Back in the late eighties a division V.P. at the company I worked for said something at a sales meeting that I’ve thought about often ever since. He said, “If you want to lose weight, make a graph.”
Of course the mere mention of the word ‘graph’ is sufficient to pique the interest of an engineer. But the message stayed with me because in an instant I saw the broad implications inherent in this simple statement.
For one thing, creating a graph is relatively simple, but keeping it up to date is another matter. It requires the discipline and habit of getting on the scale each day and plotting the number on the graph. This alone suggests a determination and willingness to make the commitment necessary to achieve the goal. I submit that the commitment to monitor is half the battle toward reaching a goal.
Second, the graph allows you to visually see the progress made (or not made) towards the goal each day. So, rather than thinking about how to lose 10 pounds, the challenge is reduced to a more manageable target of perhaps 1 pound a week over the next 10 weeks. The specific correction needed mid-week may amount to deciding to skip Friday night pizza, or at least working it off the following Saturday.
Third, this allows you to observe cause-and-effect of small changes more readily. Did skipping the pizza result in the desired weight loss? Did that brisk walk (or run) have an impact on your weight? If you run twice as long tomorrow, will it result in twice the weight loss? In short, incremental measurements such as this allow you to adjust your mental model that relates diet and exercise to weight gain or loss.
And lastly, the graph serves as a visual reward of your progress and allows you to experience the increasing gratification over time that comes from effecting change for the better. It reinforces your resolve to get the job done and allows you the satisfaction of seeing visually the positive effects of an otherwise non-obvious change. If you look at the same tree every day you’re not likely to see much in the way of change; but if you measure the height and plot the value each day you’ll see a steady progression of growth that gives you a much better appreciation of the tree as a living organism.
All of these implications (and perhaps even more) were rolled into that one simple statement: “If you want to lose weight, make a graph.”
Such is the power of graphing that an entire management discipline sprang into life in the eighties and beyond. This is the discipline of Key Performance Indicators (KPIs) and dashboard reporting that are increasingly being relied upon by organizations throughout the world to monitor and react to events that have critical impact on their business.
The first site is operated by Charley Kyd, a corporate financial analyst who was making dashboards more than 25 years ago back in the days of Lotus 1-2-3. I bought his book “Dashboard Reporting with Excel” a few years ago and it has heavily influenced my thinking ever since. I still correspond with Charley by email from time to time and have found him to be one of the most helpful vendors I have ever done business with. He is always responsive to his email messages and most generous with his time and assistance.
The second site is operated by Hubert Lee in a blog-type format. Hubert finds and displays really outstanding examples of innovative dashboards. I used the color scheme and layout of one of the templates found on his site to design my dashboard. I don’t know where he finds them, but I suggest you check out the website quickly in case the Dashboard Spy receives his “burn notice” and disappears forever (which reminds me, I need to make arrangements to buy Hubert a gin and tonic).
So given the benefits of dashboards and the resources available to construct them, how can this concept be applied to the management of your investment portfolio?
Well, for starters you might do a web search (as I did) on phrases like “investment portfolio dashboard” or “retirement portfolio dashboard” or simply “retirement dashboard” (by the way, include the quotes in your search string). Using the first phrase, I came up with 2 hits on Google. That’s right, 2. The second phrase also yielded 2 results. The third phrase was somewhat better with 706 results. Of these, only about 2 or 3 links out of the first half dozen pages of hits seemed even close to what I was looking for, but on further investigation I determined that they were really more in the way of what I would call simulators or planning tools as opposed to management or decision support tools.
So why aren’t there any dashboards (let alone KPIs for them to monitor) for investment portfolios?
Perhaps “investment portfolio dashboard” is an oxymoron of sorts from the standpoint that if you have a “buy and hold” portfolio there really is no need for a dashboard. After all, what’s the point of a dashboard if you’re not going to take any action on the basis of the various readouts from the gauges?
Remember the early days of the “check engine” lights on your automobile dashboard? Some drivers put black vinyl tape over the light to keep it from distracting them. This actually makes sense if you’re not using the “check engine” light as a KPI when you operate your automobile.
But, of course, you ignore such indicators at your peril. Engine temperature increasing? Fuel gauge showing a decreasing quantity of gasoline in the tank? Don’t worry, just keep on driving. Sooner or later the readings on both gauges will “revert to the mean”…. (please pardon this attempt at math humor).
Getting back to the subject at hand, if Johnson Harper LLC as an organization is founded on the premise that investment results can be managed and controlled, then it stands to reason that there must be metrics that can be used to measure, monitor, and adjust the portfolios under our management in response to changing conditions in the capital markets.
So I was left to design and implement my own dashboard, and here is a screenshot of the result of my labors (if you want a larger, more readable version of the screenshot, select the link to the .pdf file below the image):
Each month, the dashboard tells me at a glance if any adjustments need to be made to the portfolio, and, if so, where to make these adjustments. The screenshot above is that of an actual client portfolio, with the name and account number changed for obvious reasons.
To better understand how this dashboard is used for monitoring and decision support, we need to first understand what we are attempting to achieve with John Doe’s investments.
