On Measurement – A History of Financial Benchmarks

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If you have built castles in the air, your work need not be lost; that is where they should be. Now put the foundations under them.
Henry David Thoreau Walden

Essential to navigating any course is knowing your intended destination, and measuring one’s current position. Since the commencement of my journey to financial independence there has been a rather restless search for, and refinement of, the right measures to use.

Knowing just how far one is through a journey also helps to provide a sense of momentum. Key to measuring how much progress has been made is consciously thinking about and defining the end point.

This piece will look through the various benchmarks and measurements adopted, retained and discarded through the my journey, to share what I have learnt about measuring progress to financial independence, and set out the logic behind my current portfolio goals.

Early benchmarks – There lies the port (1999-2006)

There is a strong argument that the first FI benchmark I ever set was the most correct, and the rest have been excursions.

In September 2004, after around three years of consciously building up an investment portfolio, I read perhaps the most foundational financial independence work, Your Money or Your Life.

A central recommendation of this book is to physically graph out monthly income and expenses, from which naturally emerges a measure of the proportion of passive investment income to actual expenses. I did this from June 2003 until December 2005. Each week my calculations produced a simple percentage result of how close I was to the ‘crossover point’ – that is, the point at which passive income exceeds monthly expenditure and financial independence is achieved.

By the time I abandoned the monthly record I was, by my rough calculations, around 80 per cent of the way to the ‘cross over’ point. This was soon to fall, however, with the significant purchase of a house to live in with part of the portfolio, and a continuing fall in interest rates affecting some cash-based savings.

This same overall approach, however, underpinned my first ever explicit benchmark set for the portfolio in 2006. It was a quite logical and simple one: yearly investment returns should match my own average yearly expenditure.

Measures multiplied and buried (2007-2016)

As a measure this was hard to improve on, but this provided no deterrence. With the investment portfolio starting to grow after the house purchase I thought about what would be meaningful benchmarks again, and came up with a layered approach.

There were three new benchmarks under this approach, broadly themed as:

  • Comfort – This benchmark was investment income to achieve the median average national salary, with progress estimated as a percentage of current portfolio value against the total portfolio needed to deliver this at an assumed rate of return.
  • Independence – This measure was to achieve investment income equal to the median salary of a Federal public servant serving at a mid-range executive level. This was chosen because it represents a very comfortable standard of living and an average level of career achievement for a person with my qualifications.
  • Freedom – This measure was for investment income to be equal to the salary of a median public servant at a more senior level in a central government agency. This would enable a lifestyle that is untroubled by material need.

The logic behind this triple standard was a recognition that just reaching a comfortable level of investment income did not necessarily encompass all of my aims. Rather, I was curious to understand what might lay beyond, and what resources might give me a lifestyle indistinguishable from most of my peers in terms of ability to fully engage with the world’s opportunities, without requiring paid work.

The decision to measure progress by reference to an external benchmark was due to two factors. First, a benchmark that is externally linked to a particular standard of living helps ensure that the goal shifts broadly with changes in the broader community. Second, it made accounting for inflation easier, as the benchmark already accounted for its effects.

Years after these three benchmarks were set, I read about the six levels of financial independence, and it was apparent that as well as drawing on some similar concepts in Your Money or Your Life I had unconsciously replicated some of these. The six levels represent an excellent framework through which to think about the different stages of financial independence. Others, such as the ChooseFI podcast, have usefully added other milestones (i.e. ‘half-FI’) to supplement the approach, and place some way markers in between some of the larger steps.

The precise numerical expression of these three layered objectives shifted through time as I learnt more about realistic return expectations and updated them for the impacts inflation. In July 2007 I set a target portfolio value target of $750 000, with the explicit – though ultimately unrealistic – expectation of it producing around $50 000 in annual portfolio income. The goal of providing for a stream of passive income specifically targeting an average income (of $58 000) can be traced back a decade to July 2009.

By 2010 I had estimated that a portfolio of around $1.1 million would be required to meet this average income benchmark. I updated this target to reflect more realistic information and evidence on likely sustainable returns in 2016, first setting my previous FI target of $1.47 million.

Finding a benchmark, or a measure of the journey, was therefore an iterative exercise – first begun and then improved on as I learnt more. Along the journey I have tracked, and in some cases continue to track, a number of other metrics. Some of these numbers fall out of existing spreadsheets, others are historical relics in little used Excel workbooks – seeming important for a time, but now neglected and overtaken as meaningful marks of progress. These other metrics include:

  • Asset reserves in weeks. A measure essentially of how long I could last if all employment income stopped tomorrow. This was a significant early metric, and was a comfort to review from time to time. To be able to note that if the worst came to the worst, it might be 6 or 12 months before I could not meet expenses gave a positive feeling of a basic level of security.
  • Passive income expressed as numbers of hours worked at minimum wage. How the portfolio income compared to the Australian minimum wage, i.e. how many hours ‘free work’ did the portfolio complete on my behalf? This is a way of thinking about the additional income a portfolio has produced at no physical cost, to consider the hours of work your dollars are putting in which you do not have to, boosting your financial progress.
  • Remaining deficit to FI target. This is simply the ‘distance still to travel’ number, and towards the mid and late stages of the journey can be more motivating and tangible to focus on than the long progress already made. At this stage, forward progress week to week might be almost invisible in percentage terms, and yet the absolute deficit can still be closing proportionally faster.

