scholarly journals CONCEPTUAL BASES OF MACRO PREDICTION ON THE BASIS OF THE NEURAL NETWORKS SYSTEMS

2017 ◽  
pp. 68-73
Author(s):  
Inna Strelchenko
Keyword(s):  
Neural Networks ◽  
Information Exchange ◽  
Large Scale ◽  
System Analysis ◽  
Global Financial Crisis ◽  
Functional Model ◽  
Training Sample ◽  
Sharp Change ◽  
The Neural Networks ◽  
The Global Financial Crisis

Introduction. Under the conditions of accelerated integration of global financial markets, the growth of information exchange speed and large-scale transmission of electronic money, the forecasting of economy scenarios under a sharp change in the environment, particularly during the global financial crisis becomes an important task. Purpose. The aim of the research is to develop and substantiate the conceptual principles of macro-prediction on the basis of the neural networks system in conditions of increasing non-linearity of the environment. Method (methodology). The use of system analysis, integrated approaches which are based on the principles of economic theory, on the one hand, and, on the other, on the conceptual basis of economic and mathematical modeling of economics and finances processes, have become the methodological basis of the research. Results. The use of the neural networks system in the task of macro prediction of the economic systems behavior under the crisis conditions has been justified. It has been definitedthe list of indicators that formed a training sample for simulation. The basic functional model of information technology of the forecasting process has been constructed.

Financial distress determinants among SMEs: empirical evidence from Sweden

2020 ◽  
Vol 47 (3) ◽  
pp. 547-560 ◽  
Author(s):  
Darush Yazdanfar ◽  
Peter Öhman
Keyword(s):  
Financial Crisis ◽  
Financial Distress ◽  
Large Scale ◽  
Global Financial Crisis ◽  
Binary Logistic Regression ◽  
Data Availability ◽  
Cross Sectional ◽  
Data Set ◽  
Content Type ◽  
The Global Financial Crisis

PurposeThe purpose of this study is to empirically investigate determinants of financial distress among small and medium-sized enterprises (SMEs) during the global financial crisis and post-crisis periods.Design/methodology/approachSeveral statistical methods, including multiple binary logistic regression, were used to analyse a longitudinal cross-sectional panel data set of 3,865 Swedish SMEs operating in five industries over the 2008–2015 period.FindingsThe results suggest that financial distress is influenced by macroeconomic conditions (i.e. the global financial crisis) and, in particular, by various firm-specific characteristics (i.e. performance, financial leverage and financial distress in previous year). However, firm size and industry affiliation have no significant relationship with financial distress.Research limitationsDue to data availability, this study is limited to a sample of Swedish SMEs in five industries covering eight years. Further research could examine the generalizability of these findings by investigating other firms operating in other industries and other countries.Originality/valueThis study is the first to examine determinants of financial distress among SMEs operating in Sweden using data from a large-scale longitudinal cross-sectional database.

scholarly journals Confidence in future monetary policy as a way to overcome the liquidity trap

2019 ◽  
Vol 5 (2) ◽  
pp. 117-135
Author(s):  
Olga Kuznetsova ◽  
Sergey Merzlyakov ◽  
Sergey Pekarski
Keyword(s):  
Monetary Policy ◽  
Interest Rates ◽  
Large Scale ◽  
Global Financial Crisis ◽  
Time Consistency ◽  
Central Banks ◽  
Time Inconsistency ◽  
Liquidity Trap ◽  
Developed Economies ◽  
The Global Financial Crisis

The global financial crisis of 2007–2009 has changed the landscape for monetary policy. Many central banks in developed economies had to employ various unconventional policy tools to overcome a liquidity trap. These included large-scale asset purchase programs, forward guidance and negative interest rate policies. While recently, some central banks were able to return to conventional monetary policy, for many countries the effectiveness of unconventional policies remains an issue. In this paper we assess diverse practices of unconventional monetary policy with a particular focus on expectations and time consistency. The principal aspect of successful policy in terms of overcoming a liquidity trap is the confidence that interest rates will remain low for a prolonged period. However, forming such expectations faces the problem of time inconsistency of optimal policy. We discuss some directions to solve this problem.

