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Relevant bibliographies by topics / Financial analysis

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Academic literature on the topic 'Financial analysis'

Author: Grafiati

Published: 4 June 2021

Last updated: 14 November 2023

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Journal articles on the topic "Financial analysis"

1

MANISHA B, RATHOD. "Financial Performance Analysis." Global Journal For Research Analysis 3, no. 5 (June 15, 2012): 9–10. http://dx.doi.org/10.15373/22778160/may2014/4.

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Thakur, Neelam, and J. S. Bhatnagar. "Financial analysis of HDFC Bank." Scientific Journal of India 2, no. 2 (December 31, 2017): 53–54. http://dx.doi.org/10.21276/24565644/2017.v2.i2.18.

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Alshowishin, Aown. "Financial Analysis." International Journal of Scientific and Research Publications (IJSRP) 11, no. 4 (April 12, 2021): 208–11. http://dx.doi.org/10.29322/ijsrp.11.04.2021.p11226.

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K., Dr Siva Nageswararao. "Financial Performance Analysis of Andhra Bank." International Journal of Psychosocial Rehabilitation 24, no. 5 (March 31, 2020): 65–75. http://dx.doi.org/10.37200/ijpr/v24i5/pr201668.

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De Moraes, Claudio Oliveira, José Americo Pereira Antunes, and Adriano Rodrigues. "Financial intermediation analysis from financial flows." Journal of Economic Studies 46, no. 3 (August 2, 2019): 727–47. http://dx.doi.org/10.1108/jes-10-2017-0302.

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Purpose The purpose of this paper is to analyze the financial friction effect of non-performing loans (NPLs) on financial intermediation (FI) through empirical evidence from the Brazilian experience. Design/methodology/approach The authors develop a new variable, financial intermediation flow and a new indicator, FI, both measures of FI. To empirically test FI, the authors use a dynamic panel data framework that draws on 101 banks (December 2000 to December 2015). Findings An increase in NPL reduces FI. Thus, NPL amplifies financial friction in FI. This result holds in different time frames, such as the pre-crisis period, the crisis period and the post-crisis period. Practical implications The FI measure developed in this study offers the policymakers a possibility to monitor financial stability. Originality/value This study adds to this debate by proposing a measure of FI derived from financial flows. This measure allows one to estimate the role of NPL as a financial friction that can pose a threat to financial stability.

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ROMIC, LIDIJA. "FINANCIAL STATEMENT ANALYSIS." International Journal of Management Cases 13, no. 3 (January 1, 2011): 149–51. http://dx.doi.org/10.5848/apbj.2011.00047.

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Mbona, Reginald Masimba, and Kong Yusheng. "Financial statement analysis." Asian Journal of Accounting Research 4, no. 2 (October 14, 2019): 233–45. http://dx.doi.org/10.1108/ajar-05-2019-0037.

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Purpose The Chinese Telecoms Industry has been rapidly growing over the years since 2001. An analysis of financial performance of the three giants in this industry is very important. However, it is difficult to know how many ratios can be used best with little information loss. The paper aims to discuss this issue. Design/methodology/approach A total of 18 financial ratios were calculated based on the financial statements for three companies, namely, China Mobile, China Unicom and China Telecom for a period of 17 years. A principal component analysis was run to come up with variables with significance value above 0.5 from each component. Findings At the end, the authors conclude how financial performance can be analysed using 12 ratios instead of the costly analysis of too many ratios that may be complex to interpret. The results also showed that ratios are all related as they come from the same statements, hence, the authors can use a few to represent the rest with limited loss of information. Originality/value This study will help different stakeholders who are interested in the financial performance of each company by giving them a shorter way to analyse performance. It will also assist those who do financial reporting on picking the ratios which matter in reflecting the performance of their companies. The use of PCA gives unbiased ratios that are most significant in assessing performance.

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Bergevin, Peter M., and Lisa K. Miller. "Financial Statement Analysis:." Journal of Business & Finance Librarianship 1, no. 4 (January 21, 1994): 49–59. http://dx.doi.org/10.1300/j109v01n04_05.

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Maas, Gerald M. "Financial Accountability Analysis." Recreational Sports Journal 12, no. 3 (May 1988): 14–15. http://dx.doi.org/10.1123/nirsa.12.3.14.