Current navigation aids (2017-2019)

My current approach is to keep benchmarking against external standards, but to supplement these with some specific personal FI benchmarks.

In January 2019 I reset my two external benchmarks of progress (Objectives #1 and #2).

  • Objective #1 is a passive income benchmark that is equal to the the median annual earnings of an Australian full time worker ($67 000). That is, approximately 50 per cent of workers earn both less and more than this figure. This is drawn from Australian Bureau of Statistics earnings data, which is updated at least annually, and which therefore can be consistently tracked through time. My logic for picking this benchmark is that any reasonable concept of ‘enough’ should encompass and be somewhat anchored around the earnings of an average worker. To have access to this income, without a single hours paid work being required, represents a significant achievement in freeing oneself all of the potential cares of working career.
  • Objective #2 is set at the approximate equivalent of average Australian full-time ordinary earnings ($83 000). As an average, this ABS benchmark is skewed upwards by a small number of higher earners. This second longer-term goal is designed to reflect a more ‘business as usual’ lifestyle reflecting my personal circumstances. At least in my current phase of life, the lower income of Objective #1 would effectively represent rather than more of a ‘leanFIRE’ concept. As I have previously observed, the income assumed in Objective #2 is closer to the level of expenditure at which I think I would truly become indifferent to working or not.

I have also started tracking these any other measures both against the FI portfolio, but also against an expanded ‘All Assets’ portfolio. This recognises that I have some significant superannuation assets that currently sit outside of the investment portfolio.

This means  I now seek to assess progress on two different bases: first, the current measure based on reliance on the investment portfolio alone and second an ‘All Assets’ measure with superannuation assets taken into account.

The reason for this dual approach was that it was artificial and distortionary to my own thinking about the issue to entirely ignore a substantial potential contributor to a FI target in the form of superannuation, even if it comes with accessibility restrictions and some legislative risk.

Due to these risk and restriction factors, I plan to continue to target financial independence through my private investment portfolio alone, with superannuation providing an additional margin of safety and buffer.

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Cross-bearings and lines of position

My other recent change was to report against an expanded set of benchmarks, beyond just my formal investment objectives.

Since January 2019 I have reported against two additional measures. First, my average annual credit card expenditure (a ‘credit card FI’ benchmark), and the second is an aggregated estimate of total current annual expenditure.

The credit card purchases measure is a way of keeping my financial progress grounded in the reality of what I actually spend. It is currently set at $73 000 per annum, equivalent to the past 12 months of credit card bills. The measure is derived by calculating how much of this expenditure the portfolio is – using the assumed real return rate of 4.19 per cent – producing in income.

This has the benefit of both automatically tracking broad spending trends and adjusting for the inflation I personally experience through time. It is also a highly salient measure. As one stands in front of a paywave machine, it is some comfort to think that portfolio income is paying over 75 per cent of the bill.

As an additional measure I also track actual month to month credit card purchases, and compare them again either current distributions or a 3 year rolling average (as illustrated below).

Measuring - 3yr cardThe total income measure is quite approximate and results from adding some known fixed expenses (such as rates and utilities) that I do not pay through credit card to my total credit card expenditure. It currently totals $96 000. As I have noted, I recognise that it is by no measure a frugal existence, and my good fortune in being able to live in this way.

An example of these measures is given below, using the portfolio position on in the recent May Monthly Portfolio Update as inputs in this case.

Measure Portfolio All Assets
Objective #1 – $1 598 000 (or $67 000 pa) 100.0% 137.3%
Objective #2 – $1 980 000 (or $83 000 pa) 80.7% 110.8%
Credit card purchases – $73 000 pa 91.8% 126.0%
Total expenses – $96 000pa 69.8% 95.8%

Future measures – the end of reckoning?

So what then for the future of benchmarks in measuring the portfolio?

For the moment, the present measures seem sufficient. Recently, however, I have added some additional metrics to watch as the portfolio changes in value.

These new ‘watch’ metrics are the required safe withdrawal rates implied by drawing each required income (i.e. $67 000 or $83 000 as per Objective #1 and 2) from the portfolio. That is, taking the target income levels as fixed, and then calculating what percentage of the portfolio this represents.

Mathematically, this is just a re-arrangement of the method of determining the level of income from the portfolio, but not assuming the current rate of return of 4.19 per cent. So it is equal to the required benchmark income divided by the Portfolio total (so for example, Objective #1 income $67 000/Example Portfolio Level of $1 430 000= 4.68 per cent).

This metric helps make visible exactly the level of investment returns (or safe withdrawal rate) that would be implied by a total reliance on the portfolio at this moment. The reason this is helpful is that a significant set of academic and other analyses cover the issue of the inverse correlation of safe withdrawal rates and equity market cycles.

Put simply, a higher safe withdrawal rate is riskier at time of expensive market valuation (pdf), i.e. good times, than after equity market falls. Conversely, low safe withdrawal rates may be marginally ‘safer’ following substantial equity market falls.

