Analysis of the connectivity between the banking and other financial service companies

Aim: This milestone aims to provide a comprehensive review of the banking and financial services sector in India along with evaluating regulatory framework and identifying the sector's resilience and responsiveness to macroeconomic shifts. Delve into recent developments and regulatory changes impacting the sector. Explain why it is important for the sector to consider macroeconomic events and their effects, like policy changes or economic downturns.

Method: A literature review of the past should be done wherein the financial services and banking sector of India should be assessed. The article should discuss the status of the sector, the evolution of the sector over time, the change in the regulatory framework and also how different macroeconomic developments are contributing towards affecting the sector. For example – the outbreak of COVID-19 resulted in a rise in credit risk, banks' change towards adopting digital services or remote work, and a change in consumer behaviour. Another case could be more inflation could result in a rise in the interest rate for controlling the inflation rate. Thus, the focus is not to just state the points but to provide adequate justification, reference for justifications or figures/data, and discuss the changes due to different macroeconomic shifts.

Structure: Write an article which will carry text (review) and some statistical information-based charts to discuss about financial and banking sector of India. Use about 15-20 references at least post-2015. The structure of the article should be as follows:

• Introduction- introduce to emphasize the significance of understanding the sector's dynamics in the context of recent changes.
• Regulatory framework of banking and financial sector
• Sector performance and trends – analyse recent trends and sector performance indicators, considering factors such as market share, profitability, and innovation
• Financial ratios important for the banking and financial sector
• The reaction of the sector to macroeconomic development – explore how the sector has reacted to recent macroeconomic developments, such as policy changes, economic fluctuations, and global events.
• Major macroeconomic events which affected the banking and finance sector in India
• Conclusion- Present the need to understand the macroeconomic aspect influence on the sector
• References

Note: Use examples from well-known financial events to illustrate the impact of spillover effects.

Aim: Financial markets generally witness the existence of a spillover effect. The overall goal 1 of this study is to define the purpose of spillover effect analysis in financial analysis. This milestone should have a brief explanation of the historical context of spillover effects. There should be a focus on highlighting how financial markets are interconnected and why understanding spillover effects is crucial for investors and analysts.

Method: A literature review of 5-7 roles from the past should be done wherein it has been identified that the spillover effect has contributed to the financial market. State the identified relevance of the spillover effect individually along with benefits. For example – the assessment of the spillover effect could contribute to building an early warning system, risk management or portfolio diversification. The focus of the assessment is not just to identify the relevance but also to state how the spillover effect is contributing to the identified aspect.

Structure: Write an article which will carry text (review) of the spillover effect for the stock market. Use at least 15 references dated post-2015. The structure of the article should be as follows:

• Introduction- introduce the concept of spillover effects in financial markets
• Main body- this section will contain a synthesis of different authors’ perspectives on the purpose of assessing the spillover effect in stock market analysis
  • Role 1
  • Role 2
  • Role 3 and so on
• Conclusion- Present a diagram of the purpose and the financial market wherein this contribution of spillover effect was derived.
• References

Note: This milestone involves the systematic review method of secondary data analysis. You must have some knowledge about systematic review and PRISMA analysis in order to work on this milestone. 

Aim: The previous milestone, “Purpose of spillover effect analysis in financial markets” focused on specifically presenting the relevance of the spillover effect for the stock market. This milestone focuses on  having a systematic review of existing studies wherein the spillover effect was examined for financial markets.

Method: Systematic review of existing literature wherein spillover effect was computed and assessed for financial markets. Review only those studies which contain some form of empirical analysis and were published in A-category journals after 2010. Use the PRISMA diagram for the study selection procedure by stating the database and search strategy. The minimum number of papers selected should be 20. The findings of these studies need to be stated in table form with the given columns

• Author (year)
• Aim of the study
• Methodology
• Variables used
• Financial market considered
• Findings (nature of spillover effect)
• Limitations of the study

Here is an example systematic review.

Presentation/ structure: to achieve this milestone, write an article in the below structure.

• Introduction to spillover effect trends and patterns present in financial market analysis
• Systematic review: Start by discussing the inclusion and exclusion criteria, search terms, database, and search strategy. So the structure of this section will be:
  • Inclusion and exclusion criteria
  • Search terms
  • Database
  • Search strategy
  • PRISMA diagram
  • Systematic review table (main part)
• Discussion- summarise the findings of the studies holistically
• Conclusion
• References

Note: Some prior knowledge about systematic review and PRISMA analysis would be advantageous for working on this milestone.

Aim: ‘Spillover effect’ is a term used for explaining the impact that unrelated events in one nation can have on the economies of other nations. The aim of this milestone is to identify the models which are adopted in existing studies for studying spillover effects. Focus on theoretical models and highlight the strengths and weaknesses of each. Examine their methodologies critically.

Method: A systematic review of existing literature related to the application of different models for the spillover effect examination needs to be done. Review only those studies wherein the statistical analysis was done and the work was published in A-category journals after 2012. Use the PRISMA diagram for the study selection procedure by stating the database and search strategy. The minimum number of papers selected should be 20. The findings of these studies need to be stated in table form with the given columns

• Author (year)
• Aim of the study
• Methodology
• Model selected
• Data analysis tool used
• Variables used
• Findings (state clearly what model contributed to defining the spillover effect)
• Limitations of the study

Here is an example systematic review.

Presentation/ structure: To achieve this milestone, write an article in the below structure.

