Big Data Analytics and Models

When uncertainty is regarded as a surprise and an event in the minds, it can be said that individuals can change the future view. Market, financial, operational, social, environmental, institutional and humanitarian risks and uncertainties are the inherent realities of the modern world. Life is suffused with randomness and volatility; everything momentous that occurs in the illustrious sweep of history, or in our individual lives, is an outcome of uncertainty. An important implication of such uncertainty is the financial instability engendered to the victims of different sorts of perils. This chapter is intended to explore big data analytics as a comprehensive technique for processing large amounts of data to uncover insights. Several techniques before big data analytics like financial econometrics and optimization models have been used. Therefore, initially these techniques are mentioned. Then, how big data analytics has altered the methods of analysis is mentioned. Lastly, cases promoting big data analytics are mentioned.

Integrative literature review of the financial fragility hypothesis proposed by Minsky

<p>This paper conducts an Integrative Literature Review on the Financial Fragility Hypothesis presented by Minsky and on Financial Fragility Applied to the Public Sector. Twenty papers were chosen that addressed the proposed theme in both quantitative and qualitative procedures. The topics discussed ways of measuring financial fragility, effects on fiscal policy and need for regulation, relations between investment, cash flow expectations, the influence of interest rates and indebtedness on firms, and financial instability. The integration reinforced the conceptual aspects and propositions presented by Minsky, broadening in an integrated way the understanding of his theoretical assumptions regarding financial fragility, addressing the causes, observations, and economic and institutional consequences, in addition to signaling for insufficiencies of more empirical studies and the public sector.</p>

Integrative literature review of the financial fragility hypothesis proposed by Minsky

<p>This paper conducts an Integrative Literature Review on the Financial Fragility Hypothesis presented by Minsky and on Financial Fragility Applied to the Public Sector. Twenty papers were chosen that addressed the proposed theme in both quantitative and qualitative procedures. The topics discussed ways of measuring financial fragility, effects on fiscal policy and need for regulation, relations between investment, cash flow expectations, the influence of interest rates and indebtedness on firms, and financial instability. The integration reinforced the conceptual aspects and propositions presented by Minsky, broadening in an integrated way the understanding of his theoretical assumptions regarding financial fragility, addressing the causes, observations, and economic and institutional consequences, in addition to signaling for insufficiencies of more empirical studies and the public sector.</p>

Banking crises and financial instability: Empirical and historical lessons

The paper examines the importance of financial instability for the development of four Norwegian banking crises. The crises are the Post First World War Crisis during the early 1920s, the mid 1920s Monetary Crisis, the Great Depression in the 1930s, and the Scandinavian Banking Crisis of 1987–1993. The paper first offers a description of the financial instability hypothesis applied by Minsky and Kindleberger, and in a recent dynamic financial crisis model. Financial instability is defined as a lack of financial markets and institutions that provide capital and liquidity at a sustainable level under stress. Financial instability basically evolves during times of overheating, overspending and extended credit granting. This is most common during significant booms. The process has devastating effects after markets have turned into a state of negative development.The paper tests the validity of the financial instability hypothesis using a quantitative structural time series model. It reveals upheaval of 10 financial and macroeconomic indicators prior to all the four crises, resulting in a state of economic overheating and asset bubble creation. This is basically explained by huge growth in debts. The overheating caused the following banking crises. Finally, the paper discusses the four crises qualitatively. Again, the conclusion is that a significant increase in money supply and debt caused overheating, asset bubbles, and thereafter, financial and banking crises, which in turn spread to other markets and industries and caused huge slumps in the real economy.

Assessing the Role of Digital Finance on Shadow Economy and Financial Instability: An Empirical Analysis of Selected South Asian Countries

The advancement in fintech technological development in emerging countries has accelerated the role of digital finance in economic development. Digital finance assists in financial inclusion; however, it may also increase the chances of financial instability due to systematic risks. Emerging countries are also in the clutches of shadow economic growth, which reduces taxable income revenue and creates pressure on financial inclusion prospects. The current study attempts to measure the impact of digital finance on the shadow economic growth and financial stability among the selected South Asian emerging countries. We have used the CUP-FM and CUP-BC estimation methods to measure the above relationship on two model frameworks from 2004 to 2018, with the former measuring the influence of digital finance on the shadow economy and the latter examining the relationship between digital finance and financial stability. In addition, the second-generation unit root test, and the Westerlund cointegration analysis are also employed to confirm the stationarity and cointegration among the variables. The result of the Westerlund’s cointegration confirms a long cointegration between the explanatory and outcome variables. Furthermore, the long-run estimation results conclude that an increase in digital finance helps in reducing the growth of the shadow economy among the selected sample countries. However, it also increases the likelihood of systematic risks and increases financial instability. The study also reveals that the control variables like unemployment and industrial productivity also have a significant influence on financial stability and the shadow economy. The findings will assist readers in comprehending how digital finance influences the shadow economy and promotes financial inclusion and stability in emerging nations.

Oil Market Shocks and Financial Instability in Asian Countries

There is no commodity whose interlinkages with the macroeconomy have been studied as extensively as oil, starting with Hamilton’s (1983) seminal study. Thousands of subsequent studies have examined the relationship between oil prices and various economic variables, including the stock market. This strand of the literature began with the pioneering work of Kling (1985). Since then, other financial markets, such as banking, have also received a fair share of analysis.

Lending standards, productivity, and credit crunches

We propose a macroeconomic model in which adverse selection in investment amplifies macroeconomic fluctuations, in line with the prominent role played by the credit crunch during the financial crisis. Endogenous lending standards emerge due to an informational asymmetry between borrowers and lenders about the riskiness of borrowers. By using loan approval probability as a screening device, banks ration credit following increases in lending risk, generating large endogenous movements in TFP, explaining why productivity often falls during crises. Furthermore, the mechanism implies that financial instability is heightened when interest rates are low.