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Summer, Martin. "Financial Contagion and Network Analysis." Annual Review of Financial Economics 5, no. 1 (November 2013): 277–97. http://dx.doi.org/10.1146/annurev-financial-110112-120948.

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Dissertations / Theses on the topic "Financial analysis"

1

Robertson, John. "Identifying, measuring and analysing changes in financial health through financial ratio analysis." Thesis, Henley Business School, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.255667.

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Kenney, Shane P. "Financial ratio analysis of audited Federal Financial Statements." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2000. http://handle.dtic.mil/100.2/ADA380207.

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Thesis (M.S. in Management)--Naval Postgraduate School, June 1998.
Thesis advisor(s): Moses, O. Douglas ; Liao, Shu S. "June 2000." Includes bibliographical references (p. 111-112). Also available online.

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Melnychuk, Oleksandr. "Ukraine Financial Markets - The Analysis of Financial Frauds." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-161874.

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Ukraine is quite new country, which faces early stages of its development. The financial market of the country has passed through different and challenging times for these 20 years and still has to choose several essential factors for the further development. The existence of financial frauds in Ukraine could be explained by lack of knowledge and information in the country as well as low level of trust to the government. The case of JSC "MMM" and Mr. Mavrodi is the best well-known example of Ponzi scheme in Ukraine and all post-Soviet countries, which gives the possibility to analyze the main features of its consequences.

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Yin, Jiang Ling. "Financial time series analysis." Thesis, University of Macau, 2011. http://umaclib3.umac.mo/record=b2492929.

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Karabut, Vadim. "Financial Analysis of Sberbank." Master's thesis, Vysoká škola ekonomická v Praze, 2014. http://www.nusl.cz/ntk/nusl-193945.

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This thesis focuses on financial analysis of Sberbank CZ. It examines the bank's financial health using the data from the bank's assets and liabilities, expenses, revenues and profits as well as profitability, liquidity and capital adequacy. All the results are compared within the banking sector using the Financial market supervision report.

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Strebeľová, Veronika. "Financial Planning and Financial Analysis of a Limited Liability Company." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-124842.

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Composition of financial plan for year 2012 and executing financial analysis of a limited liability company. In composition of financial plan were used three variant -- an optimistic, a realistic and a pesimistic. Used methods of financial analysis were analysis of absolute indicators and financial ratios, including logaritmical decomposition of Return on Equity. Comparing each of those variants with reality valid on May 31, 2012.

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Robertson, Calum Stewart. "Real time financial information analysis." Thesis, Queensland University of Technology, 2008. https://eprints.qut.edu.au/16609/1/Calum_Robertson_Thesis.pdf.

