Range-Based Estimation of Stochastic Volatility Models

We propose using the price range in the estimation of stochastic volatility models. We show theoretically, numerically, and empirically that range-based volatility proxies are not only highly efficient, but also approximately Gaussian and robust to microstructure noise. Hence range-based Gaussian quasi-maximum likelihood estimation produces highly efficient estimates of stochastic volatility models and extractions of latent volatility. We use our method to examine the dynamics of daily exchange rate volatility and find the evidence points strongly toward two-factor models with one highly persistent factor and one quickly mean-reverting factor.     

A Hybrid Fuzzy-Probabilistic Bargaining Approach for Multi-objective Optimization of Contamination Warning Sensors in Water Distribution Systems

Group Decision and Negotiation - Water Distribution System (WDS) are strategic infrastructures in all countries. In recent decades, several optimization-based frameworks have been developed to...     

Merton Model and Capital Measurement in Commercial Banks: A Case Study of Selected Emerging Countries in Southeast Asia

Following the implementation of Basel III criteria concerning the supervision of banks capital, this paper attempts to examine the competence of Merton-type probability of default as an indicator for measuring optimal capital in commercial banks of five Southeast Asian emerging economies. The estimated default risk changes are consistent with the changes in market value of banks’ asset in countries studied. Using a forward-looking approach, the banks required capital has been measured to reach a hypothetical level of probability of default as an accepted level by policy makers. Empirical results show that the banks had to increase their current capital in order to reduce the risk of bankruptcy in crisis times. The findings of this study refer evidently to the efficiency of Merton-type default risk to estimate the adequate capital and to use in micro and macro-prudential studies or stress tests on commercial banks.     

Vessel and voyage determinants of tanker freight rates and contract times

The behavior of shipping freight (charter) rates and the timing of shipping contracts affect the transportation costs of charterers and the operating cash flows of shipowners. Although the literature has established macroeconomic determinants of shipping freight rates, there has been no systematic investigation of microeconomic determinants of freight rates and the delivery time of chartered ships (the laycan period) in the tanker market. Therefore, the aim of this paper is to investigate the importance of vessel and contract specific factors in the determination of tanker freight rates and laycan periods in shipping contracts. Individual tanker shipping contracts from January 2006 to March 2009 are used to estimate freight rates and laycan periods using a system of simultaneous equations. The estimation results suggest that the duration of the laycan period is an important determinant of the shipping freight rate and vice versa. Other determinants of freight rates include the vessel's hull type, fixture deadweight utilization ratio, vessel age, and voyage routes. Determinants of the laycan period include the former determinants as well as the Baltic Dirty Tanker Index and its volatility.     

A Markov regime switching approach for hedging stock indices

In this paper we describe a new approach for determining time‐varying minimum variance hedge ratio in stock index futures markets by using Markov Regime Switching (MRS) models. The rationale behind the use of these models stems from the fact that the dynamic relationship between spot and futures returns may be characterized by regime shifts, which, in turn, suggests that by allowing the hedge ratio to be dependent upon the “state of the market,” one may obtain more efficient hedge ratios and hence, superior hedging performance compared to other methods in the literature. The performance of the MRS hedge ratios is compared to that of alternative models such as GARCH, Error Correction and OLS in the FTSE 100 and S&P 500 markets. In and out‐of‐sample tests indicate that MRS hedge ratios outperform the other models in reducing portfolio risk in the FTSE 100 market. In the S&P 500 market the MRS model outperforms the other hedging strategies only within sample. Overall, the results indicate that by using MRS models market agents may be able to increase the performance of their hedges, measured in terms of variance reduction and increase in their utility. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:649–674, 2004     

Identifying contextual effective factors on total fertility rate decline in Iran: a qualitative framework-based study

This study was conducted to explain the contextual factors associated with total fertility rate (TFR) decline to help policymakers. A qualitative approach and Leichter contextual analysis framework were applied to conduct this study. The participants were selected using purposive sampling method, and also the interviews continued until data saturation was reached. Individuals with knowledge and perspectives on population policies were included in the study to improve the research credibility. The data validity was achieved by applying the maximum variety in selecting the sample. The results were classified into four groups, including situational, structural, cultural, and environmental factors. Situational factors included political sanctions, drought, and road accidents. Structural factors involved government policies, the absence of monitoring, paying no attention to the required conditions, housing status, employment status, economic status, and other issues. Cultural factors were classified into the seven categories, including divorce, socio-economic development, women's employment, marriage age, urbanization, and other issues and factors included international treaties, and the western influence. Policymakers and administrators in the field of demographic policies can make more accurate strategies to increase TFR by recognizing the causes that reduce fertility with the help of providing the possibility to understand better the factors affecting the TFR decline.

