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The Financial Institutions and Markets. history assignment help and resources: history assignment help and resources

 

 

Plymouth Business School

Module Title: Financial Institutions and Markets

 

 

Case Studies Coursework Module Code: ACF201

 

 

By (Name)

 

Case 1: The Economic (And Non-Economic) Impact of ‘Brexit’ On the UK’s Financial
Services Sector

 

Brexit will have both economic and non-economic impacts on the UK’s financial service sector and EU members. UK’s financial services sector contributes imperatively to the UK’s overall economy. Based on the 2013 statistical data, the UK’s financial services sector contributes over £60 billion a year in a tax that employs over 1.1 million people. It is estimated that around £200 billion annual financial revenue trickle into the UK economy from the financial services sector. This takes into account both banking services and other related professional services. The UK economy is dependent on the health of the financial services sector. Therefore, the British exit from the European Union will significantly impact the health of the UK’s financial services sector. The paper aims to discuss the economic (and non-economic) impact of ‘Brexit’ on the UK’s financial services sector.

The British exit from the European Union has had economic impact on the workforce in financial services. As pointed out previously, the sector employs over 2.2 million people. This takes into account employee in the management consultancy, legal services, and accounting services. It is estimated that Brexit will lead to a loss of over 483,000 employees in the management consultancy, 314,000 in the legal services, and approximately 391,000 employees in the accounting services (James, S. and Quaglia, 2019, p.258). Most individuals depend on the well-paid employment opportunities that originate from a cluster of financial services such as legal services in UK’sUK cities. Financial Services in Manchester alone employs more than 31,000 people and approximately 26,000 and 24 000 people in Leeds and Bristol. The contraction will greatly impact the economy of these regional economies in financial services due to the British’s existence in the EU. Employees who work in legal services will find it hard to travel for work in the EU countries.

The move will also result in a contraction in the exportation of financial services. Scotland’s regional economies significantly depend on the exportation of financial services, especially to the European Union. Based on the 2017 statistical data, financial and Insurance services are the largest source of Scotland. The figure below shows Scotland’s rate of export in 2017.

Figure 1:Scotland’s Major sources of export in 2017

Scotland’s financial services are highly marketable in the EU market. EU is thus an important export market for Scotland’s financial services. Edinburgh exports up to 18% of its financial services to the European Union Market. On the other hand, London city exports up to 15% of its financial services to the EU market. Scotland, therefore, heavily rely on the EU single market for its financial services. Brexit will make it hard for Scotland to export its financial services to the EU market (Zhang, 2018, p1). The result will be an annual loss of more than £3,137 000 due to the market’s contraction for the exportation of financial services.

Brexit will have a significant economic impact on the sales and trading of financial services, resulting in a restriction on the UK’s financial services in the EU market.  This will result in a reduction in tax and revenue due to a contraction in the market size. Although the financial services would still be priced from the UK, restrictions in the sales of the UK’s financial products will negatively impact its revenue (Dhingra et al., 2018, p.9). The move will also negatively influence the management of the assets. Although portfolio management will be delegated to the UK, UK-based firms will not be allowed to distribute their financial asset in the EU market.

The exportation of the UK’s financial products into the EU market will significantly affect trade barriers. Trade barriers are trade restrictions imposed by countries to regulate the terms of trade (Campos, 2019, p.1). The EU countries are likely to impose trade barriers that will regulate the number of financial services exported to the EU markets. Trade between countries is negatively impacted by the introduction of trade barriers leading to a reduction in economic output. The introduced trade barriers will reduce the number of financial services the UK financial sector will be exported into the EU market. Besides, the cost of doing business for the UK will also increase due to the introduction of the trade barriers. The performance of the UK’s financial services in the EU markets will be negatively impacted by the introduction of trade barriers and trade tariffs.

The UK’s financial sector also be significantly affected by the reduction in foreign direct investment. The growth of the entire economy heavily relies on the level of foreign direct investment. The EU countries contribute up to 42.6% revenue to the UK’s economy from foreign direct investment. The amount of revenue received from a foreign direct investment is dependent on the country’s attractiveness to foreign investors. The UK’s financial sector has been attractive to the EU investors contributing to its growth in recent years. The attractiveness of this sector to the EU investors depend on its existence in the EU. The attractiveness of this sector to the EU investors will, therefore, negatively impacted by Brexit.

The health of the UK’s financial services sector will also be negatively impacted by the migrations regulations that will result from Brexit. Changes in rules governing migration will negatively impact the migration of skilled and unskilled workers between the UK and the EU countries. Brexit will negatively impact the free movement of professional financial services providers. Changes in the migration rules resulting from Brexit will negatively impact the health of the UK’s financial services sector.

Conclusion

Brexit will result in both economic and non-economic impacts on the         UK’s financial service sector. The performance of the UK’s financial services in the EU markets will be impacted negatively by introducing trade barriers and trade tariffs. Changes in the migration rules resulting from Brexit will negatively impact the health of the UK’s financial services sector. The British exit from the European Union will have an economic impact on the financial services workforce.

 

References

Campos, N.F., 2019. B for Brexit: A Survey of the Economics Academic Literature.

Dhingra, S., Ottaviano, G., Rappoport, V., Sampson, T. and Thomas, C., 2018. UK trade and FDI: A post‐Brexit perspective. Papers in Regional Science, 97(1), pp.9-24.

James, S. and Quaglia, L., 2019. Brexit, the city and the contingent power of finance. New political economy, 24(2), pp.258-271.

Zhang, X., 2018. The impact of financial, macroeconomic and non-economic factors on the hospitality industry in Spain and the UK.

 

 

Case 2: Bank Interest Rates for Trustworthy Customer

A yield curve refers to a structure that represents the association between time series and interest rates. The curve has the time on the x-axis and the yield values of various maturities. According to Dewachter, Iania, and Lyrio (2012), there are generally 4 yield curves categories: normal, inverted, steep, and flat curves. In a normal yield curve, the long-term yields are generally higher than the short-term yield because they involve higher risks (Gerhart and Lütkebohmert, 2019). On the other hand, an inverted yield curve is characterized by the inverse of a normal curve. In this case, short-term securities have greater yields relative to long-term securities.  A steep yield curve is characterized by a short-term yield that is normal and higher long-term yields. On the other hand, a flat yield curve has a similar yield for both long-term and short-term securities.

The yield curve theories include Pure expectation theory, which also refers to as unbiased expectation. The theory assumes that different maturities are substitutes, with the curve’s shape being determined by the market’s expectation. The expectations on the long-term and short-term interest and inflation are significantly different. This theory implies that whenever inflation and interest rates are expected to higher in the future, the resulting yield curve is normal (Choudhry, 2019). As a result, this theory is used in identifying forward interest rates (Choudhry, 2019).