Safe withdrawal rates are typically designed to not fail given a long backtested history of actual market movements over a range of conditions. Yet there is still value in eyeballing the assumed safe withdrawal rate as a cross-check on any decision to cease paid work, and feeling comfortable with that figure.

Observations – Finding a True North  

The power of setting goals and benchmarks cannot be underestimated. My own observations on the process of measuring progress to FI goals are summarised below:

  • Starting is better than finding the best measure. Overall though I have found and discarded many measures and goals along the way, but the choice to start to measure and hold myself accountable for progress was a powerful motivation and tool. Each measure and benchmark helped in its time.
  • Different measures may serve you at different times. Linked to the above, different measures will seem relevant and motivating through different stages of the journey, whether it be ‘reaching zero’, a saving rate or progress towards a specific FI number. Those changes in which measures seem the best fit may actually be important markers of the changing phases of the journey
  • Inflation should be accounted for in any measure. With inflation at historic lows, this may seem unimportant, but with apologies to Trotsky: ‘You may not be interested in inflation, but inflation is interested in you’. FI measures that don’t account for the impact of inflation on purchasing power over years and decades ahead are dangerous to your future lifestyle and goals. Whether it is updating nominal dollar targets regularly for inflation, or exclusively using ‘real’ dollars and rates of return alone, it is critical that goals account for inflation impacts.
  • Measures will be personal choices. The right measures will be deeply personal, influenced by circumstances, preferences, and future goals. There is not likely to be one ‘right’ set designed just for you, even though many of the most common measures (the 4 per cent safe withdrawal rate ‘rule of thumb’ or savings rates) have sound logic behind them.
  • Choose measures that make you consider the whole picture. It is possible to fixate on a single measure for clarity, and for this to provide only a narrow or incomplete view of progress. So behavioural ‘framing’ impacts should be considered when setting measures. That is, consider what the measure might obscure or hide, and its impact on your choices. Examples might be: assets left out of consideration in net worth style measures. Ideally, between them the measures adopted should provide a holistic picture of overall progress, without distorting decision-making by leaving out important aspects of your financial decision-making or circumstances.

Set and Drift – Estimating Future Income from the Portfolio

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Cultivate an asset which the passing of time itself improves.
Seneca, Letters XV

The focus of the voyage to financial independence so far has been designing the portfolio, and measuring the distance still to travel. There is more basic question to be asked as the journey progresses – will the portfolio produce the income targets set for it, or will something need to change?

Currently, the income estimates from the portfolio targets – $67 000 from a short-term target of around $1.6 million and $83 000 from a target of around $2.0 million in several years – are set on an assumption of a total portfolio return of 4.19 per cent.

That does not mean, however, that the portfolio will simply automatically produce an income of that level. Just pointing the ship in the direction of travel is not enough. This is because the total return assumes both capital growth and distributions or interest.

This analysis examines what income the portfolio is likely to produce when the targets are achieved, and assesses whether or not selling down or changing the portfolio in other ways to meet the income goals may be necessary.

To answer this question, history and three different methods of estimating the potential income produced by the portfolio are reviewed.

Approach #1 – Navigation by landmarks

The first approach is to simply use what is already known to establish one’s position.

Previous analyses have discussed the overall trends in portfolio distributions, and reached some approximate estimates of the likely underlying level of distributions. These estimates differ according to the precise method chosen, and time period considered. So far, these analyses have established that the portfolio appears to be generating between:

  • $5 000 per month or $60 000 per year, if an approach where the moving average of the past three years of distributions is used; or
  • $3 800 per month or $45 000 per year, if a conservative approach of an average of the past four years of distributions is applied.

This is healthy progress, however, both of these figures are short of the Objective #1 income requirement of $67 000 per year (or $5600 per month), and even further from the projection of $83 000 (or $6 900 per month) under Objective #2.

Will the future look like the past?

These historical figures are useful because they are real data based on holdings in the actual portfolio. Their disadvantages are that they are backward-looking. This has two possible impacts.

  • First, the growth of more than 50 per cent in the total portfolio size over even the past three years means that the level of historical distributions will underestimate the income generation potential from the now larger portfolio. In short, this is like trying to estimate interest from a bank account by looking at your balance three years ago.
  • Second, the distributions of three or four years ago will reflect past asset allocations, and investment products.  As an example of this, two years ago the portfolio contained over $55 000 invested in Ratesetter’s peer to peer lending platform. This was earning an average income return of 9.1 per cent. Today, Ratesetter is less than half of this size, due to a slow asset reallocation process and withdrawals as loans mature.

This suggests a purely backward view of the actual achieved distributions may be incomplete and misleading.

Taking an average distribution rate approach

The other potential way of estimating the income return of the portfolio is to use the average distribution rate of the portfolio in the past.

The rate is calculated as total distributions over a defined period divided by the average portfolio level over the same period.

This eliminates any errors from the first impact discussed above of growing portfolio growth size, as it is a rate rather than a level measure. It does not eliminate the second impact. For example, higher interest rates meant that cash holdings in 2013-14 could make up over third of total distributions, a position not likely to reoccur in the short or even medium term.