• Relevance of assessing theoretical models proposed in the past for studying spillover effects in financial markets
• Systematic review: Start by discussing the inclusion and exclusion criteria, search terms, database, and search strategy. So the structure of this section will be:
  • Inclusion and exclusion criteria
  • Search terms
  • Database
  • Search strategy
  • PRISMA diagram
  • Systematic review table (main part)
• Discussion- summarise the findings of the studies holistically
• Conclusion
• References

Note: Some prior knowledge about systematic review and PRISMA analysis would be advantageous for working on this milestone.

Aim: ‘Spillover effect’ is a term used for explaining the impact that unrelated events in one nation can have on the economies of other nations. Many authors in the past have examined the spillover effect empirically, i.e., by using numeric data of variables from these countries and examining the effect statistically. The aim of this milestone is to review studies which have specifically used the TVP-VAR test. Use systematic review method wherein the application of the TVP-VAR method for spillover effect was examined for stock price analysis.

Method: Systematic review of the existing studies wherein the TVP-VAR model was applied for the examination of the spillover effect. Review only those studies which contain some form of empirical analysis and were published in A-category journals after 2010. Use the PRISMA diagram for the study selection procedure by stating the database and search strategy. The minimum number of papers selected should be 15. The findings of these studies need to be stated in table form with the given columns

• Author (year)
• Aim of the study
• Methodology
• Variables used
• Financial market considered
• Findings (application of TVP-VAR test in spillover effect)
• Limitations of the study

Here is an example systematic review.

Presentation/ structure: to achieve this milestone, write an article in the below structure.

• Introduction to highlight the importance of understanding the TVP-VAR methodology in capturing time-varying dynamics in stock markets
• Systematic review: Start by discussing the inclusion and exclusion criteria, search terms, database, and search strategy. So the structure of this section will be:
  • Inclusion and exclusion criteria
  • Search terms
  • Database
  • Search strategy
  • PRISMA diagram
  • Systematic review table (main part)
• Discussion- summarise the findings of the studies holistically
• Conclusion
• References

Note 1: This milestone cannot be achieved until all the previous milestones in ‘Goal 1’ have been completed.

Note 2: Prior experience in making conceptual frameworks and hypotheses is mandatory in order to attempt this milestone.

Aim: This is the concluding milestone of Goal 1 of the study on “To review the relevance of the spillover effect in stock market analysis”. The purpose of the milestone is to draw the conceptual framework diagram which shows the variables representing major events and their spillover effect on the stock market.

Method: This conceptual framework will be constructed based on the information derived from the review of literature in the previous articles of milestone. The diagram must represent three distinct boxes:

• Major events (specify major macroeconomic events) – independent variable
• Changes in stock market – dependent variable

Refer to this article for an example conceptual framework diagram. You can also use your own. Do not copy-paste any diagram or image from any source.

Structure: To achieve this milestone, prepare an 1000-word article in the below structure.

• Introduction- summarise the literature's main information by constructive synthesis and not copy-pasting.
• Conceptual framework DIAGRAM for building linkage between spillover effect and stock market
• Explanatory paragraph for the diagram: explain the relationship
• Hypotheses: draw hypotheses from the diagrams. They must be in null (H0) and alternate (H1) format.
• Concluding paragraph: Summarize the key findings

Aim: The milestone aims to have a review of the major macroeconomic events which affect the banking and financial services. The previous milestone, “Review of the banking and financial services sector of India (including regulatory framework and reactions to macroeconomic developments)”, identified that there is the existence of macroeconomic events which affect the functioning of these sectors. Though each event is significant, some of the major events have led to changes in economies across the world. These events hold a major role in defining the functioning of the sectors. Thus, while working on enhancing banking and financial sector functioning, it is required to identify the major macroeconomic events which affected the sector and their impact.

Method: A literature review of past research needs to be done to identify the impact of major macroeconomic events. The researchers identified the oil crisis of 2007, the 2011 environmental crisis (earthquake and tsunami in Japan), COVID-19 pandemic, and the 2022 Russia-Ukraine war are the main significant events which marked the change for the banking and financial sector. This article will discuss the environmental conditions which led to the event and how these events affected the sector. For example – the oil crisis resulted in banking providing credit to customers at lower prime rates and lending funds even to risky customers. Thus, the article is not aiming towards just stating the events but also defining these events' impact by providing adequate justification and references.  

Structure: Write this article based on text (review) and some numerical details for discussing the impact of the macroeconomic event. Use about 15-20 references at least post-2010. The structure of the article should be as follows:

• Introduction- introduce to influence of different macroeconomic events on the banking and financial sector
• The oil crisis of 2007 and its impact – state about the crisis, what led to the crisis, what its impact and mainly how it affected the banking and financial sector of India
• The environmental crisis of 2011 and its impact – state about the crisis, what led to the crisis, what its impact and mainly how it affected the banking and financial sector of India
• COVID-19 and its impact– state about the crisis, what led to the crisis, what its impact and mainly how it affected the banking and financial sector of India
• Russia-Ukraine war and its impact – state about the crisis, what led to the crisis, what was its impact and mainly how it affected the banking and financial sector of India
• Conclusion- Present the need to understand the macroeconomic aspect influence on the sector
• References

Note 1: This milestone cannot be achieved until the previous milestone ‘Conceptual framework, variables and hypotheses’ is completed.

Note 2: Prior experience in writing research methodologies is mandatory for working on this milestone.