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The efficient market hypothesis states that an efficient market incorporates all available information to provide an accurate valuation of an asset. Presently investors and researchers attempt to forecast future returns (profit/loss if the asset is held for a certain period) and volatility (variance of the returns) of the asset based on past trading behaviour, and commonly ignore non-numerical information. It is almost impossible to forecast future returns for frequently traded assets such as stocks, bonds, and currencies, so many institutional investors prefer to forecast future volatility. Volatility is frequently used by traders and fund managers to measure the risk of continuing to own the asset. Most volatility forecasting models completely disregard the arrival of news and therefore theoretically violate the efficient market hypothesis. The aim of this research is to investigate how the inclusion of details of the arrival of asset specific news (news which is relevant to the asset) can improve the volatility forecasts of a model. The problem is that the efficient market hypothesis indicates that only new information will cause the market to react, and therefore it is necessary to determine whether the news contains any new information. Most news does not include any new information and therefore assuming all news will trigger abnormal market behaviour is unlikely to improve the performance of a model. Furthermore news which causes a shock, i.e., news which contains highly unexpected new information, will cause a greater change in volatility than news which contains expected information. Therefore to produce a model that factors in the arrival of news into volatility forecasts, it is beneficial to examine the content to predict the reaction to the news. This research combines the field of econometrics with machine learning and intelligent data analysis. All hypotheses tested within this thesis are tested on a large collection of stocks traded in the US, UK and Australia. To my knowledge, this is the largest dataset used for the types of experiments conducted in this thesis. In this thesis evidence is provided to suggest that asset specific news is correlated with abnormal returns, volatility, and volatility forecast errors. There is also evidence to suggest that abnormal volumes and trading activity correlate to asset specific news. This confirms the findings of previous studies though in most cases only a small dataset was used and often only one or two time series (i.e., return, volatility, volume etc.) were used. Furthermore many studies did not investigate the intraday effect of news (i.e., the reaction on the day the news was released). The studies which investigated the intraday effect tended to focus on macroeconomic news, which is scheduled and eagerly anticipated by investors. Therefore the behaviour is easier to detect that for asset specific news. It is demonstrated that the content of news can be used to forecast abnormal returns and forecast periods when the given volatility forecasting model exhibits abnormally large errors (the difference between the realised volatility and the volatility which the given model forecast) with a high degree of accuracy. This was achieved by analysing the content of past news which correlated with abnormal market behaviour. For this research a new method for ranking terms is introduced and demonstrated to be very effective. Previous studies have revealed that the content of news can be used to forecast abnormal returns but, to my knowledge, no study has investigated the volatility forecast error. Furthermore, most previous studies have used a small dataset, and to forecast at relatively low frequencies (most are daily, though one is hourly). To the best of my knowledge no previous study has use such a large dataset to predict the high frequency (as little as 5 minutes) market reaction to news. Nor has any previous study achieved classification accuracies as high as those achieved in this thesis. Finally, a news aware volatility forecasting model is produced and the evidence demonstrates that the performance is better than an alternative model which does not account for news under certain circumstances. Furthermore it is demonstrated that using the content of news to choose documents which are more likely to cause the market to react yields better forecasts. Very few researchers have included the arrival of news in a volatility forecasting model, and all of these have used small datasets. Furthermore, to my knowledge, none of these researchers have used the content of the news to choose news which is more likely to cause the market to react.

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Robertson, Calum Stewart. "Real time financial information analysis." Queensland University of Technology, 2008. http://eprints.qut.edu.au/16609/.

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The efficient market hypothesis states that an efficient market incorporates all available information to provide an accurate valuation of an asset. Presently investors and researchers attempt to forecast future returns (profit/loss if the asset is held for a certain period) and volatility (variance of the returns) of the asset based on past trading behaviour, and commonly ignore non-numerical information. It is almost impossible to forecast future returns for frequently traded assets such as stocks, bonds, and currencies, so many institutional investors prefer to forecast future volatility. Volatility is frequently used by traders and fund managers to measure the risk of continuing to own the asset. Most volatility forecasting models completely disregard the arrival of news and therefore theoretically violate the efficient market hypothesis. The aim of this research is to investigate how the inclusion of details of the arrival of asset specific news (news which is relevant to the asset) can improve the volatility forecasts of a model. The problem is that the efficient market hypothesis indicates that only new information will cause the market to react, and therefore it is necessary to determine whether the news contains any new information. Most news does not include any new information and therefore assuming all news will trigger abnormal market behaviour is unlikely to improve the performance of a model. Furthermore news which causes a shock, i.e., news which contains highly unexpected new information, will cause a greater change in volatility than news which contains expected information. Therefore to produce a model that factors in the arrival of news into volatility forecasts, it is beneficial to examine the content to predict the reaction to the news. This research combines the field of econometrics with machine learning and intelligent data analysis. All hypotheses tested within this thesis are tested on a large collection of stocks traded in the US, UK and Australia. To my knowledge, this is the largest dataset used for the types of experiments conducted in this thesis. In this thesis evidence is provided to suggest that asset specific news is correlated with abnormal returns, volatility, and volatility forecast errors. There is also evidence to suggest that abnormal volumes and trading activity correlate to asset specific news. This confirms the findings of previous studies though in most cases only a small dataset was used and often only one or two time series (i.e., return, volatility, volume etc.) were used. Furthermore many studies did not investigate the intraday effect of news (i.e., the reaction on the day the news was released). The studies which investigated the intraday effect tended to focus on macroeconomic news, which is scheduled and eagerly anticipated by investors. Therefore the behaviour is easier to detect that for asset specific news. It is demonstrated that the content of news can be used to forecast abnormal returns and forecast periods when the given volatility forecasting model exhibits abnormally large errors (the difference between the realised volatility and the volatility which the given model forecast) with a high degree of accuracy. This was achieved by analysing the content of past news which correlated with abnormal market behaviour. For this research a new method for ranking terms is introduced and demonstrated to be very effective. Previous studies have revealed that the content of news can be used to forecast abnormal returns but, to my knowledge, no study has investigated the volatility forecast error. Furthermore, most previous studies have used a small dataset, and to forecast at relatively low frequencies (most are daily, though one is hourly). To the best of my knowledge no previous study has use such a large dataset to predict the high frequency (as little as 5 minutes) market reaction to news. Nor has any previous study achieved classification accuracies as high as those achieved in this thesis. Finally, a news aware volatility forecasting model is produced and the evidence demonstrates that the performance is better than an alternative model which does not account for news under certain circumstances. Furthermore it is demonstrated that using the content of news to choose documents which are more likely to cause the market to react yields better forecasts. Very few researchers have included the arrival of news in a volatility forecasting model, and all of these have used small datasets. Furthermore, to my knowledge, none of these researchers have used the content of the news to choose news which is more likely to cause the market to react.

