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Article
Publication date: 2 October 2017

Dilip Kumar and Srinivasan Maheswaran

This paper aims to propose a framework based on the unbiased extreme value volatility estimator (namely, the AddRS estimator) to compute and predict the long position and…

Abstract

Purpose

This paper aims to propose a framework based on the unbiased extreme value volatility estimator (namely, the AddRS estimator) to compute and predict the long position and the short position value-at-risk (VaR) and stressed expected shortfall (ES). The precise prediction of VaR and ES measures has important implications toward financial institutions, fund managers, portfolio managers, regulators and business practitioners.

Design/methodology/approach

The proposed framework is based on the Giot and Laurent (2004) approach and incorporates characteristics like long memory, fat tails and skewness. The authors evaluate its VaR and ES forecasting performance using various backtesting approaches for both long and short positions on four global indices (S&P 500, CAC 40, Indice BOVESPA [IBOVESPA] and S&P CNX Nifty) and compare the results with that of various alternative models.

Findings

The findings indicate that the proposed framework outperforms the alternative models in predicting the long and the short position VaR and stressed ES. The findings also indicate that the VaR forecasts based on the proposed framework provide the least total loss for various long and short position VaR, and this supports the superior properties of the proposed framework in forecasting VaR more accurately.

Originality/value

The study contributes by providing a framework to predict more accurate VaR and stressed ES measures based on the unbiased extreme value volatility estimator.

Details

Studies in Economics and Finance, vol. 34 no. 4
Type: Research Article
ISSN: 1086-7376

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Article
Publication date: 11 December 2017

Xiaoguang Wang, Ningyuan Song, Lu Zhang and Yanyu Jiang

The purpose of this paper is to understand the subjects contained in the Dunhuang mural images as well as their relation structures.

Abstract

Purpose

The purpose of this paper is to understand the subjects contained in the Dunhuang mural images as well as their relation structures.

Design/methodology/approach

This paper performed content analysis based on Panofsky’s theory and 237 research papers related to the Dunhuang mural images. UNICET software was also used to study the correlation structures of subject network.

Findings

The results show that the three levels of subject have all captured the attention of Dunhuang mural researchers, the iconology occupy the critical position in the whole image study, and the correlation between iconography and iconology was strong. Further analysis reveals that cultural development, production, and power and domination have high centralities in the subject network.

Research limitations/implications

The research samples come from three major Chinese journal databases. However, there are still many authoritative monographs and foreign publications about the Dunhuang murals which are not included in this study.

Originality/value

The results uncover the subject hierarchies and structures contained in the Dunhuang murals from the angle of image scholarship which express scholars’ intention and contribute to the deep semantic annotation on digital Dunhuang mural images.

Details

Journal of Documentation, vol. 74 no. 2
Type: Research Article
ISSN: 0022-0418

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Article
Publication date: 13 October 2021

Knut Lehre Seip and Dan Zhang

This study aims to address the fundamental question on how the major players in the economy dynamically interact with each other: among the central bank, the investors in…

Abstract

Purpose

This study aims to address the fundamental question on how the major players in the economy dynamically interact with each other: among the central bank, the investors in the bond market and the firms and consumers that contribute to the economic growth, who gets information from whom, when and why?

Design/methodology/approach

To answer “who follows whom,” the authors apply a novel technique to examine the lead–lag relations between three time series, the federal funds rate, the treasury yield curve and the gross domestic product (GDP). To investigate “when and why,” the authors combine the lead–lag relations with principal component analysis to cluster economic states that are similar with respect to the eight macroeconomic variables.

Findings

The authors show that during the period 1977–2019, the bond market potentially obtained information from the federal funds rate (61% of the time) and less often (34% of time) from the changes in the GDP. Meanwhile, the funds rate decision by the Federal Reserve seems to lead the economic growth about 63% of the time. The analysis also suggests that the bond market obtained information directly from GDP when unemployment and inflation was high. In addition, the authors find that the federal funds rate was leading the GDP when the GDP deviated from the target value, consistent with the Federal Reserve’s policy of boosting and damping the economy when the GDP growth is low or high, respectively.

Originality/value

This study provides insights into the fundamental questions that have important implications for empirical work on the monetary policy, financial stability and economic activities.

Details

Journal of Financial Economic Policy, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1757-6385

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Article
Publication date: 5 May 2021

Avinash Jawade

This study aims to analyze the influence of firm characteristics in dividend payout in a concentrated ownership setting.