Yet it still may be an approximate guide because while overall portfolio asset allocation has shifted in the past two and half years, it has remained within some broad bounds. As an example, total equity holdings were at 70 per cent of the portfolio both 5 and 10 years ago. Additionally, using a median long-term average of 4.4 per cent will tend to reduce the impact of one-off changes and outlier data points.

As established in Wind in the Sails the average distribution rate over the past two decades has been around 4.4 per cent.

SAD Dist AverageThis implies that the portfolio would produce:

  • $5 900 per month or $70 300 per annum income when the portfolio is at Objective #1 (e.g. this suggests that the target income at Objective #1 would be met, with around $3 000 to ‘spare’).
  • $7 300 per month or $87 100 per annum income when the portfolio is at Objective #2 (e.g. as above it suggests meeting Objective #2 would produce around $4 000 more income than actually targeted).

An interesting implication of this is that the portfolio has been producing distributions (at 4.4 per cent) at a rate that is higher than the overall rate of assumed long-term total return (around 4.2 per cent).

This is consistent with the fact that the Vanguard funds, and to some extent shares and other ETFs have been realising and distributing capital growth, not just income. This means that if I truly believe my long-term total return forecast is more accurate than the distributions estimate, I would need to re-invest the difference, to ensure I was not drawing down the portfolio at a higher rate than intended.

Approach #2 – Navigation by ‘dead reckoning’

A different approach to reaching an income estimate from the portfolio is to forget about the actual history of the portfolio, and look to what the record shows about the average distribution rate from the asset classes themselves.

That is, to construct an hypothetical estimate of what the portfolio should produce, based on external historical data on average income from the individual portfolio components of Australian shares, international shares, and fixed interest.

To do this, estimates of the long-term income generated by each of the asset classes in the portfolio are needed. For this ‘dead reckoning approach’ I have used the following estimates.

Table 1 – Asset class and portfolio income assumptions

Asset class Allocation Estimated income Source
Australian shares 45% 4.0% RBA, 1995-2019, May Chart Pack
International shares 30% 2.0% RBA, 1995-2019, May Chart Pack
Bonds 15% 1.0% Dimson, Marsh and Staunton Triumph of the Optimists 101 Years of Global Investment Returns, Table 6.1
Gold/Bitcoin 10% 0% N/A
Total portfolio 100% 2.55%

This analysis suggests that at the target allocation for the portfolio, based on long-term historical data, it should produce an income return of around 2.6%.

This equates to:

  • $3 400 per month or $40 700 per year when the portfolio is at Objective #1
  • $4 200 per month or $50 500 per year when the portfolio is at Objective #2

These figures are also well short of the income needs set, and so imply a need to sell down assets significantly to capture some of the portfolio’s capital growth.

Abstractions and obstructions

Of course these figures are highly averaged and make some simplifications. Year to year management will not benefit from such stylised and smooth average returns. Income will be subject to large variations in distribution levels and capital growth will vary across asset classes and individual holdings.

Another simplification is that is analysis does not include the value of franking credits. If it is assumed that Australian equities continued to pay out their historical level of dividends, and the franking credit rate remains at the historical average of around 70 per cent then Australian shares dividends should yield closer to 5.2 per cent, lifting the total income return of the portfolio to around 3.1 per cent. In turn, this would marginally reduce the capital sell-down required. Adjusting for this impact means the portfolio income would be $4100 per month at Objective #1, and $5100 per month Objective #2

Yet these assumptions can be challenged. It is possible that the overall dividend yield of the Australian market will fall and converge with other markets. This would be particularly likely to happen if further changes to dividend imputations or the treatment franking credits to occur. It could also occur due to a maturing and deepening of Australian equity markets and domestic investment opportunities available to Australian firms. Shorter term, uncertainty around the future ability of shareholders to fully benefit from franking credits could encourage a payout of credits currently held by Australian firms.

Approach #3 – Cross-checking the coordinates

Due to these simplifications and assumptions, it is appropriate to cross-check the results of one method with other available data. An alternative to either a purely historical approach using distributions received, or the stylised hypothetical above discussed in Approach #2, is relying on tax data.

Specifically, taxable investment income can be estimated as the sum of the return items for partnerships and trusts, foreign source income and franking credits (i.e. items 13, 20 and 24) in a tax return.This has been previously discussed here.

Using this data is – of course – not independent of my own records of distributions. Its benefit is that it strictly relies on verified data provided in tax calculations. This will include income distributions and realised capital gains from within Vanguard funds, for example, but will not pick up unrealised capital gains.

As with Approach #1, as the portfolio has changed in size and composition the absolute historical levels of taxable will not necessarily produce the best estimate of the expected level of distributions looking forward. For example, because it is drawing on a period in which the portfolio was smaller, a five year average of investment income would suggest future annual investment income of $32 300 or $2 700 per month.

So instead an ‘average rate’ approach can be used to overcome this. Over of the past five years, the portfolio has produced an annual taxable investment income of around 3.5 per cent of the value of portfolio. This in turn implies an average taxable investment income of:

  • $4700 per month or $56 000 per year when the portfolio is at Objective #1; and
  • $5800 per month or $69 000 per year when the portfolio is at Objective #2

Once again, these estimates imply the existence of a significant income gap remaining at reaching both portfolio objectives.

