Assignment Brief – Postgraduate Programme (UK and Qatar) MSc Finance MSc International Finance and Investment MSc Business with Programme (for students taking the module) Module Code: MN0493 Module Title: Investments and Risk Management Distributed on: 25/01/2021 Submission Time and Date: TBC Word Limit: 3,000 words Weighting This coursework accounts for 100 % of the total mark for this module Submission of Assessment Electronic Management of Assessment (EMA): This assignment should be submitted online via Turnitin by the given deadline. You will find a Turnitin link on the module’s eLP site. It is your responsibility to ensure that your assignment arrives before the submission deadline stated above. See the University policy on late submission of work (the relevant extract is set out below). Instructions on Assignment: In Teaching Week 3 of Semester 2 you are instructed to engage in the following activities: Assume you were approached by a client five years ago with £1000,000* to invest in the portfolio of equities. As an asset manager working for a reputable company in the city, you asked various questions related to risk appetite and investment objectives of the client who agreed to invest the fund passively for the first five-year period. This year your client decided to invest the money actively for the 10-week period from teaching week 3 to week 12. In teaching week 3, you are therefore required to reinvest the realised money from passive investment in an active portfolio for which you have decided to make a thorough economic environment analysis and forecasting including a reassessment of your client’s risk tolerance and investment objectives. In this active investment period, your client has agreed with you to make investment in Equities (stocks) and Fixed-Income securities (corporate bonds). The client has surplus fund so if the money available from the realisation of passive portfolio is less than £1000,000, the client will fund the difference amount to invest in the active portfolio i.e., you will have a minimum of £1,000,000 to invest in the new portfolio. During the active portfolio management period of 10 weeks, you are instructed to select a range of suitable equities and bonds (only corporate bonds) for inclusion in the portfolio. In this period, you can buy, hold or sell securities. However, such decisions should be based on the findings of appropriate investment theory, models and relevant analysis. Additionally, you should compare your portfolio performance with suitable benchmark(s) and provide narrative interpretation of the evaluation. You are encouraged to make use of the Bloomberg trading terminals for portfolio functionalities where available (but excel may be used). * Should you decide to invest in currency other than GBP, you can take equivalent amount of £1000,000 and this conversion is allowed for both passive and active investments. Required: 1. Report the major points of your discussions with the client. This should include construction of the portfolios and you should provide the detail of the allocation with justification demonstrating how the https://livenorthumbriaacmy.sharepoint.com/personal/binam_ghimire_northumbria_ac_uk/Documents/Desktop/Desktop1/MN0493/MN0493_100%_CWa ssignment_20.21.docx Page 1 of 5 Assignment Brief – Postgraduate asset allocation match the investor profiling. The allocation in the active portfolio should consider the market forecast. Your discussion should be supported by relevant theories and academic literature. (15 marks) 2. Management of the stocks and bond portfolio (active portfolio only): Details of changes made including reflection on strategy selected and reasons for portfolio restructuring. You should undertake a minimum of three rebalancing. Your rebalancing strategies should be supported by relevant investment theories and assets pricing models. (30 marks) 3. A final evaluation of overall performance (for both the active and passive portfolio) as at the end of Teaching Week 12 carried out using suitable quantitative measures including both the absolute and relative performance evaluations. You should explain the performance difference between your portfolio and the given benchmark(s) using risk adjusted and other techniques, such as tracking error and attribution analysis. (40 marks) 4. In line with the Value at Risk method of risk measurement, explain the risk exposure faced by your client’s portfolio. Client has also requested information about hedging risk using derivative instruments. As such, this section of your report should include relevant literature for VaR, risk exposure, and an illustrative example of hedging using Derivatives. (15 marks) Late submission of work Where coursework is submitted without approval, after the published hand-in deadline, the following penalties will apply. For coursework submitted up to 1 working day (24 hours) after the published hand-in deadline without approval, 10% of the total marks available for the assessment (i.e.100%) shall be deducted from the assessment mark. For clarity: a late piece of work that would have scored 65%, 55% or 45% had it been handed in on time will be awarded 55%, 45% or 35% respectively as 10% of the total available marks will have been deducted. The Penalty does not apply to Pass/Fail Modules, i.e. there will be no penalty for late submission if assessments on Pass/Fail are submitted up to 1 working day (24 hours) after the published hand-in deadline. Coursework submitted more than 1 working day (24 hours) after the published hand-in deadline without approval will be regarded as not having been completed. A mark of zero will be awarded for the assessment and the module will be failed, irrespective of the overall module mark. For clarity: if the original hand-in time on working day A is 12noon the 24 hour late submission allowance will end at 12noon on working day B. These provisions apply to all assessments, including those assessed on a Pass/Fail basis. Word limits and penalties If the assignment is within +10% of the stated word limit no penalty will apply. The word count is to be declared on the front page of your assignment and the assignment cover sheet. The word count does not include: https://livenorthumbriaacmy.sharepoint.com/personal/binam_ghimire_northumbria_ac_uk/Documents/Desktop/Desktop1/MN0493/MN0493_100%_CWa ssignment_20.21.docx Page 2 of 5 Assignment Brief – Postgraduate • Title and Contents page • Glossary • Reference list • Appendices • Bibliography • Quotes from interviews and focus groups. • Appropriate tables, figures and illustrations Please note, in text citations [e.g. (Smith, 2011)] and direct secondary quotations [e.g. “dib-dab nonsense analysis” (Smith, 2011 p.123)] are INCLUDED in the word count. If this word count is falsified, students are reminded that under ARNA page 30 Section 3.4 this will be regarded as academic misconduct. If the word limit of the full assignment exceeds the +10% limit, 10% of the mark provisionally awarded to the assignment will be deducted. For example: if the assignment is worth 70 marks but is above the word limit by more than 10%, a penalty of 7 marks will be imposed, giving a final mark of 63. Students must retain an electronic copy of this assignment (including ALL appendices) and it must be made available within 24hours of them requesting it be submitted. Note: For those assessments or partial assessments based on calculation, multiple choice etc., marks will be gained on an accumulative basis. In these cases, marks allocated to each section will be made clear. Time limits and penalties for presentations The time allocated for the presentation must be adhered to. At the end of this time, the presentation will be stopped and will be marked based on what has been delivered within the time limit. Academic Misconduct The Assessment Regulations for Northumbria Awards (ARNA) contain the Regulations and procedures applying to cheating, plagiarism and other forms of academic misconduct. The full policy is available at: http://www.northumbria.ac.uk/sd/central/ar/qualitysupport/asspolicies/ You are reminded that plagiarism, collusion and other forms of academic misconduct as referred to in the Academic Misconduct procedure of the assessment regulations are taken very seriously by Newcastle Business School. Assignments in which evidence of plagiarism or other forms of academic misconduct is found may receive a mark of zero. Mapping to Programme Goals and Objectives: This assessment will contribute directly to the following Postgraduate programme goals and objectives. Goal One: Be independent, reflective critical thinkers x 1. x 2. Demonstrate awareness of their personal strengths and weaknesses through critical reflective practice. Understand and challenge personal patterns of thinking and behaving. Goal Two: Be culturally and ethically aware x 1. Demonstrate their ability to work in diverse groups and teams. 2. Reflect on their own ethical values. Goal Three: Have developed leadership and management capability https://livenorthumbriaacmy.sharepoint.com/personal/binam_ghimire_northumbria_ac_uk/Documents/Desktop/Desktop1/MN0493/MN0493_100%_CWa ssignment_20.21.docx Page 3 of 5 Assignment Brief – Postgraduate 1. Demonstrate their personal contribution to team effectiveness. x 2. Communicate complex issues effectively. x 3. Demonstrate decision making and problem solving skills. 