHF screening accuracy (98.98%) with the random forest (RF) classifier, indicating that the IBS and LF/HF had good complementarity. Therefore, fApEn_IBS effusively reflects the complexity of autonomic nerves in CHF and is a valuable CHF assessment tool.

Hybrid Extreme Learning Machine dan Firefly Algorithm untuk Meramalkan Nilai Tukar Rupiah terhadap Dolar

Every country has a currency as a medium of exchange and the movement of its exchange rate can affect the economy of the country. In Indonesia, since the freely floating exchange rates system has been applied in August 1997, the value of rupiah currency in the foreign exchange market can change at any time. Considering the massive impacts of exchange rate fluctuation on the economy, then forecasting the exchange rate of rupiah against the US dollar is important to help Indonesia’s economic growth. The aims of this thesis is to predict the estimated exchange rate of rupiah against the US dollar in the future by using hybrid artificial neural network extreme learning machine (ELM) method and firefly algorithm (FA). In the training process, ELM-FA hybrid has a role to obtain the best weight and bias. The weight and bias that obtained will be used for forecasting and to know the success rate of the training process, the validation test process is required. Based on the implementation of program and simulation for some parameter values on the exchange rate data from Jan 2015 until Jan 2018, with four input and hidden nodes, and one output node, obtained the smallest MSE of the training is 0.000480513 with MSE of the testing is 0.0000854107. The relatively small MSE value indicates that ELM-FA network is able to recognize the data pattern well and able to predict the test data well.

Effect of Exchange Rate Fluctuation and Foreign Reserves on Macroeconomic Performance in Nigeria

This study examines the effect of Exchange Rate Fluctuation and Foreign Reserves on Macroeconomics Performance in Nigeria from 1980-2019. The variables of interest include External Debt, Reserves, Exchange Rate, External Debt Servicing and Government Expenditure were analyzed using co-integration, auto-redistribution lag model (ARDL) and Granger Causality test to understand the long and short run relationship between the variables. Result revealed that there is a unidirectional relationship between foreign reserves and the exchange rate. Exchange rate Granger causes foreign reserves in Nigeria, while foreign reserves do not granger cause exchange rate Granger. This means that as the exchange rate depreciates or appreciates, it always has an impact on Nigeria's foreign reserves. The study recommends among other thing that the government should ensure that the country's foreign reserves are used and managed efficiently. This is because it has been established that foreign reserves have a beneficial impact on macroeconomic performance and stimulate economic growth both of which help to enhance the Nigerian economy.

Determinants of Exchange Rate Volatility and Its Implication on the Nigerian Economy (1995-2020)

The study investigates the determinants of exchange rate volatility and its implication on the growth of the Nigerian economy; for the period (1995-2020). Secondary data were collected from the Central Bank of Nigeria Statistical Bulletin, 2020. The study employs Gross Domestic Product as proxy for the Nigerian economy and used as the dependent variable; whereas, exchange rate, import trade and export trade were used as explanatory variables to measure exchange rate fluctuation. Time series econometric techniques are used to test the hypotheses. Exchange rate has an insignificant impact on Gross Domestic Product in Nigeria. Import trade has a significant impact on Gross Domestic Product in Nigeria. Export trade has a significant impact on Gross Domestic Product in Nigeria. The error-correction result confirms that about 71% short-run adjustment speed from long-run disequilibrium. The coefficient of determination indicates that about 68% of the variations in the growth of the Nigerian economy can be explain by changes in exchange rate volatility variables. The study concludes that exchange rate fluctuation is positive; but, had a significant impact on the performance of the Nigerian economy. The study recommends that Government should encourage the export promotion strategies in order to maintain a surplus balance of trade and also conducive environment, adequate security, effective fiscal. The policy towards interest rate should be made such that savings would be stimulated thereby placing more funds in the hands of banks to intermediate to investors seeking funds. Government and policy makers should provide infrastructural facilities so that foreign investors will be attracted to invest in Nigeria. Government and policy makers should increase their surveillance on the commercial banks; in order to address the issue of arbitrarily increase of the exchange rate.

Supply chain movement risk in the sneaker industry: an empirical study

In light of the COVID-19 pandemic and the Sino–US trade war, this study proposes a grey sharing decision-making evaluation model for production base movement and the sustainable operation of enterprises in the footwear industry. First, a focus group technique was employed; personnel from the footwear industry, corresponding government agencies, and the academic community were invited to jointly identify the most important criteria when considering a production base movement. The group listed seven criteria: labor cost, materials, exchange rate fluctuation, tariff, supply chain, transfer cost, and the government. The grey situation decision-making algorithm based on group knowledge and entropy were used to identify the most suitable country for production base movement.

Temporal and geographic analysis of trichinellosis incidence in Chile with risk assessment

Trichinellosis is a foodborne disease caused by several Trichinella species around the world. In Chile, the domestic cycle was fairly well-studied in previous decades, but has been neglected in recent years. The aims of this study were to analyze, geographically, the incidence of trichinellosis in Chile to assess the relative risk and to analyze the incidence rate fluctuation in the last decades. Using temporal data spanning 1964–2019, as well as geographical data from 2010 to 2019, the time series of cases was analyzed with ARIMA models to explore trends and periodicity. The Dickey-Fuller test was used to study trends, and the Portmanteau test was used to study white noise in the model residuals. The Besag-York-Mollie (BYM) model was used to create Bayesian maps of the level of risk relative to that expected by the overall population. The association of the relative risk with the number of farmed swine was assessed with Spearman’s correlation. The number of annual cases varied between 5 and 220 (mean: 65.13); the annual rate of reported cases varied between 0.03 and 1.9 cases per 105 inhabitants (mean: 0.53). The cases of trichinellosis in Chile showed a downward trend that has become more evident since the 1980s. No periodicities were detected via the autocorrelation function. Communes (the smallest geographical administrative subdivision) with high incidence rates and high relative risk were mostly observed in the Araucanía region. The relative risk of the commune was significantly associated with the number of farmed pigs and boar (Sus scrofa Linnaeus, 1758). The results allowed us to state that trichinellosis is not a (re)emerging disease in Chile, but the severe economic poverty rate of the Mapuche Indigenous peoples and the high number of backyard and free-ranging pigs seem to be associated with the high risk of trichinellosis in the Araucanía region.