Liquidity preference theory is an assertion because investors often tend to prefer short term securities. After all, long term securities are characterized by greater interest (Lavoie and Reissl, 2019). The theory suggests that investors must be able to compensate with a greater return on long-term investments. Market segmentation theory is based on the idea that detached demand and supply determinants exist for short-term securities and interplays in specific markets, thus determining the yield curve’s shape (O’Donnell, 2020). Preferred habitat theory is synonymous to the market segmentation theory since it proposes separate market participants with varied willingness and ability that determine preferred maturities (O’Donnell, 2020).

Table (1) shows the US Treasury Yield Curve Rates on 12/24/2020 obtained from the US Department of the Treasury.

Table 1:US Treasury Yield Curve Rates on 12/24/2020

Date
Yield

1 Mo
0.09

2 Mo
0.09

3 Mo
0.09

6 Mo
0.09

1 Yr
0.1

2 Yr
0.13

3 Yr
0.17

5 Yr
0.37

7 Yr
0.66

10 Yr
0.94

20 Yr
1.46

30 Yr
1.66

The yield curve is obtained by plotting the Yield (Y-Axis) and time series (Date) in the X-Axis. The resulting Yield curve for the US Department of the treasury is shown in figure (2) below.

Figure 2:Current US Treasury Yield Curve

From the Yield Curve in figure (2), it is observed that between 1 Month and 1 Year, the Yield curve is a flat one since there is no change in yield as maturity increases. From 1 Year Maturity to 30 Years Maturity, the Yield curve is observed to be a steep yield curve with an upward slope where greater risks (associated with long-term securities) have greater yield relative to short-term securities associated with lesser risks.

 

Application of Pure Expectation Theory to find interest rates expected on a two-year bond one year from now

Pure Expectation theory implies that short- and long-term rates move together. From the Yield curve in figure (2), the interest rates on a 1-year bond =0.1% while the interest rates on a 2-year bond =0.13%. From Pure Expectation theory, the interest rates on a two-year bond a year from now is computed as

Add 1 to the 2-year bond interest rates

The result is then squared.

The result is then divided by the current 1-year bond interest rates.

However, the Bank has to charge 2% higher than the expected value from the treasury bond. Therefore, the total expected interest in the 2-year Bond after 1 year

In this case, it is observed that the investor earns an equivalent return to the present interest rate of a 2-year bond. Should the investor choose to invest in a one-year bond at 0.1%, the bond yield for the following year’s Bond will have to increase to 0.16% for this investment to advantageous. It is observed that bonds with longer maturities have greater interest rates compared to those with lesser maturities.

The interest rate on two-year security if the investor attaches liquidity premiums of 0.001, 0.0015, and 0.0017 to two- and three-year bonds.

From the problem statement, the desired interest rate is on 2-year security.

The interest rate on a 2-year bond=0.13% from the Yield curve while that on a 1-Year Bond =0.1%.

The premium on a 2-year bond is therefore computed as

The Bank, however, has to charge 2% higher than the expected interest rates on the treasury bond. Therefore, the interest in a 2-year bond becomes

The minimum interest rate for five-year fixed-rate loans and how this rate would be adjusted for customers that have some credit risks

5-Year Bond has an interest rate of 0.37%. However, when a daily interest rate for a 5-year bond for the year 2020 is plotted, it is observed that the daily interest rates vary, as shown in figure (3). Using the data from National Treasury, figure (3) shows trends in 5-year bond interest rates.

Figure 3: 5 Yr. Treasury Bond Interest Rate for the Year 2020

Figure (3) observed that the interest rates on 5-year Bond were highly volatile in 2020 and seemed comparatively constant at an interest rate of 0.4%. 2020 has a year that has been characterized by uncertainties, such as the outbreak of the COVID 19 pandemic that has influenced the financial market. Figure (4) shows the 2019 graph

Figure 4:5 Yr. Treasury Bond Interest Rate for the Year 2019

Compared to the 2020 data, the 2019 interest rates from the National Treasury are relatively constant. Since a minimum fixed rate is desired, using the most recent year (202) data, the relatively constant rate of 0.4% is chosen.

Since the Bank desired to charge 2% higher, the recommended fixed rate becomes

To adjust the rate for the customers with credit risks, the liquidity premium is added to the fixed rate. The Bank’s estimate for the liquidity premium =0.9%. Therefore, for the customers that have credit risks, the fixed interest rate becomes

 

 

 

 

 

 

 

 

 

 

Reference list

Choudhry, M. (2019). Analyzing and Interpreting the Yield Curve. [online] Google Books. John Wiley & Sons. Available at: https://books.google.co.ke/books?hl=en&lr=&id=ThuMDwAAQBAJ&oi=fnd&pg=PR9&dq=pure+expectation+theory+of+yield+curves&ots=X1ZT4tSwJt&sig=MKVGaebNcz8j4lQNbmqS_f5uyGQ&redir_esc=y#v=onepage&q=pureexpectationtheoryofyieldcurves&f=false [Accessed 28 Dec. 2020].

Dewachter, H., Iania, L. and Lyrio, M. (2012). INFORMATION IN THE YIELD CURVE: A MACRO-FINANCE APPROACH. Journal of Applied Econometrics, 29(1), pp.42–64.

Gerhart, C. and Lütkebohmert, E. (2019). Empirical Analysis and Forecasting of Multiple Yield Curves. SSRN Electronic Journal.

Lavoie, M. and Reissl, S. (2019). Further insights on endogenous money and the liquidity preference theory of interest. Journal of Post Keynesian Economics, 42(4), pp.503–526.

O’Donnell, M. (2020). Yield Curve Theories and Their Applications Over Time. Senior Projects, Spring 2020. [online] Available at: https://digitalcommons.bard.edu/senproj_s2020/115/ [Accessed 28 Dec. 2020].

 

Case 3: Share Purchase

For the purchase of alpha shares, Alex has to place a limit order since the maximum amount he is capable of paying 45.

The merits and demerits

Limit order. Limit orders are involved price; if the security value is currently out of the parameter set in the limit order, the transaction will not happen. As a result, Alex should comfortably place a limit order since he is not ready to pay more than 45 for the shares.
Market order. These orders are executed on the current market price immediately. They are relevant where the priority is execution as opposed to limit order that prioritizes price. Since the priority is the price, not execution, it is not suitable for Alex.
The argument made by Jill is inaccurate. Purchasing alpha shares market order is inappropriate. Sales of the gamma shares and placing a block order can yield a lower selling price since the price paid in the block orders’ case is the average price of the involved shares. Therefore, it could result in a negative impact on the portfolio, thus inappropriate for large orders.
For the 1st crossing session, A’s order to purchase 100000 shares will match Alex’s order to sell 150000 shares at 37. Sales of the remaining 50000 Alex’s shares and 50000 B’s shares remains unmatched at the end of the 1st crossing session.
During the second cross-session, D’s order to purchase 150000 shares matches the 50000 remaining Alex’s shares, B’s order to sell 5000 shares, and E’s order to sell 50000 shares. By the end of the send crossing session, C’s purchase of 20000 shares at 36 remains unfilled.
European electronic crossing is cheap and capable of preserving anonymity that allows for 6 crossing opportunities of trade daily. They are also known to allow participants to place restrictions, for instance, minimum fill and price. All the orders submitted to the network is good for a day, which implies that any unfulfilled section of an order has an automatic resubmission to a subsequent crossing session during the day.