4. Carry out presentations and lead discussions. Goal Four: Have developed and applied knowledge of international business and management theory x 1. Acquire, interpret and apply knowledge of international business, management and organisational functions. Goal Five: Have developed a range of research skills and project capabilities x 1. x 2. Plan and complete a major individual piece of research on a contemporary business, management or leadership topic of their choice. Demonstrate skills of analysis and synthesis in the application of research methods to the exploration of contemporary business issues. Goal Six: Have developed specialist knowledge about the theory and practice of your programme of study x 1. Demonstrate specialist functional knowledge in relation to your programme of study. https://livenorthumbriaacmy.sharepoint.com/personal/binam_ghimire_northumbria_ac_uk/Documents/Desktop/Desktop1/MN0493/MN0493_100%_CWa ssignment_20.21.docx Page 4 of 5 Assignment Brief – Postgraduate Module Specific Assessment Criteria Required 0 - 39 Standard Not Met 1(Fail) 40 – 49 Standard Not Met 2 (Fail) 60- 69 Pass Meets Standard 2 (Commendation) 50 - 59 pass Meets Standard 1 (Pass) 70 – 79 Exceeds Standard 1 (Distinction) 80 - 89 Exceeds Standard 2 (Distinction - 80s) 90 - 100 Exceeds Standard 3 (Distinction and Outstanding) Insufficient:: *explanation of investment approach, strategies market view, and asset allocation decisions – but lack of support from theories; lack of clarification of the assumptions used; weak market view. Asset allocation decisions do not match investor profiling or limited. Excellent*discussion of investment Good : *some good discussion of approach, strategies which are very well investment approach and strategies Very good : *discussion of investment linked to and supported by theories. which may have a link to and support approach, strategies which are linked to *discussion of market view which is fact from theories *discussion of market view and supported by theories. *discussion of based and established on the clear and with some good assumptions and based market view which is fact based and most appropriate on facts although limited*discussion of established on the clear assumptions. assumptions.*discussion of asset asset allocation decisions but the theory *discussion of asset allocation decisions allocation decisions which is clearly can provide more support, good link which is clearly linked to investor linked to investor profiling, and between asset allocation decisions and profiling. supported by asset allocation investor profiling. optimisation process. Q2. Rebalancing 30% *Poor, limited or no discussion of rebalancing strategies; weak understanding and application or no application of models to back up investment decisions; poor or no academic literature review; *Inadequate discussion of rebalancing strategies; some link to and supported by investment theories; understanding and application of models to back up investment decisions but not good enough; academic literature review may be available but there is no clear direction; reflections showing poor understanding of finance theories. *Good discussion of rebalancing strategies; which are linked to and supported by relevant traditional investment theories *good understanding and application of models to back up your investment decisions; *academic literature review which demonstrates a good understanding of the big picture in investment areas. *Very good discussion of rebalancing strategies; which are linked to and well supported by relevant traditional investment theories * very good understanding and application of models to back up your investment decisions *academic literature review; which demonstrates a very good understanding of the big picture in investment areas. *Excellent discussion of rebalancing strategies which are robustly linked to and fully supported by relevant traditional investment theories * excellent understanding and application of models to back up your investment decisions; *academic literature review which demonstrates a deep understanding of the big picture in investment areas. *Highly detailed research and exemplary *Unusually strong * detailed research discussion of rebalancing strategies and exemplary discussion of rebalancing which are robustly linked to and fully strategies which are robustly linked to supported by relevant traditional and fully supported by relevant investment theories * Outstanding traditional investment theories * understanding and application of models understanding and application of models to back up your investment decisions; to back up your investment decisions; *academic literature review which *academic literature review which demonstrates a deep understanding of the demonstrates a very deep understanding big picture in investment areas. of the big picture in investment areas. Q. 3 Evaluation 40% Poor, Limited or No: *awareness of risk adjusted return measures and performance attribution analysis*calculation of portfolio's performance as well as benchmark performance *performance attribution analysis, tracking error * evaluation and understanding of asset allocation skills and share selection skills *academic linkage for both active and passive and other strategies. Inadequate:*awareness of risk adjusted return measures and performance attribution analysis*calculation of portfolio's performance as well as benchmark(s) performance *performance attribution analysis, tracking error *linking of results with irrationality where relevant * evaluation and understanding of asset allocation skills and share selection skills *academic linkage for both active and passive and other strategies. Good:*awareness of risk adjusted return measures and performance attribution analysis*calculation of portfolio's performance as well as benchmark(s) performance *performance attribution analysis, tracking error * evaluation and understanding of asset allocation skills and share selection skills *academic linkage for both active and passive and other strategies. Very good: *awareness of risk adjusted return measures and performance attribution analysis*Calculation of portfolio's performance as well as benchmark(s) performance *performance attribution analysis, tracking error * evaluation and understanding of asset allocation skills and share selection skills *academic linkage for both active and passive and other strategies *Excellent: *awareness of risk adjusted return measures and performance attribution analysis*calculation of portfolio's performance as well as benchmark(s) performance *performance attribution analysis, tracking error *linking of results with irrationality where relevant * professional presentation, evaluation and understanding of asset allocation skills, *academic linkage for both active and passive and other strategies *Outstanding: *awareness of risk adjusted return measures and performance attribution analysis*calculation of portfolio's performance as well as benchmark(s) performance *performance attribution analysis, tracking error *linking of results with irrationality where relevant * professional presentation, evaluation and understanding of asset allocation skills, *academic linkage for both active and passive and other strategies Outstanding *awareness of risk adjusted return measures and performance attribution analysis,*calculation of portfolio's performance as well as benchmark(s) performance *performance attribution analysis, tracking error *linking of results with irrationality where relevant * professional presentation, unusually strong evaluation and understanding of asset allocation skills, *especially strong academic linkage for both active and passive and other strategies Evidence of limited knowledge, VaR/ Derivatives may be incomplete Good: Knowledge of VaR computation. *one illustration of hedging strategy using Derivatives (such as, options). Adequate interpretation of the presented results and some literature. Very good: Knowledge of VaR computation. *one illustration of hedging strategy using Derivatives (such as, options). Very good interpretation of the presented results and discussions of relevant literature. Excellent: Knowledge of VaR computation. *illustration(s) of hedging strategy using Derivatives (such as, options). Excellent interpretation of the presented results and discussions of relevant literature. Outstanding: Knowledge of VaR computation. * illustration(s) of hedging strategy using Derivatives (such as, options). Outstanding interpretation of the presented results and discussions of relevant literature. Outstanding: *Knowledge of VaR computation. * illustration(s) of hedging strategy using Derivatives (such as, options). Outstanding and especially strong interpretation of the presented results and discussions of relevant literature. *Limited or very poor understanding shown on investment philosophy, strategies, market view, and asset Q. 1 Investment Philosophy allocation concept. The link between 15% theory, assumptions, investor's profiling and the investment decisions is again either very poor or missing. Q.4 VaR and Derivatives Incomplete or part of work 15% may be missing. Note: Outstanding and unusually strong Outstanding *discussion of investment *discussion of investment approach, approach, strategies and linkage with strategies and linkage with theories that theories that are exemplary. *discussion are exemplary. *discussion of market of market view which is fact based and view which is fact based and established established on the clear and most on the clear and most appropriate appropriate assumptions.*discussion of assumptions. *discussion of asset asset allocation decisions which is allocation decisions which is clearly clearly linked to investor profiling, and linked to investor profiling, and supported by asset allocation supported by asset allocation optimisation process. optimisation process. Students are advised to retain an electronic copy of their assignment answer. https://livenorthumbriaac-my.sharepoint.com/personal/binam_ghimire_northumbria_ac_uk/Documents/Desktop/Desktop1/MN0493/MN0493_100%_CWassignment_20.21.docx Page 5 of 5 C INVESTMENT AND RISK MANAGEMENT TUTOR - BINAM GHIMIRE Word Count: 3213 MN0493 - INVESTMENT AND RISK MANAGEMENT 1|Page CONTENTS 1. Portfolio Overview ...................................................................................... 2 1.1. Passive Portfolio ...................................................................................... 2 1.1.1. Investment Philosophy....................................................................... 2 1.1.2. Investor Profile................................................................................... 2 1.1.3. Passive Portfolio Results ................................................................... 2 1.2 Active Investment Portfolio ...................................................................... 3 1.2.1. Investment Philosophy....................................................................... 3 1.3. Asset Allocation ....................................................................................... 3 1.3.1 Portfolio size ....................................................................................... 3 1.3.2 Diversification ..................................................................................... 