Note 3: This milestone involves collection of numeric data from secondary sources. Therefore prior experience in data mining from economics/ statistical data websites like World Bank, RBI, etc. is preferred.

Aim: This is the first milestone in Goal 2 of this study. Overall, the goal is to use primary data of consumers from India to show how online influencers are affecting their perception and purchasing action towards any product or brand. The purpose of this particular milestone is to explain the methodological process undertaken to achieve this goal.

Background: The study aims to examine the spillover effect examination for the banking and finance sector. This spillover effect examination is dual-step based i.e.

• Spillover effect for banking stocks – the examination is to assess how different companies in the banking sector are witnessing the spillover effect
• Spillover effect for banking and finance stocks – the examination is to determine which of the subsidiaries of the banking and finance sector are having a dominant spillover effect

Method: The study will include data from 2005 to 2023 which is collected for the closing price and opening price of banking companies and their subsidiaries companies stocks, along with other macroeconomic data like inflation, GDP, or exchange rate based on Goal 1. Even data for some of the financial ratios like P/E or ROI could be integrated based on the role of the control variable as identified in Goal 1. Use references to support and justify your approaches. Herein, the focus would be on understanding the interconnectivity between selected banking stocks only and the interconnectivity between banking stocks and the other subsidiary companies' stocks

After you collect this data, send the files to the Module Creator. Upload the data for all companies of the banking sector in 1 worksheet of a single Excel file. Create separate worksheets in a single Excel file for each sector of the banking and finance sector.

Structure: to achieve this milestone, write a 1000-word article in the following structure.

• Introduction – summarize the importance of assessing inter-connectivity
• Findings of the conceptual framework (brief description of the findings of the previous milestone)
• Introduction to our chosen methodology (use of secondary data to achieve the goal)
• Data collection process
  • Data source: BSE, World Bank, or other open-access database
  • Data period - 1^st January 2005-31^st December 2023
  • Banking and financial sector subsidiaries - like NBFC, insurance, housing finance, and other financial service-based companies like microfinance.
  • List of companies for each sector (financial services and banking)
  • Variables considered
  • Events considered
    • 2007 oil crisis
    • 2011 environmental crisis
    • 2019 Covid-19 pandemic
    • 2022 Russia-Ukraine war
• Data analysis procedure
  • Tool - R language
  • Data processing – to eliminate the missing values data and clear the data
  • Analysis method – descriptive analysis, trend analysis, assumption testing (stationarity, co-integration), correlation, correlation, total connectedness table, net connectedness graph, total connectedness index, and deduction about the nature of fluctuation
• Concluding paragraph: Reiterate the expected findings from the proposed hypotheses.
• References

Note 1: This milestone involves using R software for statistical analysis. Prior experience in statistical analysis and R software is therefore mandatory.

Note 2: This milestone involves analysis of the data collected in the previous milestone “Methodology of applying the TVP VAR test”. Therefore you cannot proceed with this milestone until the previous milestone is completed. Get in touch with the Module Creator to obtain the data.

Aim: Trend analysis is a critical statistical analysis method which represents patterns and trends of an industry using graphs. For example, sales and revenues of a company for 10-year period can be examined graphically by using trend analysis. This article aims to perform trend analysis of banking stock prices for BSE index.

Method: The article performs data analysis for the top 10 companies of each banking and financial sector companies. The data presented for the closing price and return of these companies for the period 1^st January 2005-31^st to December 2023 was collected in the previous milestone i.e. “Methodology of applying the TVP VAR test”. R language must be used for analysis and presenting trend analysis. For simplified presentation, you can have comparative trend presentation of companies using this link.

Structure: to achieve this milestone, write a 1000-word article in the following structure after performing the test in R software.

Avoid using too much text to explain. It must not repeat what is already being seen in the graph.

• Introduction – present the need for trend analysis for this study and summarize the variables and methodology considered for this trend analysis.
• Descriptive statistics – number of observations, mean, std. deviation, skewness, kurtosis
• Trend analysis for each sector and its statistical explanation of observed trends, emphasizing their relevance in the banking sector.
• Conclusion - Summarize key findings from the trend analysis of banking stock prices using the R language

Note 1: This milestone involves using R software for statistical analysis. Prior experience in statistical analysis and R software is therefore mandatory.

Note 2: This milestone involves analysis of the data collected in the previous milestone “Methodology of applying the TVP VAR test”. Therefore you cannot proceed with this milestone until the previous milestone is completed. Get in touch with the Module Creator to obtain the data.

Aim: In statistics, time series datasets need to be checked for stationarity first. In this study, we are aiming to examine the spillover effect of BSE banking stocks for the time period 2005-2023. Therefore the aim of this milestone is to conduct the stationarity test on the dataset and to present comprehensive results from the test.

Method: The dataset has data of closing price and opening price, macroeconomic indicators (inflation, GDP, or exchange rate), and financial ratios (P/E or ROI). These variables' selections are based on goal 1. The data of these companies was collected for the period 1^st January 2005-31^st to December 2023. As stock market is volatile leading to daily fluctuations in stock prices, so to stabilize the data, compute the return (closing price – opening price). The dynamic nature of the dataset can also be understood by checking the previous milestone “Trend analysis of India’s banking stock prices”.

Use R language for performing the stationarity test using ADF stationarity method. Each of the variable for each of the companies must be assessed. For processing, firstly compute return and then perform ADF test for return data, selected macroeconomic variables and financial ratios in milestone 1 for all companies and sectors. For the procedure of stationarity analysis, you can refer to this video.

