scholarly journals Financial Fear Index in the Digital Financial Assets Market

2021 ◽  
Vol 25 (4) ◽  
pp. 136-151
Author(s):  
A. О. Ovcharov ◽  
V. A. Matveev
Keyword(s):  
Option Price ◽  
Weighted Average ◽  
Financial Instability ◽  
Financial Assets ◽  
Index Model ◽  
Time Estimates ◽  
Volatility Index ◽  
Price Risks ◽  
Fear Index ◽  
Using Data

The relevance of the research topic is due to the increasing role of non-traditional financial instruments that contribute to financial instability. Therefore, various indicators are required to reflect the situation in the digital financial assets market, the volatility quotes, and the level of investor confidence. The aim of the study is to develop and test on empirical data a generalized indicator of financial instability (financial fear index) in the digital financial assets market. The novelty of the research lies in the adaptation of the classic model of building the volatility index to the cryptocurrency market.The authors use statistical methods for collecting and processing data, analyzing time series, weighing, designing economic indicators. The paper summarizes the results of modern research on the correlation between digitalization and financial instability. The authors conclude that at certain short periods of 2020 the ruble-dollar volatility was comparable or even higher than the ruble-bitcoin one. In addition, there is much less fear and uncertainty in the cryptocurrency market today than there was at the end of 2018. The main result of the study is the financial fear index model based on the method of calculating the weighted average option price of the underlying asset and hedging of price risks. The model has been tested using data on the bid and ask prices of cryptocurrencies at a specific point in time. Estimates have been obtained indicating the growing instability in the digital financial asset market. The authors offer recommendations regarding the index threshold values, which indicate the level of investors’ fear.

Impact of oil volatility shocks on global emerging market stock returns

2017 ◽  
Vol 13 (5) ◽  
pp. 578-591 ◽  
Author(s):  
Probal Dutta ◽  
Md Hasib Noor ◽  
Anupam Dutta
Keyword(s):  
Stock Returns ◽  
Emerging Market ◽  
Equity Returns ◽  
Oil Price ◽  
Financial Assets ◽  
Stock Market Returns ◽  
Content Type ◽  
Volatility Index ◽  
Jump Model ◽  
Oil Price Risk

Purpose The purpose of this paper is to investigate whether the crude oil volatility index (OVX) plays any key role in explaining the trend in emerging market stock returns from a global standpoint. Design/methodology/approach At the empirical stage, different forms of the GARCH-jump model have been estimated. Findings The findings confirm the effects of OVX on equity returns. In addition, the results document that there exist time-varying jumps in the stock market returns. Besides, the impacts of OVX shocks appear to be symmetric. The analysis further shows that the magnitude of OVX impact is marginally bigger than that of the conventional oil price shocks. Originality/value Since various financial assets are traded on the basis of oil and equity markets, investors, for instance, could use the findings of this study for taking proper investment decisions and gaining better portfolio diversification benefits. Additionally, policymakers could utilize the results to develop effective measures and strategies in order to minimize the oil price risk.

scholarly journals Optimal ash particle refractive index model for simulating the brightness temperature spectrum of volcanic ash clouds from satellite infrared sounder measurements

2021 ◽  
Author(s):  
Hiroshi Ishimoto ◽  
Masahiro Hayashi ◽  
Yuzo Mano
Keyword(s):  
Refractive Index ◽  
Brightness Temperature ◽  
Volcanic Ash ◽  
Satellite Measurements ◽  
Temperature Spectrum ◽  
Index Model ◽  
Rock Types ◽  
Volcanic Events ◽  
Atmospheric Sounding ◽  
Using Data