3 2. Equity Portfolio Management ..................................................................... 4 2.1 Efficient Market Hypothesis ...................................................................... 4 2.2 Capital Asset Pricing Model (CAPM) .......................................................... 4 2.2.1 Beta Values ......................................................................................... 4 2.2.2 Security Market Line ........................................................................... 5 2.2.3 Multi Factor Model ............................................................................. 5 2.3 Fundamental and technical analysis.......................................................... 6 2.3.1 Past stock price movement ................................................................. 6 2.3.2 P/E ratio, Gordon’s growth model ...................................................... 6 3. Bond Portfolio Management ....................................................................... 7 3.1 Credit ratings ............................................................................................ 7 3.2 Interest rates ............................................................................................ 7 3.3. Yields ....................................................................................................... 7 3.4 Duration, Modified Duration ..................................................................... 8 3.5 Bond laddering.......................................................................................... 8 MN0493 - INVESTMENT AND RISK MANAGEMENT 2|Page 4. Portfolio Performance Evaluation................................................................ 9 5. VAR .......................................................................................................... 10 5.1 Methods of VAR ...................................................................................... 10 5.2. VAR Results ............................................................................................ 11 6. Option Strategy ............................................................................................ 12 Appendices ...................................................................................................... 14 7. Appendix One – Risk Assessment ................................................................. 15 8. Appendix Two – Market Forecast................................................................. 16 9. Appendix Three – Portfolio Allocation ......................................................... 18 10. Appendix Four – Benchmark Selection ....................................................... 20 11. Appendix Five – Bonds ............................................................................... 22 12. Appendix Six – Equities .............................................................................. 24 13. Appendix Seven – Evaluation of portfolios performance ........................... 26 14. Appendix Eight – VAR Methods.................................................................. 29 References .......................................................... Error! Bookmark not defined. MN0493 - INVESTMENT AND RISK MANAGEMENT 3|Page List of figures Figure 1 – Expected Return Formula Figure 2 – Security Market Line Graph Figure 3 - Gordon’s growth model formula Figure 4 – UK Yield Curve Figure 5 – US Yield Curve Figure 6 – Bond Laddering Figure 7 – Portfolio Performance Graph Figure 8 -Straddle Purchase Figure 9 – Straddle Write Figure 10 – Asset Allocation Figure 11 – Sector Diversification - Passive Figure 12 - Sector Diversification - Active Figure 13 – Country Diversification- Passive Figure 14 – Country Diversification – Active Figure 15 – Credit Ratings Figure 16 – Equity Correlation Figure 17 – Benchmark Comparison Figure 18 – Equity Curve MN0493 - INVESTMENT AND RISK MANAGEMENT 0|Page List of tables Table 1 – Beta Values Table 2 – Bond Duration Table 3 – Portfolio Evaluation Ratios Table 4 – Value-at-Risk Results Table 5 – Risk Assessment Table 6 – Economic Forecast Table 7 – Benchmark Selection Table 8 – Bond Selection Table 9 – Bond Credit Rating Table 10 – Bond Correlation Table 11 – Equity Portfolio Table 12 - Monte Carlo Simulation - Method Table 13 - Monte Carlo Simulation - Results Table 14 - Variance Covariance - Method Table 15 - Variance Covariance - Results Table 16 - Historical Simulation – Method Table 17 - Historical Simulation – Results MN0493 - INVESTMENT AND RISK MANAGEMENT 1|Page 1. Portfolio Overview 1.1. Passive Portfolio This section of the report will review the results from XYZ’s passive portfolio. This portfolio was created five years ago for client XYZ, who approached me with £1,000,000 to invest. After a detailed discussion and an analysis of the client’s investment objectives and risk appetite, it was agreed that the funds would be invested passively for the first five-year period. 1.1.1. Investment Philosophy According to William Sharpe’s investment theory, active investing is essentially a zero sum game before costs and hence a negative-sum game after accounting for the costs associated with buying and selling. This implies that following a passive investment strategy of simply buying and holding assets would lead to a better performance than many actively managed investments funds as it keeps costs to a minimum (Sharpe, 1991; Blitz, 2014). For this passive fund, a top down approach was applied. The top down approach begins with a broad overview of the global market, reviewing variables such as inflation and GDP, this economic forecast is available in Appendix 2. . Following this, the analysis narrows to consider different industries and sectors. This step aims to minimise risk and maximize returns by accounting for the fact different industries will inevitably react differently to the same event. Neely and Cooley (2004) found that almost half of the funds they surveyed had selected their stocks without consideration of the industries included. The final stage of the top down approach is a fundamental analysis of the security's intrinsic value relative to the security's market value (Dolan & Stevens, 2010). 1.1.2. Investor Profile Client XYZ is an inexperienced investor that has inherited a large sum of money from a deceased relative. They wish to invest this money in order to fund their children’s university studies as well as paying of their own mortgage. As the client’s children are still young, there is no immediate need for a large influx of cash and so the money will be invested passively for an agreed period of five years with the possibility of changing to active investment in the future. While the client would like to see a decent return from this investment, they are somewhat risk adverse as these funds are necessary for their children’s education, hence the risk tolerance level has been classed as moderate. A risk analysis is available in Appendix 1. 1.1.3. Passive Portfolio Results This portfolio began with an investment of £1,000,000 and after a successful period of 5 years passive investment. The portfolio gained £1,414,850 bringing the total to £2,414,850. This money was then reinvested into the active portfolio. MN0493 - INVESTMENT AND RISK MANAGEMENT 2|Page 1.2 Active Investment Portfolio After five years of passive investment, client XYZ has agreed to change the investment strategy and invest actively for a trial period of ten weeks. The client is pleased with the results so far and following a reassessment of the client’s objectives and risk appetite, it is evident that their investment objectives have not changed. 1.2.1. Investment Philosophy Choosing to manage the portfolio actively is essentially challenging the previously mentioned Sharpe theory that actively managed funds result in no gain after the deduction of fees. By choosing to actively manage this portfolio we are deciding to view the market as inefficient, aiming to facilitate a return higher than the market return for securities with equal risk (Cox, 2017). Tactical asset allocation (TAA) was applied to exploit any inefficiencies in the market. TAA refers to the active adjustment of a portfolio’s asset allocation based on short term market forecasts and fluxuations (Stockton & Shtekhman, 2010). An overview of portfolio management is available in the next section. 1.3. Asset Allocation Diversification is often considered the main method of reducing volatility while maintaining its expected returns, while total protection from risk is impossible due to systematic risk (Neale and Pike, 2009; Rubinstein, 2002), studies suggest diversification can reduce portfolio risk by up to 30% (French & Poterba, 1991, Roberts & Bernstein, 2000). For this portfolio, the principals of Markowitz’s modern portfolio theory (MPT) were utilised. This theory states that assets with less correlation will present less risk as they will respond differently to volatility in the markets. (Markowitz, 1952; 1991). In addition to MPT, the portfolio was diversified across different industries and countries. While both methods show significant results (Aked, Brightman and Cavaglia, 2000), studies suggest that industry diversification is more relevant than country diversification and so more focus was on including a range of industries (Baca, Garbe and Weiss, 2000; Morrison & Tuominen, 2018). 1.3.1 Portfolio size Regarding the amount of equities within a portfolio, literature has not agreed on a specific number that minimises risk, with renowned theories ranging from 10 equities (Evans & Archer, 1968) to 30 equities (Statman, 1987). For the passive portfolio, a mid point of 20 equities was used, although this figure varied in the active portfolio with the buying and selling of stocks. 1.3.2 Diversification Diversification strategies were applied to both the equity and bond portfolios. The portfolios were diversified by sector as well as country. Full details of diversification are available in appendix 3. MN0493 - INVESTMENT AND RISK MANAGEMENT 3|Page 2. Equity Portfolio Management In addition to diversifying the portfolio, there was a range of selection criteria implemented. The beta value of each stock was calculated and was an important factor in which stocks to invest in. The beta was used to calculate CAPM, which in itself was utilised as well as the successive theories such as Jensen (1968), Sharpe (1966) and Treynor (1965) amongst others, located in Appendix 7. 