Abstract

Purpose

This study aims to analyze the influence of firm characteristics in dividend payout in a concentrated ownership setting.

Design/methodology/approach

This study is probably the first to use the lasso technique for model selection and error prediction in the study of dividend payout in India. The lasso method comprises subsampling the available data set and performing reiterative regressions on those samples to generate the model with the best fit. This study incorporates four different ways of performing lasso treatment to get the best fit among them.

Findings

This study analyzes the influence of firm characteristics on dividend payout in the Indian context and asserts that firms with growth potential and earnings volatility do not hesitate to cut dividends. This study does not find evidence for signaling, agency cost and life cycle theories in a concentrated ownership setting. Earnings is the single most important factor to have a positive influence on dividend, while excessively leveraged firms are restrictive of dividend payout. Taxation has a prominent role in altering the way firms pay dividend.

Research limitations/implications

The recent changes in buyback taxation offer another opportunity to test the reactive behavior of firms. Also, given the disregard for traditional motivations, further research needs to be done to determine if dividend adjustments (on the lower side) help enhance firm value or not.

Practical implications

This study may help investors view dividends in a proper perspective. Firms give importance to investments over dividends and thus investors need not dwell on dividend changes if firms fulfill their growth potential.

Social implications

It lends perspective to investors about dividend changes and its importance.

Originality/value

The methodology used for analysis is absolutely original in the literature pertaining to dividend policy in the Indian context. The literature is abundant with theories advocating or opposing the eminence of dividend payout; however, this study takes a holistic view of all influential dividend determinants in literature to understand dividend payout.

Details

Journal of Indian Business Research, vol. 13 no. 2
Type: Research Article
ISSN: 1755-4195

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Book part
Publication date: 23 May 2019

Bruno S. Sergi, Elena G. Popkova, Aleksei V. Bogoviz and Yulia V. Ragulina

The purpose of the article is to study the recent tendencies of growth of Russia’s agro-industrial complex (AIC), determine the optimal scenario of its development, and…

Abstract

The purpose of the article is to study the recent tendencies of growth of Russia’s agro-industrial complex (AIC), determine the optimal scenario of its development, and develop recommendations in the sphere of state regulation for its practical implementation. While there are tendencies of growing production and increase in Russia’s export, against this background, there is a tendency of quicker increase of import of food – if it continues, positive balance of foreign trade of food products in 2018 will turn into negative balance in 2020–2024. Though efficiency of crop farming is peculiar for a tendency of quick growth, efficiency of animal breeding is stable, which does not allow overcoming the growing deficit of food in Russia, which grows under the influence of the tendency of wear of fixed funds and slow implementation of new fixed funds due to insufficient financing. Scenarios of mid-term (i.e., until 2024) growth of Russia’s AIC are compiled, of which the most optimal is scenario that requires technological advancements, due to which increase in the value of index of food security up to 85.00 points (27%) will be achieved and the set goals of growth and development of Russia’s AIC will be reached. For a successful optimal scenario of the growth of Russia’s AIC, we offer recommendations in the sphere of state regulation of its digital modernization: adoption of the national strategy of transition to AIC 4.0 within the program “Digital economy of the RF,” development of import substitution in the AIC with emphasis on B2B markets, preparation of the technological platform for transition to AIC 4.0, and sufficient financing for digital modernization of the AIC.

Details

Modeling Economic Growth in Contemporary Russia
Type: Book
ISBN: 978-1-78973-265-8

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Book part
Publication date: 4 November 2021

Chaido Dritsaki and Melina Dritsaki

The term “economic growth” refers to the increase of real gross national product or gross domestic product or per capita income. National income or else national product…

Abstract

The term “economic growth” refers to the increase of real gross national product or gross domestic product or per capita income. National income or else national product is usually expressed as a measure of total added value of a domestic economy known as gross domestic product (GDP). Generally, GDP measures the value of economic activity within a country during a specific time period. The current study aims to find the most suitable model that adjusts on a time-series data set using Box-Jenkins methodology and to examine the forecasting ability of this model. The analysis used quarterly data for Greece from the first quarter of 1995 until the third quarter of 2019. Nonlinear maximum likelihood estimation (maximum likelihood-ML) was applied to estimate the model using the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm while covariance matrix was estimated using the negative of the matrix of log-likelihood second derivatives (Hessian-observed). Forecasting of the time series was achieved both with dynamic as well as static procedures using all forecasting criteria.