The Global Financial Crisis: what have we learned so far?

2015 ◽  
Vol 11 (2) ◽  
pp. 134-161 ◽  
Author(s):  
Karyn L. Neuhauser
Keyword(s):  
Financial Crisis ◽  
Large Scale ◽  
Global Financial Crisis ◽  
Financial System ◽  
Future Research ◽  
Financial Assets ◽  
Content Type ◽  
The Subject ◽  
The Global Financial Crisis ◽  
Number Of Citations

Purpose – The purpose of this paper is to provide a cohesive review of the major findings in the literature concerning the Global Financial Crisis. Design/methodology/approach – Papers published in top-rated finance and economics journal since the crisis up to the present were reviewed. A large number of these were selected for inclusion, primarily based on the number of citations they had received adjusted for the amount of time elapsed since their publication, but also partly based on how well they fit in with the narrative. Findings – Much has been done to investigate the causes of the Global Financial Crisis, its effects on various aspects of the financial system, and the effectiveness of regulatory measures undertaken to restore the financial system. While more remains to be done, the existing body of research paints an interesting picture of what happened and why it happened, describes the interrelationships between the mortgage markets and financial markets created by the large scale securitization of financial assets, identifies the problems created by these inter-linkages and offers possible solutions, and assesses the effectiveness of the regulatory response to the crisis. Originality/value – This study summarizes a vast amount of literature using a framework that allows the reader to quickly absorb a large amount of information as well as identify specific works that they may wish to examine more closely. By providing a picture of what has been done, it may also assist the reader in identifying areas that should be the subject of future research.

scholarly journals Two Major Economic Crises in the Early Twenty-First Century and their Impact on Central Bank Independence

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Marek Dabrowski
Keyword(s):  
Monetary Policy ◽  
Financial Crisis ◽  
Large Scale ◽  
Global Financial Crisis ◽  
First Century ◽  
Economic Crises ◽  
Government Bonds ◽  
Early Twenty ◽  
Twenty First Century ◽  
The Global Financial Crisis

Abstract Two major economic crises in the early twenty-first century have had a serious impact on monetary policy and CB independence. Disruption in financial intermediation and associated deflationary pressures caused by the global financial crisis of 2007–2009 and European financial crisis of 2010–2015 pushed central banks (CBs) in major currency areas towards adoption of unconventional monetary policy measures, including large-scale purchase of government bonds (quantitative easing). The same approach has been taken by CBs in response to the COVID-19 crisis in 2020 even if the characteristics of this crisis differ from the previous one. As a result of both crises, CBs have become major holders of government bonds and de facto – main creditors of governments. Against rapidly deteriorating fiscal balances, CBs have become hostages of fiscal policies, which compromises their independence. Risks to the CB independence also come from their additional mandates (beyond price stability) and populist political pressures.

scholarly journals Multilingual Automatic Term Extraction in Low-Resource Domains

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
NGOC TAN LE ◽  
Fatiha Sadat
Keyword(s):  
Neural Networks ◽  
Language Processing ◽  
Large Scale ◽  
Data Augmentation ◽  
Shared Task ◽  
Low Resource ◽  
Term Extraction ◽  
Augmentation Techniques ◽  
Automatic Term Extraction ◽  
The Neural Networks

With the emergence of the neural networks-based approaches, research on information extraction has benefited from large-scale raw texts by leveraging them using pre-trained embeddings and other data augmentation techniques to deal with challenges and issues in Natural Language Processing tasks. In this paper, we propose an approach using sequence-to-sequence neural networks-based models to deal with term extraction for low-resource domain. Our empirical experiments, evaluating on the multilingual ACTER dataset provided in the LREC-TermEval 2020 shared task on automatic term extraction, proved the efficiency of deep learning approach, in the case of low-data settings, for the automatic term extraction task.

