scholarly journals PECULIARITIES OF EVALUATION OF IMBALANCES OF DEVELOPMENT OF MODERN STOCK EXCHANGE MARKETS

2021 ◽  
Author(s):  
Eleonora Tereshchenko ◽  
Darya Semenova
Keyword(s):  
Stock Markets ◽  
Financial Stress ◽  
Financial Sector ◽  
Investment Strategy ◽  
Economic Index ◽  
Stress Index ◽  
Exchange Market ◽  
Important Indicator ◽  
Economic Nature ◽  
Trigger Events

The development of the domestic exchange market is constrained by the imperfection of legislative and regulatory regulation of the activities of market participants, the suboptimal infrastructure of the market and the lack of a coherent, fully debugged mechanism for assessing financial instability. Stock market indices of financial stress are used as an important indicator of economic processes, they are the most acceptable tools for financial analysis in world practice, and also reflect fluctuations in supply and demand for securities and are used by investors to form an effective investment strategy. It is proposed to use the method for calculating a structured index of financial stress, which includes a set of factors and indicators as key indicators of the exchange market. The features of filling of each of the constituent elements of this index are disclosed. The indicator characterizing trigger events is separately highlighted, its relationship with stress testing is shown, which makes it possible to assess the vulnerability of the system to shocks of various nature. The presented methodology for calculating the financial stress index, including a set of individual and general financial indicators, will make it possible to respond in a timely and timely manner to periods of exacerbation of instability in the financial sector, identify threats and vulnerabilities. The article proposes a method for determining the general economic index, which is carried out by aggregating indicators of sectoral imbalances in indicators of general economic nature. The use of aggregation tools implies the fact that the excess reserve (stock) of liquidity in a particular sector is not able to balance or mitigate its lack to others. Of course, this is rational, because when trigger events occur, which implies the need for expectations, uncertainty about the credit quality of counterparties often increases. This means that financial markets cannot always provide liquidity flows. The main advantages of the proposed method of calculating the general economic index, which aggregates the indicators of sectoral imbalances in the indicators of general economic nature of modern stock markets should include the ability to prevent and prevent crises at all levels of management decisions. This system can and should become a common tool for maintaining the necessary sustainable economic processes. The highlighted features of determining the imbalances in the development of stock markets will allow to relevantly reflect the main periods of growing instability in the financial sector of Ukraine.

scholarly journals A Financial Stress Index for Ukraine

2017 ◽  
pp. 5-13 ◽  
Author(s):  
Lesia Tyshchenko ◽  
Atilla Csajbok
Keyword(s):  
Financial Crisis ◽  
Foreign Exchange ◽  
Quantitative Measurement ◽  
Foreign Exchange Market ◽  
Banking Sector ◽  
Financial Stress ◽  
Stress Index ◽  
Exchange Market ◽  
The Past ◽  
Financial Stress Index

In this paper, we develop a daily Financial Stress Index (FSI) for the comprehensive quantitative measurement of the degree of stress in Ukraine’s financial system. We use 14 individual indicators grouped into four sub-indices – the banking sector, corporate debt, government debt, and the foreign exchange market – to construct the FSI. The index measures the level of stress and vulnerability of the financial sector and enables to compare this level at current moment with its dynamic in the past. The FSI can signal the start of a financial crisis and can be used to assess the effectiveness of anti-crisis measures.

The link between financial stress index and economic activity: prominent Granger causalities across frequencies in Luxembourg

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pejman Bahramian ◽  
Andisheh Saliminezhad ◽  
Şule Aker
Keyword(s):  
Granger Causality ◽  
Time Domain ◽  
Economic Activity ◽  
Financial Stress ◽  
Financial Sector ◽  
Stress Index ◽  
Content Type ◽  
Financial Stress Index ◽  
The Time Domain ◽  
The Relationship