2.1 Efficient Market Hypothesis Malkiel & Fama’s 1970 theory of market efficiency is highly debated amongst academics and investors, with the inefficiency of the stock markets being a fundamental assumption of active fund managers (Beechey, Gruen & Vickery, 2000). The exploitation of market inefficiency is what allows for investors to beat the benchmark, with this notion being essentially prevalent during times of crisis and financial turbulence (Basu, 1977; Fox & Sklar, 2009). Taking into consideration the current state of the economy and volatility of the markets, this portfolio aims to exploit market inconsistencies by incorporating current news to predict possible stock movements (Fawcett & Provost, 1999). 2.2 Capital Asset Pricing Model (CAPM) The Capital Asset Pricing Model of Sharpe (1966) and Lintner (1965) is used to quantify the relationship between the systematic risk and expected return of an equity. There are many criticisms of the model stemming from theoretical failings, as a result of assumptions made, such as the assumptions that markets are efficient, investors are risk adverse and transactions costs are not present. Despite these assumptions, the CAPM model is widely accepted by many academics (Blume & Friend, 1973; Fama & French, 2004). The CAPM expected return of the portfolio equities ranged from a low of 1.1% to a high of 6.42%, with the portfolio expected return at 4.30%. These figures are charted in figure 2. The expected return was calculated as shown below in Figure 1 Figure 1 Derived from (Reilly & Brown, 2015) 2.2.1 Beta Values While Beta is used in the calculation of CAPM, it is also a useful tool itself. Beta is a simple measure of systematic risk assigned to equities and signifies the volatility of a stock when compared to the market (Mullins, 1982). For this portfolio, due to the client’s moderate risk tolerance, and increased market volatility, the investor chose to only purchase equities with a beta below one with the exception of Netflix, as it was significantly undervalued at the time so was deemed a safe purchase. MN0493 - INVESTMENT AND RISK MANAGEMENT 4|Page Table 1 2.2.2 Security Market Line The security market line is a graphical representation of the CAPM results. The Alpha (or market risk premium) figure is calculated by deducting the actual return from expected return to deduce how the equity exceeds expectations (Sinha, 2012). Shares that performed below their expected return are considered overvalued and vice versa, the SML helps visualise which shares are overvalued by plotting them below the SML line or undervalued, which will be above the SML line (Dybvig & Ross, 1985; Green, 1986). As seen in figure 2, while more of the stocks were undervalued than overvalued. There are some outliers, with BiomX Inc (PHGE/U) very overvalued and Netflix (NFLX) very undervalued. Figure 2 Rf SML β 2.2.3 Multi Factor Model While CAPM can be used to demonstrate the relationship between risk and return, it only considers deviation in returns as a source of systematic risk (Bello, 2008). Fama and French modified this by increasing it into a three factor model, by adding factors relating to size and value (Fama & French, 2004; Durand, 2011). Having ran the multi factor model on this portfolio we see that there is no presence of small stocks effect or value premium effect, and that the p-value is only statistically significant for the market risk factor and with a negative coefficient. MN0493 - INVESTMENT AND RISK MANAGEMENT 5|Page 2.3 Fundamental and technical analysis 2.3.1 Past stock price movement The use of past stock data rejects the fundamental assumptions of EMH as discussed above, however studying the past movements of a stock or the market itself can help give an indication of volatility or sentiment, (Engle, 1982; Koopman et al, 2005; Khedr & Yaseen, 2017). While the use of historical data is limited (Liow, 1997), this portfolio did observe historical performance when choosing stocks for the portfolio. 2.3.2 P/E ratio, Gordon’s growth model The P/E ratio is another method of valuing an equity, it is equal to the share price divided by earnings per share (Shen, 2000; Gottwald, 2012). This ratio helps to determine if the stock is correctly priced, with theory suggesting that low P/E ratios will outperform higher p/e shares (Nicholson, 1960). Figure 3 P= D1 r-g Where: D1 = Dividend r = Rate of Return g = Growth rate Adapted from Gordon (1962) Gordons Growth model (figure 3) was also implemented alongside P/E ratio to help deduce if the shares were valued correctly. GGM relates the value of a stock to its expected dividends and expected growth rate in dividends (Armour et al, 2016). While the Gordon growth model can be a good indicator of price, it is considered fundamentally flawed by some, due to its assumptions and so it will be utilised as a secondary method, having consulted the SML line and Intrinsic price first. MN0493 - INVESTMENT AND RISK MANAGEMENT 6|Page 3. Bond Portfolio Management 3.1 Credit ratings Credit ratings were an important factor in bond selection. The Standard and Poor's Global Ratings were used in line with using S&P as a benchmark, however Moody's ratings were also considered in order to have an accurate picture of the bond, these are two out of three of the best credit agencies in the world. These credit rating agencies gather a range of information to make informed judgments about their creditworthiness (White, 2018). In order to assure that the bonds chosen were unlikely to default, only bonds with a rating of A or above were considered, as shown in appendix 5. 3.2 Interest rates Interest rate volatility has a direct effect on bond prices; however, they move in opposite directions, e.g. a rise in interest rates causes a fall in bond prices and vice versa (Shiller, 1979). This correlation will have more effect on short term bonds than long term and so short term bonds are considered less risky. This relationship means that interest rates are a significant variable when it comes to bond pricing. 3.3. Yields A bonds yield reflects the return to investors from the coupon and maturity cash flow. The yield curve acts as a graphical representation of the yield expected over different periods of time, by plotting the bond’s yield against the time to maturity. While the curve can form many shapes, it is normally upward sloping indicating that bonds with longer maturities attain higher yields (Campbell, 1995). Figure 4 Figure 5 (World Government Bonds, 2020). MN0493 - INVESTMENT AND RISK MANAGEMENT 7|Page 3.4 Duration, Modified Duration Duration is a measurement of the sensitivity of bond price to fluxuations in interest rates, it is considered a better way to summarize the timing of bond flows than maturity (Reilly & Sidhu, 1980). Bonds with higher duration will be susceptible to greater impact of sensitivity towards interest rate volatility (Hatchondo & Martinez, 2009) Table 2 Name Duration Modified Duration APPLE INC 5.58 15.52 2.80 5.55 15.20 2.74 WALT DISNEY HSBC BANK 3.5 Bond laddering Bond laddering is essentially another method of diversification, this strategy involves buying bonds with different maturity dates to minimise the impact of changing interest rates, as the investor can respond more timely to any changes. While there was attempts to imply laddering techniques, there was other criteria deemed more important and so two bonds had the same maturity. Figure 6 MN0493 - INVESTMENT AND RISK MANAGEMENT 8|Page 4. Portfolio Performance Evaluation Many methods were applied in order to evaluate the portfolios performance, including the application of a wide range of theories and ratios as shown in Table 3. A full analysis of these figures is available in appendix 7. The passive portfolio increased by 141.49% to turn the initial £1,000,000 investment into£2,414,850, this was the starting amount for the active portfolio. Overall, the portfolio did finish with a profit of £15,443 bringing the total to £2,430,293. While this was only an increase of 0.64%, the active portfolio was operating in particularly volatile times that seen coronavirus cause some of the biggest stock market losses since the recession. Hence, while profits were small, they are better that losses and so this portfolio could be classed as successful. Figure 7 Unfortunately, the portfolio did not beat the benchmark in this case however it did finish as a profitable portfolio. The ratios in table 3 give a better indication as to portfolio performance and are discussed in detail in appendix 7 Table 3 MN0493 - INVESTMENT AND RISK MANAGEMENT 9|Page 5. VAR Risk management is an essential part of portfolio management, to help the investor cope with any sudden changes in the market (Orhan & Köksal, 2012; Teller & Kock, 2013). This portfolio has implemented many methods of reducing risk, from diversification to strategic equity selection. A popular method of measuring this risk is Value-at-Risk or VAR, which is used to summarise the portfolios exposure to risk in a single figure (Jorion, 1996). The VAR figure is essentially an estimate of the largest loss that the portfolio would suffer under normal market changes (Hopper, 1996). This helps the investor to balance their portfolio to secure the greatest expected return with the least level of risk (Beder, 1995). There are three main methods of VAR, namely historical simulation method, variance-covariance method (sometimes referred to as Delta-normal approach) , and the Monte Carlo simulation. The methods all differ slightly and so their results will too, for example, one method may show good results for a portfolio in the short run, but not work well over a longer period of time (Hopper, 1996). For this reason, all three methods were implemented to assure that the portfolios risk was measured accurately. 