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Ghezelayagh, Bahar. "Multiscale analysis of financial volatility." Thesis, University of East Anglia, 2013. https://ueaeprints.uea.ac.uk/59252/.

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This thesis is concerned with the modeling of financial time series data. It introduces to the economics literature a set of techniques for this purpose that are rooted in engineering and physics, but almost unheard of in economics. The key feature of these techniques is that they combine the available information in the time and frequency domains simultaneously, making it possible to enjoy the advantages of both forms of analysis. The thesis is divided into three sections. First, after briefly outlining the Fourier methods, a more exible technique that allows for the study of time-scale dependent phenomena (motivated from a discussion on Heisenberg's uncertainty principle) namely Wavelet method is defined. A complete account of discrete and continuous wavelet transformations, and wavelet variation is provided and the advantages of wavelet-multiresolution analysis over Fourier methods are demonstrated. In the second section, the statistical properties of financial returns at 1-day, 5-day and 10-day sampling intervals are studied using S&P500 index for over a decade, and the links between dependence properties of financial returns at lower sampling frequencies are explored. The concepts of temporal aggregation and skip sampling are discussed and the effects of temporal aggregation on long range dependent time series are theoretically outlined and then tested through simulations and empirically via S&P500. In the third section, the variation of two years of five-minute GBP/USD exchange rate is analysed and the notion of realised variation is explored. The characteristics of the intraday data at different sampling frequencies (5-minute, 30-minute, 60-minute, 10-hour, 1-day, and 5-day) are compared with each other and filtered out from seasonalities using the wavelet multiscaling technique. We find that temporal aggregation does not change the decay rate of autocorrelation functions of long-memory data of certain frequencies, however the level at which the autocorrelation functions start from move upward for daily data. This thesis adds to the literature by outlining and comparing the effects of aggregation between daily and intra-daily frequencies for the realised variances, which to our knowledge is a first. The effect temporal aggregation has on daily data is different from intra-daily data, and we provide three reasons why this might be. First, at higher frequencies strong periodocities distort the autocorrelation functions which could bring down the decay rate and mask the long memory feature of the data. Second, the choice of realised variance is crucial in this matter and different functions can result in contradictory outcomes. Third, as the order of aggregation increases the decay rate does not depend on the order of the aggregation.

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Griffioen, Gerwin Alfred Wilhelm. "Technical analysis in financial markets." [Amsterdam : Amsterdam : Thela Thesis] ; Universiteit van Amsterdam [Host], 2003. http://dare.uva.nl/document/87469.

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Books on the topic "Financial analysis"

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Financial information analysis. Chichester: Wiley, 2001.

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Financial analysis. New York: Prentice Hall International, 1990.

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Financial analysis. 2nd ed. London: Prentice Hall, 1995.

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Chartered Institute of Management Accountants. Financial analysis. 5th ed. London: BPP Learning Media, 2008.

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Chartered Institute of Management Accountants., ed. Financial analysis. London: BPP Professional Education, 2005.

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Chartered Institute of Management Accountants, ed. Financial analysis. Oxford: Elsevier, 2007.

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Chartered Institute of Management Accountants., ed. Financial analysis. London: BPP Professional Education, 2004.