Summary of results

So far historical data from the portfolio and three different approaches have been set out to seek to answer the question: how much income is the portfolio likely to produce?

Comparing estimates and income requirements

These individual estimates (blue) and the average of all estimates (green) are summarised in the charts below, and compared to the monthly income requirements (red) of both of the portfolio objectives. The chart below sets out the estimates for Objective #1.SAD Chart Ob1The following chart sets out the same data and projections for the portfolio when it reaches Objective #2 (a portfolio total of $1 980 000).SAD Chart Ob2-corrThe analysis shows that:

  • Portfolio income is likely to be below target at reaching Objective #1 – Using the approaches and history as a guide the portfolio should on average produce an income of around $57 000 per annum at Objective #1
  • And also below target at Objective #2 – When Objective #2 is reached portfolio income should on average be around $71 000
  • Therefore an income gap does exist to solve – Under most estimation approaches there will be a significant income shortfall at reaching both Objective #1 and #2
  • The gap is significant, but not disastrous – Assuming an equal weighting to the three approaches and actual historical distributions over the past three years the size of the income gap will be around $900 per month at Objective #1 (or $10 200 per annum) and greater, around $1000 per month at Objective #2 (or $12 000 per annum)
  • Only one estimation approach doesn’t identify a gap – Only if the ‘average distribution rate’ approach under Approach #1 is accurate will there be no income shortfall.

This implies that at the $1.6 million target of Objective #1, a small portion of any portfolio gains (around 0.6% of the value of the total portfolio) would need to be sold each year to meet this income gap. An identical result applies at the Objective #2, around 0.6% of value of the total portfolio would need to be sold annually.

Another intriguing implication of the reaching the average estimates is that it allows for an approximation of the required portfolio level to rely entirely on portfolio income, and avoid any sale of assets. At both portfolio Objectives the average of all estimation approaches indicate portfolio income of around 3.5 per cent.

Reversing this figure for the target portfolio income (e.g. for $67 000 at Objective #1 is 0.035/67000) implies a portfolio need of $1.91 million. For the higher target income for Objective #2, the implied portfolio required to not draw down capital is close to $2.4 million. This would require many additional years of future paid work to achieve.

Trailing clouds of vagueness

There are many caveats, inexactitudes and simplifications that should loom large in interpreting these results. The level of future returns as well as their income and capital components are unknowable and volatile.

In particular, the volatility of returns introduces key sequence of return risks that are simplified away by the reliance on deceptively stable historical estimates or averages. Particularly sharp movement in asset prices could change the asset allocation. Legislative or market changes could change the balance of income and capital appreciation targeted by Australian firms.

For these reasons, the analysis does not make me consider any particular remedial action. It indicates that under a range of assumptions and average outcomes, there will need to be a sale of some investments to meet the portfolio incomes targeted.

The same analysis shows that the superficially attractive choice to live only off portfolio income would in reality mean aiming for a target around 20 per cent higher – needing an extra $300 000 to $400 000 – potentially adding many years to the journey.

The relatively small scale of the required sales is the most surprising outcome of this analysis. Selling around 0.6 per cent of the portfolio annually does not on its face appear to be a high drawdown in most market conditions.

Another potential issue to consider is what this result means for asset allocation. There is no doubt that history would suggest that the income gap could be reduced by either reducing the bond allocation, or lower yielding international shares.

To give a sense of the magnitudes of this – using the ‘dead reckoning’ Approach #2 set out above – allocating 100 per cent of the equity portfolio to Australian shares would produce around $900 per month (or $10 300 per year) additional distributions at the Objective #1 portfolio of $1.6 million.

In theory, this domestic shares only option would all but close the income gap. Yet the benefits of diversification and risk reduction bonds and international shares offer make this a trade-off to consider, not a clear choice. At present, my plan would be to revisit this issue at my annual review of the portfolio asset allocation.

In the meantime, having produced these estimates has helped starting to think in more concrete terms about the draw down phase, its challenges and mechanics. In a small way, this seems to clear some of the clouds away, and enable me to glimpse some possible futures more clearly.

* Note: The historical average estimate for this purpose has been proportionally adjusted to increase based on the increased size of the portfolio between now and reaching Objective #2

On the Wind – Reviewing the Record of Distributions and Expenses

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But no new findings will ever be made if we rest content with the findings of the past.
Seneca, Letters XXXVII

Measuring distributions and expenses

Over the last three years the investment portfolio has delivered substantial distributions, leading to a brief period in which it appeared that an accidental goal of ‘Credit card FI’ might have been met. Subsequently that prospect receded, due to a sharply lower set of distributions for the half year to December 2018.

Over six months ago Reviewing the Log examined the issue of how my current passive income from distributions compared against both my credit card expenditure and total spending.

This article seeks to update that previous analysis, but also to go further and reach a fuller and more robust picture of overall trends in how distributions and expenses compare over time.