John’s portfolio has been designed to attempt to achieve 3 core results by year-end 2010:
1) Generate free cash of $46,508 from dividends, interest, and options revenue. This represents 10% of the initial total portfolio value of $465,080 as of December 31, 2009.
2) Increase value of invested assets by a minimum of 3.5% to a level of at least $481,361 (based on the starting balance of $465,080). Note this value does not include free cash generated.
3) In the event of a significant decline across all asset classes (similar to 2008/2009 market conditions), maintain a minimum portfolio value no less than $418,575. This represents a maximum decline in portfolio value of -10% (again based on the starting balance of $465,080).
Each section contains Key Performance Indicators (KPIs) that are utilized in the following manner:
Located at the bottom of the dashboard just left of center is the Account Summary section. This shows the total liquidation value of the portfolio at the end of the current month, previous month, and start of the year. This quickly summarizes overall change to date in John’s portfolio. Here we see that the portfolio is up a modest 2.4% over the 4 months since January 1, with most of that gain having occurred in the previous month (2%). Glancing at the short positions relative to the long positions, I can see that short positions currently make up about 5% of the portfolio. Ideally this number should be about 2%. This tells me that covered calls written against the long positions in his portfolio are, on balance, “in-the-money” and may be called away on expiration. The indicated action is to “buy back some equity” to get the short positions more in line with the long positions. But how? The next place to look is the Allocation section of the report.
Located in the upper left corner, the allocation section shows how John’s holdings are divided amongst the 9 asset classes I currently use to maintain a well-diversified portfolio. The target percentages in the far right column of this table were established based on John’s risk/reward profiling, which in turn is reflected in the portfolio design objectives above that were approved by the client. We see that John is currently overweight in Fixed Income and Energy, and he is underweight in Commodities, International Equities, Cash, and Real Estate. In combination with the information from the Account Summary section, this tells me to consider possibly ‘beefing up’ Commodities, International Equities, and/or Real Estate to reduce the short positions. It also suggests that some Fixed Income and/or Energy holdings can be moved to Cash. But what specific holdings should be adjusted? To answer this question, I next look at the Holdings section in the top center of the report.
Using the slider control on the left side of this table (the dashboard only displays the first 8 of John’s total of 19 holdings), I can look at each of the individual ETF holdings in John’s portfolio. Sorted in decreasing order by current value, we see that the iShares Barclays 20+ Year Treasury Bond Fund (considered as ‘Fixed Income’ in my asset allocation table) is the largest position in the portfolio. And although TLT holdings have increased very significantly since the start of the year, it is important to note that the valuation includes purchases and sales of the ETF in addition to any changes in the market price of TLT. The key control indicator is the running YTD Change plot on the right side of this table. For each individual holding, I want the vertical bar to be at or above the horizontal black line by the end of the year. This line represents an increase of 3.5% above the starting valuation for the year. If I can keep the bars at or above this line for each holding in John’s portfolio, then I will have fulfilled Objective #2 above. In the case of TLT, this bar reflects the jump in holdings as a result of some cash-secured puts that were assigned to John in April. I can therefore liquidate some of the TLT as a means of either generating cash for the portfolio or increasing the holdings of positions that are currently underweight. The actual decision, of course, depends on an assessment of this ‘graphlet’ for each of John’s holdings as I scroll up and down within this table (which obviously you cannot do on the static screenshot).
Cash Balance (k$)
The next area of focus is the Cash Balance section in the upper right corner. The intent is to have the bar at or above the diagonal target line (which represents the amount of cash needed to achieve Objective #1 above) by year end. Here I am significantly below target for John’s portfolio, with a decline in cash balance in April. The decline is largely due to the put options on TLT that were assigned to John during the month, and as such this represents a transfer from the Cash asset class to the Fixed Income asset class. The extent to which I make adjustments to get this back on track depends on the potential impact on the Asset Valuation indicator which is displayed just below the Cash Balance graph.
Asset Valuation (k$)
The Asset Valuation graph plots the value of the non-cash positions in the portfolio. As such, these are the assets being invested to generate a return. The target line shows progress towards Objective #2 above (3.5% growth in asset value). In John’s case, the EOY Target value of $481,361 displayed below the graph represents a 3.5% increase in the initial value of his portfolio ($465,083) on January 1, 2010. Here we see a jump up in asset value in April, again due largely to the transfer from the Cash asset class to the Fixed Income asset class (as represented by increased holdings of TLT).
Portfolio Value (k$)
The combined growth of both Cash Balance and Asset Valuation is shown in the Portfolio Value graph at the middle left side of the dashboard. On balance, the offset of the decline in cash balance against the gain in asset valuation resulted in overall portfolio value growth that has begun to close the gap between target vs. actual. Taken in combination with the previous two sections, this tells me to focus a bit more on free cash generation for the month of May.
Min. Valuation (k$)
The Minimum Valuation tracking indicator located below the Portfolio Value graph shows progress towards Objective #3 (limit maximum decline in portfolio value to -10% based on the initial valuation as of January 1, 2010). This is largely achieved via the purchase of long-term Put options that expire in December, 2010, or January, 2011. Although proceeding steadily towards target, this plot indicates the need for me to look for Put buying opportunities on some of the positions. Typically, I look for holdings that have run up in price significantly since the beginning of the year. This represents an opportunity to purchase the Put option (the strike price of which is based on the underlying asset price as of January 1, not the current price) at a relative ‘bargain’ price.