Justification: European electronic crossing networks display not the name of the buyer nor the seller. Therefore, Jill is accurate to mention the preservation of anonymity. The networks are also cheaper and save the cost of intermediaries in executing the transaction.  The limit also orders aids in limiting buying/selling. The minimum fill feature ensures that at least the prescribed number of the shares are matched.

Benchmark construction and measurement of performance portfolio concerning the benchmark are the key concept in the investment process. In most cases, benchmark choice is either a market index or an agglomeration of different market indices.

Because the choice of security does not influence design, merits from a credible reputation of renowned financial firms, credit rating agencies, and other popular international stock exchanges are used as the reference point.

 

In most cases, the use of capitalization-weighted indices is justified. For asset allocation purposes and performance measurement, the index efficiency assumption is central.

Case 4: Time value of money analysis

0        1        2    year

|        |        |                                            lump sum

100   cash flow

0      1       2      3

|        |        |        |                                    annuity

100     100    100

 

0      1      2       3

|        |        |        |                                            uneven cash flow stream

-50 100   75     50

 

In this case, a lump sum refers to a single flow. For instance, a $100 inflow in the 2nd depicted at the top of the line. On the other hand, an annuity is a series of equal cash flow that occurs in equal intervals shown at the middle timeline center. An even cash flow is characterized by an irregular series of cash flows that do not make an annuity as depicted by the lower timeline. The -50, in this case, represents a cash outflow instead of a receipt or inflow.

 

The relationship gives the final and present value relationship in cash flow.

PV is the present value, FV is the final value, i is the interest rate and the time duration.

In this case,

Substituting in the equations,

Dividing all through with PV and simplifying

 

Introducing natural logarithm on both sides,

Ordinary annuity payments are made at the end of each period. As a result, the 1st payment is made 1 period from the current day. An annuity due, on the other hand, has its first payment today. An end-of-period payment, therefore, characterizes an ordinary annuity while a beginning-of-period payment characterizes an annuity due.

The annuity shown is an ordinary annuity. It is converted to annuity due by shifting each payment to the left and ending up with payment under zero and no payment under three.

 

Using Present value final value and the relationship defined in part B,

For the 1st year

For the second year

For the third year

 

For the 4th year

Therefore

Total net present value

Using present value final value relationship, we have

 

Where

Therefore

Therefore

Introducing logarithm, we obtain

Taking antilog on both sides

From which

Accounts whose interests are paid more often than once a year, for example, semi-annually, quarterly are characterized by higher future values since the interest earned is more frequent.
The quoted, or stated, or simple, rate () refers to the quoted percentage rate of return. On the other hand, the annual percentage rate (APR) refers to the annual rate of interest that the investors charge the borrowers in a year. The periodic rate refers to the period numbers’ annual interest rate (periodic rate = inom/m).

The effective annual rate refers to the rate that makes PV grow to the same FV as under the multi-period. For 10%

Semi-annually

Quarterly

 

 

 

Daily

 

 

Using EAR computed in iii,

Semi-annually

Quarterly

Should the annual compounding be used, the nominal rate will be equivalent to the effective annual rate. The use of more compounding makes the effective annual rate to be greater than the nominal rate.
Construction of the amortization schedule for a $1000 loan whose annual interest rate is 10% with 3 equal installments.

The first step involves identifying the face amount to $1000 as the present value of a 3-year annuity with a 10% rate. Therefore

0       1         2        3

|          |          |          |

-1,000 PMT  PMT  PMT

From which we develop the equations

 

 

 

The resulting equation is observed to have only 1 unknown; the resulting equations are then solved to obtain the value of PMT. This is easily evaluated using a financial calculator with the inputs n=3, PV=-1000, FV=0, i=10. Upon pressing the PMT button, the resulting PMT value obtained is read as

For the Amortization schedule, the following points are made

The computed $402.1 annual payment is inclusive of both the interest and the principal. For the first year, the interest is computed as
The resulting repayment of principal is computed as the difference between $402.11 annual payment and the computed interest payment therefore
The resulting loan at the end of the first year is then computed as

The above procedures are then extended to the second and the third year as follows. For the second year,

Again, the annual payment of $ 402.1 is still inclusive of both the interest and the principal. The beginning balance is the closing balance for year 1

Therefore

The resulting repayment of principal is computed as the difference between $402.11 annual payment and the computed interest payment therefore
The resulting loan at the end of the first year is then computed as

Again, for the third year, the closing second year load is used as the beginning balance.

Therefore

The resulting repayment of principal is computed as the difference between $402.11 annual payment and the computed interest payment therefore
The resulting loan at the end of the first year is then computed as

It is observed that that the interest obtained each year reduces since the beginning load balance declines with the repayment. Because the payment remains constant and the interest rate component reduces with time, the resulting principal repayment increases each year, as shown in figure (5).

 

Figure 5: Interest, Principal Repayment, and Loan of the Amortization

On the other end, the interest component is an expense that is deducted from the business and is taxable to the lender. The payment has to be adjusted by a few cents within the final year; to be precise, the payments should be adjusted by payment of less than $3.279 to end up with zero ending balance. On the other hand, the lender receives a 10% interest rate on the average investment each year until the entire $1000 load is paid off.

Case 5: Effect of Brexit Referendum Result on FTSE Financial Sector

Introduction

This case examines the Financial sector reaction to the Brexit referendum result. Barclays, a company listed in FTSE 100 financial sector, is used as a case study. The reaction of the financial market to the noted event is investigated using market efficiency theories. An efficient market assumes that all the investors are risk-averse and can utilize the accessible information in optimizing their trading profits and well-being (Rossi and Gunardi, 2018). Depending on the accessible and available information that the investors can use in their trading choices, a capital-efficient market is categorized into three different forms: strong, semi-strong, and weak form (Bachar, 2016). Several concepts characterize financial market efficiency. The most common is informational or price efficiency, an indicator of how quickly and completely the price of a single asset reflects available information (Ausloos, Jovanovic and Schinckus, 2016). In this case, the possible impact of Brexit referendum result announcement on the financial market is investigated by analyzing the behavior of average abnormal returns (AAR) and cumulative average returns (CAAR) for an 11-days observation period centered on the result announcement day (24th June 2016).