Structure: to achieve this milestone, write a 1000-word article after completing the analysis using R software in the following structure. Avoid presentation of too much text and make the article more precise by explaining significance of values.

• Introduction – present the need for stationarity analysis for this study and how the stock prices and other variables have the presence of a trend.
• Return computation to detrend the stock prices
• Stationarity test – using adf test for all variables stationarity test and its statistical explanation
• Conclusion - Summarize key findings from the stationarity test of all variables using the R language
• References

Note 3: Your submission must include R files, your analysis results, dataset in MS Excel format, and write-up of the article in MS Word format.

Note 1: This milestone involves using R software for statistical analysis. Prior experience in statistical analysis and R software is therefore mandatory.

Note 2: This milestone involves analysis of the data collected in the previous milestone “Methodology of applying the TVP VAR test”. Get in touch with the Module Creator to obtain the data. Do not proceed with this milestone unless the previous one is completed.

Note 3: Your submission must include R files, your analysis results, dataset in MS Excel format, and write-up of the article in MS Word format.

Aim: In time series, to assess the long term and short term relationship between variables, co-integration between the variables is tested. For this, johansen cointegration test is used. In this study the aim to determine the spillover effect in presence of many macroeconomic factors and the financial ratios. Therefore, understanding of long term linkage between the variables i.e. return and other selected macroeconomic factors and financial ratios is also essential. The aim of this milestone is to explore and analyze the co-integration relationships for macroeconomic factors, financial ratios and banking stock prices.

Method: Perform Johansen Cointegration test for all the companies of each banking and financial sector companies. The data is presented for the return, macroeconomic indicators (inflation, GDP, or exchange rate), and financial ratios(P/E or ROI). The data of companies for these variables was collected for the period 1^st January 2005-31^st to December 2023 in goal 1. To work on this knowledge of milestones 1, 2 and 3 of goal 2 is essential.

For having better understanding of the dataset and their nature you should refer to already completed milestones. Use R language for the analysis and study of the cointegration relationship between macroeconomic factors and banking stock prices. You should use Johansen cointegration test for analysis and herein consider all the variables i.e. return, , macroeconomic indicators (inflation, GDP, or exchange rate), and financial ratios(P/E or ROI). ‘Returns’ will be dependent variable. Include constant in your analysis. The details of the Johansen cointegration method can be read here and its application could be seen here.

Structure: to achieve this milestone, write a 1000-word article along with performing the analysis. Be precise with writing and avoid repetition of the same values which have inserted in table

• Introduction – present the need for cointegration analysis for this study
• Cointegration analysis– using a cointegration test and its statistical explanation. The table of results could have values of cointegration equation, trace statsitics, critical value, and prob.
• Conclusion - Summarize key findings about long-term and short-term relationships between variables from the cointegration test of all variables using the R language
• References

Note 1: This milestone involves using R software for statistical analysis. Prior experience in statistical analysis and R software is therefore mandatory

Note 2: This milestone involves analysis of the data collected in the previous milestone “Methodology of applying the TVP VAR test”. Get in touch with the Module Creator to obtain the data. This milestone cannot be achieved until all the previous milestones in ‘Goal 1’ and Goal 2 have been completed.

Note 3: Your submission must include R files, your analysis results, dataset in MS Excel format, and write-up of the article in MS Word format.

Aim: In time series, the correlation analysis need to be performed for understanding the relationship between variables. The overall aim of this study is to establish the presence of spillover effect of banking stocks on other financial services stocks. But for this, we need to establish the linkage between the variables in order to understand whether the macroeconomic factors and the financial ratios have contribution in the affected stocks or not. Therefore, to meet this need, the article aims to assess the correlation between macroeconomic factors, financial ratios and banking stock prices.

Method: Perform correlation analysis for all the companies of each banking and financial sector companies. The data is presented for the return, macroeconomic indicators (inflation, GDP, or exchange rate), and financial ratios(P/E or ROI). The data of companies for these variables was collected for the period 1^st January 2005-31^st to December 2023 in goal 1.

Although there are different methods of doing correlation analysis like using coefficient like Pearson, visual presentation of correlation is also effective as it conveys the status of linkage between the variables. The aim of this milestone is not on understanding correlation magnitude but to determine spillover effect. Therefore, visual presentation of correlation is enough. Use R language to conduct the correlation analysis with cor() function and the Pearson method. Then generate the heatmap for correlation. The analysis procedure with R is explained here and here.

Structure: to achieve this milestone, write a 1000-word article in the following structure after performing the correlation analysis in R language.

• Introduction – present the need for correlation and how visual presentation is better than numeric.
• Correlation matrix – present the correlation matrix values for macroeconomic factors and return
• Correlation heatmap - explain the different shades of correlation and interpret them to briefly explain the correlation between the variables
• Conclusion - Summarize key findings from the correlation test of all variables using the R language

Note 1: This milestone involves using R software for statistical analysis. Prior experience in statistical analysis and R software is therefore mandatory

Note 2: This milestone involves analysis of the data collected in the previous milestone “Methodology of applying the TVP VAR test”. Get in touch with the Module Creator to obtain the data. This milestone cannot be achieved until all the previous milestones in ‘Goal 1’ and Goal 2 have been completed.

Note 3: Prior knowledge/ experience in conducting TVP-VAR test is mandatory to work on this milestone.