scholarly journals ACCUMULATION OF CAPITAL IN VOLATILE MARKET CONDITIONS

2017 ◽  
Vol 19 (2(64)) ◽  
pp. 94-100
Author(s):  
N.I. Duchinska ◽  
J.N. Chayka
Keyword(s):  
Capital Accumulation ◽  
Large Scale ◽  
Global Financial Crisis ◽  
Import Substitution ◽  
High Standard ◽  
Developed Countries ◽  
Voluntary Association ◽  
Role Of The State ◽  
Positive Rate ◽  
The Global Financial Crisis

There are three stages of the process of capital accumulation in Ukraine. At the first stage there was a primary accumulation of capital. At this stage, the accumulation of capital was largely unearned and was not based on the voluntary association of private capital, but due to the policy and rapid dismantling of state-owned enterprises and the creation of various companies on their basis. Capital formation was carried out at the expense of the mechanism of large-scale and rapid redistribution of assets between industries and economic entities, as a result of the development of the principles of self-financing and self-financing, which began in the mid-80's of the twentieth century. The second stage is characterized by a positive rate of accumulation of capital. At this stage, the pace of GDP decline slowed down, and the pace of capital accumulation was positive. Positive features of the accumulation process were the global financial crisis of 1998. Due to the rapid devaluation of the hryvnia, the position of national producers strengthened and the domestic consumer market expanded significantly, and the process of import substitution began. At the third stage, negative rates of accumulation were noted. Assessing the influence of domestic mechanisms of accumulation and overflow of capital on the peculiarities of the development of the domestic economic structure, it is necessary to note the rather high standard of gross fixed capital accumulation, which fluctuates within the limits of 20 - 25%. Despite the fact that the indicators for the formation and use of gross and net savings in Ukraine correspond to the proportions inherent in developed countries, the domestic economy is constantly experiencing a lack of investment, which is explained by the inadequate motivation of investors to implement large-scale investment and innovation projects, the ineffectiveness of the national system of transformation of savings in investment and Needs to improve the mechanisms of accumulation and overflow of capital and increase the role of the state in stimulating this process .

scholarly journals What Microeconomic Fundamentals Drove Global Oil Prices during 1986–2020?

2021 ◽  
Vol 14 (8) ◽  
pp. 391
Author(s):  
Anastasios G. Malliaris ◽  
Mary Malliaris
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Financial Crisis ◽  
Global Financial Crisis ◽  
Supply And Demand ◽  
Oil Prices ◽  
Main Hypothesis ◽  
Oil Market ◽  
The Global Financial Crisis ◽  
The Impact

The global financial crisis of 2007–2009 caused major economic disturbances in the oil market. In this paper, we consider five variables that describe the microeconomics of the supply of and demand for oil, and evaluate their importance before, during and after the global financial crisis. We consider five dissimilar regimes during the period of January 1986 to the end of 2020: two regimes prior to the global financial crisis, the regime during the crisis, and two regimes after the crisis. The main hypothesis tested is that oil fundamentals of supply and demand remained important, even though the five regimes were dissimilar. We built five boosted and over-fitted neural networks to capture the exact relationships between spot oil prices and oil data related to these prices. This analysis shows that, while the inputs into an accurate neural network can remain the same, the impact of each variable can change considerably during different regimes.

Financial crisis and SME capital structure: Swedish empirical evidence

2019 ◽  
Vol 46 (4) ◽  
pp. 925-941 ◽  
Author(s):  
Darush Yazdanfar ◽  
Peter Öhman ◽  
Saeid Homayoun
Keyword(s):  
Financial Crisis ◽  
Capital Structure ◽  
Large Scale ◽  
Global Financial Crisis ◽  
Ordinary Least Squares ◽  
Data Availability ◽  
Cross Sectional ◽  
Content Type ◽  
The Global Financial Crisis