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Bragg, Steven M. Financial Analysis. New York: John Wiley & Sons, Ltd., 2006.

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Harrington, Diana R. Corporate financial analysis. 2nd ed. Plano, Tex: Business Publications, 1986.

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R, Subramanyam K., and Halsey Robert F, eds. Financial statement analysis. 8th ed. Boston, Ma: McGraw-Hill Irwin, 2003.

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Book chapters on the topic "Financial analysis"

1

Zafra-Gómez, José L. "Financial Analysis." In Global Encyclopedia of Public Administration, Public Policy, and Governance, 2176–83. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-20928-9_2282.

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Zafra-Gómez, José L. "Financial Analysis." In Global Encyclopedia of Public Administration, Public Policy, and Governance, 1–9. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31816-5_2282-1.

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Wang, Xinhao, and Rainer vom Hofe. "Financial Analysis." In Selected Methods of Planning Analysis, 173–223. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2826-2_4.

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Goel, Sandeep. "Financial analysis." In Finance for Non-Finance People, 60–110. Second edition. | Abingdon, Oxon ; New York, NY : Routledge, 2019.: Routledge India, 2019. http://dx.doi.org/10.4324/9780429196669-5.

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Kuratko, Donald F., and Jeffrey S. Hornsby. "Financial Analysis." In New Venture Management, 195–215. Third edition. | New York: Routledge, 2021.: Routledge, 2020. http://dx.doi.org/10.4324/9781003034292-12.

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Knott, Geoffrey. "Financial Analysis." In Financial Management, 13–28. London: Macmillan Education UK, 1998. http://dx.doi.org/10.1007/978-1-349-14766-3_2.

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Thibierge, Christophe, and Andrew Beresford. "Financial Analysis." In A Practical Guide to Corporate Finance, 8–46. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137492548_2.

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Baumers, Martin, and John Dominy. "Financial Analysis." In Practical Management for the Digital Age, 339–60. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003222903-17.

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Olson, Kent, and John Westra. "Financial Analysis." In The Economics of Farm Management, 212–48. 2nd ed. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003280712-13.

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Arcos-Vargas, Ángel, and Laureleen Riviere. "Financial Analysis." In Grid Parity and Carbon Footprint, 63–66. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-06064-0_5.

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Conference papers on the topic "Financial analysis"

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Namazov, Vugar. "Structured financing: linkage between commodities and financial markets." In Systems Analysis in Economics - 2020. Moscow, "Science" Publishing House, 2021. http://dx.doi.org/10.33278/sae-2020.book1.308-31.

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Haimovitch, Larry. "Financial Analysis." In The Marketplace for Medical Lasers, edited by Morris R. Levitt and Michael Moretti. SPIE, 1988. http://dx.doi.org/10.1117/12.947560.

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Trencheva, Miglena. "PREPARATION OF FINANCIAL STATEMENTS AND FINANCIAL RISK ANALYSIS." In 14th annual International Conference of Education, Research and Innovation. IATED, 2021. http://dx.doi.org/10.21125/iceri.2021.0514.

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Kontemal, Anna. "Management of the financial state of the enterprise on the basis of its analysis." In Conferința științifică internațională studențească „Provocările contabilității în viziunea tinerilor cercetători”, ediția VII. Academy of Economic Studies of Moldova, 2023. http://dx.doi.org/10.53486/issc2023.61.

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Taking into account the economic, epidemiological and military situation that has developed on the territory of our state, the study of issues of managing the financial condition of economic entities becomes relevant, because only financially stable and profitable enterprises are the basis for the stabilization and development of the economy of our state today and in the post-war period. In the process of research, it was established that the financial condition determines the real and potential ability of the enterprise to ensure a sufficient level of financing of its economic activity, a certain level of self-development and the ability to repay its obligations. Financial status management is one of the significant functional areas of the financial management system, which is related to other management systems and is based on a systematic and comprehensive assessment using various techniques and methods of analysis. With the help of coefficient, aggregate and integral methods of diagnosis, it was established that the financial condition of the enterprise is unstable, therefore the author proposed directions for ensuring its stability: increasing revenue from sales of products; reduction of production costs; increase in labor productivity; activation of sales activities; asset restructuring and receivables management.

