## Portfolio optimisation Assignment Available

Portfolio optimisation

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1. By doing the optimisation using Excel Solver, you are required to construct a mean variance efficient portfolio frontier for any 10 randomly selected ordinary shares listed on a stock market. For all your calculations, you should use the 60 monthly returns, sample means, standard deviations, and covariance and correlation matrices. Plot the portfolio frontier and comment on the weights of the portfolios along the portfolio frontier including in your discussion the correlations among the 10 shares.

2. Identify a risk-less asset and provide the rationale for your choice of the risk less asset.

3. By combining the risk-less asset with the 10 shares, plot the straight line efficient portfolio frontier and select the tangent portfolio on the portfolio frontier.

4. Assume that the short selling is not allowed, how your efficient frontiers would differ from those with short selling allowed in questions 1 and 3 above.

5. Identify the appropriate benchmark index and justify your choice of the benchmark index.

6. Evaluate the performance of the tangent portfolio selected above using:

a) Sharpe’s Measure
b) Treynor’s Measure
c) M2 Measure
d) Jensen’s Performance Measure
e) The Appraisal Ratio.

7. Comment on the limitation of your analysis.

8. Critically evaluate the gains in the performance of the identified portfolio along with the associated risks from investing in other asset classes, for instance, investment in gilts (including index linked), corporate bonds, convertible bonds, commodities, real estate, hedge funds and exchange traded funds.

NB

This is a portfolio optimization assignment.

It has to be done with excel after the report writing on word.

Introduction
Investing in the stock markets is highly dependent on the performance of the portfolio in which a certain investor has put his/her money. This principle of portfolio optimization was popularized by Markowitz who developed an appropriate method through which an investor could devise the most important stock portfolio for investment by avoiding risky stocks and prioritizing on investing in the stocks with the highest potential for maximum returns. Therefore, Markowitz portfolio indicates that it is necessary to increase assets and/or stocks in an investment portfolio the where the total risk of that portfolio is considered to be low or as measured by the standard deviation (or variance) of total return declines continuously, whereas the envisaged portfolio return is a weighted average of the expected returns of the individual assets. This implies that investing portfolios instead of individual assets and/or stocks, investors have a chance of significantly lowering the total risk of investing without necessarily sacrificing returns on their investments.

Therefore, the Markowitz’s mean-variance theory is usually implemented through the Excel Solver spreadsheet calculations meaning that it always optimize allocation of assets by finding the stock distribution through which there is minimization of the standard deviation or variance of the portfolio while at the same time sustaining the desired return on the stocks and/or assets. The origin of modern portfolio theory was in the 1950s with Harry Markowitz’s pioneering work in mean-variance portfolio optimization. However, prior to Markowitz’s innovation, heuristics were the ones who significantly influenced finance more than mathematical modeling. Mean-variance optimization is currently considered the core technique used by pension funds and hedge funds for portfolio diversification.
Most investors trade risk off against the envisaged return on their investments. Mean-variance optimization plays a crucial role in the identification of the investment portfolio responsible for the minimization of risk (i.e. standard deviation) for a given return. In most cases the line which is formed when the envisaged returns are plotted against the minimized standard deviation becomes the most efficient frontier for determining the most appropriate investment portfolio.
Background of Stock Portfolio Optimization
There is a certain return for every stock in the market and it is assumed that a normal distribution is portrayed by this return. This implies that the distribution for these returns for the stock can be completely described using the mean which represents the expected return as well as variance of the returns. Moreover, between any pair of stocks covariance of the returns can be computed whereby the stocks that show positive covariances, it means that they move together while the stocks that show negative covariances move in the opposite directions. Therefore, if the envisaged returns for a certain stock return or a group of stock’s returns are known, a portfolio of these stocks can be put together because of their desired variance (risk) in the stock market as a result of their envisaged return. Thus, solver, excel is mainly used for the purpose of picking the portfolio in possession of the least variance for an envisaged return meaning that the investor is likely to gain profits from his/her investment.
However, the expected return as well as the portfolio’s variance can be calculated using the method that was developed by Harry Markowitz which is crucial in the computation of portfolio return in terms of the sum of individual stock covariances and variances between stocks’ pairs in a certain portfolio. This is definitely the right thing to do from a mathematical standpoint, even though all covariances between any portfolios pair of stocks is considered meaning there would be so many calculations that would be required to accomplish this task. Alternatively, another method was devised by William Sharpe for the determination of the envisaged return and variance for a certain portfolio. This is a simpler method compared to the previous one because it assumes that any stock’s return has two parts such as the beta part which depends on the entire market performance, and the second one which is independent of the market. These two methods have been extensively used to determine the performance of specific groups of stock portfolios in the stock markets across the world for a considerable period of time.

Discussion
In our considered example, the optimal portfolio in stock market provides a risk-return trade off for superior to investing in all the shares within the UK stock exchange market. For instance, through the computations of the Excel Solver it has been determined. For instance, the portfolio optimization analysis began with the analysis of descriptive aspects of the considered 10 stock returns over a period of 60 months including means, standard deviations, and median. Moreover, the correlation and covariance matrix as well as correlation coefficient all seem to indicate that there is significant relationship between the 10 stocks considered over the 60 months.

Moreover, there are also other performance ratios such as the Treynor’s measure, Sharpe ratio, Jensen’s Performance Measure, and the appraisal ratio. For instance, Treynor’s measure of 0.4 which is relatively low considering that it is below the half mark, this implies that selected portfolio is not that better since the higher the Treynor’s measure. The Sharpe ratio is almost identical to the Treynor measure, with exception of the fact that the risk measure is the standard deviation of the portfolio rather than only considering the systematic risk, as represented by beta. Therefore, the Sharpe ratio of 1.6 is indicative of a portfolio that is not performing better. This may be attributable to the selected stock with lowly performing returns, except a few which show considerable performance.

Jensen’s Performance Measure analyses the performance of an investment by not only looking at the overall return of a portfolio, but also at the risk of that portfolio. For instance, when two mutual stocks, rationally an investor would go the one that is less risky meaning that the obtained value of 0.2 is and indicative of considerable performance of the stocks.