Beta (S&P 500)
The last two KPI charts (Beta and 5-Month Efficiency) are admittedly rather esoteric. Both are located in the lower right corner of the dashboard. Beta is a plot of the monthly change in overall portfolio value versus the monthly change in the S&P 500 index. For example, for the month of January the S&P 500 index declined by -3.7% and John’s portfolio declined in value by -1.1%. In February, the S&P was up 2.9% and John’s portfolio was up 1.0%. In March the S&P was up 5.9% and John’s portfolio was up only 0.5%. But in April John’s portfolio grew by 2.0% while the S&P was up only 1.5%.
What we’re trying to determine with this graph is if there is any ongoing relationship between what John’s portfolio is doing and what the ‘market’ (as represented by the S&P 500 index) is doing. Mathematically, we’re attempting to see if John’s portfolio is correlated with the S&P 500. And because John’s portfolio is effectively being managed on an absolute return basis (rather than a relative return basis) we actually want there to be little, if any, correlation between his portfolio and the S&P 500. In short, we want John’s portfolio to achieve the target growth objectives regardless of what happens in the market over the coming year.
For our purposes, ‘Beta’ is the slope of the straight line that best connects the dots on this graph. We would like the slope to be zero (i.e., flat horizontal line). We would like the intercept (the point where the line crosses the vertical axis at 0% change in the S&P 500) to be around 1%. But even more importantly, we would like the value of ‘Correlation’ to be close to 0 as well.
Correlation is a measure of how closely John’s portfolio changes each month relative to the change in the S&P 500. The number can range between +1 and -1. The closer the number is to 1, the more highly-correlated John’s portfolio is to the S&P 500. So, for example, if John held only the SPY etf in his portfolio (which holds the same stocks in the same proportion as the S&P 500), the correlation value for a plot such as this would be very close to 1.0.
If the correlation value is close to zero, then we say that the portfolio is ‘non-correlated’ with the S&P 500. And if the value is close to -1, then the portfolio is deemed to be ‘negatively correlated’ with the S&P 500; that is, whenever the S&P 500 goes up, the portfolio goes down (and vice versa).
Ideally, we’d like to see the Correlation value for John’s portfolio to settle out somewhere below 0.3 but above -0.3. This plot becomes more meaningful as the year progresses (more data points are plotted), but for now the value of 0.5 is acceptable.
And also note (in case I am reminded of this by any math professors reading this post) that the relevance of Beta and the intercept value mentioned above diminishes as Correlation approaches 0.
The 5-Month Efficiency chart is based on the Sharpe Ratio, a commonly used metric in portfolio management. We calculate it on a rolling 5-month basis by dividing the average monthly change in the portfolio by the standard deviation of these changes over this period.
I use this as a measure of the extent to which I am actually controlling the portfolio results. It is desirable to have this value as high as possible. To get a feel for how this works, imagine that a portfolio could be controlled to exactly achieve a growth of 1% each month for a year (12.7% compounded total annual return). The average monthly change in the portfolio would be exactly 1%. The standard deviation would be exactly 0 (there is no deviation). The efficiency in this case would be 1 divided by 0, or infinity. Clearly such a level of control is unachievable, and in actuality it is very difficult to even approach an efficiency value of 1.0 using this method of calculation.
And (again for the mathematical purists out there) the relevance of such a calculation over such a small sample size (5 data points) is highly questionable. But I use this metric nonetheless as a means to observe whether or not the systematic changes I make to client portfolios seem to have an impact on the rolling 5-month efficiency.
So how can you benefit from all of this?
a) Consider forwarding a link to this post to your financial adviser. Ask him or her how this dashboard compares to the one they use to monitor and adjust your portfolio to achieve your targeted return. If they aren’t currently using a dashboard, tell them that they can contact me and I will be glad to send them the working spreadsheet version as a template so that they can adjust it to reflect the KPIs they do use in managing their clients’ portfolios.
b) Come back to this website each month. I’ll be posting a screenshot of John’s portfolio each month so that you can see if Johnson Harper LLC is making suitable progress in achieving the targeted results by year end. To be automatically notified when future postings are made, simply enter your email address into the ‘Email Subscription’ section at the upper right of this web page.
If you’d like your own copy of the actual spreadsheet showing how it is linked to John’s monthly statements from the brokerage firm (in this case Interactive Brokers), let me know. I’ll talk to Mr. Harper (see the post “Who is Harper” on this site) to see what I can do about getting you a working copy…
One final important caveat needs to be mentioned. The dashboard as currently designed does not take into account any contributions made to the account or distributions taken from the account. We do not expect to add to or withdraw from John’s portfolio throughout 2010. Should contributions or withdrawals be made to an account, the dashboard and calculations would have to be modified to accommodate this more complex scenario.
Thanks for reading, and as usual please see the disclaimer above and to the right on this webpage about the suitability of this information for your own set of circumstances.