Stochastic Volatility Models and Simulated Maximum Likelihood Estimation

Financial time series studies indicate that the lognormal assumption for the return of an underlying security is often violated in practice. This is due to the presence of time-varying volatility in the return series. The most common departures are due to a fat left-tail of the return distribution, volatility clustering or persistence, and asymmetry of the volatility. To account for these characteristics of time-varying volatility, many volatility models have been proposed and studied in the financial time series literature. Two main conditional-variance model specifications are the autoregressive conditional heteroscedasticity (ARCH) and the stochastic volatility (SV) models. The SV model, proposed by Taylor (1986), is a useful alternative to the ARCH family (Engle (1982)). It incorporates time-dependency of the volatility through a latent process, which is an autoregressive model of order 1 (AR(1)), and successfully accounts for the stylized facts of the return series implied by the characteristics of time-varying volatility. In this thesis, we review both ARCH and SV models but focus on the SV model and its variations. We consider two modified SV models. One is an autoregressive process with stochastic volatility errors (AR--SV) and the other is the Markov regime switching stochastic volatility (MSSV) model. The AR--SV model consists of two AR processes. The conditional mean process is an AR(p) model , and the conditional variance process is an AR(1) model. One notable advantage of the AR--SV model is that it better captures volatility persistence by considering the AR structure in the conditional mean process. The MSSV model consists of the SV model and a discrete Markov process. In this model, the volatility can switch from a low level to a high level at random points in time, and this feature better captures the volatility movement. We study the moment properties and the likelihood functions associated with these models. In spite of the simple structure of the SV models, it is not easy to estimate parameters by conventional estimation methods such as maximum likelihood estimation (MLE) or the Bayesian method because of the presence of the latent log-variance process. Of the various estimation methods proposed in the SV model literature, we consider the simulated maximum likelihood (SML) method with the efficient importance sampling (EIS) technique, one of the most efficient estimation methods for SV models. In particular, the EIS technique is applied in the SML to reduce the MC sampling error. It increases the accuracy of the estimates by determining an importance function with a conditional density function of the latent log variance at time t given the latent log variance and the return at time t-1. Initially we perform an empirical study to compare the estimation of the SV model using the SML method with EIS and the Markov chain Monte Carlo (MCMC) method with Gibbs sampling. We conclude that SML has a slight edge over MCMC. We then introduce the SML approach in the AR--SV models and study the performance of the estimation method through simulation studies and real-data analysis. In the analysis, we use the AIC and BIC criteria to determine the order of the AR process and perform model diagnostics for the goodness of fit. In addition, we introduce the MSSV models and extend the SML approach with EIS to estimate this new model. Simulation studies and empirical studies with several return series indicate that this model is reasonable when there is a possibility of volatility switching at random time points. Based on our analysis, the modified SV, AR--SV, and MSSV models capture the stylized facts of financial return series reasonably well, and the SML estimation method with the EIS technique works very well in the models and the cases considered

A Comparison of the Restaurant Selection Preferences between Residents and Visitors of South Florida

The purpose of the present study is to examine of selection preferences and to compare residents’ preferences with visitors’ ones in South Florida. Using data 290 customers in full-service restaurants, results show that consumers’ restaurant selection preference between residents and visitors is not significantly different; however, there are significant differences among demographic profiles. Implications are discussed to develop unique marketing strategies to attract both residents and visitors in South Florida

Revisiting small-world network models: Exploring technical realizations and the equivalence of the Newman-Watts and Harary models

We address the relatively less known facts on the equivalence and technical realizations surrounding two network models showing the "small-world" property, namely the Newman-Watts and the Harary models. We provide the most accurate (in terms of faithfulness to the original literature) versions of these models to clarify the deviation from them existing in their variants adopted in one of the most popular network analysis packages. The difference in technical realizations of those models could be conceived as minor details, but we discover significantly notable changes caused by the possibly inadvertent modification. For the Harary model, the stochasticity in the original formulation allows a much wider range of the clustering coefficient and the average shortest path length. For the Newman-Watts model, due to the drastically different degree distributions, the clustering coefficient can also be affected, which is verified by our higher-order analytic derivation. During the process, we discover the equivalence of the Newman-Watts (better known in the network science or physics community) and the Harary (better known in the graph theory or mathematics community) models under a specific condition of restricted parity in variables, which would bridge the two relatively independently developed models in different fields. Our result highlights the importance of each detailed step in constructing network models and the possibility of deeply related models, even if they might initially appear distinct in terms of the time period or the academic disciplines from which they emerged.Comment: 11 pages, 5 figures, 1 table, to appear in J. Korean Phys. So