Finally, the Appraisal Ratio of 0.5 shows that it is necessary to attempt to beat the returns of a relevant benchmark or of the overall market. The appraisal ratio measures the portfolio performance by comparing the return of their stock picks to the specific risk of those selections, hence the higher the ratio, the better the performance of the portfolio in question.

This implies that two step must always be taken prior to determining where to invest in the stock market, where the first one regards the determination of the allocation of stocks/assets between the riskless portfolio and the risky assets and/or stocks. The second step is the determination of the allocation of resources between the risky and riskless portfolios.

However, considering that all the portfolios of riskless and risky assets have a similar Sharpe ratio, all investors do not have one optimal portfolio, but their allocation is often determined by specific factors that are individual like the objectives of the investor or risk aversion of the investor, taking into account factors like the investor’s horizon, wealth, etc. Furthermore, the extent to which the volatility of the portfolio can be decreased is highly dependent on the correlation whereby, the lower the average correlation of the stocks within a certain portfolio, then it implies that that is the lower an investor can decrease the volatility of the portfolio. This is a clear indication that this has provided the author of this assignment with succinct knowledge of determining the optimal allocations in stock markets.

Conclusion
Through this assignment it has been shown that, it is possible to use specialized spreadsheets for the calculation of important risk and return related portfolio statistics in the stock markets as well as minimizing the overall risk or maximizing the expected return of a multi-stock portfolio. However, it is essential to know that irrespective of these calculations being useful when creating investment portfolios, they rest on the assumption that historical relationships between asset classes and individual assets will hold in the future. This means that it is always crucial for investors to choose a period that they feel is representative of a “typical” market cycle, in order to avoid a capturing a repetitive cycle that is not relevant.

Moreover, the mean-variance portfolio optimization has its limitations, despite the fact that it is very helpful in choosing appropriate portfolios. For example, using standard deviation (or variance) as a proxy for risk can only be considered valid for normally distributed returns, and not any other returns which is not always the case in the stock markets. In addition, the premise of the Markowitz theory means that investors are not likely to make any alterations to their asset allocation after it has been optimized. Finally, fund managers or investors may not necessarily be interested in the minimization of risk (i.e. standard deviation or variance), but instead they may be interested in reducing the correlation of a fund to a benchmark. These are the limitations of the used method, even it is very crucial in determining portfolio optimization.

Reference List
Arnold, G. (2008), Corporate Financial Management, Third Edition, New York, NY: Pearson Education Limited.

Craig, W. H. (2008), Excel Modelling and Estimation in Investments, Third Edition, Indiana University, Prentice Hall, Inc.
FTSE Website http://www.ftse.com/products/indices/uk

Goldfarb, D. and Iyengar, G. (2003), “Robust Portfolio Selection Problems”. Mathematics of Operations Research, Vol.28 Issue 1, pp. 1-38.

Jackson, M. and Staunton, M. (2001), Advanced Modelling in Finance using Excel and VBA. Chichester, England: John Wiley & Sons.

Markowitz, H.M. (1959), Portfolio Selection: Efficient Diversification of Investments. New York, NY: John Wiley & Sons.

Markowitz, H.M. (1952). “Portfolio selection” The Journal of Finance, Vol. 7 Issue 1, pp. 77-91.

Sharpe, W.F., (1964), “Capital asset prices: A theory of market equilibrium under conditions of risk”. Journal of Finance, Vol. 19 Issue 3, pp. 425-442.

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## How macroeconomic factors affect stock returns

How macroeconomic factors affect stock returns

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examine how macroeconomic factors affect stock returns.
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The goal of the project: We examine how macroeconomic factors affect stock returns.
Empirically, we can test the following model;
Rt= ?0 + ?1*Market Indext-1+ ?2*Inflationt-1+ ?3*GDP Growtht-1+ ?4*TERMt-1+ ?5*RISKt-1+?

1. Dependent variable: firms’ stock returns
I posted firms’ stock returns in three industries (air, auto, and computer) to Blackboard. You can analyze any firm as you wish. You can pick multiple firms from three different industries, or a single firm from a specific industry.

Variable Explanations
DATE: the end of trading date at each month
COMNAM: Company name
EXCHCD: Exchange code (1: NYSE, 2: AMEX, and 3:NASDAQ)
HSICCD: Industry classification (e.g., The SIC 4512 represents an airline industry.
PRC: Stock price at the end of each month’s trading date
RET: Stock returns at the end of each month’s trading date
SHROUT: shares outstanding
VWRETD: Market index
2. Independent variables: macroeconomic variables
* The Source of data: http://research.stlouisfed.org/fred2/tags/series
Download data as long as we believe that variables may affect stock returns.
There are some candidates for independent variables.
Market Index=VWRETD, and Firm Size= PRC*SHROUT
Inflation= log (CPIt / CPIt-1), and GDP Growth=log (GDPt / GDPt-1)
TERM= 10-year T/B – 3-month T/B, and RISK= BAAt – 10-year T/B?

Questions
1) Report summary statistics (n, mean, median, standard deviation, min, max) of your picked variables.
2)Why do you include such independent variables? Give me a brief explanation.
3) Run a regression and report coefficients and t-statistics for the explanatory variables.
4) Interpret coefficients of each variable. Compare it with your prediction
* To obtain full credit (20 points), you need to submit it by July 8th, 2014.Grade below 10 points will be counted as zero.
* The minimum requirement is 5 different firms and 5 independent variables.
* TERM and RISK should be included as independent variables.
* If you need a reference, please look at the paper written by Nai-Fu Chen, Richard Roll, and Stephen A. Ross. The title is “Economic Forces and the Stock Market (Journal of Business, 1986)”.