Data Sources and Sample Identification

Barclays’ stock prices are used as a representation of the FTSE 100 financial banking sector’s stock price behavior.  Barclays bank is one of the FTSE 100 listed companies under the banking financial sector. It is a British multinational investment bank and a financial service company whose headquarter is located in London. Other than investment banking, this organization is organized into 4 primary businesses: personal banking, investment management, corporate banking, and wealth management. Because of its diversity in the financial sector, investigating the impact of the referendum result on Barclays provides a likely impact of the Brexit referendum result announcement event on 24th June 2016. Barclays stock prices within the observation period are obtained from Yahoo finance.

Data analysis and Calculations

Assuming that the FTSE 100 financial sector is an efficient market, all the new pricing relevant information is immediately incorporated into stock prices; hence the newly announced information (announcement of Brexit referendum results) is automatically reflected Barclays stock results. The stock returns for the 11 days window (-5, 5) are computed using the formula.

The normal (expected) return (NR) is then computed using a market-adjusted return that assumes that the return on a stock is expected to be equivalent to the return on the market. The normal or expected return (NR) for stock i for each of the days in the event window (-5, 5) is treated as equivalent to the return on the market  each day over the event window (-5,5). Hence

The abnormal return (AR), which is the primary aim of the event study is computed the difference between the actual return (R) of the Barclays stock on that particular day and the expected return is obtained from FTSE 100 for all the days within (-5, 5) event window. Hence

This variable offers the initial indication of the market reaction to the news. The level of abnormal returns is used to determine whether the event has a significant impact on the financial sector market behaviors.

Because varied events consistently influence the stocks, their prices are continuously volatile. To avoid incorporating other information that is not relevant to the announcement of Brexit referendum results on the British banking sector. As a result, average abnormal returns are computed using the formula.

Cumulative average abnormal returns (CAAR) are then computed to represent price reaction over the period around the studied event. This variable is used in indicating abnormal returns. It is computed using the formula below.

 

Empirical Results

Day
Close
FTSE 100
R
NR
AR
AAR
CAAR

-5
165.75
6680.6
0.066968
0.004086
0.062882
0.062882
0.062882

-4
176.85
6707.9
0.019791
0.000388
0.019403
0.041143
0.104024

-3
180.35
6710.5
0.009149
0.017167
-0.00802
0.024756
0.12878

-2
182
6825.7
0.027198
0.001348
0.02585
0.025029
0.153809

-1
186.95
6834.9
-0.17679
0.001448
-0.17823
-0.01562
0.138186

0
153.9
6844.8
-0.17349
-0.00541
-0.16808
-0.04103
0.097152

1
127.2
6807.8
0.033805
-0.00795
0.041752
-0.02921
0.067945

2
131.5
6753.7
0.049049
-0.01972
0.068772
-0.01696
0.050986

3
137.95
6620.5
0.004712
-0.01503
0.019741
-0.01288
0.038104

4
138.6
6521
0.010101
0.013434
-0.00333
-0.01193
0.026177

5
140
6608.6
-0.02464
0.003314
-0.02796
-0.01338
0.012793

 

 

Figure 6: CAAR VS Days

Discussion

From the empirical results, it was observed that before the Brexit results announced, cumulative average abnormal returns on Barclays stocks increased until a day just before the result announcement that it started falling. The decline observed a day before the actual announcement was made is attributable to the possibility of the election results leaking to the investors before the actual announcements are made. As a result, investors react to their anticipated decline in stock prices. The CAAR continues to fall even after the announcement of the referendum result, as shown in figure (6).

From the Market-Adjusted Return Model analysis conducted in this paper, it is desired to hypothesize that the average abnormal returns are significantly different from zero. Using the computed values of AAR in the table, the Hypothesis

Using t-test, the Hypothesis is tested as shown in table (2)

Table 2: Hypothesis Testing Results

Hypothesis testing

Data

Null Hypothesis m=
0

Level of Significance
0.05

Sample Size
10

Sample Mean
-0.00500888

Sample Standard Deviation
0.026324796

Intermediate Calculations

Standard Error of the Mean
0.0083

Degrees of Freedom
9

t-Test Statistic
-0.6017

Two-Tail Test
 

Lower Critical Value
-2.2622

Upper Critical Value
2.2622

p-Value
0.5622

Do not reject the null Hypothesis
 

The hypothesis test observed that the average abnormal returns are not significantly different from zero since the null Hypothesis is rejected. From this test, it can be seen that no abnormal performance is observed due to the event (announcement Brexit Referendum outcome) on Back lays. This analysis is based on Jong’s (2007) findings, who pointed out that abnormal returns are all centered around one particular event, and the average should reflect the impact of that event.

Figure (5) shows a graph of cumulative abnormal returns over the study period. From the figure, it is observed that 4 days before the announcement of the results, CAAR was increasing before beginning to decline up to 5 days after the event. Statistically, it is observed that CAAR exists around the event day. This indicates that the market perceived the referendum’s announcement as possessing new information content; hence the Financial sector of FTSE companies was sensitive to the news.

Conclusion

The empirical results obtained indicate that announcement of Brexit referendum results on 24th June 2016 that concluded that UK was to ‘leave’ EU had a significant impact on UK’s banking daily abnormal and cumulative average abnormal returns. Within an 11-day window period (5 days before the result announcement and 5 days after announcement), it was observed that the average abnormal returns on Barclays bank stocks dropped after the announcement of the results. Although statistically, the values of CAAR around the event day are not significantly different from zero, Barclays’ CAAR had a significant drop due to the Brexit referendum result that allowed UK to leave the EU.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Reference list

Ausloos, M., Jovanovic, F., and Schinckus, C. (2016). On the “usual” misunderstandings between econophysics and finance: Some clarifications on modeling approaches and efficient market hypothesis. International Review of Financial Analysis, [online] 47, pp.7–14. Available at: https://www.sciencedirect.com/science/article/abs/pii/S1057521916300849 [Accessed 28 Dec. 2020].

Bachar FAKHRY (2016). A Literature Review of the Efficient Market Hypothesis. Turkish Economic Review, [online] 3(3), pp.431–442. Available at: http://kspjournals.org/index.php/TER/article/view/928.

Rossi, M. and Gunardi, A. (2018). Efficient Market Hypothesis And Stock Market Anomalies: Empirical Evidence In Four European Countries. Journal of Applied Business Research (JABR), 34(1), pp.183–192.

