Can short-term foreign exchange volatility be predicted by the Global Hazard Index?

This paper examines the predictive properties of risk indicators for the foreign exchange markets. In particular it considers the predictive properties of historical volatilities and implied volatilities for movements in various bilateral exchange rates and compares them with the analogous properties of a composite indicator of risk, the Global Hazard Index (GHI). The GHI is a function of the implied volatility derived from currency options on the three major exchange rates, i.e. the euro-US dollar, the US dollar-yen and the euro-yen. For the empirical analysis this paper employs the concept of kernel volatility, which, loosely speaking, expresses the volatility of one variable conditional on the level of another. Simple regressions show that the levels of all the indicators on a particular day have a strong link to the variance of the nominal bilateral exchange rate on the next day. A strong overall influence is displayed by the GHI, especially for the currencies of small open economies. JEL Classification: F01, F31

A global hazard index for the world foreign exchange markets

This paper proposes a forward-looking indicator of risk in the foreign exchange markets calculated from the implied volatilities of currency options according to the Garman-Kohlhagen model. We discuss the properties of such indicator and stress that it is related to a notion of risk that does not coincide with that of Gaussian risk underlying most mainstream models. We postulate that it is associated with a broader definition of risk, which we call hazard in order to avoid confusion. The properties of the Global Hazard Indicator (GHI) are assessed against the background of the market turbulence in 1998. This period has been characterized by abnormal fluctuations in the exchange rate markets spurred by a sequence of shocks in some emerging economies and in South East Asia, which have raised fear of contagion in developed countries

Can short-term foreign exchange volatility be predicted by the Global Hazard Index?

This paper examines the predictive properties of risk indicators for the foreign exchange markets. In particular it considers the predictive properties of historical volatilities and implied volatilities for movements in various bilateral exchange rates and compares them with the analogous properties of a composite indicator of risk, the Global Hazard Index (GHI). The GHI is a function of the implied volatility derived from currency options on the three major exchange rates, i.e. the euro-US dollar, the US dollar-yen and the euro-yen. For the empirical analysis this paper employs the concept of kernel volatility, which, loosely speaking, expresses the volatility of one variable conditional on the level of another. Simple regressions show that the levels of all the indicators on a particular day have a strong link to the variance of the nominal bilateral exchange rate on the next day. A strong overall influence is displayed by the GHI, especially for the currencies of small open economies

A global hazard index for the world foreign exchange markets

This paper proposes a forward-looking indicator of risk in the foreign exchange markets calculated from the implied volatilities of currency options according to the Garman-Kohlhagen model. We discuss the properties of such indicator and stress that it is related to a notion of risk that does not coincide with that of Gaussian risk underlying most mainstream models. We postulate that it is associated with a broader definition of risk, which we call hazard in order to avoid confusion. The properties of the Global Hazard Indicator (GHI) are assessed against the background of the market turbulence in 1998. This period has been characterized by abnormal fluctuations in the exchange rate markets spurred by a sequence of shocks in some emerging economies and in South East Asia, which have raised fear of contagion in developed countries. JEL Classification: F01, F31world foreign exchange markets

A machine-learning based bio-psycho-social model for the prediction of non-obstructive and obstructive coronary artery disease

Background: Mechanisms of myocardial ischemia in obstructive and non-obstructive coronary artery disease (CAD), and the interplay between clinical, functional, biological and psycho-social features, are still far to be fully elucidated. Objectives: To develop a machine-learning (ML) model for the supervised prediction of obstructive versus non-obstructive CAD. Methods: From the EVA study, we analysed adults hospitalized for IHD undergoing conventional coronary angiography (CCA). Non-obstructive CAD was defined by a stenosis < 50% in one or more vessels. Baseline clinical and psycho-socio-cultural characteristics were used for computing a Rockwood and Mitnitski frailty index, and a gender score according to GENESIS-PRAXY methodology. Serum concentration of inflammatory cytokines was measured with a multiplex flow cytometry assay. Through an XGBoost classifier combined with an explainable artificial intelligence tool (SHAP), we identified the most influential features in discriminating obstructive versus non-obstructive CAD. Results: Among the overall EVA cohort (n = 509), 311 individuals (mean age 67 ± 11 years, 38% females; 67% obstructive CAD) with complete data were analysed. The ML-based model (83% accuracy and 87% precision) showed that while obstructive CAD was associated with higher frailty index, older age and a cytokine signature characterized by IL-1β, IL-12p70 and IL-33, non-obstructive CAD was associated with a higher gender score (i.e., social characteristics traditionally ascribed to women) and with a cytokine signature characterized by IL-18, IL-8, IL-23. Conclusions: Integrating clinical, biological, and psycho-social features, we have optimized a sex- and gender-unbiased model that discriminates obstructive and non-obstructive CAD. Further mechanistic studies will shed light on the biological plausibility of these associations. Clinical trial registration: NCT02737982