### How macroeconomic factors affect stock returns

Abstract

There are many macroeconomic factors that affect the stock market globally. Inflation and deflation have adverse financial effects on a company’s profitability which subsequently affect the stock market. The rate of increment on the prices of goods and other services constitutes inflation besides the increase in the cost of transportation and manufacturing expenses. (Swann, 2009) The stock market responds powerfully when the rate of inflation is low and weakens when it increases as most companies reduce their expenditures because of high cost of goods and services and the general money in economy reduces which results in reduced activities at the stock market. Deflation in most quarters is regarded as a sign of a weak economy as it also leads to a decrease in the stock market. (Chen, Roll and Ross, 1986)

The interest rates are established and monitored by Federal Reserve Board. Higher rates of interests are caused by the expensive nature of borrowing money. Money becomes too expensive to borrow. To subsidize their high rates of interests, most companies may opt to lay off workers and reduce expenditures on other goods. Higher rates of interests imply that even companies will not be comfortable when borrowing as the rate of interests becomes exorbitant and their income will also be affected. (Cairns, 2004) When the income of listed companies reduces then the investments in the stock market is also affected negatively.

1

 Sun Microsystems PRC RET SHROUT WRETD n 132 132 133 133 Mean 22.36021 0.001747 2447123 0.002766 Median 114.34 -0.08963 955344.5 -0.184 STD 34.098 0.16257 1201797 0.048607 Min 2.59 -0.39474 385583 -0.18462 Max 132.25 0.564103 3602000 0.110533 FRANKLIN ELCTRONIC PUBLISHS PRC RET SHROUT WRETD n 133 133 134 134 Mean 3.182147 0.013589 8063.91 0.003009 Median 9.445006 0.066578 8504.844 0.053974 STD 4.080006 0.21349 402.3438 0.053359 Min -3.845 -0.46429 7818 -0.18462 Max 11.9375 1.141434 8387 0.110533 SILICON GRAPHICS INC PRC RET SHROUT WRETD n 82 82 83 83 Mean 4.081159 0.025353 211362.6 0.003827 Median 14.69741 0.253384 439218.6 0.012599 STD 14.06612 0.521925 57156.86 0.041823 Min 0.44 -0.54676 182872 -0.10253 Max 20.5625 2.782609 268272 0.083911 APPLE COMPUTER INC PRC RET SHROUT WRETD n 96 96 96 96 Mean 43.137 0.035008 438980.5 0.004941 Median 63.01375 -0.03415 498318.5 0.024586 STD 30.86698 0.056931 511806 0.019459 Min 14.14 -0.57744 136417 -0.10253 Max 135.8125 0.453782 860220 0.083911 UAL CORP PRC RET SHROUT WRETD n 51 51 52 52 Mean 36.4751 -0.05963 56649.73 -0.00232 Median 62.25 0.042932 74327 0.060554 STD 43.42343 0.187492 32795.61 0.019813 Min 0.84 -0.51765 49792 -0.10253 Max 80.75 0.326258 99506 0.083911 FORD MOTOR CO PRC RET SHROUT WRETD n 144 144 144 144 Mean 17.04726 0.009958 1961721 0.004096 Median 39.11375 0.054011 2270481 0.053095 STD 31.57055 0.00097 1599931 0.02086 Min 16.79 0.053325 1139159 0.038345 Max 63.9375 1.273764 3401803 0.110533
1. Independent variables are included as they determine or influence other variables. An independent variable when manipulated determines or influences the change in the other dependent variable. This study seeks to determine if a relationship exists between the returns of the stock market and the macro economic factors that may affect the overall performance of the stock market.
2. Ford Motor Co
 SUMMARY OUTPUT Regression Statistics Multiple R 0.4995218 R Square 0.249522 Adjusted R Square 0.244237 Standard Error 0.148835 Observations 144 ANOVA df SS MS F Significance F Regression 1 1.04585 1.04585 47.213 1.849E-10 Residual 142 3.14556 0.02215 Total 143 4.19142 Coefficient Standard error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0.0029 0.0124 0.2290 0.8192 -0.0218 0.0275 -0.0218 0.0275 VWRETD 1.7354 0.2526 6.8712 0.0000 1.2361 2.2347 1.2361 2.2347

Franklin Electronic Publish Inc

 SUMMARY OUTPUT Regression Statistics Multiple R 0.31 R Square 0.09 Adjusted R Square 0.09 Standard Error 0.23 Observations 133.00 ANOVA df SS MS F Sig F Regression 1 0.715 0.715 13.554 0.000 Residual 131 6.915 0.053 Total 132 7.631 Coeff Std Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0.0094 0.019955 0.47106 0.6383832 -0.03 0.048876 -0.03008 0.048876 VWRETD 1.5147 0.411416 3.68157 0.0003377 0.7008 2.328532 0.700776 2.328532

UAL Corp

 SUMMARY OUTPUT Regression Statistics Multiple R 0.552 R Square 0.304 Adjusted R Square 0.290 Standard Error 0.156 Observations 51.000 ANOVA df SS MS F Sign f Regression 1 0.521 0.521 21.442 0.000 Residual 49 1.191 0.024 Total 50 1.712 Coeff Std error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -0.052 0.022 -2.372 0.022 -0.096 -0.008 -0.096 -0.008 VWRETD 1.933 0.418 4.631 0.000 1.094 2.772 1.094 2.772

Sun Microsystems

 Regression Statistics Multiple R 0.664 R Square 0.441 Adjusted  R Square 0.437 Standard Error 0.122 Observations 132.000 ANOVA df SS MS F Significance F Regression 1 1.527 1.527 102.6 3.92E-18 Residual 130 1.935 0.015 Total 131 3.462 Coeffici Std Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -0.005 0.011 -0.476 0.635 -0.026 0.016 -0.026 0.016 VWRETD 2.219 0.219 10.130 0.000 1.785 2.652 1.785 2.652

Silicon

 Regression Statistics Multiple R 0.260 R Square 0.067 Adjusted R Square 0.056 Standard Error 0.403 Observations 82.00 ANOVA df SS MS F Sig  F Regression 1 0.939 0.939 5.787 0.018 Residual 80 12.97 0.162 Total 81 13.91 Coe Std error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0.017 0.045 0.391 0.697 -0.071 0.106 -0.071 0.106 VWRETD 2.338 0.972 2.406 0.018 0.404 4.272 0.404 4.272

1. Interpretation

Ford Motor Co.

