scholarly journals Modeling the segment interactions of Ukraine’s financial market

2020 ◽  
Vol 17 (2) ◽  
pp. 101-112 ◽  
Author(s):  
Liudmyla Prymostka ◽  
Іryna Krasnova ◽  
Ganna Kulish ◽  
Andrii Nikitin ◽  
Valentyna Shevaldina
Keyword(s):  
Time Series ◽  
Financial Market ◽  
Foreign Exchange Market ◽  
Credit Market ◽  
Market Segments ◽  
State Budget ◽  
Dynamic Relationship ◽  
Registration Number ◽  
External Conditions ◽  
State Registration

This study is devoted to assessing the level of individual segments interconnectedness within the financial market of Ukraine (FMU) and their dynamics in uncertain conditions. The methodology of the systematic approach is used to investigate the dynamic relationship between individual segments of the financial market of Ukraine, namely credit (deposit-credit) market, stock market (market of securities), government securities market, currency market, and interbank market. The study of financial market dynamics focuses on the description of the price indicators of individual market segments, which are monitored using time series analysis and statistical methods. The results of the time series assessment revealed the fractal characteristics of the Ukrainian financial market as a measure of sustainability (namely inertia). It is revealed that all segments of the financial market, except credit, are characterized by persistence. It is established that the development of market segments is uneven and is characterized as bifurcation. The credit segment is addicted to insider behavior and has the highest risk concentration. It is revealed that the foreign exchange market is still in crisis. The results of modeling the correlation relationships between market segments have shown that, in the presence of such relationships, they differ in the strength and nature of the interaction. They are volatile, unstable, and situational, dependent on external conditions. The credit market has a relationship with other segments, not significantly strong but stable. The results of the analysis indicate the dynamic development of segments within the Ukrainian financial market in the presence of interconnections between them. AcknowledgmentThe study was conducted within the framework of the State Budget of the Kyiv National Economic University named after Vadym Hetman on the topic “Innovative development of banking activities in the integrated financial environment” (state registration number 0117U001178).  

scholarly journals Central bank's communication and markets' reactions: Polish evidence

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Janusz Brzeszczyński ◽  
Jerzy Gajdka ◽  
Tomasz Schabek ◽  
Ali M Kutan
Keyword(s):  
Monetary Policy ◽  
Foreign Exchange ◽  
Financial Market ◽  
Foreign Exchange Market ◽  
Emerging Market ◽  
Public Information ◽  
Exchange Market ◽  
Market Segments ◽  
Content Type ◽  
The Impact

PurposeThis study contributes to the pool of knowledge about the impact of monetary policy communication of central banks on financial instruments' prices and assets' value in emerging markets.Design/methodology/approachEmpirical analysis is executed using the National Bank of Poland (NBP) announcements about its monetary policy covering the data from the broad financial market in its three main segments: stock market, foreign exchange market and bonds market. The reactions are measured relative to the changes in the NBP announcements and also with respect to investors' expectations. Autoregressive conditional heteroscedasticity (ARCH) models with dummy variables are used as the main methodological tool.FindingsBonds market and foreign exchange market are the most sensitive market segments, while interest rate and money supply are the most influential types of announcements. The changes of the revealed new macroeconomic figures had more impact on assets' prices movements than the deviations from their expectations. Moreover, greater diversity of the Monetary Policy Council (MPC) members' opinions on the voted motions, captured in the MPC voting reports, is associated with more cases of statistically significant NBP communication events.Practical implicationsThe findings have direct relevance for fund managers, portfolio analysts, investors and also for financial market regulators.Originality/valueThe results provide novel evidence about how the emerging financial market responds to monetary policy announcements. They help understand the nature of the impact of public information on financial assets' valuation and on movements of their prices, analysed comprehensively in three market segments, in the emerging market environment.

scholarly journals Evolving Importance of Securities Market to Ensure Economic Growth: Evidence from Armenia

2017 ◽  
Vol 64 (4) ◽  
pp. 473-485
Author(s):  
Ashot Salnazaryan ◽  
Haykaz Aramyan
Keyword(s):  
Economic Growth ◽  
Financial Market ◽  
Credit Market ◽  
Securities Market ◽  
Market Segments ◽  
Corporate Securities ◽  
Regression Techniques ◽  
The Impact ◽  
The Relationship