APPLICATION OF EFFICIENT MARKET HYPOTHESES as history essay help

APPLICATION OF EFFICIENT MARKET HYPOTHESES, COST & BUDGETING PRACTICES IN VODAFONE COMPANY

by [Name]

 

Course

Professor’s Name

Institution

Location of Institution

Date

 

PART 1:APPLICATION AND CRITICAL EVALUATION OF EFFICIENT MARKET HYPOTHESES

1.      INTRODUCTION

Market efficiency can be accessed by analysing stock prices. Analysis of how the stock market responds to available information such as dividend announcement and leadership change is useful in financial trading decisions (Mclaney, 2017). Investors in the financial market should anticipate future stock prices using available information, either publicly or privately acquired. This essay describes the efficient market hypothesis before investigating how Vodafone stock prices respond to dividend announcement and change of a CEO to assess its efficiency.

2.      EFFICIENT MARKET HYPOTHESIS

An efficient market is one whose capital market’s asset prices reflect all the publicly accessible information on security. Within the assumptions of an efficient market, all the investors are risk-averse and can utilise the accessible information in optimising their trading profits and well-being (Fama, 1970). Depending on the accessible and available information that the investors can use in their trading choices, a capital-efficient market is categorised into three different forms: strong, semi-strong and weak form (FAMA, 1991).

 

Figure 1: Three different forms of capital market efficiency adapted from class notes Risk Measurement &Efficient Market Hypothesis by Dr Jatin Pancholi

A weak form one whose asset price is predictable using the information on historical prices of the assets. In this case, the trends on the asset price movement are used by the technical analyst. As a result, a Random Walk Model does not apply to a weak capital market (Fama, 1995). On the other hand, a semi-strong has asset prices that are not reflected in the historical price patterns but the publicly accessible information such as earnings announcement, changes in the leadership, financial statements, and organisational revolution. A strong, efficient capital market is characterised by asset price that has immediate incorporation of the privately, publicly available information and historical data. Current literature argues that asset prices are not only random but also unpredictable, based on historical data. Therefore, RWM is applicable in testing for the efficiency of a market. Chung and Hrazdil (2011) concluded that the U.K.’s market is a pure random walk system, an indicator of an efficient capital market.

Vodafone as a company is listed London stock exchange. It is, therefore assumed that Vodafone stocks are traded in an efficient market. It is therefore assumed that its stock prices are an indicator of the available market information.

However, other studies have demonstrated that financial markets can overreact or underreact to informative events (Dasilas and Leventis, 2011). The underreaction and overreaction hypothesis states that asset prices move below or beyond the new equilibrium levels justified by the news. Following this step, the investors can recognise their underreaction or overreaction and act thus adjusting the prices back to a new equilibrium (characterised by an opposite movement to the initial direction) (Chung and Hrazdil, 2011).

3. COMPANY BACKGROUND

The company was founded in 1984 as Vodafone Group Co., Ltd. By, on June 29, 1999, following the merger of Inc. (Air-Touch Communications), the company name was changed to Vodafone Air-Touch (Vodafone Group Plc, 2019). However, after the shareholders consented in July 2000, the initial Name Vodafone Group Co., Ltd was retained. The company is known in the telecommunication industry for outstanding high-tech products and has in the recent past grown to be ranked second largest telecommunication company in the U.K. following British Telecom. The company is operating in 19 major countries around the globe. Four major professional fields are associated with the company; mobile communications, fixed connectivity, IoT (Internet of Things) technology, and cloud and hosting services (Vodafone Group Plc, 2019). Before looking into the financial analysis, which is the basis of the paper, it is essential to looks into Vodafone’s competitive nature.

The Vodafone analysis covered in this paper examines the reaction of Vodafone stock process to selective information such as dividend announcement, leadership change and the January effect about the underreaction and overreaction hypothesis.

4. ANALYSIS

4.1. Vodafone’s investors’ reaction to dividend announcement

Under the hypothesis of an efficient market, stock prices should instantaneously reflect the new information, thus reflecting what the investors expect as their future earnings. As a result, earning announcement should have an immediate impact on stock prices in an efficient market (FAMA, 1991). As a result, investors will hardly earn abnormal returns. In a real-life scenario, the financial market is likely to either underreact or overreact to the information events. Thus, it is a challenger on the Efficient Market Hypothesis theory since some investors are capable of earning superior returns while not bearing additional risks by taking advantage of the underreaction and overreaction of the market (Chung and Hrazdil, 2011).

Analysis of how Vodafone investors respond to dividend announcement is conducted using empirical methods using stock prices. The historical data reveals a drift in the stock returns following dividend announcements, referred to as PEAD (Post Earning Announcement Drift) and a comparatively short-term drift in the stock returns just before the earnings announcements. In this analysis, the event day refers to the day the news of earning announcements were first published in the London Stock Exchange within the study period of 2018 and 2019. The analysed data include the stock prices of 12 days before and after the event day.

The Actual Daily Returns is computed from the formula.

Rt – Actual Daily Return of share on day t

Pt – Price of stock on day t

Pt-1 – Price of stock on day t-1

The Expected Returns – Average 12-day returns are computed using the formula.

The Abnormal Returns  is computed using the formula below.

The Cumulative Abnormal Returns CARs is computed using the formula shown below.

Table 1 in the appendices demonstrates Vodafone stock prices response’s empirical results, cumulative abnormal returns CARs and abnormal returns A.R.s 12 days before and after earning announcement on November 13 2018. On this date, the EPS announcement was negative (-1.948), an indicator of bad news for the investors relative to the previous earning.

Figure 2 shows that the investors seem to earn less immediately after the event day with a significant decline in the trading volume. It still observed that the earning increases for the last 3 days before event day and decline significantly just before the announcement. 3 days after the announcement, cumulative earnings are observed to increase and remain comparatively high for the next 4 days before experiencing a decline that corresponds to the announced negative earnings announced in the stock exchange.

Figure 2:CARs 12 days before and 12 days after earning announcement.

From the above trend, it can be concluded that the investors underreacted to the earning changed in 2018.

Analysis of stock price response to Vodafone’s earnings announcement during November 2018 and May 2019 is shown in table 2 in the appendices. The announcement on May 13, 2019, was negative and from figure (3), it is seen that immediately after the event day, the stock prices fall significantly before rising implying that the investors overreacted to the announcement. Thus, there is a shred of evidence to conclude that accounting information significantly impacts Vodafone stock prices. Vodafone investors are capable of earning significant abnormal returns around event days. The underreaction and overreactions towards dividend announcement prevent Vodafone stock market from being efficient due to asymmetric information around the announcement days.

Figure 3:CARs 12 days before and 12 days after earning announcement

4.2. Vodafone Investor’s Reaction to Leadership Change.

Under the assumptions of EMH, stock prices are supposed to reflect all the available market information. This section analyses the impact of CEO change on Vodafone stock prices. On November 4 2019, Vodafone appointed Vivek Badrinth as the CEO of its new European tower business. The stock response to this change in the executive is investigated by observing CARs and A.R.s behaviour following this news.

Figure 4:CARs 12 days before and 12 days after Leadership Change.