Details

Modeling Economic Growth in Contemporary Greece
Type: Book
ISBN: 978-1-80071-123-5

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Book part
Publication date: 8 November 2021

Taniya Ghosh and Sakshi Agarwal

Significant evidence in the literature points to money demand instability and therefore inaccurate forecasting. In view of this issue, this chapter seeks to use a method…

Abstract

Significant evidence in the literature points to money demand instability and therefore inaccurate forecasting. In view of this issue, this chapter seeks to use a method, innovative for money demand literature, that is, the machine learning model to predict money demand. Specifically, this chapter uses Random Forest Regression to predict money demand using monthly data in the Indian context over the period April-1996 to December-2018 using the variables usually used in literature. The chapter finds that in money demand prediction, the Random Forest Regression performs fairly well. The results are also compared to traditional models and it is found that the Random Forest Regression model has the potential to enhance the prediction of money demand over what traditional models predicts.

Details

Environmental, Social, and Governance Perspectives on Economic Development in Asia
Type: Book
ISBN: 978-1-80117-594-4

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Book part
Publication date: 8 November 2019

Anna Koroleva and Alina Dutina

The purpose of this chapter is to describe and analyze the economic advantage of the geographical location of the Republic of Belarus. The current state of the Belarusian…

Abstract

The purpose of this chapter is to describe and analyze the economic advantage of the geographical location of the Republic of Belarus. The current state of the Belarusian logistics system is analyzed in detail in the chapter. Thus effects of each direction of transportations are analyzed and also approaches to assessment of their cost efficiency are formulated. The factors influencing the export of transport services as well as the development of trends in the transport sector of Belarus are defined. The main directions and ways of improvement of logistics in the Republic of Belarus are described.

Details

Modeling Economic Growth in Contemporary Belarus
Type: Book
ISBN: 978-1-83867-695-7

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Book part
Publication date: 21 October 2019

Moritz Kath and Natalia Ribberink

The promotion of low tariffs and free trade has been the underlying driver of global economic growth. The recent political developments in the United States and Great…

Abstract

The promotion of low tariffs and free trade has been the underlying driver of global economic growth. The recent political developments in the United States and Great Britain calls into question, whether free trade will be supported by the governments of the industrialized world in the future. Shortly after being inaugurated in 2017, the President of the United States has repeatedly announced his plans to impose punitive tariffs on the import of foreign products in order to protect the country’s domestic economy. Besides a controversial border adjustment tax, he has frequently brought up the possibility of imposing a 35% tariff on automobile imports. The chapter aims to analyze the effects of such a tariff on trade in the automotive sector between the United States and Germany as well as on German automobile manufacturers. It takes a quantitative approach to draw a conclusion about the relationship between import tariffs on automobiles and passenger vehicle imports from Germany to the United States utilizing a fixed effects regression model based on panel data. The model finds a significant negative correlation between the examined variables, but even in a worst case scenario, German manufacturers are resilient to the predicted revenue losses caused by a tariff increase.

Details

International Business in a VUCA World: The Changing Role of States and Firms
Type: Book
ISBN: 978-1-83867-256-0

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Book part
Publication date: 19 March 2018

Jordan French

The most popular method for calculating asset prices is the Capital Asset Pricing Model (CAPM). What is the appropriate amount of years to use in the estimation and which…

Abstract

The most popular method for calculating asset prices is the Capital Asset Pricing Model (CAPM). What is the appropriate amount of years to use in the estimation and which variation of the capital asset pricing beta provides the best results? This research looks at the out-of-sample forecasting capabilities of three popular CAPM ex-post constant beta models from 2005 to 2014. A total of 11 portfolios, five from developed and six from developing markets, are used to test the amount of input years that will reduce the mispricing in both types of markets. It is found that the best beta model to use varies between developed and developing markets. Additionally, in developing markets, a shortened span of historical years improves the pricing, contrary to popular studies that use 5 to 10 years of historical data. There are many different CAPM studies implementing various betas, using different data input lengths and run in various countries. This study empirically tests the best practices for those interested in successfully using the CAPM for their basic needs, finding that overall the simple ex-post constant beta is mispriced by 0.2 (developing) to 0.3 percent (developed). It is better to use short three-year estimation windows with the market beta in developing economies and longer nine-year estimation windows with the adjusted beta in developed economies.

Details

Global Tensions in Financial Markets
Type: Book
ISBN: 978-1-78714-839-0

Keywords

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