5.1 Methods of VAR Firstly, there was historical simulation, which uses historical data and replicates the portfolios current reactions (Jorion, 1996). This method is completely nonparametric so is not required to fit a normal distribution which captures nonnormality in the data however ignores volatility (Christoffersen & Gonçalves, 2004). The issues with this is that volatility will vary over time and by ignoring this, the results could be slightly skewed (Hopper, 1996; Linsmeier & Pearson, 2000). The second method was variance-covariance, which assumes that market factors follow a normal distribution. This distribution is utilised to determine the portfolio loss that will not be exceeded x% of the time (Linsmeier & Pearson, 2000). This method builds a variance-covariance matrix of portfolio changes assuming normally distributed changes in the market to measures the maximum loss as a certain level of confidence (Benninga & Wiener, 1998). Third was the Monte Carlo simulation, which creates a large number of possible scenarios and the associated losses of that scenario. This method implements random number generation in order to generate thousands of hypothetical changes in the market leading to thousands of hypothetical portfolio losses to determines the portfolio VAR (Benninga & Wiener, 1998; Linsmeier & Pearson, 2000). MN0493 - INVESTMENT AND RISK MANAGEMENT 10 | P a g e 5.2. VAR Results The VAR was calculated for 90%, 95% and 99% confidence, however this portfolio will focus on the 95% confidence figures. The results are given in GBP indicating the maximum amount of money the portfolio would lose 95% of the time. The three methods gave varied results, ranging from a loss of 43K to 64K, which signified a loss of 5.5% to 8% respectively. Further details about the calculation of VAR are in appendix 9. Table 4 There are some flaws with VAR in that each method is essentially only an estimate, and hence liable to a level of estimation risk itself. As VAR does not incorporate variables such as political risk, liquidity risk or regulatory risk, if any of these atypical market fluxuations were to occur they would be outside the scope of VAR estimates. This is particularly prevalent currently as the market is abnormally volatile due to the impact of coronavirus. While there are some limitations of VAR, it is still considered the most popular method of measuring portfolio risk, and by implementing all three methods, the investor will have a better picture of possible losses (Beder, 1995; Jorion, 1996). MN0493 - INVESTMENT AND RISK MANAGEMENT 11 | P a g e 6. Option Strategy Having measured the risk of the portfolio, it was important to seek a method of hedging the risk of volatility and changes in the market. Hedging is used to reduce the risk of a particular investment by taking on another investment (Naik, 1993). Options are a form of hedging, an option grants the holder of the option the right, but not necessarily the obligation to buy or sell a share at a set price. There are two types of option, the call option gives the holder the right to buy the share at a certain price and the put options gives the holder the right to sell the share at a certain price, both by an assigned date (Hull, 2014). A straddle is an options strategy that involves simultaneously purchasing both a call and put option with the same price and the same expiration date. If the investor believed that Activision shares might rise or fall, but were unsure of which, they could hedge the risk by creating a straddle. This involves the purchase of both a call and put option at the current price of $65 with an expiration date in the near future. The price of the $65 call and $65 put would combine to be the total cost of the straddle, or premium. The premium in this case was $5 meaning that the stock needs to rise or fall around 8% (5/65) in order to make a profit. Figure 8 Figure 9 Within the straddle there was two methods implicated, a straddle write and a straddle purchase. The straddle purchase involves buying both a call and a put with the same terms, while the straddle write would involve selling a call when the seller does not yet own the stock. The two methods have contrasting results in that the profit of a straddle write would be opposite to that of a straddle purchase, with the straddle purchase yielding a V shaped profit graph and straddle write an inverted V, as shown in figures 8 and 9. The straddle for ATVI has two break-even points at £55 and £75. MN0493 - INVESTMENT AND RISK MANAGEMENT 12 | P a g e APPENDICES 7. Appendix One – Risk Assessment ............................................................. 16 8. Appendix Two – Market Forecast ............................................................. 17 9. Appendix Three – Portfolio Allocation...................................................... 19 9.1. Asset Allocation..................................................................................... 19 9.2. Equity diversification............................................................................. 19 9.3 Bond diversification .............................................................................. 19 10. Appendix Four – Benchmark Selection ................................................... 21 10.1 Benchmark Selection ............................................................................ 21 10.2 Expected Return ................................................................................... 21 10.3 Standard Deviation .............................................................................. 22 10.4 Utility Score: ......................................................................................... 22 11. Appendix Five – Bonds ........................................................................... 23 11.1 Bond Selection ..................................................................................... 23 11.2 Maturity ............................................................................................... 23 11.3 Country ................................................................................................. 23 11.4 Credit Rating......................................................................................... 24 11.5 Correlation ........................................................................................... 24 12. Appendix Six – Equities .......................................................................... 25 12.1 Equity Selection .................................................................................... 25 12.2 P/E Ratio............................................................................................... 25 12.3 Gordons Growth Model ....................................................................... 26 12.4 CAPM .................................................................................................... 26 12.5 Correlation ........................................................................................... 26 12.6 Interpretation of results ....................................................................... 26 MN0493 - INVESTMENT AND RISK MANAGEMENT 13 | P a g e 13. Appendix Seven – Evaluation of portfolios performance ........................ 27 13.1) Portfolio Performance ........................................................................ 27 13.2)Weekly profits/loss .............................................................................. 27 13.3) Coefficient of Variation Ratio (CV) ...................................................... 28 13.4) Sharpe Ratio ........................................................................................ 28 13.5) Treynor Ratio ...................................................................................... 28 13.6) Jensen’s Alpha ..................................................................................... 28 13.7) M2 ratio .............................................................................................. 29 13.8) Calmar Ratio........................................................................................ 29 13.9) Tracking Error ...................................................................................... 29 13.10) Information Ratio .............................................................................. 29 14. Appendix Eight – Log of Purchases ......................................................... 30 15. Appendix Nine – VAR Methods .............................................................. 32 References ................................................................................................... 34 MN0493 - INVESTMENT AND RISK MANAGEMENT 14 | P a g e 7. Appendix One – Risk Assessment As discussed in section one, Client XYZ is an inexperienced investor that has invested their £1,000,000 inheritance into a portfolio of stocks and bonds. After a successful five year period of passive investment, the portfolio was changed to active investing. The client does not need high levels of liquidity as they have other cash reserves available, and the time span for the portfolio is longer term as the money is to be used for his children’s education as well as the mortgage on a property. Having conducted a number of tests with numerous investment professionals, the clients risk tolerance was classed as moderate. This risk tolerance was incorporated into every aspect of the portfolio selection in order to assure that the risk level of the portfolio was in line with the client’s desires. Table 5 Med - High Risk Oxfords risk tolerance assessment scored the client 37/50, placing them in the Medium to High Risk category. (StandardLife, 2020) Moderate Risk (Vanguard, 2018) Vanguards risk tolerance assessment recommended a 50/50 split of equity and bonds Moderate Risk The CalcXML risk tolerance assessment scored the client 54/80 suggesting the client is at moderate risk level. (CALCXML, 2020) Moderate Risk The Bright Start risk tolerance assessment categorises this client as moderate risk (BrightStart, 2020) Moderate Risk University of Missouri’s risk tolerance assessment scored the client 28/847 suggesting the client is at moderate risk level. (University of Missouri, 2020) MN0493 - INVESTMENT AND RISK MANAGEMENT 15 | P a g e 8. Appendix Two – Market Forecast The active investment period may only be 12 weeks, however the economy is particularly volatile due to the coronavirus and Brexit, and so it was crucial to conduct a market forecast to assess the variables that may affect the portfolio. Table 6 GDP While the 4th quarter of 2019 displayed a GDP rise of 2.1%, this was followed by a stark increase in the 1st quarter of 2020, where the US seen its first decline since 2014, and greatest quarterly decline since the 2008 recession, with a GDP of -4.8%. This figure is only expected to get worse with economists predicting this could fall as low as it