In particular, this article seeks to identify the likely current ‘gap’ between distributions and monthly expenses. This represents a different and arguably more empirical way of viewing and measuring actual day-to-day progress to FI, compared to simply tracking progress to a numerical portfolio goal.

Even so, they are in some senses also different sides of the same coin. This is because the portfolio goals I am aiming for are reverse engineered from target FI income levels, which are translated into lump sum targets, using an assumed average return (currently 4.19 per cent). Each month I report a percentage progress towards these goals. Currently, by this simple lump sum measure, the portfolio is around 90 per cent of the way to Objective #1 and just under 75 per cent of the way to Objective #2.

Re-examining the logs and records

When the monthly record of credit card expenses, total expenses and distributions is examined it is clear that credit card expenditure is volatile, but has a comparatively stable average of around $6000 per month, or around $72 000 per annum. The distributions, on the other hand, have been either stable or growing for most of the past six years, with the exception of the large reduction in the half year to December 2018. During this last half year to December, distributions averaged at around $2 600 a month.

The chart below sets out a ‘credit card only’ (blue) and a ‘total expenses’ series against an averaged measure of monthly portfolio distributions (in red). The green line represents actual credit card expenses, added to an equal monthly contribution of other non-credit card expenses. Total expenses here just includes items such as rates, energy and utility costs, day to day cash, as well as contributions to irregular major expenses such as holidays, house and car repairs, as well as eventual car replacement. Fig 1 - monthly

Note that all segments of the red line reflect annual distributions, except the last period from July 2018 onwards. The red line from July 2018 to the present will need to be revised once the June 2019 half year distributions are known.

This revision is highly likely to lift the currently assumed average distribution for 2018-19 of about $2600 per month. This lift is likely because currently the red line from July 2018 onwards is based on a simple extrapolation or continuation of the traditionally lower December figures. The true underlying level of distributions this financial year may well be higher. In fact, June half year distributions have usually been well above the interim dividend amounts of the December half year.

Depending on the estimation method used, the June 2019 half year distribution could be in the range of $23 000 to $51 000, with an average estimate of around $42 000. This in turn could lead to total annual distributions for financial year 2018-19 being in the range of $39 000 to $66 000 (or between $3 250 to $5 500 per month respectively). For comparison, the five year average of distribution is around $45 000 (or $3 750 per month). The final figure will simply be an unknown factor until early July.

Off-course or temporary shallows?

The same considerations are relevant for examining a second measure of progress. The below figure charts the proportion of total expenses met by annual distributions.Fig 2 - Total Ex DistSince the last update of this graph more than six months ago, the proportion of expenses met by portfolio distributions has fallen, and for the same reason – the low distributions in the half year to December 2018.

Even with this significant fall, from July 2018 to the present, these lower distributions have generally been sufficient to meet between 30 to 40 per cent of total expenses. In overall trend terms, it also suggests the true underlying distributions potential of the portfolio is likely to be sitting at around 60 to 70 per cent (see dotted trend line).

Looking through the weather – adjusting the view

These two ways of viewing progress each have their advantages, but suffer the same disadvantage of being volatile measures of progress. This volatility arises from both monthly variations in expenses, and large variations in distributions between and within years. These variations occur due to a range of factors, such as realisations of capital gains related to rebalancing within some pre-mixed Vanguard retail funds, as well as changes in bond yields or interest rates.

To address this the following chart seeks to account for these multiple sources of variation by adopting a three year moving average for both credit card expenses and distributions. The trade-offs in using this approach is that a three year moving average reduces the time period able to be covered, and can also mute broader emerging trends that should be of concern. Additionally, three years is not close to a complete economic cycle. Thus it is quite possible, for example, for distributions that are abnormally high for two consecutive years to impact this moving average measure.

The advantages of an averaged approach are obvious, however. By reducing the variations and monthly ‘noise’, and taking a relatively conservative assumption (in an increasing portfolio) that the last three years may provide an approximate guide to the true underlying level of distributions, a clearer and more stable picture of overall progress can be gained.Fig 3 no outlineFrom this particular view, a few points emerge:

  • Credit card expenses have remained very stable at around $6 000 across the past three years with no systematic movements up or down
  • From January 2017 onwards distributions increased steadily until they reached around $5 000 per month in the middle of 2018
  • Since that time they have levelled off, and even slightly reduced, as the lower recent distributions form a greater part of the average

The data in the chart suggests a remaining gap of approximately $1 000 per month between distributions and credit card expenses, or distributions being sufficient to meet approximately 80 per cent of credit card expenses or 60 per cent of total expenses. In turn, this means that viewed as a multi-year average, ‘credit card FI’ has not been receding as sharply as volatile month to month figures suggest. It remains, in short, in view if not yet in range. The true average gap measured in these term is likely to continue to gently increase in the lead up to June 2019 distributions, but then potentially either level off or continue to close.

Overall this measure better reflects how the journey has felt so far. A beginning from a firm basis, constant steady progress over the time of the journey, but some significant distance to close yet.

Taking new bearings – an alternative approach

To reach the best view of where one is, it is sometimes useful to use cross-checks that relies on slightly different data.