It is observed that Vodafone stock prices increase steadily following executive leadership change, an indicator of the investors’ reluctance in their expectation towards the new executive’s ability and ‘interpretation’ of the ‘good news’. However, on November 11, CAR started to a steady decline. The asymmetric nature of the information can explain this trend. The trend captured in figure 4 demonstrates the fluctuation of abnormal returns and cumulative abnormal returns following the announcement of new leadership.

5. CONCLUSION

From the definition of an efficient market, it is observed that dividend announcement impacts Vodafone stock prices. Vodafone investors are capable of earning abnormal returns due to asymmetry in the information content of the earning announcement. There are cases where the investors underreact and cases when they underreact to the accounting information, an observation that is attributable to asymmetric information on the announcements. It is also observed that a change in leadership also has a significant impact on stock prices as stock prices are observed to increase as a result of executive leadership change.

PART 2: PRACTICAL APPLICATION OF COST & BUDGETING PRACTICES

NATURE OF THE BUSINESS IN WHICH THE COMPANY OPERATES AND THE COMPANY’S CURRENT SITUATION.

As mentioned in part one of the assignment, Vodafone Group Co., Ltd was founded in 1984. The company operates in telecommunication industry providing outstanding high-tech products. The company has in the recent past grown to be ranked second largest telecommunication company in the U.K. following British Telecom. The company has over 60,000 employees employed in different parts of the world (Vodafone Group Plc, 2019, p.1). The company operates in four major professional fields are associated with the company in 19 major countries around the world. The company faces stiff competition from other companies  dealing in the same product and services. The company’s current situation can be evaluated by analysing its current financial performance. Despite the impact of the pandemic, the company has registered an increase in revenue compared to 2019 when the pandemic struck. The company has registered an increase in organic service revenue growth by 0.8% compared to the previous year. The growth in organic services revenue is associated with the company’s ability to grow its customer base during the pandemic. The figure below represents the growth in organic services revenue.

Growth in Organic Services Revenue

Figure1: growth in organic services revenue

Other than the growth in organic services revenue, the company has realised an increase in the return on capital employed ratio from 3.5 in 2019 to 4.0 in 2020. Return on capital employed is the measure of how efficient a company generate profits (Vodafone Group Plc, 2019, p.1). Based on the increased return on capital employed ratio the firm is currently more efficient in generating its revenue compared to the previous year. The company therefore has a favorable financial performance in the current year compared to the previous year.

ORGANISATION STRUCTURE

Based on information obtained from an interview with Siad, the company has adopted hierarchical organisational structure with Nick Read as the Chief Executive Officer. Gerard Kleisterlee is the chairman of the company. Margherita Della Valle is the Chief Financial Officer of the organisation while Valerie Gooding cbe is the Senior Independent Director and Workforce Engagement Lead. Hierarchical organisational structure is a type of structure where the chain of command starts from the top to the lower level of management positions. The application of this structure speed up decision making process (Mohr,2017, p.1). The clearly defined authority and responsibility improves the level of management. The adoption of hierarchical structure result in control and discipline.

PRODUCT/SERVICES PORTFOLIO

The company offers a range of products and communication. Based on information obtained from an interview with Siad the firm offers fixed-line services such as broadband that offers high-speed connectivity to the customers. The company also offers V by Vodafone that enable the consumers to connect IoT devices to their dedicated global IoT network (Vodafone Group Plc, 2019, p.1). Besides, the company offer Vodafone T.V. The firm has recently launched 5G network to improve their service delivery in mobile services. The 5G network aims to improve customers’ experience calling, texting and data usage. The firm offers fixed-line services such as broadband that offers high-speed connectivity to the customers. The IOT solutions services offered by the company enable the users to communicate securely through the 5G network. Other than the IOT solutions, the company also offers public and private cloud services. Vodafone company also offers Carrier services. The company also offers range of services to its African consumers. This includes M-pesa service as a payment platform. The M-pesa services enable easy transfer of money as well as merchant payment services. Vodafone is committed to providing quality services to its consumers globally.

DIFFERENT TYPES OF COST WITH EXAMPLES

Vodafone companies has different costs. Fixed costs are costs that remain constant as the with changes in the total output. It is imperative to note that, fixed costs would remain the same even if the company do not produce anything. For the Vodafone company, the fixed costs include the costs of building the company, insurance and legal bills. Other examples of fixed costs include costs of providing M-pesa services as well as the cost of installing 5G network to its customers. The company also has variable costs. Variable costs vary with variation in the output produced (Drury, 2018, p.1). For the Vodafone company the variable costs include service cost and the costs on interest charged. The total cost is given by the formula Total costs =Fixed costs +Variable costs. The company also employ marginal costs. Marginal costs are the cost of producing extra unit. The company employ this type of costs in producing more mobile services to meet the increased customer demand.

BUDGETING PRACTICES

The company has adopted various budgeting practices to ensure proper planning. Based on information obtained from an interview with Siad, Vodafone company applies the use of performance-based framework as a budgeting practice. The use and application of this type of budgeting practices enable the firm to establish a strong link between the investments and outcomes (Batra, and Verma, 2017, p.29). The company also applies this budgeting practice in allocating resources to specific activities. The use of a performance-based framework as a budgeting practice clearly demonstrate how a specific financial investment impacts the business through its outcomes thereby allowing for a deeper level of analysis and a greater understanding of return of investment. The company also employ the analysis of non-financial data as a budgeting practice. The firm uses this type of budgeting practices in providing a clear picture of the organisation’s current financial performance. The company has also utilised the use of updated budget as needed in the budgeting process. Most of the company’s budget are fixed and inflexible. The application of updated budgets as needed allows for material deviations during the year (Miller, Hildreth, and Stewart, 2019, p.1281). The application of this practices enables organisations to update their budget plans to reflect the current situation of the organisation. Finally, the organisation perform what-if Analysis as a budgeting practice. Performance of what if analysis in the budgeting process allows for the budget plan to aaccommodate unusual disruptions or drastic changes. The application of this type of budgeting practice has enabled the organisation to remain resilient during the pandemic. Performance of what if analysis in the budgeting process ensures the company carefully prepare and weigh in risks.

MANAGEMENT CONTROL PRACTICES

Management control practices are mechanisms that allow the company to efficiently manage the available resources. Management control practices enable the firm to achieve productivity, efficiency, and consistency in the management of the company resources (Choi, 2020, p.112). Based on information obtained from an interview with Siad, Vodafone company has adopted performance management as a management control practice. The firm applies this practice in improving performance of the team where there is lag in performance. This is achieved through evaluation of the performance of teams and individuals against the objectives of the company. The management control practice enables the manger to take corrective action to improve the performance of teams whose performance has deviated from the company’s objectives and reward those whose performance matches the organisation’s objectives. The application of performance management as a management control practices in the management of Vodafone company therefore aids in achievement of productivity, efficiency, and consistency in the management of the company resources.