     

Closing information asymmetries: A scale agnostic approach for exploring equity implications of broadband provision

A persistent challenge for telecommunications policy is the determination of broadband provision footprints in both space and time. In the United States, Form 477 data from the Federal Communications Commission (FCC) provide a valuable snapshot of broadband provision at the block level, but there are often inconsistencies with the underlying data. These inconsistencies include overly-optimistic self-reports from providers, requirements to report broadband provision within inflexible census administrative units, and a modest temporal reporting schedule (biannual) with a significant, one year temporal lag. These uncertainties are often compounded by telecommunications providers refusing to disclose any information on service footprints, geographic expansion plans or the characteristics of populations served by broadband. This type of obfuscation drastically limits the ability of policy analysts to evaluate outcomes (both positive and negative) associated with service provision and the digital divide, more generally. With the recent entry of Google Fiber to several metropolitan markets in the United States, many of the broadband reporting and evaluation challenges have re-emerged. The purpose of this paper is to leverage basic data mining techniques, a scale agnostic geographic framework and exploratory spatial data analysis (ESDA), to uncover the geographic intricacies of Google Fiber (Fiber) service for both Provo, Utah and Austin, Texas and compare them to Form 477 reports. In addition, we use basic statistical approaches to explore issues of broadband access and equity, accounting for the differences in socio-economic and demographic status of the populace served/not served for both cities, as well as basic pricing within and between communities.     

Dynamics of credit spread moments of European corporate bond indexes

Traditional quantitative credit risk models assume that changes in credit spreads are normally distributed but empirical evidence shows that they are likely to be skewed, fat-tailed, and change behaviour over time. Not taking into account such characteristics can compromise calculation of loss probabilities, pricing of credit derivatives, and profitability of trading strategies. Therefore, the aim of this study is to investigate the dynamics of higher moments of changes in credit spreads of European corporate bond indexes using extensions of GARCH type models that allow for time-varying volatility, skewness and kurtosis of changes in credit spreads as well as a regime-switching GARCH model which allows for regime shifts in the volatility of changes in credit spreads. Performance evaluation methods are used to assess which model captures the dynamics of observed distribution of the changes in credit spreads, produces superior volatility forecasts and Value-at-Risk estimates, and yields profitable trading strategies. The results presented can have significant implications for risk management, trading activities, and pricing of credit derivatives.     

Women and culture of poverty (a qualitative study of the culture of poverty among the Iranian caretaker women)

This study examines the culture of poverty among women who are caretakers of their families and supported by the Behzisti Organization (an Iranian governmental Welfare Institution) of Sari Township. It employs Oscar Lewis’s theory of the culture of poverty to reveal the nature and dimensions of poverty as experienced by these women. Employing in-depth, semi-structured interviews, we spoke with 28 women and Behzisti assistants. These interview data were analyzed through thematic analysis. Resultant themes indicated general elements of poverty such as lack of literacy and the accommodation issue, but also indicated other outcomes of women in poverty, including irresponsibility, dis-participation, secrecy, gender bias, sexual vulnerability, forced remarriage, low- risking and beggary. For these women, poverty has multiple dimensions and a continuing trajectory.     

A Markov regime switching approach for hedging energy commodities

This paper estimates constant and dynamic hedge ratios in the New York Mercantile Exchange oil futures markets and examines their hedging performance. We also introduce a Markov regime switching vector error correction model with GARCH error structure. This specification links the concept of disequilibrium with that of uncertainty (as measured by the conditional second moments) across high and low volatility regimes. Overall, in and out-of-sample tests indicate that state dependent hedge ratios are able to provide significant reduction in portfolio risk.