An alternative approach to reaching a sound estimate which takes into account more stable annual data is to use tax assessment data. The chart below is based on assessed taxable investment income. It is taken from the tax return items of income from partnerships and trusts, foreign source income, and franking credits (i.e. items 13, 20 and 24, excluding capital gains) over the past ten years. This taxable income then given as a proportion of my portfolio objective #1, of $67 000 per year.

Fig 4 - TaxableFrom this chart some observations can be made:

  • For the past three years the equivalent of around 50 to 60 per cent of my first financial independence objective of $67 000 has been met by investment income
  • The past two years have been materially higher than other years – this could perhaps represent an anomaly, however, the overall portfolio that was producing distributions also grew by around 70 per cent since 2015-16, which would tend to support the higher later figures being sustainable
  • Annual variations do occur – with two out of 10 years registering some backward movement

The picture from taxable investment income then seems to support a gradual movement over the past three financial years materially closer to Objective #1, and some confidence that this is more likely than not to be maintained in the current financial year. Taking a three year average it suggests in investment income terms that around 55 to 60 per cent of Objective #1 income is likely to be covered by current distributions.

Summary – on the wind or a voyage becalmed?

Looking at the data highlights a few different points. Progress is not always linear, or exponential, even with compounding effects and well into the FI journey. Yet equally it shows it is possible over the course of several years to go from distributions making a small supporting contribution to ongoing expenses, to the equivalent of paying off the majority of a monthly credit card bill.

From reviewing the records and expanded data it is apparent that ‘credit card FI’ – not exactly a universally recognised stage of FI – is not yet achieved. Longer term progress on the goal will be clearer when June distributions are finalised in the next three months.

Depending on their final levels, between 55 and 90 per cent of annual credit card expenses will be covered by annual distributions. Reviewing past averages of card expenditures and distributions indicates that about 80 per cent of journey may be complete already, leaving a gap of only $1 000 per month.

Moving beyond credit card expenses – the lower distributions over the past six months have been equivalent to only 30 to 40 per cent of total expenses. Using independent tax assessment data indicates that the portfolio is currently generating between 50 and 60 per cent of the total yearly expenditure target under Portfolio Objective #1, with recent portfolio growth meaning the higher end of this range is a more probable guide than the lower.

In the first examination of these trends more than six months ago I observed the inevitable issue of volatility and noted that is was not impossible for future periods of higher expenditure to coincide with lower portfolio income. This could still occur, and clear precedents exist for it. Averages and forecasts have the power to mislead as well as guide.

Yet overall, looking back at the record puts some firm underpinnings to the progress already made – and leads me to strain forward for the next set of bearings.

Waypoints of the Passage – A History of Portfolio Progress

IMG_20190121_135415_489
Day by day, what you choose, what you think and what you do is who you become.
Heraclitus

When I started this record of my journey to financial independence, the voyage had already commenced. In fact, based on the measures used, it was already around two-thirds complete. This article seeks to fill in the blank pages in the log and answer the questions: what happened before this? How did the portfolio progress and grow since it started? How was it built and how did it evolve over time?

Looking back, much of the journey and portfolio progress seemed to take place at a slow but steady pace, likely because of a reliance on automated regular investments in  various funds. This piece will seek to chart the progress and describe the main investment vehicles used, to help answer what the early years of voyage looked like.

Outward bound and initial bearings

While in some senses the portfolio commenced as far back as 1999, with a first purchase of Telstra shares and some expensive actively managed share funds, this article focuses on the period from 2007 onwards.

Prior to 2007 I was regularly investing, however I was also saving for, and subsequently reducing, a home mortgage. Probably the single most significant starting investment I made in this period before 2007 was commencing in March 2001 sizeable regular monthly investments in Vanguard’s Diversified High Growth retail fund, which has continued to form part of the portfolio ever since.

It was only from early 2007 that a single focus was on building the portfolio for the purpose of any kind of financial independence. This goal itself was a slowly evolving journey, with revisions and adaptations.

For example, in July 2007 I set a target of $750 000, with the over ambitious view that that might produce around $50 000 in annual portfolio income. The goal of providing for a stream of passive income of $58 000 I can trace back to at least July 2009. Back then, my return assumptions were optimistic, and I envisaged the goal being achievable around 2020. By 2010 I had estimated that a portfolio of around $1.1 million would be required, a target which I updated to reflect more realistic information and evidence on likely sustainable returns in 2016, first setting my previous target of $1.47 million.

Progress of the voyage – movement in the portfolio

The overall pattern of growth in the portfolio since this time is shown below (with green denoting the period covered by the blog).

Figure 1 - Waypoints

It contains three main phases.

Initial progress – 2007-2012

During the first phase, and first few years progress was slow, despite a growing savings rate. Part of this was the impact of the global financial crisis. This did not cause an absolute decline in the portfolio, but was a major contributor to the small increase over January 2008 to January 2009.

To give a sense of what happened in this period in total, the portfolio went from around $152 000 in July 2007, to $228 000 in July 2009, and probably the worst of it was reflected in the portfolio only increasing around $10 000 from January 2008 to January 2009. That means that without new contributions it would have gone backwards over that year. Regardless,  I did continue to invest. The portfolio was around 60 per cent equities during that period. On reflection, I’m glad that the global financial crisis happened while I still had a relatively low portfolio level compared to today.