Note 4: Your submission must include R files, your analysis results, dataset in MS Excel format, and write-up of the article in MS Word format.

Aim: Oil crisis of 2007 affected the financial markets and asset price. During this time, banks were affected by each others’ performance due to inter-connectedness in interbank lending, credit exposure, system risk, or payment and settlement system. To determine the dominant ones we must assess the connection between banks and how oil crisis has affected this interconnectedness. Therefore, the aim of this milestone is to build TVP-VAR model for assessing the spillover effect on the banking stocks during the oil crisis.

Method: Perform the TVP VAR test for all the companies. The dataset includes data of return, macroeconomic indicators and financial indicators for the period 1^st January 2005-31^st to December 2023. The knowledge of all the previous milestones 2 is essential for building TVP-VAR model.

Set the model using connectedness approach. Once the model is set, use the commands like PlotTC, PlotNC, and PlotTCI for building the graphs and study the interlinkage between variables. You can visit the link for the procedure. Use R language for performing this analysis.

Structure: to achieve this milestone, write a 1000-word article in the following structure after performing the correlation analysis in R language.

• Introduction – present the oil crisis's impact on banking sector companies and its spillover effect
• Findings of total connectedness test
• Findings of net connectedness test
• Findings of Total connectedness index
• Conclusion - Summarize key findings by discussing the nature of fluctuations around the oil crisis

Note 1: This milestone involves using R software for statistical analysis. Prior experience in statistical analysis and R software is therefore mandatory

Note 2: This milestone involves analysis of the data collected in the previous milestone “Methodology of applying the TVP VAR test”. Get in touch with the Module Creator to obtain the data. This milestone cannot be achieved until all the previous milestones in ‘Goal 1’ and Goal 2 have been completed.

Note 3: Prior knowledge/ experience in conducting TVP-VAR test is mandatory to work on this milestone.

Note 4: Your submission must include R files, your analysis results, dataset in MS Excel format, and write-up of the article in MS Word format.

Aim: Environmental crises are known to affect the banking sector. For example, after the 2011 earthquake and tsunami stricked Japan, the third largest economy of world, there has been reduction in global economic growth and increased volatility for the financial markets across world. This is called the ‘spillover effect’. The overall aim of this module is to examine the presence of the spillover effect of banking stocks on other financial services stocks. The aim of this particular milestone is to assess the spillover effect on banking stocks during the environmental crisis by building  TVP-VAR model.

Method: Perform the TVP VAR test for all the companies. The dataset includes data of return, macroeconomic indicators and financial indicators for the period 1^st January 2005-31^st to December 2023. The knowledge of all the previous milestones 2 is essential for building TVP-VAR model.

Set the model using connectednessapproach. Once the model is set, use the commands like PlotTC, PlotNC, and PlotTCI for building the graphs and study the interlinkage between variables. You can visit the link for the procedure. Use R language for analysis.

Structure: to achieve this milestone, write a 1000-word article in the following structure and also complete the analysis.

• Introduction – present the environmental crisis impact on banking sector companies and its spillover effect
• Findings of Total connectedness
• Findings of Net connectedness
• Findings of Total connectedness index
• Conclusion - Summarize key findings by discussing the nature of fluctuations around the environmental crisis
• References

Note 1: This milestone involves using R software for statistical analysis. Prior experience in statistical analysis and R software is therefore mandatory

Note 2: This milestone involves analysis of the data collected in the previous milestone “Methodology of applying the TVP VAR test”. Get in touch with the Module Creator to obtain the data. This milestone cannot be achieved until all the previous milestones in ‘Goal 1’ and Goal 2 have been completed.

Note 3: Prior knowledge/ experience in conducting TVP-VAR test is mandatory to work on this milestone.

Note 4: Your submission must include R files, your analysis results, dataset in MS Excel format, and write-up of the article in MS Word format.

Aim: COVID-19 also has been the global event which resulted in creating high volatility and instability in the global financial market. This is called the ‘spillover effect’. The overall aim of this module is to examine the presence of the spillover effect of banking stocks on other financial services stocks. The aim of this particular milestone is to understand spillover effect of banking stocks on other financial services stocks for BSE index during the Covid-19 pandemic using the TVP-VAR model.

Method: Perform the TVP VAR test for all the companies. The dataset includes data of return, macroeconomic indicators and financial indicators for the period 1^st January 2005-31^st to December 2023. The knowledge of all the previous milestones 2 is essential for building TVP-VAR model.

Set the model using connectednessapproach. Once the model is set, use the commands like PlotTC, PlotNC, and PlotTCI for building the graphs and study the interlinkage between variables. Visit the link for the procedure. R language will be used for analysis.

Structure: to achieve this milestone, write a 1000-word article in the following structure and also complete the analysis .

• Introduction – present the COVID-19 impact on banking sector companies and its spillover effect
• Findings of Total connectedness
• Findings of Net connectedness
• Findings of Total connectedness index
• Conclusion - Summarize key findings by discussing the nature of fluctuations around COVID-19
• References

Note 1: This milestone involves using R software for statistical analysis. Prior experience in statistical analysis and R software is therefore mandatory

Note 2: This milestone involves analysis of the data collected in the previous milestone “Methodology of applying the TVP VAR test”. Get in touch with the Module Creator to obtain the data. This milestone cannot be achieved until all the previous milestones in ‘Goal 1’ and Goal 2 have been completed.

Note 3: Prior knowledge/ experience in conducting TVP-VAR test is mandatory to work on this milestone.