The thesis of the study is to establish if a relationship exists between the performance of individual stocks belonging to different companies and the performance of the stock market and if the stock market can be affected by macroeconomic factors such as real GDP growth, inflation, interest rates or unemployment.

P-Value – 0.8192 It indicates that the significant relationship between the returns of the market and the performance of the markets index is very low.

Coefficient – 1.7354 The slope is of the graph is positive which indicates that the stock returns increases relatively to the increase in the stock index.

R square – 0.2495 The R square measures the strength of the relationship, how strong or weak the relationship is. In this case we can conclude that the variability of the stock market index explains only 24.95% of the stock returns.

Franklin Electronic Publish Inc

P-Value – 0.6383 It indicates that the significant relationship between the returns of the market and the performance of the markets index is very low.

Coefficient – 1.514 The slope is of the graph is positive which indicates that the stock returns increases relatively to the increase in the stock index.

R square – 0.09 The R square measures the strength of the relationship, how strong or weak the relationship is. In this case we can conclude that the variability of the stock market index explains only 9 % of the stock returns.

UAL Corp

P-Value – 0.022 It indicates that the significant relationship between the returns of the market and the performance of the markets index is very low.

Coefficient – 1.933 The slope is of the graph is positive which indicates that the stock returns increases relatively to the increase in the stock index.

R square – 0.304 The R square measures the strength of the relationship, how strong or weak the relationship is. In this case we can conclude that the variability of the stock market index explains only 30.4% of the stock returns.

Sun Microsystems

P-Value – 0.635 It indicates that the significant relationship between the returns of the market and the performance of the markets index is very low.

Coefficient – 2.219 The slope is of the graph is positive which indicates that the stock returns increases relatively to the increase in the stock index.

R square – 0.441 The R square measures the strength of the relationship, how strong or weak the relationship is. In this case we can conclude that the variability of the stock market index explains only 44.1% of the stock returns. (Draper & Smith, 1998)

Silicon

P-Value – 0.697 It indicates that the significant relationship between the returns of the market and the performance of the markets index is very low.

Coefficient – 2.338 The slope is of the graph is positive which indicates that the stock returns increases relatively to the increase in the stock index.

R square – 0.067 The R square measures the strength of the relationship, how strong or weak the relationship is. In this case we can conclude that the variability of the stock market index explains only 6.7% of the stock returns.

The Relationship Between RET and WRETD

My findings that are based on the graph above indicate that there is no relationship between the returns on the stock market and the general performance of the stock index. My predictions were that the relationship that exists between the stock market and the performance of the individual stocks is very limited.

Macro-Economic Analysis

USA Macro-Economic Indicators

The analysis from the above graphs indicate that there is a significant relationship between the returns on company stocks and the macro economic factors such as real GDP growth, unemployment level and inflation rate. When the macro-economic factors in the growing are positively improving then most company stocks post good returns. When the factors are negative, for instance when the rates of inflation and unemployment are so high then the stock returns also post low returns. In the year 2008, during the global economic crisis, most economies registered negative real GDP growth, the unemployment levels were so high and inflation rates were at their peak in most countries. The stock returns for most countries were also affected negatively and they registered a drop in their earnings. When inflation rates are so high most companies lay off workers to reduce expenses and decrease borrowings due to the high cost of borrowing while unemployment levels increases, the real GDP growth also decreases due to reduced circulation of money in the economy. (Swann, 2009)  The company stocks are calculated and classified as per its volatility and in accordance with the stock market risks and beta. During the economic crisis of 2008, the volatility of most stocks were at their highest together with the term of most bonds.

1. My investment strategy would be to invest as per the performance of the individual company stock and not the general performance of the stock market.

References

Cairns, J (2004). Interest Rate Models – An Introduction. Princeton University Press.

Chen, N., Roll, R. and Ross, S.A. (1986) Economic Forces and the Stock Market. Journal of Business.

Draper, N.R., Smith, H. (1998). Applied Regression Analysis (3rd Ed.). John Wiley.

Sullivan, Sheffrin, S (2003). Economics: Principles in action. Upper Saddle River, New Jersey

Pearson, Prentice Hall.

Swann, C. (2009) “GDP and the Economy – Advance Estimates for the Second Quarter of 2009,” Survey of Current Business, August 2009.

http://research.stlouisfed.org/fred2/tags/series?t=&pageID=9

http://research.stlouisfed.org/publications/iet

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## Analysis of investment choices Assignment

Analysis of investment choices

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Table 2 below shows five alternative ways to invest a £100,000 lump sum. Explain how each of the investments might be exposed to the three high-level risks: capital risk, income risk and liquidity risk. Discuss how your assessment of each investment might change if the expected inflation rate fell from 4% to 2% a year.

Table 2: Alternative ways of investing a £100,000 lump sum
_________________________________________________________________________
Investment Key facts
Cashstream+ account
Instant savings account with NewBank, a former UK building society turned into a commercial bank.
Nominal interest rate: 2% a year, variable.
From the bank’s income statement: proportion of total bank income from net interest = 23%.
_____________________________________________________________________
Gold Star Saver account
Fixed-term savings account with Queen’s Bank, one of the oldest high-street banks in the country.
Interest rate: 1.25% a year, guaranteed for four years.
From the bank’s income statement: proportion of total bank income from net interest = 65%.
________________________________________________________________________
Gilt: 3% Treasury 2020
Government bonds with a redemption date of 2020.
Interest rate: 3% a year, guaranteed until redemption of bond in 2020.
_________________________________________________________________________
eSuits shares
Shares in rapidly growing company eSuits, a new e-commerce outfit selling bespoke gentlemen’s suits online, also listed on the London Stock Exchange.
__________________________________________________________________________
No dividend yet. Annual profits predicted to grow by 8% pa (might pay dividend later). Standard deviation of annualised return: 30%.
___________________________________________________________________________
Farmhouse in France Second home and holiday-let proposition, purchase price £300,000; mortgage obtained for £250,000 over 20 years at 6% variable interest; return expected to average 25% a year.