did during the great depression. (BEA, 2020; Casselman, 2020) INFLATION Inflation has fallen from 2.3% when active trading began in February to 0.3% as of April, similarly to GDP this is the worst drop since the 2008 crisis and demonstrates how distressed the market is. (Smith, 2020; TradingEconomics, 2020) UNEMPLOYMENT April also seen landmark statistics for unemployment, with a rise of 10.3 percentage points to 14.7%. This is both the highest rate and largest monthly increase known, since the data began in 1948. While the rate of layoffs appears to be slowing, there is no sign of a significant rise in employment coming any time soon. (Bureau of Labour Statistics, 2020; Rushe, 2020). I MN0493 - INVESTMENT AND RISK MANAGEMENT 16 | P a g e NTEREST RATES In an unprecedented move, the Federal Reserve cut the interest rate to zero in March, in an attempt to minimise the effects of economic downturn. While this was impactful itself, there is speculation that we may even see negative interest rates soon. (Financial Times, 2020; Smith, 2020) USD & GBP The effects of changes in these rates are particularly prevalent in this portfolio as these are the two active currencies in both the bond and equity portfolio. With much uncertainty surrounding Brexit and coronavirus, the British Pound has been particularly volatile falling nearly 3% against the dollar in May, the worst performance amongst major currencies. Yearto-date, the pound has fallen nearly 8% against the dollar, which has conversely, been rising steadily since hitting a low in March, with a recent rise of 7% against other main currencies. (Kollmeyer, 2020; LaMonica, 2020) MN0493 - INVESTMENT AND RISK MANAGEMENT 17 | P a g e 9. Appendix Three – Portfolio Allocation 9.1. Asset Allocation Initial investment for the active portfolio was £2,414,850, which was been split between equities and bonds at an approximate 60/40 rate, based on the risk analysis. In practice, this became a 55/35 split of equities and bonds to leave 10% free cash. The cash surplus was left aside for liquidity reasons as well as to have available cash if an attractive stock opportunity arose. Figure 10 9.2. Equity diversification In relation to the aforementioned MPT (Markowitz, 1952: 1991), the majority of stocks chosen for the portfolio had low correlation with almost a quarter having negative correlation, to help minimise effects of volatility, see appendix 6 for the Correlation matrix. Additionally, industry diversification was applied with 4 sectors and 8 sub-industries in the passive portfolio, rising to 6 sectors and 11 sub-industries after readjustments in the active portfolio, see figures 11 and 12 below. Passive Sector Breakdown Figure 11 Active Sector Breakdown Figure 12 MN0493 - INVESTMENT AND RISK MANAGEMENT 18 | P a g e Furthermore, both passive and active portfolios were diversified internationally (figures 13 & 14) as they contained equities from both USA and UK. As the weeks progressed in active management, the portfolio became mainly US stocks as these were performing better throughout the economic downfall. Passive Country Breakdown Figure 13 Active Country Breakdown Figure 14 9.3 Bond diversification Bond diversification differed from equity as bonds have been proven to have less linkage to bad news and market volatility (Kaplanis & Schaefer, 1991; Engle and Sheppard, 2006). There are substantial arguments to suggest that factors such as credit rating can overweigh any benefits of diversification in respect to bonds, therefore slightly more focus was put on credit rating than bond diversification and all bonds selected were of a very high rating as displayed in appendix 5 While focus was on the ratings, there was still attempts to diversify. The correlation between bonds was examined and the matrix can be seen in appendix 7. Two thirds of the bonds showed negative correlation with the remaining third showing slightly high correlation. As well as correlation, sector and country diversification were noted, with the 3 bonds coming from 3 different sectors in an attempt to further reduce risk. Regarding international diversification, the portfolio was again split between UK and USA bonds. The choice to limit country diversification to only two countries for both bonds and equity was due to currency risk. Investing in international markets exposes the client to currency risk through the volatility of exchange rates (Kaplanis & Schaefer, 1991; Haslem, 2009). MN0493 - INVESTMENT AND RISK MANAGEMENT 19 | P a g e 10. Appendix Four – Benchmark Selection 10.1 Benchmark Selection As my portfolio consists of 55% US equity and 66% US bonds, the S&P 500 Index was chosen as a benchmark. When selecting this benchmark there was a number of factors to consider, the CFA cite the following characteristics as necessary for a suitable benchmark. (Table 7) Table 7 Benchmark Characteristics Description Unambiguous The identities and weights of securities are clearly defined Investable Measurable It is possible to forgo active management and simply hold the benchmark. Benchmark return is readily calculable on a reasonably frequent basis Appropriate The benchmark is consistent with my investment style Reflective The manager has current investment knowledge of the securities within the benchmark S&P 500 ✓ ✓ ✓ ✓ ✓ 10.2 Expected Return The probabilities and the returns were calculated using historical data from the Standard and Poors 500 over the past two years Probability of Bear market = 24% Return of Bear market = -3.68% Probability of a Bull market = 76% Return of Bull market = 3.23% Ere = (PBear X RBear) + (PBull X RBull) = (24% X -3.68%) + (76% X 3.23%) Expected Return = 1.57% MN0493 - INVESTMENT AND RISK MANAGEMENT 20 | P a g e 10.3 Standard Deviation SD = √ (PBear X (RBear – Ere) 2) + (PBull X (RBear – Ere) 2) = √ (24% X (24% – 1.57%) 2) + (76% X (76% – 1.57%) 2) = 4.02% As the standard deviation of the benchmark is not high, it is appropriate to Hanna’s risk tolerance, which is classified as risk adverse. 10.4 Utility Score: Since the risk tolerance score of moderate is 3. The utility score is found US = ER – ½Aơ2 US = 1.57% – ½(3)(4.017%)2 US = 1.33% Although a higher utility score may insinuate the possibility for higher return, the clients moderate risk tolerance means that the average utility score is expected. The lower the risk tolerance, the lower the utility score is likely to be. MN0493 - INVESTMENT AND RISK MANAGEMENT 21 | P a g e 11. Appendix Five – Bonds 11.1 Bond Selection As discussed in appendix 3, there was both sector and country diversification for bonds, with three different sectors and two different countries included in the bond portfolio. However, the main focus in this portfolios bond selection was credit rating, in order to assure the bonds did not default. Other factors considered include maturity and correlation. Table 8 Tag AAPL 2.4 DIS 2 HSBC 6.5 Name APPLE INC WALT DISNEY HSBC BANK Issue Maturity 03/05/2013 03/05/2023 06/09/2019 01/09/2029 07/07/1998 07/07/2023 Coupon 2.4 2 6.5 Issue Price £79.72 £77.00 £109.23 Currency USD USD GDP Country USA USA UK 11.2 Maturity The selected bonds have maturities within a 10 year range to soften the effects of bond price volatility. The maturity of the bonds is an important factor in how the bond price reacts to fluxuations in interest rates, which was discussed alongside duration in section 3. 11.3 Country The Bonds chosen were a selection of UK and USA bonds. Country diversification can reduce risk in the case of one’s home country becoming unstable. Political instability or market volatility can cause significant increase in risk for an investor and so both countries included in the portfolio are developed nations to minimise these risks, however the portfolio is still prone to currency risk. Currency risk is present in any international investing, as the investor can stand to gain/lose as either nations currency rate changes. The level of currency risk increases with the amount of currencies introduced to the portfolio, and so this portfolio contains investments in only the two biggest and arguably safest markets. MN0493 - INVESTMENT AND RISK MANAGEMENT 22 | P a g e 11.4 Credit Rating Table 9 Name S&P Moody’s APPLE INC AA+ Aa1 WALT DISNEY A a2 HSBC BANK AA - Aa3 Credit ratings were an important factor in this portfolio for risk management purposes. Bonds with a lower credit rating, such as junk bonds, are more likely to default. Apple and HSBC both rank in the highest category according to both Standard and Poor's Global Ratings and Moody's Investments. As two of the most reliable rating agencies in the world, these ratings meant that the investor could classify them as low risk. The Disney bonds were still classified as A, however they fell into the next category of medium risk. As the clients risk profile was moderate, two thirds low risk and one third medium risk was deemed appropriate. Figure 15 11.5 Correlation Table 10 AAPL 2.4 DIS 2 HSBC 6.5 AAPL 2.4 DIS 2 HSBC 6.5 1 -0.486 -0.744 -0.486 1 0.855 -0.744 0.855 1 Due to the small number of bonds held in the portfolio, the correlation was less significant than in the equity portfolio. As seen in table 10, 2 out of 3 bonds showed negative correlation, meaning that these bond prices would move in opposite directions, hedging risk. While HSBC and Disney showed slightly high correlation of 0.855, these assets operate in different countries which should reduce the effect of this correlation slightly. MN0493 - INVESTMENT AND RISK MANAGEMENT 23 | P a g e 12. Appendix Six – Equities 12.1 Equity Selection The screening criteria was that the stocks should have a health grade above or equal to A as well as a beta lower than 1. I then selected the top 20 stocks in this selection when ranked by P/E ratio. In addition, I included three bonds, namely Apple, Disney and HSBC. Table 11 17/02/20 24/02/20 02/03/20 09/03/20 16/03/20 23/03/20 30/03/20 06/04/20 13/04/20 20/04/20 ABC LN Bought Hold Sold ANIP US Bought Hold Sold ARYAU US Bought Hold Hold Hold Hold Hold Hold Hold Hold Hold ATIF US Bought Hold Hold Hold Hold Hold Hold Hold Hold Hold AZN LN Bought Hold Hold Hold Hold Hold Hold Hold Hold Hold BRK LN Bought Hold Hold Sold CEY LN Bought Hold Hold Hold Hold Hold Hold Hold Hold Hold CFFAU US Bought Hold Hold Hold Hold Hold Hold Hold Hold Hold CLIN LN Bought Hold Hold Sold DPH LN Bought Hold Hold Hold Hold Sold FRES LN