Abstract. Using data from the Infrared Atmospheric Sounding Interferometer (IASI) measurements of volcanic ash clouds and radiative transfer calculations, we identify the optimal refractive index model for simulating the measured brightness temperature spectrum of volcanic ash material. We assume that the optimal refractive index model has the smallest root mean square of the brightness temperature difference between measurements and simulations for channels in the wavenumber range of 750–1400 cm−1 and compare 21 refractive index models for optical properties of ash particles, including recently published models. From the results of numerical simulations for 164 pixels of IASI measurements for ash clouds from 11 volcanoes, we found that the measured brightness temperature spectrum could be well simulated using certain newly established refractive index models. In the cases of Eyjafjallajökull and Grímsvötn ash clouds, the optimal refractive index models determined through numerical simulation correspond to those deduced from the chemical composition of ash samples for the same volcanic eruption events. This finding suggests that infrared sounder measurement of volcanic ash clouds is an effective approach to estimating the optimal refractive index model. However, discrepancies between the estimated refractive index models based on satellite measurements and the associated volcanic rock types were observed for some volcanic events.

scholarly journals ANALYSIS OF MARKET VOLATILITY VIA A DYNAMICALLY PURIFIED OPTION PRICE PROCESS

2014 ◽  
Vol 09 (03) ◽  
pp. 1450006 ◽  
Author(s):  
CHUONG LUONG ◽  
NIKOLAI DOKUCHAEV
Keyword(s):  
Stock Price ◽  
Implied Volatility ◽  
Financial Time Series ◽  
Option Price ◽  
Option Prices ◽  
Price Process ◽  
Volatility Index ◽  
Quadratic Interpolation ◽  
Dynamic Estimation ◽  
The Impact

The paper studies methods of dynamic estimation of volatility for financial time series. We suggest to estimate the volatility as the implied volatility inferred from some artificial "dynamically purified" price process that in theory allows to eliminate the impact of the stock price movements. The complete elimination would be possible if the option prices were available for continuous sets of strike prices and expiration times. In practice, we have to use only finite sets of available prices. We discuss the construction of this process from the available option prices using different methods. In order to overcome the incompleteness of the available option prices, we suggests several interpolation approaches, including the first order Taylor series extrapolation and quadratic interpolation. We examine the potential of the implied volatility derived from this proposed process for forecasting of the future volatility, in comparison with the traditional implied volatility process such as the volatility index VIX.

scholarly journals On an Empirical Definition of Money for Pakistan

1988 ◽  
Vol 27 (4II) ◽  
pp. 853-859 ◽  
Author(s):  
Najam Us Saqib ◽  
Aliya H. Khan
Keyword(s):  
Demand Function ◽  
Weighted Average ◽  
Monetary Economics ◽  
Financial Assets ◽  
Direct Measure ◽  
Monetary Aggregate ◽  
Demand Deposits ◽  
Empirical Issue ◽  
Definition Of

In the realm of monetary economics, the question of the appropriate definition of money is both crucial and controversial. Various definitions of money offered by monetary economists differ widely. While narrowly defined money consists of currency and demand deposits only. other broader definitions of money include a host of other assets as well. The choice of the most appropriate monetary aggregate is an empirical issue and needs to be settled empirically. In the literature a number of methods are available for defining money empirically. To mention only two of them, Meltzer (1963) and Laidler (1966) consider that definition o f money the most appropriate which gives the most stable demand function for money while Chetty (1969), Moroney and Wilberatte (1976), Boughton (1981) and Husted and Rush (1984) infer their definition of money on the basis of the degree of substitutability between narrowly defined money and other financial assets. Although the two methods are closely linked, the latter has the advantage of providing a direct measure of the degree of substitutability between various financial assets and also allows for defining money as a sort of weighted average of these assets based on this substitutability rather than a simple-sum aggregation.

scholarly journals Unifying diagnostic criteria for gestational diabetes mellitus

2021 ◽  
Author(s):  
Suhail A Doi ◽  
Mohammed Bashir ◽  
Michael T Sheehan ◽  
Adedayo A Onitilo ◽  
Tawanda Chivese ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
High Risk ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Cape Town ◽  
Weighted Average ◽  
Tolerance Test ◽  
Large For Gestational Age ◽  
Observational Study Design ◽  
Using Data