Note 4: Your submission must include R files, your analysis results, dataset in MS Excel format, and write-up of the article in MS Word format.

Aim: the Russia-Ukraine War had a compounding effect on stock prices across the world. As the war resulted in tightening financial conditions and having persistent high inflation, the economic position of countries across the world was also affected. This is called the ‘spillover effect’. The overall aim of this module is to examine the presence of the spillover effect of banking stocks on other financial services stocks. The aim of this particular milestone is to examine the spillover effect of banking stocks on other financial services stocks listed on BSE during the Russia-Ukraine war using the TVP-VAR model.

Method: Perform the TVP-VAR analysis for all banking companies. The data includes the variables of return, macroeconomic indicators and financial indicators. The data of these companies was collected for the period 1^st January 2005-31^st to December 2023.

Set the model using connectednessapproach. Once the model is set, use the commands like PlotTC, PlotNC, and PlotTCI for building the graphs and study the interlinkage between variables. You can visit the link for the procedure. Use R language for analysis.

Structure: to achieve this milestone, write a 1000-word article in the following structure and complete the analysis.

• Introduction – present the Russia-Ukraine war's impact on banking sector companies and its spillover effect
• Findings of Total connectedness
• Findings of Net connectedness
• Findings of Total connectedness index
• Conclusion - Summarize key findings by discussing the nature of fluctuations around the Russia-Ukraine war

Note 1: This milestone involves using R software for statistical analysis. Prior experience in statistical analysis and R software is therefore mandatory

Note 2: The data for milestone depends upon all the previous milestone titled “Interconnectedness of banking stocks concerning the Russia-Ukraine war using TVP-VAR analysis”. Therefore you must not proceed with this milestone unless the previous one is completed.

Note 3: Prior knowledge of TVP-VAR test is mandatory to work on this milestone.

Note 4: Your submission must include R files, your analysis results, dataset in MS Excel format, and write-up of the article in MS Word format.

Aim: So far in this study, we have examined the presence of spillover effect in the banking and financial services stocks listed in BSE index for different events between 2005 and 2023. We studied the 2007 oil crisis, 2011 environmental crisis, 2019 Covid-19 pandemic and the 2022 Russia-Ukraine war. These effects were studied in different milestones. The aim of this milestone is to summarise the findings from those milestones and conclude the study in relation to the overall goal, i.e. “is there a spillover effect of banking stocks on financial services stocks for the Bombay Stock Exchange?”

Method: Firstly, read all the previous milestones in this study. Every milestone is important for understanding the context. Then compare the findings from each of the events, i.e., 2007 oil crisis, 2011 environmental crisis, 2019 Covid-19 pandemic and the 2022 Russia-Ukraine war with the findings from secondary research, i.e., already published research papers examining spillover effect. Finally, critically review our study’s findings in context of the study goal. Each crisis impact and the deductions should be supported with the literature published in A rated journal. About 4-5 papers for each crisis should be used.

Structure: Write an article which will carry text (review) of the spillover effect for the banking stocks. The structure of the article should be as follows:

• Introduction- introduce the spillover effect for the banking companies. Don’t copy-paste anything from the previous article. Base the work on constructive synthesis.
• Main body- this section will contain a synthesis of key findings of milestones 6, 7, 8, and 9 and their critical review using different authors’ perspectives on the existence of spillover effect in banking sector companies and the contribution of identified dominant companies
  • Oil crisis
  • Environmental crisis
  • COVID-19
  • Russia-Ukraine war
• Conclusion- Present a diagram denoting which companies under each had a dominant role in the banking sector and how.
• References

Note 1: This milestone involves using R software for statistical analysis. Prior experience in statistical analysis and R software is therefore mandatory

Note 2: This milestone involves analysis of the data collected in the previous milestone “Methodology of applying the TVP VAR test”. Get in touch with the Module Creator to obtain the data. This milestone cannot be achieved until all the previous milestones in ‘Goal 1’ and Goal 2 have been completed.

Note 3: Prior knowledge/ experience in conducting TVP-VAR test is mandatory to work on this milestone.

Note 4: Your submission must include R files, your analysis results, dataset in MS Excel format, and write-up of the article in MS Word format.

Aim: Oil crisis of 2007 affected the financial markets. During this time, banks were affected by each others’ performance due to inter-connectedness in interbank lending, credit exposure, system risk, or payment and settlement system. This is called the ‘spillover effect’. The overall aim of this module is to examine the presence of the spillover effect of banking stocks on other financial services stocks. Therefore, the aim of this milestone is to build TVP-VAR model for assessing the spillover effect of the banking subsidiary stocks on the financial services stocks for the Bombay Stock Exchange after the 2007 oil crisis. “Banking subsidiary stocks” include NBFC, insurance, housing finance, and microfinance stocks.

Method: Perform the TVP VAR test for all the companies. The dataset includes data of return, macroeconomic indicators and financial indicators for the period 1^st January 2005-31^st to December 2023. The knowledge of all the previous milestones 2 is essential for building TVP-VAR model.

Set the model using connectedness approach. Once the model is set, use the commands like PlotTC, PlotNC, and PlotTCI for building the graphs and study the interlinkage between variables. You can visit the link for the procedure. Use R language for performing this analysis.

Structure: to achieve this milestone, write a 1000-word article in the following structure after performing the correlation analysis in R language.