Purpose The purpose of this paper is to empirically examine capital structure determinants of small- and medium-sized enterprises (SMEs) during and after the global financial crisis. Design/methodology/approach Statistical methods, including ordinary least squares and the generalised method of moments, were used to analyse a sample of over 40,800 Swedish SMEs operating in four industries during the 2008–2015 period. Findings The results indicate that the independent variables – i.e. financial crisis, profitability, size, tangibility and industry affiliation – to various degrees explain changes in short-term debt (STD) and long-term debt (LTD) ratios. In particular, the empirical findings indicate that the sampled SMEs tended to rely more on STD and LTD during (2008–2009) than after (2010–2015) the financial crisis. Research limitations/implications Due to data availability, the current study is limited to a sample of Swedish SMEs in four industries covering eight years. Further research could examine the generalisability of these findings by investigating other firms operating in other industries and other countries. Originality/value This study is one of few examining determinants of short- and long-term SME debt during and after the global financial crisis, using data from a large-scale cross-sectional database.

A Fault Diagnosis Method Based on Combination of Neural Network and Fault Dictionary

2013 ◽  
Vol 765-767 ◽  
pp. 2078-2081
Author(s):  
Ya Feng Meng ◽  
Sai Zhu ◽  
Rong Li Han
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Fault Diagnosis ◽  
Real Time ◽  
Large Scale ◽  
Fault Dictionary ◽  
Diagnosis Method ◽  
The Neural Networks ◽  
Trained Neural Network ◽  
Complex Circuits

Neural network and Fault dictionary are two kinds of very useful fault diagnosis method. But for large scale and complex circuits, the fault dictionary is huge, and the speed of fault searching affects the efficiency of real-time diagnosing. When the fault samples are few, it is difficulty to train the neural network, and the trained neural network can not diagnose the entire faults. In this paper, a new fault diagnosis method based on combination of neural network and fault dictionary is introduced. The fault dictionary with large scale is divided into several son fault dictionary with smaller scale, and the search index of the son dictionary is organized with the neural networks trained with the son fault dictionary. The complexity of training neural network is reduced, and this method using the neural networks ability that could accurately describe the relation between input data and corresponding goal organizes the index in a multilayer binary tree with many neural networks. Through this index, the seeking scope is reduced greatly, the searching speed is raised, and the efficiency of real-time diagnosing is improved. At last, the validity of the method is proved by the experimental results.

scholarly journals Access to bank finance for UK SMEs in the wake of the recent financial crisis

2016 ◽  
Vol 22 (6) ◽  
pp. 903-932 ◽  
Author(s):  
Marc Cowling ◽  
Weixi Liu ◽  
Ning Zhang
Keyword(s):  
Financial Crisis ◽  
Small Business ◽  
Large Scale ◽  
Global Financial Crisis ◽  
Credit Rationing ◽  
Economic Downturn ◽  
Content Type ◽  
External Finance ◽  
Risk Rating ◽  
The Global Financial Crisis

Purpose The purpose of this paper is to investigate how entrepreneurs demand for external finance changed as the economy continued to be mired in its third and fourth years of the global financial crisis (GFC) and whether or not external finance has become more difficult to access as the recession progressed. Design/methodology/approach Using a large-scale survey data on over 30,000 UK small- and medium-sized enterprises between July 2011 and March 2013, the authors estimate a series of conditional probit models to empirically test the determinants of the supply of, and demand for external finance. Findings Older firms and those with a higher risk rating, and a record of financial delinquency, were more likely to have a demand for external finance. The opposite was true for women-led businesses and firms with positive profits. In general finance was more readily available to older firms post-GFC, but banks were very unwilling to advance money to firms with a high-risk rating or a record of any financial delinquency. It is estimated that a maximum of 42,000 smaller firms were denied credit, which was significantly lower than the peak of 119,000 during the financial crisis. Originality/value This paper provides timely evidence that adds to the general understanding of what really happens in the market for small business financing three to five years into an economic downturn and in the early post-GFC period, from both a demand and supply perspective. This will enable the authors to consider what the potential impacts of credit rationing on the small business sector are and also identify areas where government action might be appropriate.

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