Abstract OBJECTIVE Disagreement about the appropriate criteria for the diagnosis of gestational diabetes mellitus (GDM) persists. This study addresses the problem by examining an alternative approach which combines information from all time-points on the glucose tolerance test (GTT) into a single index and expands the GDM spectrum beyond the current binary approach into four categories using data from three geographically and ethnically distinct populations. DESIGN Retrospective observational study design SETTING Data from Wisconsin, USA (723 women) was used in derivation of the criterion and data from Doha, Qatar (1284 women) and Cape Town, South Africa (220 women) for validation. PARTICIPANTS Pregnant women without pre-existing diabetes with a GTT done between 23 and 30 weeks gestation MAIN OUTCOME MEASURE A novel index was derived from the GTT termed the weighted average glucose (wAG). This was categorized into four pre-defined groups (henceforth National Priorities Research Program (NPRP) criterion); i) normal gestational glycemia (NGG), ii) impaired gestational glycemia (IGG), iii) GDM and iv) high risk GDM (hGDM). RESULTS In the Doha cohort, compared to the NGG group, the odds of large for gestational age babies increased 1.33 fold (P=0.432), 2.86 fold (P<0.001) and 3.35 fold (P<0.001) in the IGG, GDM and hGDM groups respectively. The odds of pregnancy induced hypertension increased 2.10 fold (P=0.024) in GDM & hGDM groups compared to the IGG and NGG groups. In the Cape Town cohort, a third of women in the GDM group and three-quarters in the hGDM group progressed to T2DM at 5 years. CONCLUSIONS The NPRP categorization identifies four distinct risk clusters of glycemia in pregnancy which may aid better decision making in routine management, avoid potential over-diagnosis of women at lower risk of complications and assist with diabetes prevention in women at high-risk after an index pregnancy with GDM.

The Varying Effects of Incarceration, Conviction, and Arrest on Wealth Outcomes among Young Adults

2019 ◽  
Vol 67 (4) ◽  
pp. 698-718 ◽  
Author(s):  
Michelle Maroto ◽  
Bryan L Sykes
Keyword(s):  
Young Adults ◽  
Criminal Justice ◽  
Criminal Justice System ◽  
Transition To Adulthood ◽  
Justice System ◽  
Financial Assets ◽  
Net Worth ◽  
Important Time ◽  
Using Data ◽  
Building Life Cycle

Abstract Previous research indicates that incarceration leads to declines in rates of homeownership and net worth, especially among baby boomers, but questions remain as to how other types of criminal justice system contact affect wealth outcomes during the transition to adulthood. Using data from the 1997 National Longitudinal Survey of Youth, we investigate how arrests, convictions, and incarceration influence net worth, financial assets, and debt among young adults. We find that most contact with the criminal justice system limited the ability of young adults to accumulate wealth between the ages of 25 and 30, an especially important time for building life-cycle wealth. Arrests were associated with asset and debt declines of 52–53 percent, and incarceration led to net worth and asset declines of 34 and 76 percent, respectively. These direct effects were also bolstered by the indirect effects of these variables through their relationship with marriage and earnings, especially in the case of incarceration. This study draws attention to how criminal justice system contact affects early adult wealth, thereby setting the stage to influence a host of life course dynamics for individuals and their families.

American Basket Option Pricing Formulas in Uncertain Environment

2021 ◽  
pp. 2150011
Author(s):  
Rong Gao ◽  
Xiaofang Yin
Keyword(s):  
Option Pricing ◽  
Option Price ◽  
Weighted Average ◽  
Call Option ◽  
Strike Price ◽  
Basket Option ◽  
Put Option ◽  
The Right ◽  
The Relationship ◽  
Financial Environment

American basket option is a contract containing multiple underlying assets, and its payoff is correlated with average prices or weighted average prices of these assets on or before the expiration date. The type of option entitles a holder the right to trade at the strike price within a specified date, and this right can be waived. Therefore, there is a certain price to be paid for acquiring this right, which produces the problem of option pricing. A lot of literature shows blackthat basket option price is usually cheaper than option portfolios on individual underlying assets. Based on this advantage, basket option blackbecomes popular among investors. Consequently, this paper predominantly explores four types of American basket option pricing in uncertain financial environment. Specifically they are American arithmetic basket call option, American arithmetic basket put option, American geometric basket call option and American geometric basket put option. Assuming that these stocks prices follow corresponding uncertain differential equations, we derive corresponding option pricing formulas. Some numerical examples are taken to illustrate the feasibility of pricing formulas. Simultaneously, this paper discusses the relationship between option price and some parameters.