The Sex-Specific Detrimental Effect of Diabetes and Gender-Related Factors on Pre-admission Medication Adherence Among Patients Hospitalized for Ischemic Heart Disease: Insights From EVA Study

Background: Sex and gender-related factors have been under-investigated as relevant determinants of health outcomes across non-communicable chronic diseases. Poor medication adherence results in adverse clinical outcomes and sex differences have been reported among patients at high cardiovascular risk, such as diabetics. The effect of diabetes and gender-related factors on medication adherence among women and men at high risk for ischemic heart disease (IHD) has not yet been fully investigated.Aim: To explore the role of sex, gender-related factors, and diabetes in pre-admission medication adherence among patients hospitalized for IHD.Materials and Methods: Data were obtained from the Endocrine Vascular disease Approach (EVA) (ClinicalTrials.gov Identifier: NCT02737982), a prospective cohort of patients admitted for IHD. We selected patients with baseline information regarding the presence of diabetes, cardiovascular risk factors, and gender-related variables (i.e., gender identity, gender role, gender relations, institutionalized gender). Our primary outcome was the proportion of pre-admission medication adherence defined through a self-reported questionnaire. We performed a sex-stratified analysis of clinical and gender-related factors associated with pre-admission medication adherence.Results: Two-hundred eighty patients admitted for IHD (35% women, mean age 70), were included. Around one-fourth of the patients were low-adherent to therapy before hospitalization, regardless of sex. Low-adherent patients were more likely diabetic (40%) and employed (40%). Sex-stratified analysis showed that low-adherent men were more likely to be employed (58 vs. 33%) and not primary earners (73 vs. 54%), with more masculine traits of personality, as compared with medium-high adherent men. Interestingly, women reporting medication low-adherence were similar for clinical and gender-related factors to those with medium-high adherence, except for diabetes (42 vs. 20%, p = 0.004). In a multivariate adjusted model only employed status was associated with poor medication adherence (OR 0.55, 95%CI 0.31–0.97). However, in the sex-stratified analysis, diabetes was independently associated with medication adherence only in women (OR 0.36; 95%CI 0.13–0.96), whereas a higher masculine BSRI was the only factor associated with medication adherence in men (OR 0.59, 95%CI 0.35–0.99).Conclusion: Pre-admission medication adherence is common in patients hospitalized for IHD, regardless of sex. However, patient-related factors such as diabetes, employment, and personality traits are associated with adherence in a sex-specific manner

The price of gold and the exchange rates

Fil: Sjaastad, Larry A.. Universidad de San Andrés. Departamento de Economía; Argentina.Fil: Scacciavillani, Fabio. Universidad de San Andrés. Departamento de Economía; Argentina

Exchange Rate Movements, Inflation Expectations, and Currency Substitution in Turkey

This paper contains an empirical analysis of currency substitution in Turkey: a simple relationship between the share of foreign currency holdings in M2X on one side and movements in the exchange rate or inflation on the other is derived from a two-stage portfolio choice model. This relationship is estimated by band spectrum regression which allows to remove from the data the short-term cyclical components. The results show that the relationship between currency substitution depends mainly on long-term movements in the exchange rate, while the effect of inflation on currency substitution is not statistically significant.

Long Memory Processes and Chronic Inflation: Detecting Homogeneous Components in a Linear Rational Expectations Model

This paper is an empirical study of the links between monetary variables and inflation based on Cagan's equation and its rational expectations solution, when the forcing variable is a fractionally integrated process. As demonstrated by Hamilton and Whiteman, the existence of bubbles and other extraneous influences can be detected only by verifying the difference in the order of integration between the monetary base and the price level series. This paper shows that a test based on fractional differencing overcomes Evans' critique and that chronic inflation is essentially a monetary phenomenon caused by fiscal imbalance.

Measures of Potential Output

This paper estimates measures of potential output for Israel, with the aim of providing evidence on whether the recent growth slowdown is principally a cyclical slowdown or a structural shift toward a slower growth path after the dramatic developments associated with the years of heavy immigration. Israel poses a challenge because traditional methods of measuring potential output assume relatively stable conditions over an extended period of time. We employ five methodologies to derive estimates and find that four of the measures imply the slowdown stems largely from reduced growth of potential output rather than a cyclical slowdown.