Analysis of Investment Choices

Investments are bound to be affected by various types of high-level risks in the market. The following discussion shows how various investments would be affected by capital risk, income risk and liquidity risk.

Cashstream + account

A savings account is unlikely to be affected by capital risk. This is because the initial amount of investment or deposit made remains intact. While the interest rates may vary, the capital investment remains unaltered and this option is therefore considered safe for risk-averse investors. Given that the interest payable is variable, the income risk is relatively high. This is because income stream paid for the investment is expected to decrease with decrease in interest rates. Liquidity risk for this type of investment is low as the investor may choose to withdraw their cash any time they wish to without restrictions as in a fixed account.

If inflation was to fall from 4% to 2% a year, there would be an increased rate of return as interest rates rise in response to the favorable inflation rates. Since real interest rate is equal to nominal rate minus inflation, the new real interest rate would shift from -2% to 0% for this investment.

Gold Star Saver account

This investment has a low capital risk the principle amount invested in a fixed account remains unchanged throughout the investment period. Income risk is also low because the interest on the account is guaranteed till maturity and is not dependent on changes in interest rates. Fixed-term savings accounts have a high liquidity risk and therefore are not suitable for investors who may need to retrieve their funds with urgency. If inflation was to reduce to 2%, the returns from the investment would remain unchanged. This is because the fixed account guarantees an interest rate of 1.25% per year. The returns are therefore fixed despite changes in the market and this may be a good investment.

Gilt: 3% Treasury 2020

Bonds have a relatively low capital risk as compared to other investments such as shares. In terms of income risk, the bond is worth investing in because the income risk is low. The bond is guaranteed to earn 3% per year until redemption. Liquidity risk is however very high. The investor will have to wait until the bond matures in 2020 in order to redeem the invested amount. This means that there is little ease in converting the bond into cash within a short period of time. A reduced rate of inflation would not affect the bond because it offers a fixed and guaranteed rate of return.

eSuits shares

This investment carries high capital risk, high income risk but has a low liquidity risk. Given that this is a business investment, the investor may have little influence on the profits or losses that the business incurs; yet their income depends on the profit made. Losses signify high chances of losing invested capital especially if the business does not work out eventually; hence high capital risk. Income depends on demand and other market factors and the income risk is high because it is difficult to predict demand. The liquidity risk is however low because the investor can easily retrieve cash upon the sale of the suits online. A reduction in inflation from 4% to 2% would mean that buyers have a higher purchasing power and demand is therefore likely to increase. Accordingly, returns for the investor would go up significantly.

Farmhouse in France

Capital risk is high for this investment; given that the prices in housing keep fluctuating and the value of the house may depreciate with time. Income risk may be high as well because income streams will depend on the availability of clients to let the farmhouse. In regards to liquidity risk, this is relatively high as disposal of the farmhouse to obtain liquid cash may take a signfificant amount of time before a potential buyer can be identified. Reduced inflation would affect this investment in a positive manner as the level of spending would go up; hence greater demand for letting the farmhouse.

Reference

Broadbent, M. & Cullen, J. (2012). Managing Financial Resources. London: Routledge

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## Choosing an investment Essay Paper Available

Choosing an investment

Investment

An investor may be interested in the net present value because of the following reasons:

Present value enables the investor to quantify expected benefits from an investment. A positive net present value is an indication that the investment is profitable while a negative value indicates that the project is not viable.

Secondly, present value determines the value of future cash-flows in ‘today’s value’ and this helps the investor to better understand the expected returns over the period of investment. According to Broadbent and Cullen (2012), it informs the investor of how much a future project would be worth if it existed today.

Choosing an investment

Present Value: Product 1

PV = C x [(1+r)n – 1 /r]

Coupon payment per year = (7% x 100) = £7

PV = 7 x (1.074 – 1/0.07)

£31.07

Present Value: Product 2

PV = FV/(1+r)n

FV = (25p x 4)6 + 5 = £11

= 11/(1+0.125)6

= £5.43

Present value: Product 3

PV = C x [(1+r)n – 1 /r]

Coupon payment per year = (11% x 100) = £11

Paid half yearly = 5.5

PV = 5.5 x (8.06-1)/0.11)

=  353.11

Based on the present values calculated above, I would consider investing in product 3. This is because the present value for the product is significantly high compared to the current value of the bond. It is therefore expected to generate more returns for the investor.

My choice would remain unchanged if the bond was to be sold at £140 because the interest rates remain unchanged. The present value of the bond is still low compared to the alternative investments.

Risks associated with holding government bonds

Governments bonds like any other investment come with various risks. Two of these risks are explained as follows:

Interest rate risk: Interest rates and bond prices are inversely related such that the prices of bonds rise when interest rates fall and go down when interest rates are high. When interest rates decline, investors in a bid to hold on to higher interest rates as long as they can will tend to buy bonds which pay a higher interest rate than the market rate. The high demand for bonds raises the prices of bonds. The opposite is true when interest rates go up; leading to low bond prices (Broadbent and Cullen, 2012).

Inflation risk: When there is a dramatic increase in inflation, investors may experience a negative rate of return as their purchasing power declines. This happens where the inflation increases at a faster rate than the investment (Broadbent and Cullen, 2012).

Reference

Broadbent, M. & Cullen, J. (2012). Managing Financial Resources. London: Routledge

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## How Macroeconomic factors Affect Stock returns Paper

Examination of how Macroeconomic factors Affect Stock returns.

Order Instructions:

Extra Project
The goal of the project: We examine how macroeconomic factors affect stock returns.
Empirically, we can test the following model;
Rt= ?0 + ?1*Market Indext-1+ ?2*Inflationt-1+ ?3*GDP Growtht-1+ ?4*TERMt-1+ ?5*RISKt-1+?