Bought Hold Hold Hold Hold Sold GORO US Bought Sold HCCHU US Bought Hold Hold Hold Hold Hold Hold Hold Hold Hold HSTM US Bought Hold Hold Hold Hold Hold Hold Hold Hold Hold HW/LN Bought Hold Hold Sold LIO LN Bought Hold Hold Sold PACQU US Bought Hold Hold Sold PHGE/U US Bought Hold Hold Hold Hold Hold Hold Hold Hold Hold SPAQ/U US Bought Hold Hold Hold Hold Hold Hold Hold Hold Hold ZTS US Bought Hold Hold Sold WMT US Bought Hold Hold Hold Hold Hold Hold Hold SBRY LN Bought Hold Hold Hold Hold Hold Hold Hold NFLX US Bought Hold Hold Hold Hold Hold Hold ATVI US Bought Hold Hold Hold Hold Hold EA US Bought Hold Hold Hold Hold Hold PG US Bought Hold Hold Hold Hold Hold ZM US Bought Hold Hold Hold Hold Hold CTXS US Bought Hold Hold Hold Hold Hold CLX US Bought Hold Hold Hold Hold Hold Buy 12.96 48.84 9.14 1.42 75.81 21.60 1.48 8.49 8.85 28.28 7.06 4.18 8.54 20.15 1.43 13.25 8.44 8.48 8.20 112.03 87.81 2.043 245.16 42.1 70.04 86.19 96.25 97.45 136.96 Sell 12.60 36.34 8.78 1.35 81.50 17.25 1.41 8.48 6.67 24.00 7.28 3.63 8.69 19.55 1.45 10.10 9.36 4.25 7.89 100.88 100.36 2.02 341.30 51.34 88.51 93.09 111.69 114.51 148.42 Return -2.78% -25.59% -3.91% -4.40% 7.51% -20.14% -4.57% -0.18% -24.59% -15.13% 3.06% -13.20% 1.82% -2.97% 1.75% -23.77% 10.97% -49.91% -3.70% -9.95% 14.29% -1.37% 39.21% 21.95% 26.37% 8.00% 16.04% 17.51% 8.37% Throughout the investment period, numerous methods were utilised to assess whether an equity should be bought or sold. This portfolio used CAPM, P/E Ratio and GGM, amongst others, to assess the equity. One asset that was purchased on week 5 was Activision (ATVI US), this asset was successful with one of the highest returns in the portfolio, as can be seen in table 11 above. The decision to purchase ATVI involved numerous calculations as shown below. 12.2 P/E Ratio Price Earning Ratio = Intrinsic Value / Earnings per Share Price Earnings Ratio = 34.23 Earnings per Share = 1.95 Intrinic Value = Price earnings ratio x Earnings per share = 66.75 P/E ratio calculations give the price as £66.75 MN0493 - INVESTMENT AND RISK MANAGEMENT 24 | P a g e 12.3 Gordons Growth Model Gordons Growth Model for ATVI was calculated using the aforementioned formula available in figure “” Risk Free Rate = 1.55% Market Expected Return = 6.06% Growth = 4.69% Dividend = 0.41 GGM = Dividend divided by rate of return minus growth rate = 65.079 Gordons Growth model gave the price as £65.08 12.4 CAPM The CAPM for ATVI was calculated using the formula in section 2, figure “”. Risk-Free Rate = 1.55% Beta = 0.61 MKT Expected Return = 6.06% CAPM = Risk free rate + Beta(Expected return – Risk free rate) = 4.30% 12.5 Correlation ARYAU US ATIF US ATVI US AZN LN CEY LN CFFAU US CLX US CTXS US EA US HCCHU US HSTM US NFLX US PG US PHGE/U US SBRY LN SPAQ/U US WMT US ZM US ARYAU US ATIF US 1 0.201 0.201 1 0.255 0.231 0.194 0.174 0.518 0.031 -0.156 0.394 -0.371 -0.077 -0.491 -0.303 0.332 0.262 -0.596 0.103 0.543 0.226 0.139 0.324 0.437 0.247 0.396 0.265 -0.087 -0.309 0.496 0.292 0.023 0.063 -0.699 -0.056 ATVI US 0.255 0.231 1 0.792 0.631 0.258 0.402 0.477 0.963 -0.307 0.876 0.884 0.881 -0.179 0.012 0.712 0.788 0.080 Figure 16 AZN LN 0.194 0.174 0.792 1 0.736 0.186 0.598 0.576 0.810 -0.287 0.523 0.909 0.658 -0.378 0.414 0.505 0.836 0.336 CEY LN 0.518 0.031 0.631 0.736 1 0.289 0.105 0.213 0.736 -0.535 0.656 0.654 0.712 0.049 0.552 0.795 0.396 -0.067 CFFAU US -0.156 0.394 0.258 0.186 0.289 1 -0.356 -0.115 0.245 -0.294 0.224 0.243 0.416 0.511 0.328 0.492 -0.175 -0.065 CLX US -0.371 -0.077 0.402 0.598 0.105 -0.356 1 0.877 0.392 0.445 0.025 0.593 0.040 -0.912 0.090 -0.130 0.827 0.806 CTXS US -0.491 -0.303 0.477 0.576 0.213 -0.115 0.877 1 0.431 0.301 0.097 0.599 0.133 -0.857 0.270 0.004 0.731 0.808 EA US 0.332 0.262 0.963 0.810 0.736 0.245 0.392 0.431 1 -0.246 0.877 0.892 0.884 -0.151 0.121 0.819 0.760 0.041 HCCHU US HSTM US NFLX US -0.596 0.543 0.139 0.103 0.226 0.324 -0.307 0.876 0.884 -0.287 0.523 0.909 -0.535 0.656 0.654 -0.294 0.224 0.243 0.445 0.025 0.593 0.301 0.097 0.599 -0.246 0.877 0.892 1 -0.473 -0.087 -0.473 1 0.623 -0.087 0.623 1 -0.584 0.928 0.660 -0.521 0.181 -0.389 -0.285 -0.100 0.140 -0.410 0.841 0.586 0.003 0.503 0.805 0.563 -0.327 0.372 PG US 0.437 0.247 0.881 0.658 0.712 0.416 0.040 0.133 0.884 -0.584 0.928 0.660 1 0.232 0.160 0.862 0.544 -0.281 PHGE/U US SBRY LN SPAQ/U US WMT US 0.396 -0.087 0.496 0.023 0.265 -0.309 0.292 0.063 -0.179 0.012 0.712 0.788 -0.378 0.414 0.505 0.836 0.049 0.552 0.795 0.396 0.511 0.328 0.492 -0.175 -0.912 0.090 -0.130 0.827 -0.857 0.270 0.004 0.731 -0.151 0.121 0.819 0.760 -0.521 -0.285 -0.410 0.003 0.181 -0.100 0.841 0.503 -0.389 0.140 0.586 0.805 0.232 0.160 0.862 0.544 1 -0.054 0.331 -0.634 -0.054 1 0.258 0.080 0.331 0.258 1 0.277 -0.634 0.080 0.277 1 -0.812 0.176 -0.342 0.427 12.6 Interpretation of results Having calculated the intrinsic value according to P/E ratio as well as the GGM price, these were then compared with the actual price. The actual price at this time was £54.91, meaning that the share was undervalued compared to the pricing methods. The CAPM figures were plotted on an SML line to determine if they were overvalued or undervalued, in this case the ATVI stock was undervalued which coincides with the findings from P/E and GGM. Additionally, a correlation matrix was created (figure 16) to check that ATVI wasn’t too highly correlated with assets already in the portfolio, having analysed correlation and combined with information from other methods, the decision was made to purchase the stock. The Security Market Line is shown in the main body in section 2.2.2. There was 11 shares sold and 9 bought over the duration of the active investment. Every buy/sell decision was prone to a similar level of investigation as shown above for ATVI. A full log is available in appendix 8. MN0493 - INVESTMENT AND RISK MANAGEMENT 25 | P a g e ZM US -0.699 -0.056 0.080 0.336 -0.067 -0.065 0.806 0.808 0.041 0.563 -0.327 0.372 -0.281 -0.812 0.176 -0.342 0.427 1 13. Appendix Seven – Evaluation of portfolios performance 13.1) Portfolio Performance While the portfolio was profitable, it did not beat the S&P benchmark. The portfolios cumulative return was 0.64% while the markets was 5.24% for the same time period. This 10 week period was particularly volatile due to coronavirus pandemic, as demonstrated in figure 17. This graph compares the portfolios weekly performance to the markets, we can see that the portfolio outperformed the market in recent weeks however the losses in the first weeks were to sever for the portfolio to catch up. Figure 17 13.2)Weekly profits/loss The portfolio won 1/3 trades, with the highest weekly loss of -3.72% on 23/03/2020 and the highest weekly return of 4.24% the following week on 30/03/2020. Figure 18 charts an equity curve to demonstrate portfolio fluxuations. An ideal curve would be a constant rise however the volatility caused a period of harsh ups and downs. Figure 18 MN0493 - INVESTMENT AND RISK MANAGEMENT 26 | P a g e 13.3) Coefficient of Variation Ratio (CV) The coefficient of variation ratio is the ratio of the standard deviation to the mean, it helps determine how risky an asset is in relation to expected return (Brown, 1998). In this case, the portfolio was beaten by the benchmark as the portfolio CV was 4.92 and the benchmark CV was 0.29. The lower the value, the better, however while the benchmark outperformed the portfolio, the portfolios CV ratio is still quite low. Portfolio CV = 4.9197 Benchmark CV = 0.2902 FORMULA: Standard Deviation divided by Mean Return 13.4) Sharpe Ratio The Sharpe ratio measures the expected portfolio return per unit of risk . It helps describe how investment return compensates the investor for the level of risk undertaken (Sharpe, 1994; Schmid & Schmidt, 2010). The benchmark performs better than the portfolio showing that the portfolio provides less return per unit of risk. Portfolio Sharpe = 0.1195 Benchmark Sharpe = 3.2942 FORMULA: (Portfolio Return – RFR) divided by standard deviation σ 13.5) Treynor Ratio Treynor ratio is similar to Sharpe in that it demonstrates return per unit of risk, however it uses market risk (beta) as opposed to total risk (standard deviation). (Hübner, 2005). Similar to the results of sharpe, the portfolio is outperformed by the benchmark. Portfolio Treynor = 0.0561 Benchmark Treynor = 0.3369 FORMULA: (Portfolio Return – RFR) divided by Beta β 13.6) Jensen’s Alpha Jensen’s Alpha is a measure of the excess return of an asset compared to the return predicted by CAPM (Jensen, 1968; Ms, 2015). The result for this portfolio was 0.11 or -11%. This means that the portfolio underperformed the CAPM expectation by 11%. Jensen’s Alpha = -0.11 FORMULA: (Portfolio Return – RFR) – (Beta (Market Return – RFR)) MN0493 - INVESTMENT AND RISK MANAGEMENT 27 | P a g e 13.7) M2 ratio Mogdigliani ratio, commonly referred to as M2 is an extension of the Sharpe ratio, it measures the returns of a portfolio, adjusted for risk and relative to the chosen benchmark. M2 ratio = 0.0277 FORMULA: M2 = (Sharpe * Benchmark σ) +RFR 13.8) Calmar Ratio Calmar is used to measure performance relative to risk. A low calmar ratio indicates the portfolio does not perform well on a risk-adjusted basis. The portfolios calmar ratio is very low, especially compared to the benchmark. Portfolio Calmar Ratio = 0.5440 Benchmark Calmar Ratio = 5.0948 FORMULA: Annual Rate of Return divided by Maximum Drawdown 13.9) Tracking Error Tracking Error measures the difference in the return fluctuations of the investment portfolio against the return fluctuations of the benchmark using standard deviation. In this portfolio, tracking error signifies that the portfolio outperformed the benchmark but only slightly. Tracking Error = 0.1910 13.10) Information Ratio Information ratio is a measure of the risk-adjusted returns of an asset relative to a chosen benchmark. The negative result in our portfolio shows that the portfolio did not provide a higher return than the benchmark. Information Ratio = -1.5077 FORMULA: (Portfolio return – Market return) divided by tracking error MN0493 - INVESTMENT AND RISK MANAGEMENT 28 | P a g e 14. Appendix Eight - Log of Purchases Each purchase involved a process of research and calculations to make informed and wise investment decisions. The investor aimed to only purchase shares that were undervalued according to P/E ratio, with a low beta (Less than one) and low correlation (correlation with less than half of the portfolio). In accordance with (Fawcett & Provost, 1999), new sources were monitored to help gain insights into good investments. News sources were interpreted to make good predictions, such as the transition to online learning in schools and universities, which lead to investments into Zoom and Citrix. 