EVALUATION OF THE COMPANY’S CURRENT BUDGETING AND MANAGEMENT CONTROL PRACTICE

Based on the above analysis, Vodafone company has efficient current budgeting and management control practices. The use of a performance-based framework as a budgeting practice clearly demonstrate how a specific financial investment impacts the business through its outcomes thereby allowing for a deeper level of analysis and a greater understanding of return of investment. Besides, the application of performance management as a management control practices in the management of Vodafone company therefore aids in achievement of productivity, efficiency, and consistency in the management of the company resources.

CRITICAL EVALUATION IN FAVOUR AND AGAINST THE ORGANISATIONS’ COSTING AND BUDGETING

The analysis of non-financial data as a budgeting practices aids the organisation in providing a clear picture of the organisation’s current financial performance. However, this budgeting practice may result in complex and inflexible budgeting plan. For future improvement, the company needs apply updated budgets as needed as budgeting practice to allow for material deviations during the year. The application of this practices will also enable the organisation to update their budget plans to reflect the current situation of the organisation. The application of variable costing enables the organisation to vary the cost of inputs based on the demands for the products. For future improvement, Vodafone company need to adopt other type of costing methods such as FIFO that would ensure effective management of the warehouse.

 

 

 

 

Reference list

Batra, R. and Verma, S., 2017. Capital budgeting practices in Indian companies. IIMB Management Review, 29(1), pp.29-44.

Choi, J.W., 2020. Studying “and”: A perspective on studying the interdependence between management control practices. Accounting, Organisations and Society, p.101188.

Chung, D.Y. and Hrazdil, K. (2011). Market Efficiency and the Post-Earnings Announcement Drift*. Contemporary Accounting Research, 28(3), pp.926–956.

Dasilas, A. and Leventis, S. (2011). Stock market reaction to dividend announcements: Evidence from the Greek stock market. International Review of Economics & Finance, 20(2), pp.302–311.

Drury, C., 2018. Cost and management accounting. Cengage Learning.

Fama, E.F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), p.383.

FAMA, E.F. (1991). Efficient Capital Markets: II. The Journal of Finance, 46(5), pp.1575–1617.

Fama, E.F. (1995). Random Walks in Stock Market Prices. Financial Analysts Journal, 51(1), pp.75–80.

MCLANEY, E. J. (2017). Business finance: theory and practice 11th Edition.

Miller, S.A., Hildreth, R.W. and Stewart, L.M., 2019. The modes of participation: A revised frame for identifying and analysing participatory budgeting practices. Administration & Society, 51(8), pp.1254-1281.

Mohr, Z. ed., 2017. Cost accounting in government: Theory and applications. Taylor & Francis.

Vodafone Group Plc, (2019); [online]. Available on https://www.vodafone.cz/

 

APPENDICES

Table 1: ARs and CARs for 12 days before and after earning announcement following earning announcement on Nov 13,2018

Closing Price
Closing Prices
Daily Return
Expected Return
Abnormal Return (AR)
Cumulative Abnormal Return (CAR)

Nov 01,2018
19.8
0.045959
-0.00597
0.051924
0.001608

Nov 02,2018
19.45
-0.01768
-0.00209
-0.01558
0.003517

Nov 03,2018
19.71
0.013368
-0.00291
0.01628
0.001798

Nov 04,2018
19.13
-0.02943
-0.00064
-0.02878
0.003252

Nov 05,2018
19.51
0.019864
-0.00431
0.024173
0.001732

Nov 06,2018
19.09
-0.02153
-0.00014
-0.02139
0.002104

Nov 07,2018
18.79
-0.01571
-0.00095
-0.01476
0.002463

Nov 08,2018
18.59
-0.01064
-0.00024
-0.01041
0.001737

Nov 09,2018
20.08
0.080151
-0.00121
0.081365
0.002271

Nov 10,2018
20.37
0.014442
0.006743
0.007699
0.007978

Nov 11,2018
19.87
-0.02455
0.007186
-0.03173
0.009451

Nov 12,2018
19.6
-0.01359
0.00483
-0.01842
0.005833

Nov 13,2018
19.83
0.011735
0.003388
0.008346
0.003754

Nov 14,2018
19.51
-0.01614
0.000536
-0.01667
0.003747

Nov 15,2018
19.52
0.000513
0.000665
-0.00015
-0.00153

Nov 16,2018
19.72
0.010246
-0.00041
0.010653
-0.00034

Nov 17,2018
20.91
0.060345
0.002899
0.057446
-0.00078

Nov 18,2018
21.24
0.015782
0.006273
0.009509
0.005857

Nov 19,2018
21.69
0.021186
0.009382
0.011805
0.004729

Nov 20,2018
21.31
-0.01752
0.012457
-0.02998
0.007283

Nov 21,2018
21.49
0.008447
0.011884
-0.00344
0.006113

Nov 22,2018
21.26
-0.0107
0.005909
-0.01661
0.006649

Nov 23,2018
20.72
-0.0254
0.003813
-0.02921
-0.00089

Nov 24,2018
20.75
0.001448
0.003742
-0.00229
-0.00373

Nov 25,2018
20.48
-0.01301
0.004995
-0.01801
-0.00146

 

Table 2:ARs and CARs for 12 days before and after earning announcement following earning announcement on May 14,2018

Closing Price
Daily Return
Expected Return
Abnormal Return (A.R.)
Cummulative Abnormal Return(CAR)
Cummulative Abnormal Return(CAR)

May 02,2019
18.6
0.023102
-0.001
0.024098
-0.00413

May 03,2019
18.56
-0.00215
0.00016
-0.00231
-0.00347

May 04,2019
18.88
0.017241
-0.00204
0.019278
-0.00427

May 05,2019
18.87
-0.00053
-0.00082
0.000289
-0.00443

May 06,2019
18.35
-0.02756
-0.00147
-0.02608
-0.00418

May 07,2019
18.35
0
-0.00394
0.003943
-0.00631

May 08,2019
18.29
-0.00327
-0.00325
-1.8E-05
-0.00559

May 09,2019
18.25
-0.00219
-0.00278
0.000595
-0.00417

May 10,2019
18.08
-0.00932
-0.00142
-0.00789
-0.00287

May 11,2019
18.34
0.014381
-0.0035
0.017882
-0.0016

May 12,2019
18.61
0.014722
-0.00102
0.015745
-0.0011

May 13,2019
18.59
-0.00107
0.002266
-0.00334
0.001668

May 14,2019
18.71
0.006455
0.001947
0.004508
0.00346

May 15,2019
18.52
-0.01015
0.00056
-0.01071
0.003592

May 16,2019
18.41
-0.00594
-0.00011
-0.00583
0.000914

May 17,2019
18.31
-0.00543
-0.00204
-0.00339
0.000643

May 18,2019
17.97
-0.01857
-0.00245
-0.01612
-0.0011

May 19,2019
17.96
-0.00056
-0.0017
0.001142
-0.00236

May 20,2019
18.37
0.022829
-0.00175
0.024574
-0.00027

May 21,2019
18.52
0.008165
0.00043
0.007736
0.001318

May 22,2019
18.52
0
0.001292
-0.00129
0.001915

May 23,2019
18.44
-0.00432
0.002069
-0.00639
0.001769

May 24,2019
18.4
-0.00217
0.00051
-0.00268
0.001885

May 25,2019
18.46
0.003261
-0.0009
0.004158
0.000303

May 26,2019
18.33
-0.00704
-0.00054
-0.00651
-0.00059

 