1. Dependent variable: firms’ stock returns
I posted firms’ stock returns in three industries (air, auto, and computer) to Blackboard. You can analyze any firm as you wish. You can pick multiple firms from three different industries, or a single firm from a specific industry.
Variable Explanations
DATE: the end of trading date at each month
COMNAM: Company name
EXCHCD: Exchange code (1: NYSE, 2: AMEX, and 3:NASDAQ)
HSICCD: Industry classification (e.g., The SIC 4512 represents an airline industry.
PRC: Stock price at the end of each month’s trading date
RET: Stock returns at the end of each month’s trading date
SHROUT: shares outstanding
VWRETD: Market index
2. Independent variables: macroeconomic variables
* The Source of data: http://research.stlouisfed.org/fred2/tags/series
Download data as long as we believe that variables may affect stock returns.
There are some candidates for independent variables.
Market Index=VWRETD, and Firm Size= PRC*SHROUT
Inflation= log (CPIt / CPIt-1), and GDP Growth=log (GDPt / GDPt-1)
TERM= 10-year T/B – 3-month T/B, and RISK= BAAt – 10-year T/B?

Questions
1) Report summary statistics (n, mean, median, standard deviation, min, max) of your picked variables.
2)Why do you include such independent variables? Give me a brief explanation.
3) Run a regression and report coefficients and t-statistics for the explanatory variables.
4) Interpret coefficients of each variable. Compare it with your prediction
* To obtain full credit (20 points), you need to submit it by July 8th, 2014.Grade below 10 points will be counted as zero.
* The minimum requirement is 5 different firms and 5 independent variables.
* TERM and RISK should be included as independent variables.
* If you need a reference, please look at the paper written by Nai-Fu Chen, Richard Roll, and Stephen A. Ross. The title is “Economic Forces and the Stock Market (Journal of Business, 1986)”.

Examination of how Macroeconomic factors Affect Stock returns.

Research Findings

The goal of the project is to examine macroeconomic factors affecting stock return using the following model Rt= ?0 + ?1*Market Index-1+ ?2*Inflation-1+ ?3*GDP Growth-1+ 4*Terms-1+?5*RISK-1+?, The study uses stocks of  from stock returns in three industries (air, auto, and computer), the dependent variable is the firms stock return, out of the several proposed independent variables the model used market index, inflation, GDP Growth , terms and risk assessment, the variables included in this study were chosen on the similar variables of existing literature from previous study on the relationship between stock return and macroeconomic variables (Chen et al, 1986).

 market index inflation production terms risk Mean 1.99 32.58 4.35 1.79 0.02 Min 1.86 14 3.68 1.119 -0.49 Max 2.12 67.90 4.86 2.14 0.33 SD 0.05 10.89 0.37 0.29 38.37 Skewness 0.11 0.19 -0.17 -0.83 -1.31 Kurtosis 2.67 2.33 1.73 2.58 14.63

The basic descriptive statistics from the raw stock data is as following indicating mean, minimum, standard deviation, maximum, skewness and kurtosis, the mean of all the exploratory variables indicating a volatile market, the standard deviation is very high which is an indicator of a very volatile market, positive and negative minimum and maximum are signs of that a market that sometimes is profit and other times brings huge losses, similarly the table indicates negative skewing with a very extreme kurtosis which also indicates that the returns are not normally distributed (Chen et al, 1986).

Regression Results

• The regression report includes the model summary and t score as well as its significance level by examining all the proposed macroeconomic variables and how they are affecting stock return using the following model From the model, the significance of  the predictors variables. R is a measure of the correlation between the observed value and the predicted value of the criterion variable. R Square (R2) is the square of this measure of correlation and indicates the proportion of the variance in the criterion variable which is accounted for by our model. In essence, this is a measure of how good a prediction of the criterion variable we can make by knowing the predictor variables. However, R square tends to somewhat over-estimate the success of the model when applied to the real world, so an Adjusted R Square value is calculated which takes into account the number of variables in the model and the number of observations (participants) our model  predictors based on which is  Market Index=VWRETD, and Firm Size= PRC*SHROUT
Inflation= log (CPIt / CPIt-1), and GDP Growth=log (GDPt / GDPt-1)
TERM= 10-year T/B – 3-month T/B, and RISK= BAAt – 10-year T/B?
We now have  an adjusted R Square value of 0.667 we can say that our model now  accounted for 66.7 % of the variance in the criterion variable. Therefore it can be deduced that the five predictors which includes inflation, interest rate,, market index, GDP Growth account for stock returns well.

Table 14

 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .667a .752 .621 4.804

 ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 178794.461 6 29799.077 6.991 .000a Residual 477429.379 112 4262.762 Total 656223.840 118 a. predictors: (Constant), Money Index, inflation, risk, consumption, treasury bill rate, production b. Dependent Variable: stockreturn

 coeffecient Model Unstandardized Coefficient Standardized Coefficient t Sig. B Std. Error Beta 1 (Constant) -192.676 156.067 -1.235 .220 inflation 1.986 1.971 .308 1.008 .016 production -2.742 1.852 -.520 -1.481 .141 consumption 25.930 13.747 .367 1.886 .062 treasury bill rate -.397 .311 -.313 -1.275 .005 risk 4.286 1.066 .460 4.022 .000 Money Index -2.526 2.876 -.120 -.878 .382 a. Dependent Variable: stockreturn

Beta (standardized Beta coefficients is a measure of the contribution of each variable to the model. A large value indicates that a unit change in this predictor variable has a large effect on the criterion variable. The t and sig(p) values gives a rough indication of the impact of each predictor variable, a big absolute t value and a small p value suggests that a predictor variable is having a large impact on the criterion variable. Our regression output evaluated indicate that all the independent variables have impact on stock return except interest rate and explaining the independent variables as used by the model, it is proposed that there will be an inverse relationship between stock price and interest rate thereby an increase in interest rate leads to an increase of the return of interest. There is a relationship between money supply or inflation and stock return where the high inflation has a negative effect on stock prices and then the exchange rate exchange rate and inflation outcomes affect cash flow which in turn affects stock return, industrial production index is aggregation of overall economic performance, and therefore when economic performance improves it will affect stock return directly risk in this case covers the effect on returns of anticipated changes on money market (Chen et al, 1986).