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Sohangir, Sahar, Nicholas Petty, and Dingding Wang. "Financial Sentiment Lexicon Analysis." In 2018 IEEE 12th International Conference on Semantic Computing (ICSC). IEEE, 2018. http://dx.doi.org/10.1109/icsc.2018.00052.

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Luo, Xin, and Pei-ai Zhang. "Game analysis of financial supervision in international financial crisis." In 2011 23rd Chinese Control and Decision Conference (CCDC). IEEE, 2011. http://dx.doi.org/10.1109/ccdc.2011.5968143.

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Chu, Weimei. "Analysis of Financial Investment Risk in Enterprise Financial Management." In 6th International Conference on Financial Innovation and Economic Development (ICFIED 2021). Paris, France: Atlantis Press, 2021. http://dx.doi.org/10.2991/aebmr.k.210319.063.

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Kertkeidkachorn, Natthawut, Rungsiman Nararatwong, Ziwei Xu, and Ryutaro Ichise. "FinKG: A Core Financial Knowledge Graph for Financial Analysis." In 2023 IEEE 17th International Conference on Semantic Computing (ICSC). IEEE, 2023. http://dx.doi.org/10.1109/icsc56153.2023.00020.

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Wen, Chunran, Xu Shen, and Zhiping Zhou. "Research on the Influencing Factors of Regional Financial Risk under Internet Financial Innovation." In 2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC). IEEE, 2018. http://dx.doi.org/10.1109/spac46244.2018.8965529.

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Hasibuan, Intan, Nurhasanah Nurhasanah, Mahroji Mahroji, and Mas Cili. "Financial Ratio Analysis to Predict Financial Distress on Islamic Bank." In Proceedings of the First Annual Conference of Economics, Business, and Social Science, ACEBISS 2019, 26 - 30 March, Jakarta, Indonesia. EAI, 2020. http://dx.doi.org/10.4108/eai.26-3-2019.2290684.

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Reports on the topic "Financial analysis"

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Wooten, William. Financial Analysis of Contract Berthing. Fort Belvoir, VA: Defense Technical Information Center, December 2006. http://dx.doi.org/10.21236/ada460296.

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Fight, Roger D., Natalie A. Bolon, and James M. Cahill. Financial analysis of pruning ponderosa pine. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 1992. http://dx.doi.org/10.2737/pnw-rp-449.

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Fight, Roger D., James M. Cahlll, Thomas D. Fahey, and Thomas A. Snellgrove. Financial analysis of pruning coast Douglas-fir. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 1987. http://dx.doi.org/10.2737/pnw-rp-390.

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Seo, Young-Woo, Joseph Giampapa, and Katia Sycara. Financial News Analysis for Intelligent Portfolio Management. Fort Belvoir, VA: Defense Technical Information Center, January 2004. http://dx.doi.org/10.21236/ada599073.

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Johnson, Caley, Erin Nobler, Leslie Eudy, and Matthew Jeffers. Financial Analysis of Battery Electric Transit Buses. Office of Scientific and Technical Information (OSTI), June 2020. http://dx.doi.org/10.2172/1659784.

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Piatti-Fünfkirchen, Moritz, and Lodewijk Smets. Public Financial Management, Health Financing and Under-Five Mortality: A Comparative Empirical Analysis. Inter-American Development Bank, February 2019. http://dx.doi.org/10.18235/0001561.

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Fight, Roger D., and John T. Chmelik. Analysts guide to FEEMA for financial analysis of ecosystem management activities. Madison, WI: U.S. Department of Agriculture, Forest Service, Forest Products Laboratory, 1998. http://dx.doi.org/10.2737/fpl-gtr-111.

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Beyeler, Walter E. FY16 Analysis report: Financial systems dependency on communications. Office of Scientific and Technical Information (OSTI), March 2017. http://dx.doi.org/10.2172/1365469.

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Cooper, Russell, and Joao Ejarque. Financial Intermediation and Aggregate Fluctuations: A Quantative Analysis. Cambridge, MA: National Bureau of Economic Research, August 1994. http://dx.doi.org/10.3386/w4819.

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Karpunin, A. Yu, and E. V. Karpunina. Distance course «Analysis and Diagnostics of Financial Insolvency». OFERNIO, March 2018. http://dx.doi.org/10.12731/ofernio.2018.23536.

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