Table 3:ARs and CARs for 12 days before and after Executive Leadership Change on November 4 2019

Date
Closing Stock Prices
Daily Return
Expected Return
Abnormal Return (A.R.)
Cummulative Abnormal Return(CAR)

10/23/2019
19.11
-0.0083
0.01019
-0.01849
0.006738

10/24/2019
18.94
-0.0089
0.00735
-0.01625
0.007503

10/25/2019
18.59
-0.01848
0.00599
-0.02447
0.003963

10/26/2019
18.88
0.0156
0.004214
0.011386
0.001363

10/27/2019
18.59
-0.01536
0.004855
-0.02021
0.001807

10/28/2019
18.13
-0.02474
0.001892
-0.02664
-0.00061

10/29/2019
18.18
0.002758
-3.3E-05
0.00279
-0.00445

10/30/2019
18.6
0.023102
-0.001
0.024098
-0.00413

10/31/2019
18.56
-0.00215
0.00016
-0.00231
-0.00347

11/1/2019
18.88
0.017241
-0.00204
0.019278
-0.00427

11/2/2019
18.87
-0.00053
-0.00082
0.000289
-0.00443

11/3/2019
18.35
-0.02756
-0.00147
-0.02608
-0.00418

11/4/2019
18.35
0
-0.00394
0.003943
-0.00631

11/5/2019
18.29
-0.00327
-0.00325
-1.8E-05
-0.00559

11/6/2019
18.25
-0.00219
-0.00278
0.000595
-0.00417

11/7/2019
18.08
-0.00932
-0.00142
-0.00789
-0.00287

11/8/2019
18.34
0.014381
-0.0035
0.017882
-0.0016

11/9/2019
18.61
0.014722
-0.00102
0.015745
-0.0011

11/10/2019
18.59
-0.00107
0.002266
-0.00334
0.001668

11/11/2019
18.71
0.006455
0.001947
0.004508
0.00346

11/12/2019
18.52
-0.01015
0.00056
-0.01071
0.003592

11/13/2019
18.41
-0.00594
-0.00011
-0.00583
0.000914

11/14/2019
18.31
-0.00543
-0.00204
-0.00339
0.000643

11/15/2019
17.97
-0.01857
-0.00245
-0.01612
-0.0011

11/16/2019
17.96
-0.00056
-0.0017
0.001142
-0.00236

 

The Interaction and Conflict Management history assignment help is it legit: history assignment help is it legit

 

Interaction and Conflict Management

 

Student’s name

Institutional Affiliation

Date

 

Interaction and Conflict Management

Indeed there was a conflict between David, Elaine, and the customer. Nevertheless, it isn’t quite clear as to who should be blamed for the genesis of the conflict. The conflict involves a situation where an employee strongly believes that the customers’ actions are wrong, and therefore she feels like the client does not deserve whatever she is requesting. On the other hand, the manager is the view that the customer is always right. Hence, an employee should not have the audacity to make any allegations against the customer or cause commotion in the store as well. Seemingly, Elaine was not in a position to serve the client because she felt like the customer also lacked decorum as well as courtesy. The client was shouting and this provoked Elaine. Therefore, it is correct to submit that the customer could not earn Elaine’s respect. It is this scenario that culminated in a conflict in the company. Furthermore, the conflict also attracted consequences. For instance, Elaine was put on probation to serve as punishment for the act which the manager considered out of order.

Elaine’s approach to this particular scenario was not so unprofessional. If she only realized that the issue was not within her jurisdiction to resolve, then she could have directed the customer to the manager’s office. Generally, almost all and sundry are of the view that the customer is always right. Elaine’s action was motivated by emotions, and that’s why she could not easily assess the situation in which she was. The way she tried to resolve the conflict almost ruined the reputation of the business. Such a mistake is costly since it can reduce the sales of the business venture; when customers avoid the brand. Therefore, she was supposed to calm down the customer and inform her that she’ll be will the manager shortly. Elaine’s approach was also a competing one. It is because Elaine alleged that the client was lying instead of directing her to the manager’s office.

That conflict at a place of work is inevitable is a fact, however, the same can be cubbed. In such situations, I would vouch for the avoiding approach. The avoiding approach basically dictates that Elaine should have completely avoided the situation by directing the customer to the manager. It denotes that she could not have tried to make any resolutions. Therefore, she needs to learn on how to assess scenarios before she acts. It goes a long way into ensuring that one understands the environment and therefore seeks the best way to negotiate and communicate. Elaine also needs to understand that every situation is a negotiation. Therefore, if a party lacks the requisite negotiation skills, then it’s upon the other person to play smart. All in all the best remedy for this scenario was simply to direct the customer to David’s office. As a manager, David had no other alternative but to punish Elaine. He punished Elaine just to remind her that the reputation of the business matters a lot. Additionally, he also endeavored to make it aware to her that the company prospers if the customers are fully satisfied. Notably, the customer overreacted because she felt ashamed of the allegations made against her by Elaine.

 

THE CONCEPT OF BULLYING IN SCHOOLS. history assignment help in canada

Topic

The topic of discussion will be on Bullying in Schools. The cases of bullying in our educational institutions have drastically risen the scale since more cases are being reported to the relevant authorities.

Thesis statement

Being subjected to bullying in our educational institutions is a hindrance to achieving educational success of an individual.

The effects of bullying

We will look into the impact bullying has had on the life of a student both physically and emotionally.

What are some of the causes of bullying in schools?

We are going to look at the major factors that bring about bullying culture in the school environment.

What are some of the actions taken against bullying in school?

Aims at highlighting all the actions taken in raising awareness and policies against bullying in our educational institutions.

Stakeholder accountability in eradicating bullying.

We will look into the roles of the different stakeholders in our educational institutions in a bid to do away with bullying in our schools. What are the roles played by the teacher? What are the roles played by the subordinate staff in the school is doing away with bullying?

Should bullying be considered a criminal offence?

We are going to look into the reasons why bullying in educational institutions should be considered a criminal offence.