• Introduction – present the oil crisis's impact on banking subsidiary companies and its spillover effect
• Findings of total connectedness test
• Findings of net connectedness test
• Findings of Total connectedness index
• Conclusion - Summarize key findings by discussing the nature of fluctuations around the oil crisis

 

Note 1: This milestone involves using R software for statistical analysis. Prior experience in statistical analysis and R software is therefore mandatory

Note 2: This milestone involves analysis of the data collected in the previous milestone “Methodology of applying the TVP VAR test”. Get in touch with the Module Creator to obtain the data. This milestone cannot be achieved until all the previous milestones in ‘Goal 1’ and Goal 2 have been completed.

Note 3: Prior knowledge/ experience in conducting TVP-VAR test is mandatory to work on this milestone.

Note 4: Your submission must include R files, your analysis results, dataset in MS Excel format, and write-up of the article in MS Word format.

Aim: Environmental crises are known to affect the banking sector. For example, after the 2011 earthquake and tsunami stricked Japan, the third largest economy of world, there has been reduction in global economic growth and increased volatility for the financial markets across world. This is called the ‘spillover effect’. The overall aim of this module is to examine the presence of the spillover effect of banking stocks on other financial services stocks. Therefore, the aim of this milestone is to build TVP-VAR model for assessing the spillover effect of the banking subsidiary stocks on the financial services stocks for the Bombay Stock Exchange after the 2011 environmental crisis. “Banking subsidiary stocks” include NBFC, insurance, housing finance, and microfinance stocks.

Method: Perform the TVP VAR test for all the companies. The dataset includes data of return, macroeconomic indicators and financial indicators for the period 1^st January 2005-31^st to December 2023. The knowledge of all the previous milestones 2 is essential for building TVP-VAR model.

Set the model using connectednessapproach. Once the model is set, use the commands like PlotTC, PlotNC, and PlotTCI for building the graphs and study the interlinkage between variables. You can visit the link for the procedure. Use R language for analysis.

Structure: to achieve this milestone, write a 1000-word article in the following structure and also complete the analysis.

• Introduction – present the environmental crisis impact on banking sector companies and its spillover effect
• Findings of Total connectedness
• Findings of Net connectedness
• Findings of Total connectedness index
• Conclusion - Summarize key findings by discussing the nature of fluctuations around the environmental crisis
• References

 

Note 1: This milestone involves using R software for statistical analysis. Prior experience in statistical analysis and R software is therefore mandatory

Note 2: This milestone involves analysis of the data collected in the previous milestone “Methodology of applying the TVP VAR test”. Get in touch with the Module Creator to obtain the data. This milestone cannot be achieved until all the previous milestones in ‘Goal 1’ and Goal 2 have been completed.

Note 3: Prior knowledge/ experience in conducting TVP-VAR test is mandatory to work on this milestone.

Note 4: Your submission must include R files, your analysis results, dataset in MS Excel format, and write-up of the article in MS Word format.

Aim: COVID-19 also has been the global event which resulted in creating high volatility and instability in the global financial market. This is called the ‘spillover effect’. The overall aim of this module is to examine the presence of the spillover effect of banking stocks on other financial services stocks. Therefore, the aim of this milestone is to build TVP-VAR model for assessing the spillover effect of the banking subsidiary stocks on the financial services stocks for the Bombay Stock Exchange after the 2019 pandemic. “Banking subsidiary stocks” include NBFC, insurance, housing finance, and microfinance stocks.

Method: Perform the TVP VAR test for all the companies. The dataset includes data of return, macroeconomic indicators and financial indicators for the period 1^st January 2005-31^st to December 2023. The knowledge of all the previous milestones 2 is essential for building TVP-VAR model.

Set the model using connectednessapproach. Once the model is set, use the commands like PlotTC, PlotNC, and PlotTCI for building the graphs and study the interlinkage between variables. Visit the link for the procedure. R language will be used for analysis.

Structure: to achieve this milestone, write a 1000-word article in the following structure and also complete the analysis .

• Introduction – present the COVID-19 impact on banking sector companies and its spillover effect
• Findings of Total connectedness
• Findings of Net connectedness
• Findings of Total connectedness index
• Conclusion - Summarize key findings by discussing the nature of fluctuations around COVID-19
• References

 

Note 1: This milestone involves using R software for statistical analysis. Prior experience in statistical analysis and R software is therefore mandatory

Note 2: This milestone involves analysis of the data collected in the previous milestone “Methodology of applying the TVP VAR test”. Get in touch with the Module Creator to obtain the data. This milestone cannot be achieved until all the previous milestones in ‘Goal 1’ and Goal 2 have been completed.

Note 3: Prior knowledge/ experience in conducting TVP-VAR test is mandatory to work on this milestone.

Note 4: Your submission must include R files, your analysis results, dataset in MS Excel format, and write-up of the article in MS Word format.

Aim: the Russia-Ukraine War had a compounding effect on stock prices across the world. As the war resulted in tightening financial conditions and having persistent high inflation, the economic position of countries across the world was also affected. This is called the ‘spillover effect’. The overall aim of this module is to examine the presence of the spillover effect of banking stocks on other financial services stocks. Therefore, the aim of this milestone is to build TVP-VAR model for assessing the spillover effect of the banking subsidiary stocks on the financial services stocks for the Bombay Stock Exchange after the 2022 Ukraine-Russia war. “Banking subsidiary stocks” include NBFC, insurance, housing finance, and microfinance stocks.