References

Chen, N. F., Roll, R., & Ross, S. A. (1986). Economic forces and the stock market. Journal of business, 383-403.

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## Portfolio optimization Assignment Available

Portfolio optimization

Order Instructions:

1. By doing the optimisation using Excel Solver, you are required to construct a mean variance efficient portfolio frontier for any 10 randomly selected ordinary shares listed on a stock market. For all your calculations, you should use the 60 monthly returns, sample means, standard deviations, and covariance and correlation matrices. Plot the portfolio frontier and comment on the weights of the portfolios along the portfolio frontier including in your discussion the correlations among the 10 shares.

2. Identify a riskless asset and provide the rationale for your choice of the riskless asset.

3. By combining the riskless asset with the 10 shares, plot the straight line efficient portfolio frontier and select the tangent portfolio on the portfolio frontier.

4. Assume that the short selling is not allowed, how your efficient frontiers would differ from those with short selling allowed in questions 1 and 3 above.

5. Identify the appropriate benchmark index and justify your choice of the benchmark index.

6. Evaluate the performance of the tangent portfolio selected above using:

a) Sharpe’s Measure
b) Treynor’s Measure
c) M2 Measure
d) Jensen’s Performance Measure
e) The Appraisal Ratio.

7. Comment on the limitation of your analysis.

8. Critically evaluate the gains in the performance of the identified portfolio along with the associated risks from investing in other asset classes, for instance,  investment in gilts (including index linked), corporate bonds, convertible bonds, commodities, real estate, hedge funds and exchange traded funds.

NB

This is a portfolio optimization assignment.

It has to be done with excel after the report writing on word.

### Portfolio optimization

Introduction

Investing in the stock markets is highly dependent on the performance of the portfolio in which a certain investor has put his/her money. This principle of portfolio optimization was popularized by Markowitz who developed an appropriate method through which an investor could devise the most important stock portfolio for investment by avoiding risky stocks and prioritizing on investing in the stocks with the highest potential for maximum returns. Therefore, Markowitz portfolio indicates that it is necessary to increase assets and/or stocks in an investment portfolio the where the total risk of that portfolio is considered to be low or as measured by the standard deviation (or variance) of total return declines continuously, whereas the envisaged portfolio return is a weighted average of the expected returns of the individual assets. This implies that investing portfolios instead of individual assets and/or stocks, investors have a chance of significantly lowering the total risk of investing without necessarily sacrificing returns on their investments.

Therefore, the Markowitz’s mean-variance theory is usually implemented through the Excel Solver spreadsheet calculations meaning that it always optimize allocation of assets by finding the stock distribution through which there is minimization of the standard deviation or variance of the portfolio while at the same time sustaining the desired return on the stocks and/or assets. The origin of modern portfolio theory was in the 1950s with Harry Markowitz’s pioneering work in mean-variance portfolio optimization.  However, prior to Markowitz’s innovation, heuristics were the ones who significantly influenced finance more than mathematical modeling. Mean-variance optimization is currently considered the core technique used by pension funds and hedge funds for portfolio diversification.

Most investors trade risk off against the envisaged return on their investments.  Mean-variance optimization plays a crucial role in the identification of the investment portfolio responsible for the minimization of risk (i.e. standard deviation) for a given return.  In most cases the line which is formed when the envisaged returns are plotted against the minimized standard deviation becomes the most efficient frontier for determining the most appropriate invetment portfolio.

Background of Stock Portfolio Optimization

There is a certain return for every stock in the market and it is assumed that a normal distribution is portrayed by this return. This implies that the distribution for these returns for the stock can be completely described using the mean which represents the expected return as well as variance of the returns. Moreover, between any pair of stocks covariance of the returns can be computed whereby the stocks that show positive covariances, it means that they move together while the stocks that show negative covariances move in the opposite directions. Therefore, if the envisaged returns for a certain stock return or a group of stock’s returns are known, a portfolio of these stocks can be put together because of their desired variance (risk) in the stock market as a result of their envisaged return. Thus, solver, excel is mainly used for the purpose of picking the portfolio in possession of the least variance for an envisaged return meaning that the investor is likely to gain profits from his/her investment.

However, the expected return as well as the portfolio’s variance can be calculated using the method that was developed by Harry Markowitz which is crucial in the computation of portfolio return in terms of the sum of individual stock covariances and variances between stocks’ pairs in a certain portfolio. This is definitely the right thing to do from a mathematical standpoint, even though all covariances between any portfolios pair of stocks is considered meaning there would be so many calculations that would be required to accomplish this task. Alternatively, another method was devised by William Sharpe for the determination of the envisaged return and variance for a certain portfolio. This is a simpler method compared to the previous one because it assumes that any stock’s return has two parts such as the beta part which depends on the entire market performance, and the second one which is independent of the market. These two methods have been extensively used to determine the performance of specific groups of stock portfolios in the stock markets across the world for a considerable period of time.

Discussion

In our considered example, the optimal portfolio in stock market provides a risk-return tradeoff for superior to investing in all the shares within the UK stock exchange market. For instance, through the computations of the Excel Solver it has been determined. For instance, the portfolio optimization analysis began with the analysis of descriptive aspects of the considered 10 stock returns over a period of 60 months including means, standard deviations, and median.  Moreover, the correlation and covariance matrix as well as correlation coefficient all seem to indicate that there is significant relationship between the 10 stocks considered over the 60 months.

Moreover, there are also other performance ratios such as the Treynor’s measure, Sharpe ratio, Jensen’s Performance Measure, and the appraisal ratio. For instance, Treynor’s measure of 0.4 which is relatively low considering that it is below the half mark, this implies that selected portfolio is not that better since the higher the Treynor’s measure. The Sharpe ratio is almost identical to the Treynor measure, with exception of the fact that the risk measure is the standard deviation of the portfolio rather than only considering the systematic risk, as represented by beta. Therefore, the Sharpe ratio of 1.6 is indicative of a portfolio that is not performing better. This may be attributable to the selected stock with lowly performing returns, except a few which show considerable performance.