Flightless-I Controls Fat Storage in Drosophila

Triglyceride homeostasis is a key process of normal development and is essential for the maintenance of energy metabolism. Dysregulation of this process leads to metabolic disorders such as obesity and hyperlipidemia. Here, we report a novel function of the Drosophila flightless-I (fliI) gene in lipid metabolism. Drosophila fliI mutants were resistant to starvation and showed increased levels of triglycerides in the fat body and intestine, whereas fliI overexpression decreased triglyceride levels. These flies suffered from metabolic stress indicated by increased levels of trehalose in hemolymph and enhanced phosphorylation of eukaryotic initiation factor 2 alpha (eIF2??). Moreover, upregulation of triglycerides via a knockdown of fliI was reversed by a knockdown of desat1 in the fat body of flies. These results indicate that fliI suppresses the expression of desat1, thereby inhibiting the development of obesity; fliI may, thus, serve as a novel therapeutic target in obesity and metabolic diseases

The Influence Of Firm’s Fair Value System On Earnings Quality Under IFRS

This paper analyzes the influence of firms’ fair value system on earnings quality under IFRS. Korean firms are required to adopt IFRS in 2011. IFRS adoption was expected to increase value relevance of book value of equity and benefit information users’ decision making. However, prior Korean studies report that value relevance of book value of equity is indifferent between under K-GAAP and IFRS. We consider that the indifference in value relevance of book value of equity after IFRS adoption is due to different level of fair value system among firms. We investigate whether the different level of fair value system among firms lead to the difference in earnings quality. Furthermore, we examine how each firm’s fair value system affect earnings quality under IFRS.  This study finds following results. First, firms with weak fair value system smooth income more frequently. Second, firms with weak fair value system experience small amount of positive profit and slight increase in net income compared to prior period more frequently. Third, firms with weak fair value system make less timely loss recognition. Lastly, book value of equity and goodwill has low relative value relevance for weak fair value systemic firms, while both book value of equity and goodwill have incremental value relevance for firms with strong fair value evaluation system

Aldoxime Dehydratase Mutants as Improved Biocatalysts for a Sustainable Synthesis of Biorenewables-Based 2-Furonitrile

Choi J-E, Shinoda S, Asano Y, Gröger H. Aldoxime Dehydratase Mutants as Improved Biocatalysts for a Sustainable Synthesis of Biorenewables-Based 2-Furonitrile. Catalysts. 2020;10(4): 362.2-Furonitrile is an interesting nitrile product for the chemical industry due to its use as intermediate in the field of fine chemicals and pharmaceuticals or as a potential sweetener, as well as due to its access from biorenewables. As an alternative to current processes based on, e.g., the ammoxidation of furfural with ammonia as a gas phase reaction running at > 400 °C, we recently reported an enzymatic dehydration of 2-furfuryl aldoxime being obtained easily from furfural and hydroxylamine. However, improving the catalytic properties of the aldoxime dehydratase biocatalyst from Rhodococcus sp. YH3-3 (OxdYH3-3) in terms of activity and stability remained a challenge. In this contribution, the successful development of aldoxime dehydratase OxdYH3-3 mutants that were generated by directed evolution and its enhanced activity toward 2-furfuryl aldoxime is reported. The mutant OxdYH3-3 N266S showed an improved activity of up to six times higher than the wild type when utilizing a substrate concentration of 50–100 mM of 2-furfuryl aldoxime

Liquid biopsy for early detection and therapeutic monitoring of hepatocellular carcinoma

Advances in our knowledge of the molecular characteristics of hepatocellular carcinoma (HCC) have enabled significant progress in the detection and therapeutic prediction of HCC. As a non-invasive alternative to tissue biopsy, liquid biopsy examines circulating cellular components such as exosomes, nucleic acids, and cell-free DNA found in body fluids (e.g., urine, saliva, ascites, and pleural effusions) and provides information about tumor characteristics. Technical advances in liquid biopsy have led to the increasing adoption of diagnostic and monitoring applications for HCC. This review summarizes the various analytes, ongoing clinical trials, and case studies of United States Food and Drug Administrationapproved in vitro diagnostic applications for liquid biopsy, and provides insight into its implementation in managing HCC

Effects of moxibustion for constipation treatment: a systematic review of randomized controlled trials

Several studies reported that moxibustion was effective in treating constipation. This systematic review assesses the clinical evidence for or against moxibustion for treating constipation. Twelve databases were searched from their inception to March 2010. Only randomized clinical trials (RCTs) were included if they compared moxibustion with placebo, sham treatment, drug therapy or no treatment. The methodological quality of these RCTs was assessed with the Cochrane risk of bias analysis. All three RCTs included in the study had a high risk of bias. Two included studies found favorable effects of moxibustion. The third RCT showed significant effects in the moxibustion group. Given that the methodological quality of all RCTs was poor, the results from the present review are insufficient to suggest that moxibustion is an effective treatment for constipation. More rigorous studies are warranted