PurposeIn spite of the certain risk imposed by financial stress on the real economy, the relationship between financial stress and economic activity is complicated and underresearched, meaning that important gaps still remain in the authors’ understanding of this critical relationship. Therefore, the current study aims to answer the significant question regarding whether a stressful financial sector has predictive power on the real sector and vice versa. Hence, the study examines the causal interrelationship between financial stress index (FSI) and economic activity in Luxembourg as a sample country.Design/methodology/approachIn this study, accompanying the time domain Granger causality framework of Hacker and Hatemi-J (2012), the authors utilize the spectral causality technique of Breitung and Candelon (2006), which is based on the study of Geweke (1982) and Hosoya (1991). This method enables the researcher to measure the degree of a particular variation in time series. Moreover, it allows considering the nonlinearities and causality cycles. The authors further apply the recent method of Farné and Montanari (2018) that is a bootstrap framework on Granger-causality spectra, which allows for disambiguation in causalities.FindingsThe time-domain approach finds evidence of bidirectional causation between the variables. However, the spectral causality results indicate the causal linkages between the series are only valid under the medium-run frequency. This study’s findings emphasize covering the frequency causality to deliver a more comprehensive picture of the interrelationship between the variables.Originality/valueThere are many studies in this area that examine the nexus between financial stress and economic activity. However, the authors believe this paper is the first study in the context of Luxemburg. The authors focus on this country since its financial sector is designated as the most important pillar for the economy. Thus, a careful and reliable examination of the relationship between the financial sector and economic activity is likely to be of considerable interest to policymakers and researchers in this field.

The Cleveland Financial Stress Index

2012 ◽  
Author(s):  
Timothy Bianco ◽  
Mikhail V. Oet ◽  
Stephen J. Ong
Keyword(s):  
Financial Stress ◽  
Stress Index ◽  
Financial Stress Index

scholarly journals Applying transfer entropy approach to investigate the information flow among ASEAN stock markets

2020 ◽  
Vol 4 (1) ◽  
pp. First
Author(s):  
Tran Thi Tuan Anh
Keyword(s):  
Information Flow ◽  
Stock Markets ◽  
Investment Strategy ◽  
The Philippines ◽  
Transfer Entropy ◽  
The Other ◽  
Information Flows ◽  
Research Results ◽  
Region Data ◽  
Asean Countries

This paper uses transfer entropy to measure and identify the information flows between stock markets in the ASEAN region. Data on daily closing stock indices, including Vietnam, the Philippines, Malaysia, Indonesia, Thailand, and Singapore, are collected for the period from March 2012 to October 2019 to calculate these transfer entropies. The research results of this article can be considered in two aspects: one is, how information flow originating from one market will be accepted by other markets and secondly, information flow that markets receive. From the perspective of incoming transfer entropy, Vietnam is the country most affected by information from the other ASEAN markets while Indonesia and Malaysia are the least affected. In terms of outgoing entropy, Thailand is the largest source of information flow to the ASEAN markets. Malaysia and the Philippines are the two countries that receive minor information impact from other countries. The research also reveals that the Singapore stock market is rather separate from the other ASEAN countries. The research results also imply that, for investors and policymakers, defining the information flows among ASEAN stock markets can help to predict market movements, thereby developing a suitable investment strategy or establishing appropriate management policies.

TOURISM INDUSTRY STRESS INDEX AND ITS RELATIONSHIP TO THE FINANCIAL STRESS INDEX

2021 ◽  
Vol 27 (2) ◽  
pp. 363-383
Author(s):  
Marina Malkina ◽  
Anton Ovcharov
Keyword(s):  
Interaction Design ◽  
Moving Average ◽  
Financial Stress ◽  
Principal Component ◽  
Tourism Industry ◽  
Real Effective Exchange Rate ◽  
Stress Index ◽  
Marginal Effect ◽  
Causality Test ◽  
Financial Stress Index

Purpose – development of the Tourism Industry Stress Index (TSI) and the Financial Stress Index (FSI) followed by an examination of their interaction. Design – The TSI, which aggregates tourist arrivals, overnight stays and net occupancy, was tested on data for Finland, Italy, Germany and Spain between 1993 and 2020. The FSI was composed of the S&P500 index, Brent oil futures, and the real effective exchange rate of the euro. Methodology / Approach – Both stress indices were calculated as the difference between the moving standard deviation and the moving average of the monthly growth rate of the selected indicators. We aggregated them by applying two alternative techniques: arithmetic mean and nonnormalized principal component analysis. The Granger causality test was utilised to assess the dependence between the indices. Findings – We identified periods of increased volatility in the European tourism market and described its connection to financial crises. The causality test of the FSI-TSI model showed that financial turmoil led to increased tourism market stress with an average lag of three months and a marginal effect of 0.2. Originality of the research – We recommend the Financial Stress Index as a predictor of the Tourism Industry Stress Index in the business cycle.

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