Jensen’s Performance Measure analyses the performance of an investment by not only looking at the overall return of a portfolio, but also at the risk of that portfolio. For instance, when two mutual stocks, rationally an investor would go the one that is less risky meaning that the obtained value of 0.2 is and indicative of considerable performance of the stocks. Finally, the Appraisal Ratio of 0.5 shows that it is necessary to attempt to beat the returns of a relevant benchmark or of the overall market. The appraisal ratio measures the portfolio performance by comparing the return of their stock picks to the specific risk of those selections, hence the higher the ratio, the better the performance of the portfolio in question.

This implies that two step must always be taken prior to determining where to invest in the stock market, where the first one regards the determination of the allocation of stocks/assets between the riskless portfolio and the risky assets and/or stocks. The second step is the determination of the allocation of resources between the risky and riskless portfolios. However, considering that all the portfolios of riskless and risky assets have a similar Sharpe ratio, all investors do not have one optimal portfolio, but their allocation is often determined by specific factors that are individual like the objectives of the investor or risk aversion of the investor, taking into account factors like the investor’s horizon, wealth, etc. Furthermore, the extent to which the volatility of the portfolio can be decreased is highly dependent on the correlation whereby, the lower the average correlation of the stocks within a certain portfolio, then it implies that that is the lower an investor can decrease the volatility of the portfolio. This is a clear indication that this has provided the author of this assignment with succinct knowledge of determining the optimal allocations in stock markets.

Conclusion

Through this assignment it has been shown that, it is possible to use specialized spreadsheets for the calculation of important risk and return related portfolio statistics in the stock markets as well as minimizing the overall risk or maximizing the expected return of a multi-stock portfolio. However, it is essential to know that irrespective of these calculations being useful when creating investment portfolios, they rest on the assumption that historical relationships between asset classes and individual assets will hold in the future. This means that it is always crucial for investors to choose a period that they feel is representative of a “typical” market cycle, in order to avoid a capturing a repetitive cycle that is not relevant.

Moreover, the mean-variance portfolio optimization has its limitations, despite the fact that it is very helpful in choosing appropriate portfolios. For example, using standard deviation (or variance) as a proxy for risk can only be considered valid for normally distributed returns, and not any other returns which is not always the case in the stock markets. In addition, the premise of the Markowitz theory means that investors are not likely to make any alterations to their asset allocation after it has been optimized. Finally, fund managers or investors may not necessarily be interested in the minimization of risk (i.e. standard deviation or variance), but instead they may be interested in reducing the correlation of a fund to a benchmark. These are the limitations of the used method, even it is very crucial in determining portfolio optimization.

Reference List

Arnold, G. (2008), Corporate Financial Management, Third Edition, New York, NY: Pearson Education Limited.

Craig, W. H. (2008), Excel Modelling and Estimation in Investments, Third Edition, Indiana University, Prentice Hall, Inc.

FTSE Website http://www.ftse.com/products/indices/uk

Goldfarb, D. and Iyengar, G. (2003), “Robust Portfolio Selection Problems”. Mathematics of Operations Research, Vol.28 Issue 1, pp. 1-38.

Jackson, M. and Staunton, M. (2001), Advanced Modelling in Finance using Excel and VBA. Chichester, England: John Wiley & Sons.

Markowitz, H.M. (1959), Portfolio Selection: Efficient Diversification of Investments. New York, NY: John Wiley & Sons.

Markowitz, H.M. (1952). “Portfolio selection” The Journal of Finance, Vol. 7 Issue 1, pp. 77-91.

Sharpe, W.F., (1964), “Capital asset prices: A theory of market equilibrium under conditions of risk”. Journal of Finance, Vol. 19 Issue 3, pp. 425-442.

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## Statement Analysis

In your statement analysis coursework assignment, discuss the relative usefulness of alternative measures of profit (or income) to equity investors. Your answer should include;

(i) a discussion of the potential contribution of key valuation models to identifying useful approaches to profit measurement from an equity investor perspective and

(ii) a review and analysis of research findings on the usefulness of alternative profit measures to investors. Your analysis should consider both reported profit measures disclosed in the GAAP based financial statements and non-GAAP profit measures produced by company management and financial analysts.

You should also use profit figures for a company of your choice to illustrate potential differences in the information conveyed to investors by different profit measures.

Approximately 80% of the total mark will be allocated to your discussion of key issues and literature and 20% to your use of company data to illustrate your points.

Word limit: No more than 1,500 words.

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## Investments, Corp. Finance and Financial Markets

Investments, Corp. Finance and Financial Markets

Assignment Question
In order to assess and manage credit risk and to minimize the risk of default on an individual advance (credit), banks can, as a first step, consider what
loaned funds are intended to be used for (or what they are being used for) and other financial circumstances of the borrower. Credit scoring is playing an increasingly prominent role in selecting good risks in consumer lending. A potential borrower (applicant) is asked a standard set of questions relating to factors such as age, assets held, financial commitments, and so on; and, based on the answers, a score is calculated reflecting the credit risk of the
applicant.
Consider the foregoing statement. Explain the method of credit scoring. Discuss various ways in which credit scoring could be employed by commercial and retail banks in order to reduce the incidence of loan defaults. Critically evaluate the effectiveness and robustness of this method as a credit risk management technique.

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## Increase in Foreign Direct Investment from China Paper

Is the increase in Foreign Direct Investment from China to blame for blame for Australia suffering from Dutch Disease

Use descriptive statistics
Regression if necessary; I understand coefficients, t-test; null hypothesis. If you do use this, then indicate the fitness of the model used as well e.g multicolinearity, autocorr….etc
I used data stream to get my data mainly from; World Bank WDI; Australian Bureau of Statistics &amp; OECD Main Economic Indicators and my main sources but indicate if you have used others

Basic Format to follow:
Most important thing to do is to indicate that Dutch Disease is occurring in Australia statistically
Then indicate how you know statistically, various components of Dutch Disease.
Then indicate if it is due to China’s INWARD FDI or not.

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