Method: Perform the TVP-VAR analysis for all banking companies. The data includes the variables of return, macroeconomic indicators and financial indicators. The data of these companies was collected for the period 1^st January 2005-31^st to December 2023.

Set the model using connectednessapproach. Once the model is set, use the commands like PlotTC, PlotNC, and PlotTCI for building the graphs and study the interlinkage between variables. You can visit the link for the procedure. Use R language for analysis.

Structure: to achieve this milestone, write a 1000-word article in the following structure and complete the analysis.

• Introduction – present the Russia-Ukraine war's impact on banking sector companies and its spillover effect
• Findings of Total connectedness
• Findings of Net connectedness
• Findings of Total connectedness index
• Conclusion - Summarize key findings by discussing the nature of fluctuations around the Russia-Ukraine war

 

Note 1: This milestone involves using R software for statistical analysis. Prior experience in statistical analysis and R software is therefore mandatory

Note 2: The data for milestone depends upon all the previous milestone titled “Interconnectedness of banking stocks concerning the Russia-Ukraine war using TVP-VAR analysis”. Therefore you must not proceed with this milestone unless the previous one is completed.

Note 3: Prior knowledge of TVP-VAR test is mandatory to work on this milestone.

Note 4: Your submission must include R files, your analysis results, dataset in MS Excel format, and write-up of the article in MS Word format.

Aim: So far in this study, we have examined the presence of spillover effect in the banking subsidiary stocks and financial services stocks listed in BSE index for different events between 2005 and 2023. We studied the 2007 oil crisis, 2011 environmental crisis, 2019 Covid-19 pandemic and the 2022 Russia-Ukraine war. These effects were studied in different milestones. The aim of this milestone is to summarise the findings from milestones related to banking subsidiary stocks and conclude the study in relation to the overall goal, i.e. “is there a spillover effect of banking subsidiary stocks on financial services stocks for the Bombay Stock Exchange?”

Method: Firstly, read all the previous milestones in this study. Every milestone is important for understanding the context. Then compare the findings from each of the events, i.e., 2007 oil crisis, 2011 environmental crisis, 2019 Covid-19 pandemic and the 2022 Russia-Ukraine war with the findings from secondary research, i.e., already published research papers examining spillover effect. Finally, critically review our study’s findings in context of the study goal. Each crisis impact and the deductions should be supported with the literature published in A rated journal. About 4-5 papers for each crisis should be used.

Structure: Write an article which will carry text (review) of the spillover effect for the banking stocks. The structure of the article should be as follows:

• Introduction- introduce the spillover effect for the banking companies. Don’t copy-paste anything from the previous article. Base the work on constructive synthesis.
• Main body- this section will contain a synthesis of key findings of milestones 6, 7, 8, and 9 and their critical review using different authors’ perspectives on the existence of spillover effect of banking subsidiary companies on the overall banking sector and the contribution of identified dominant companies
  • Oil crisis
  • Environmental crisis
  • COVID-19
  • Russia-Ukraine war
• Conclusion- Present a diagram denoting which companies under each had a dominant role in the banking sector and how.
• References

 

Note 1: This milestone depends upon the findings of the previous milestone ‘Status of spillover effect for banking stocks and its subsidiaries’. Therefore you cannot proceed with this until the previous milestone has been completed.

Note 2: Knowledge of R language, TVP VAR test and the concept of spillover effect is mandatory to work on this milestone.

Aim: In this study so far, we have seen how banking stocks and banking subsidiary (insurance, NBFCs, microfinance) stocks performance have a spillover effect on the overall banking sector. This overall study is split into two goals. In the first goal we identified the factors which are relevant in the spillover analysis. In the second goal we analysed the spillover effect for all banking and its subsidiary stocks for the Bombay Stock Exchange for four major events between 2005 and 2023. Now the aim of this milestone is to explain how the banking and financial services sectors can use the findings of this study to make strategic decisions related to risk management, resource allocation and improvement of overall resilience of the companies.

Method: Firstly, read all the previous milestones in this study. Every milestone is important for understanding the context. Then compare the findings from each of the events, i.e., 2007 oil crisis, 2011 environmental crisis, 2019 Covid-19 pandemic and the 2022 Russia-Ukraine war with the findings from secondary research, i.e., already published research papers examining spillover effect.

Next, critically review real-world examples in context of spillover effect. Show how managers and stakeholders from the financial services industry have used spillover effect to make important decisions to improve their financial health such as risk management (for making diversification strategies), asset allocation, credit risk assessment (to making informed lending decisions and sensitivity analysis), and regulatory compliance.

Do not explain any theory here. Focus on the case analysis with sufficient statistical evidence. Do not copy-paste any information from the previous milestones or any other source. The analysis should be a synthesis of the data, not reframing.

Structure. In order to achieve this milestone, write a 1000 words article in the below format.

• Introduction to ‘spillover effect’ study in stock markets, and its relevance in the banking and financial services industry
• Recap of the findings of our primary study
• Application of ‘spillover effect’ for stock prices in banking sector companies (correlate our primary analysis findings with real-life case examples from the banking and financial services industry)
  • Risk management
  • Resource allocation
  • Credit risk assessment
• Practical recommendations for stakeholders – highlight the recommendation as per spillover analysis for stakeholders concerning risk mitigation, proactive strategies or investment adjustments
• Conclusion – summarize the main takeaways and stress stakeholders' urgency to apply spillover knowledge for preparing for economic uncertainties.