Abstract This research aims to reveal the importance of securities market in ensuring economic growth in Armenia. In order to make the research more substantial, we also examined the impact of other financial market segments, such as insurance market and credit market, on the economic growth. To estimate the relationship between financial market segments and economic growth, an empirical research was conducted using correlation and regression techniques. The research reveals that the most significant impact on the economic growth among Armenian financial market segments has the credit market of Armenia. There is no significant relationship between economic growth and insurance, as well as corporate securities market. It is pointed out in the research, that the evolving importance of the role of securities market in the economic growth is not yet demonstrated in Armenia, which, perhaps, results from the absence of interaction between securities market and economy in Armenia.

scholarly journals Memories of the Gold Foreign Exchange Market Based on a Moving V-Statistic and Wavelet-Based Multiresolution Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-7
Author(s):  
Peng Zheng ◽  
Bin Liu ◽  
Zhongli Zhou
Keyword(s):  
Time Series ◽  
Foreign Exchange ◽  
Financial Market ◽  
Multiresolution Analysis ◽  
Foreign Exchange Market ◽  
Financial Time Series ◽  
Time Windows ◽  
Memory Model ◽  
Forecasting Returns ◽  
Theory Research

Memory in finance is the foundation of a well-established forecasting model, and new financial theory research shows that the stochastic memory model depends on different time windows. To accurately identify the multivariate long memory model in the financial market, this paper proposes the concept of a moving V-statistic on the basis of a modified R/S method to determine whether the time series has a long-range dependence and subsequently to apply wavelet-based multiresolution analysis to study the multifractality of the financial time series to determine the initial data windows. Finally, we check the moving V-statistic estimation in wavelet analysis in the same condition; the paper selects the volatilities of the gold foreign exchange rates to evaluate the moving V-statistic. According to the results, the method of testing memory established in this paper can identify the breakpoint of the memories effectively. Furthermore, this method can provide support for forecasting returns in the financial market.

scholarly journals THE EFFECTS OF VOLATILITY SPILLOVER ON THE LARGEST GLOBAL FINANCIAL MARKET SEGMENTS

2019 ◽  
pp. 319
Author(s):  
Irena Janković
Keyword(s):  
Stock Market ◽  
Foreign Exchange ◽  
Financial Market ◽  
Foreign Exchange Market ◽  
Bond Market ◽  
Volatility Spillover ◽  
Exchange Market ◽  
Market Segments

The aim of the paper is to present and analyse indicators of financial connectedness and volatility spillover on important segments of the global financial market – the stock market, bond market, CDS market, and foreign exchange market. Total, net, and directional measures of volatility spillover are presented and analysed, indicating the level of connectedness of countries’ particular market segments and the level of volatility spillover in periods of crisis and stability.

scholarly journals Assessment of the level of financial and economic security at machine-building enterprises: evidence from Ukraine

2020 ◽  
Vol 18 (1) ◽  
pp. 33-47 ◽  
Author(s):  
Alla Cherep ◽  
Dmytro Babmindra ◽  
Lina Khudoliei ◽  
Yuliya Kusakova
Keyword(s):  
Financial Stability ◽  
Evaluation Method ◽  
Economic Security ◽  
Machine Building ◽  
State Budget ◽  
National University ◽  
Registration Number ◽  
State Registration ◽  
Integral Indicator ◽  
Building Enterprises

Determining the level of financial and economic security of an enterprise allows assessing the real possibilities to confront internal and external challenges and defining the potential for future development. To develop proposals on assessing this level, the study uses data on machine-building enterprises of Zaporizhzhia region (Ukraine) and applies integral method, regression analysis and normalization. The expert evaluation method was used to form the system of key parameters. The experts were economists, the accounting departments’ and the economic security departments’ members of the studied enterprises. The experts selected six indices that they consider to be the most representative of the financial and economic security of an enterprise. These parameters were used to calculate the integral indicator of the level of financial and economic security of enterprises. Harrington’s approach was used to group enterprises according to their level of financial and economic security (very high, high, steady, satisfactory and unsatisfactory). The calculations have shown that the integral indicator of financial and economic security of the enterprises of Zaporizhzhia region ranged from 0.32 to 0.66 for the period 2014–2018. It was justified that along with the support of financial stability, solvency, business activity, profitability, investment attractiveness and innovativeness and absent sharp changes in the environment, the level of financial and economic security of machine builders will increase from 0.4 to 11.9%. AcknowledgmentThe study was carried out within the framework of the state budget theme (state registration number 0117U000512), Establishment of Business Incubators on the Basis of Innovative Development and Ensuring National Financial and Economic Security (2017–2019), Faculty of Economics, Zaporizhzhya National University.

scholarly journals Detecting Predictable Segments of Chaotic Financial Time Series via Neural Network

Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 823
Author(s):  
Tianle Zhou ◽  
Chaoyi Chu ◽  
Chaobin Xu ◽  
Weihao Liu ◽  
Hao Yu
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Phase Space ◽  
Financial Market ◽  
Financial Time Series ◽  
Influential Factors ◽  
Series Data ◽  
Phase Point ◽  
Price Fluctuations ◽  
Financial Time

In this study, a new idea is proposed to analyze the financial market and detect price fluctuations, by integrating the technology of PSR (phase space reconstruction) and SOM (self organizing maps) neural network algorithms. The prediction of price and index in the financial market has always been a challenging and significant subject in time-series studies, and the prediction accuracy or the sensitivity of timely warning price fluctuations plays an important role in improving returns and avoiding risks for investors. However, it is the high volatility and chaotic dynamics of financial time series that constitute the most significantly influential factors affecting the prediction effect. As a solution, the time series is first projected into a phase space by PSR, and the phase tracks are then sliced into several parts. SOM neural network is used to cluster the phase track parts and extract the linear components in each embedded dimension. After that, LSTM (long short-term memory) is used to test the results of clustering. When there are multiple linear components in the m-dimension phase point, the superposition of these linear components still remains the linear property, and they exhibit order and periodicity in phase space, thereby providing a possibility for time series prediction. In this study, the Dow Jones index, Nikkei index, China growth enterprise market index and Chinese gold price are tested to determine the validity of the model. To summarize, the model has proven itself able to mark the unpredictable time series area and evaluate the unpredictable risk by using 1-dimension time series data.

LEARNING DYNAMICS AND NONLINEAR MISSPECIFICATION IN AN ARTIFICIAL FINANCIAL MARKET

2009 ◽  
Vol 13 (5) ◽  
pp. 625-655 ◽  
Author(s):  
Christophre Georges ◽  
John C. Wallace
Keyword(s):  
Time Series ◽  
Financial Market ◽  
Consistency Condition ◽  
Nonlinear Structure ◽  
State Variable ◽  
Bounded Memory ◽  
Long Run ◽  
Finite Memory ◽  
Aggregate Dynamics ◽  
True Structure

In this paper, we explore the consequence of learning to forecast in a very simple environment. Agents have bounded memory and incorrectly believe that there is nonlinear structure underlying the aggregate time series dynamics. Under social learning with finite memory, agents may be unable to learn the true structure of the economy and rather may chase spurious trends, destabilizing the actual aggregate dynamics. We explore the degree to which agents' forecasts are drawn toward a minimal state variable learning equilibrium as well as a weaker long-run consistency condition.

FINANCIAL AND SECURITY POLICIES FOR SUSTAINABLE DEVELOPMENT

2021 ◽  
Keyword(s):  
Sustainable Development ◽  
Financial Management ◽  
Economic Security ◽  
Security Policies ◽  
Economic Issues ◽  
Social Sphere ◽  
State Pedagogical ◽  
Registration Number ◽  
State Registration ◽  
Practical Recommendations

The monograph represents the results of research of the scientific and pedagogical staff of the Department of Finance, Accounting and Economic Security of Pavlo Tychyna Uman State Pedagogical University on the research topic “Problems of financial support of economic and social sphere” (state registration number 0116U000117). Theoretical & methodological provisions and practical recommendations on the formation of conceptual framework and applied tools for assessing, monitoring and financial management at the global, national and micro levels in the permanent conditions of risks, threats and challenges to the security of sustainable development are given in the monograph. Recommended for readers interested in economic issues, academics, professionals, postgraduates, educators and students.

Modeling Sales-Advertising Relationships: An Integrated Time Series–Econometric Approach

1983 ◽  
Vol 20 (3) ◽  
pp. 291-295 ◽  
Author(s):  
Robert P. Leone
Keyword(s):  
Time Series ◽  
Model Building ◽  
Time Series Data ◽  
Multivariate Time Series ◽  
Series Data ◽  
Response Models ◽  
Dynamic Relationship ◽  
Sales Response ◽  
Integrated Time Series ◽  
Econometric Approach

Since Palda's pioneering work investigating the dynamic relationship between sales and advertising, the marketing literature has contained many articles on the topic of sales response model building. Until recently, most of these articles have reported the construction of econometric models based on time series data. Recent applications of multivariate time series extensions of the work by Box and Jenkins have shown the usefulness of this methodology in building sales response models. The author discusses the distinctions between the econometric and time series approaches and, through a multivariate time series analysis, explores the competitive environment of an industry in which advertising is the main source of competition.

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