You will build a risk tab that compares your portfolio with two benchmarks on the measures from this module.
A risk desk doesn't send the portfolio manager seven separate reports. It sends one page with the main numbers side by side, so anyone can see in a minute what kind of risk the portfolio carries and how that compares with the alternatives. This exercise builds that page for your account. It becomes the second tab of your workbook, next to the returns tab from lesson 1.8.
Allow about forty minutes if your returns data is already in the workbook, longer if you still need benchmark data.
Create a tab called Risk. Down the left side, the rows are the measures from this module. Across the top, three columns: your portfolio, a world equity index and your blended benchmark from lesson 1.6, Choose a benchmark that matches what you actually hold. Every figure is in SGD, on total return, over the same window.
Rows: annualised volatility, maximum drawdown, longest time under water, Sharpe ratio, Sortino ratio, beta to the world index, and one-month 95% Value at Risk
Use monthly data if you have it, and the longest common window you can get, ideally ten years. Write the window, the data frequency, the risk-free rate you used and where you got it in a notes cell at the top. Without those four notes, nobody, including you next year, can tell what the numbers mean.
Each row uses a method from earlier in this module. Volatility comes from lesson 2.1: the standard deviation of monthly returns times the square root of 12. Drawdown and time under water come from lesson 2.2, using a running peak column. Sharpe and Sortino come from lesson 2.3, with the T-bill yield you looked up on the MAS website. Beta comes from lesson 2.4, using SLOPE against the world index, so the world index's own beta is 1 by definition. Value at Risk comes from lesson 2.6, using the historical method.
Put the formulas on a separate calculation tab and pull only the results onto the Risk tab. The page should be readable at a glance.
Here is Marcus's dashboard, using the made-up ten years of yearly returns from lesson 2.3 so you can check your formulas on a small data set. Yearly data understates drawdowns, as lesson 2.2 warned, so your monthly figures will look worse.
Volatility: portfolio 11.3%, world index 12.5%, blended benchmark 10.0%. Maximum drawdown: minus 18%, minus 16% and minus 13.4%. Longest time under water: two years, one year and two years. Sharpe ratio: 0.37, 0.48 and 0.41. Sortino ratio: 0.57, 0.84 and 0.68. Beta to the world index: 0.88, 1.00 and 0.80. One-month 95% Value at Risk, from monthly data: 6.4% for the portfolio, with made-up figures of 7.0% and 5.5% for the two benchmarks.
Beside the summary, paste the correlation matrix of your largest holdings that you built for lesson 2.4, Beta, correlation and why diversification shrinks in a crisis, with pairs above 0.8 marked. The summary tells you how much risk you carry. The matrix tells you where it comes from.
The numbers matter less than what you conclude from them. Read across each row and ask where your portfolio sits between the two benchmarks.
Marcus noticed three things. His volatility sat above his blended benchmark's, yet his Sharpe and Sortino ratios were lower, so he had taken more risk than his own target allocation and not been paid for it. His beta of 0.88 and correlation of 0.98 with world shares meant his account was, in practice, one large bet on global equities. And his matrix showed where the extra came from: bank shares that duplicated his STI ETF, and a chip stock that amplified his world ETF's biggest holdings.
He wrote: "My largest risk is a deep fall in global shares, which I chose when I set an 80% equity target. On top of that I carry extra risk from my bank and chip holdings, which raised my volatility above my benchmark's without raising my risk-adjusted return. That part I did not choose deliberately, and I'll come back to it when I write position limits in module 11."
That's the standard. The first sentence names the biggest risk, the second says what the numbers show about it, and the third says whether it was a choice. None of it says what to buy or sell. That decision comes later in the course, with sizing rules in lesson 11.3, Position and sector limits, and concentration risk.
One screen, three columns, seven rows, a notes cell with window, frequency, risk-free rate and sources, a correlation matrix with clusters marked, and three sentences. If any of your ratios look far better than both benchmarks, check the window first: a short history that misses a fall can make almost any portfolio look safe. Then build yours from your own data and write your three sentences.
Build the risk tab in your workbook and write three sentences on the largest risk it shows and whether you meant to take it.
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