02/03/20 At this time, the global coronavirus pandemic was just beginning to hit the western world and ‘panic shopping’ became an issue. The investor felt that this was an opportunity to profit by investing in supermarket chains. Bought WMT US @112.91 Intrinsic value was calculated at 114.18, meaning that this share was undervalued Beta of 0.58, deemed appropriate for the portfolio as it was well below the market beta of 1. Walmart showed low correlation with most of the portfolio and negative correlation with two assets. Bought SBRY LN @2.043 Intrinsic value was calculated at 4.93 meaning that this share was undervalued Beta of 0.6, deemed appropriate for the portfolio as it was well below the market beta of 1. Sainsburys only had high correlation with one asset in the portfolio and had low or no correlation with the rest. 09/03/20 Bought NFLX US @315.25 Intrinsic value was calculated at 375.44 meaning that this share was undervalued Beta of 1.08, slightly over the market beta of one, however deemed a safe investment as it was significantly undervalued. Netflix had little or no correlation with the portfolio, out of all the purchase decisions this was the most correlated asset. In hindsight, this was a slightly risky decision, with correlation and beta as possible obstacles, however the investor felt that the lockdown in many countries would lead to an increase in use of streaming services, this risk paid off and was a profitable purchase. 16/03/20 At this time, the pandemic had led to national lockdowns, the decision was made to investment in industries that were likely to rise in this situation, including video games, streaming services and online learning. Bought ATVI US @54.91 Intrinsic value was calculated at 66.75 meaning that this share was undervalued Beta of 0.92, deemed appropriate for the portfolio as it was below the market beta of 1. Activision showed little or no correlation with more than half of the portfolio MN0493 - INVESTMENT AND RISK MANAGEMENT 29 | P a g e Bought EA US @90.06 Intrinsic value was calculated at 100.14 meaning that this share was undervalued Beta of 0.83, deemed appropriate for the portfolio as it was well the market beta of 1. EA showed little or no correlation with more than half of the portfolio Bought PG US @110.83 Intrinsic value was calculated at 110.01 meaning that this share was slightly overvalued. Beta of 0.65, deemed appropriate for the portfolio as it was well below the market beta of 1. P&G showed little or no correlation with more than half of the portfolio Bought ZM US @123.77 Intrinsic value was calculated at 134.80 meaning that this share was undervalued Beta of -0.1, deemed appropriate for the portfolio as a negative beta will move opposite the market. Zoom showed the highest level of negative correlation, meaning that it would react in the opposite way to the market. Having negatively correlated assets is important as it hedges risk, any drops in the market will lead to gains in the portfolio. Bought CTXS US @125.31 Intrinsic value was calculated at 141.57 meaning that this share was undervalued Beta of 0.75, deemed appropriate for the portfolio as it was below the market beta of 1. Citrix showed little or no correlation with more than half of the portfolio Bought CLX US @176.12 Intrinsic value was calculated at 173.23 meaning that this share was slightly overvalued. Beta of 0.39, deemed appropriate for the portfolio as it was well below the market beta of 1. Clorox showed little or no correlation with more than half of the portfolio MN0493 - INVESTMENT AND RISK MANAGEMENT 30 | P a g e 15. Appendix Nine – VAR Methods Monte Carlo Simulation FORMULA: CELL D1 = Expected Return*Time + Standard Deviation*normsinv* √𝑇𝑖𝑚𝑒 PERCENTILE(D1, 5%) FOR 95% CONFIDENCE MCS VaR 95% VaR in £ 1 2 3 4 5 6 7 8 9 10 -0.06067 MCS VaR 95% -0.06917 Monte Carlo Simulation - Method -£45,505.07 Table VaR -£51,878.55 12in £ =RAND =NORMSINV 0.953698639 1.681825296 0.825527538 0.936637757 0.887384122 1.212733425 0.551670228 0.129882306 0.343808588 -0.402090838 0.156698468 -1.008119835 0.103481543 -1.26196026 0.434799708 -0.164167334 0.414179738 -0.216806077 0.154638283 -1.016741189 MCS VaR 95% -0.07597 VaR in £ -£56,977.33 0.18578816 0.033284428 0.102794239 0.016660306 -0.07766937 -0.058784988 0.003208695 0.003208695 0.003208695 0.003208695 Monte Carlo Simulation - Results Table 13 MCS Given VAR 90% -£30,294.97 95% -£43,912.19 99% -£54,805.96 Variance Covariance FORMULA: = Investment amount * Standard deviation * Z Value Variance Covariance Method Table 14 Investment Mean Return SD Portfolio Signma £750,000.00 0.18% 4.51% Mean Investment SD Sigma Investment £751,329.79 £33,859.37 MN0493 - INVESTMENT AND RISK MANAGEMENT 31 | P a g e Variance Covariance Results Table 15 VCV Given VAR 90% -£42,062.74 95% -£54,363.92 99% -£77,438.89 Historical Simulation FORMULA: PERCENTILE(portfolio returns, 5%) * portfolio value FOR 95% CONFIDENCE Historical Simulation – Method Table 16 Value Returns Portfolio Portfolio Return Benchmark return £750,000.00 £772,168.68 £710,370.18 £746,514.23 £678,863.32 £688,416.54 £712,371.39 £727,029.06 £725,659.21 £799,062.24 £806,244.98 2.96% -8.00% 5.09% -9.06% 1.41% 3.48% 2.06% -0.19% 10.12% 0.90% -1.25% -11.49% 0.61% -8.79% -14.98% 10.26% -2.08% 12.10% 3.04% -1.32% Historical Simulation – Results Table 17 HS Given VAR 90% -£60,818.55 95% -£64,392.67 MN0493 - INVESTMENT AND RISK MANAGEMENT 99% -£67,251.97 32 | P a g e MN0493 - INVESTMENT AND RISK MANAGEMENT 33 | P a g e Week 3, Lecture 1: Evaluation of Portfolio Performance Objectives ❑Discussion on the topics of: ❑Portfolio Performance Evaluation ❑Raw Return Analysis ❑Risk Adjusted Return Techniques: ❑Sharpe Ratio, Treynor Ratio, Jensen Alpha, Information Ratio Tracking Error ❑M2 ❑Modified Sharpe 2 3 Portfolio Managers ❑High Returns: Above Average ❑Low Risk: Eliminate unique risk (diversify) E(U) = f [E(R), σ ] 2 ❑Outperformance ❑ Superior Timing ❑ Superior Selection ❑ French, K. R. (2008). Presidential address: The cost of active investing. The Journal of Finance, 63(4), 1537-1573. ❑It is difficult to beat the benchmark. 4 Portfolio Managers ❑Boxplot diagram for peer group comparison ❑Diamond for average return of fund manager ❑Square for Benchmark average return 5 Raw Returns ❑Absolute and relative returns ❑Returns: Arithmetic, Geometric, annualizing, HPR, single period, multiple periods, ❑Statistically significant results 6 Risk Adjusted Returns ❑Treynor, Sharpe, Jensen and Information Treynor, J. L. (1965). How to rate management of Investment Funds. Harvard Business Review, 43 (1), 63-75. Sharpe, W. F. (1966) Mutual fund performance. The Journal of Business, 39(1), 119-138. Jensen, M. C. (1968). The performance of mutual funds in the period 1945–1964. The Journal of finance, 23(2), 389-416. Treynor, J. L., & Black, F. (1973). How to use security analysis to improve portfolio selection. The journal of business, 46(1), 66-86. E(rP ) − rf TP = β E (rP ) − rf SP = σP a = Rp – [Rf + [βp x (Rm – Rf)] αp σA = 7 Tracking Error ❑Standard deviation of outperformance ❑Mostly used in passive portfolio performance evaluation 𝑛 σ𝑖=1 𝑅𝑃 − 𝑅𝐵 𝑁−1 2 ❑Where, 𝑅𝑃 is the return from the portfolio and 𝑅𝐵 is the return from the benchmark so (𝑅𝑃 −𝑅𝐵 ) gives outperformance for each period. 8 Modigliani and Modigliani ❑Leah Modigliani and Franco Modigliani, 1997 ❑Modigliani and Modigliani (1997) called it Risk Adjusted Performance Measure (RAP). It is more commonly known as 𝑀2 Modigliani, F., & Leah, M. (1997). Risk-adjusted performance. Journal of Portfolio Management, 23 (2), 45-54. 9 Modigliani and Modigliani ❑𝑀2 borrows from capital market theory by assuming a portfolio is leveraged or de-leveraged until its volatility (as measured by standard deviation) matches that of its benchmark. 2 𝑀 = 𝐸 𝑅𝑃 − 𝑅𝐹 𝜎𝑃 𝑥 + 𝑅𝐹 = 𝑆𝑃 𝑥 𝜎𝐵 + 𝑅𝐹 𝜎𝐵 10 Modified Sharpe Ratio ❑Israelson (2005) MSR = ER/SD(ER/absER) Israelsen, C. (2005). A refinement to the Sharpe ratio and information ratio. Journal of Asset Management, 5(6), 423-427. 11 Thank you 12 Week 3, Lecture 2: Bloomberg for Active Portfolio Objectives ❑To apply Bloomberg for Portfolio creation ❑To create an active portfolio 2 3 How much do you have to invest? ❑I have more than a million ❑I have less than a million ❑If less you can top up to make it a million (but not more) 4 5 How many? ❑Minimum …. stocks ❑Minimum … Bonds 6 Thank you 7 Workshop 3, MN0493 Section A (Questions directly relevant to your assignment task). 1. 2. Construct your Active portfolio as required by the assignment task. You should include at least 2 corporate bonds and 5 stocks in your portfolio. Discuss how the stocks you selected correspond to investment objective and risk tolerance of your client. Section B (Questions motivated from lecture topic this week and Bloomberg related). 1. 2. Use Excel file – “PensionFundData_Question” available in the module Blackboard site in week 3 and calculate the results for cells highlighted in yellow (in column C). Comment on your results. Apply PORT function in Bloomberg to evaluate the performance of your passive portfolio. Section C, Self-directed learning activity 1. 2. 3. Chapter 21, Reilly and Brown – Answer problems on pages 710-711. Aim to answer as many questions as possible possible from the word file on foundation concepts (File name: Week3and4_Questions_important2helpyouunderstandfoundationconcept.docx) Read the articles provided in this week lecture slides and summarise your understanding. 123 by Sunil Kumar Submission date: 15-May-2021 07:03AM (UTC-0400) Submission ID: 1586625653 File name: tutor_1.docx (25.61K) Word count: 3445 Character count: 19112 2 1 1 1 1 1 1 1 4 1 1 1 1 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 123 ORIGINALITY REPORT 35 3% % SIMILARITY INDEX INTERNET SOURCES 0% PUBLICATIONS 35% STUDENT PAPERS PRIMARY SOURCES 1 Submitted to University of Northumbria at Newcastle 33% Student Paper 2 mds.mdh.se 1% 3 Submitted to University of Hull 1% 4 etheses.dur.ac.uk Internet Source Student Paper
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