scholarly journals The multiplex nature of global financial contagions

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
R. Maria del Rio-Chanona ◽  
Yevgeniya Korniyenko ◽  
Manasa Patnam ◽  
Mason A. Porter
Keyword(s):  
Financial Distress ◽  
Financial Stability ◽  
Global Financial Crisis ◽  
Threshold Model ◽  
Financial Assets ◽  
Financial Network ◽  
Node Importance ◽  
Multiplex Network ◽  
Cross Country ◽  
Using Data

Abstract As illustrated by the 2008 global financial crisis, the financial distress of one country can trigger financial distress in other countries. We examine the problem of identifying such “systemically important” countries (i.e., countries whose financial distress can trigger further distress), which is important for assessing global financial stability. Using data on bilateral financial positions that are split by asset type, we build a multiplex global financial network in which nodes represent countries, edges encode cross-country financial assets of various types, and layers represent asset types. We examine the temporal evolution of a measure of node importance known as MultiRank centrality, and we find that several major European countries decrease in rank and that several major Asian countries increase in rank since 2008. We then develop a multiplex threshold model of financial contagions in which a shock can propagate either within a layer or between layers. We find that the number of systemically important countries can be twice as large when we take into account the heterogeneity of financial exposures (i.e., when using a multiplex network) than in a contagion on an associated aggregate global financial network (i.e., on a monolayer network), as is often examined in other studies. We also study the extent to which buffers can reduce the propagation of financial distress. Our analysis suggests that accounting for both intralayer and interlayer propagation of contagions in a multiplex structure of financial assets is important for understanding interconnected financial systems of countries.

scholarly journals Dynamic Responses of Standard and Poor’s Regional Bank Index to the U.S. Fear Index, VIX

2021 ◽  
Vol 14 (3) ◽  
pp. 114
Author(s):  
Bahram Adrangi ◽  
Arjun Chatrath ◽  
Madhuparna Kolay ◽  
Kambiz Raffiee
Keyword(s):  
Capacity Utilization ◽  
Dynamic Responses ◽  
Volatility Index ◽  
Daily Data ◽  
Standard And Poor's ◽  
Regional Bank ◽  
Fear Index ◽  
Trade Volatility ◽  
Chicago Board Of Trade ◽  
The U.S

This study examines the reaction of the Standard and Poor’s Regional Bank Index (SPRB) to the U.S. equity market fear index (i.e., the Chicago Board of Trade Volatility Index [VIX]). The VIX is designed to perform as a leading indicator of the volatility in equity markets. However, practitioners observe many periods of divergence between the VIX and S&P 500. Our paper examines the daily data for the period of 2009 through 2019. We show that once the effects of consumer confidence and capacity utilization are accounted for, there is a negative association between the VIX and regional bank performance.

scholarly journals A Case for using a Real Asset Transaction Approach for Estimating the Cost of Capital from Rural Telephone Company Data

2018 ◽  
pp. 5-16
Author(s):  
Victor Glass ◽  
Keyword(s):  
Risk Premium ◽  
Cost Of Capital ◽  
Traditional Approach ◽  
Weighted Average ◽  
Cash Flows ◽  
Financial Assets ◽  
Publicly Traded ◽  
Local Exchange ◽  
Telephone Companies ◽  
The Cost

This paper develops a real asset transaction approach for estimating the cost of capital for rural telephone companies whose financial assets are not publicly traded. The transaction approach uses the actual purchase prices of rural local exchange carriers (RLECs)’ properties and cash flows for estimating the rate of return required by buyers and sellers of RLEC properties. The transaction approach produces higher cost of capital estimates than a traditional approach using a weighted average of debt and equity costs of proxy companies traded on organized exchanges. The estimated difference is in line with the risk premium estimated for small non-traded companies estimated by Duff and Phelps Ibbotson.

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