During this first phase, there was little compounding of returns, and the slow rate of progress here is captured very effectively in recent infographics and discussions from Four Pillars. The first $100 000 of the portfolio was achieved in 2007, and portfolio passed $300 000 through 2010, three years into the journey.

Expanding horizons – 2013-2017

The second period was one of significant yearly growth between 2013 and 2017. During this phase distributions started making an appreciable and sustained contribution to portfolio growth around $20 000 per year.

During this period the portfolio approximately doubled in size, and started approaching the psychological point of $1 000 000.

The journey as logged – 2017 onwards

The third period, since the commencement of regular writing in early 2017, has been dominated by a a break in the otherwise smooth and slightly exponential portfolio growth pattern from early years.

The increased in the value of bitcoin in late 2017 and then subsequent fall through 2018 has been responsible for this one-off blip in the chart, but absent any further significant increases, its capacity to introduce volatility into the overall portfolio has been reduced

Contributions over the voyage

Over the journey so far, most investment has taken place in Vanguard retail funds (High Growth, Growth, Balanced, and Diversified Bonds), with these funds receiving just over 66 per cent by value of total contributions. Around 90 per cent of total contributions by value been made into passive index funds, or passive ETFs.

The graph below illustrates the investment vehicles that contributions were made to on an annual basis. It is designed to answer the question, where did new investment get directed each year?

Figure 2 - Waypoints

From 2007 to 2015 contributions to Vanguard retail fund made up 90 per cent of yearly investments made, with the exception of a large single investment in a gold ETF in 2009.

The actual investment allocation between the various Vanguard funds differed from year to year, with a focus on building up each individual fund to a minimum size, assisted by inertia from many of these being automatic deductions left unchanged for a year or more. Achieving a notional target allocation set in investment plans also provided some guidance for which Vanguard fund was contributed to at any given time.

At one stage, as well, I sought risk management from an ‘bucket’ approach to splitting investments between different funds with different allocations, with the thought that over time this would achieve a greater margin of safety.

Over time, however, absorbing investment and finance theory led me to see that this was a wasteful, duplicative, and overly complex way of constructing an asset allocation, which had the potential to distract from critical whole of portfolio decisions about risk tolerance and capacity. This led to eventually to ceasing to contribute to some of the smaller and more conservative Vanguard retail fund holdings.

Before 2015, the only exceptions to this pattern of shifting Vanguard retail fund investments were some investments in gold ETFs, and a small exploratory investment in an early retail index fund associated with Bankwest, which had relatively high fees.

In 2015, this stability changed, with three significant non-Vanguard investments. This included  a continued investment in gold ETFs, a small exploration into Bitcoin, and a substantial investment in the peer to peer lender Ratesetter. This period coincided with an increased focus on investments, and some free time to explore this interest more closely.

This increased in 2016, with my first small contributions to BrickX, Goldmoney, and Raiz (then Acorns).  2017 saw the first investments made in Australian equity ETFs, with direction of major re-investment of distributions into Vanguard’s VAS ETF, rather than back into the Vanguard retail funds, which had been my practice previously.

Last year I halted any reinvestment in the Vanguard retail funds that had made up the bulk of my previous investment focus, moving from May onwards to regular investments in Betashares A200 Australian equities ETF. This has been driven by a two main reasons.

First, low cost purchases of ETFs now make it possible to buy small portions of A200 more economically. This means accessing a low MER of 0.07%, rather than 0.35% for the Vanguard fund I was contributing too.

Second, the Vanguard High Growth Fund still contains a 10 per cent bond allocation, meaning with each investment movement to my desired asset allocation was being slowed.

Shifting loads – tracking the movement in assets

Having seen how the level of the portfolio and the contributions shifted over time, this section discusses how the composition and asset allocation of the portfolio itself changed.

At the broadest level, the asset allocation of the portfolio has been relatively stable through time. The chart below sets out the allocation for major asset classes over the period 2007-2019.Figure 3 - WaypointThe major influences on asset allocation have been the original targets set, new contributions which have typically been directed to re-balancing towards a target allocation, and in places, major market movements (most notably the short-lived Bitcoin price appreciation in 2017-18).

The average actual share allocation across the period is around 67 per cent, which is relatively close to my previous target of 65 per cent. This target has recently been increased to 75 per cent.  Average exposure to fixed interests and bonds has been around 23 per cent. The only significant divergences from movement around these levels arose from:

  • a gradual increase in share and bond holdings due to a deliberate reduction in conservative funds holding any cash from 2007-2010;
  • an increase in bond holdings to 29 per cent of portfolio assets in 2015; and
  • a one-off drop in share and bond allocations as Bitcoin briefly rose to make up 14 per cent of the portfolio in 2018

Recently, the share allocation has been rising towards and over 70 per cent, reflecting consistent contributions to Australian equities (mainly in ETFs) through the past two years.

Distributions over the voyage

One of the most satisfying elements of the journey so far has been the growth in distributions over time. These I have tracked in detail since the first half of 2000, with a good continuous record of dividends and fund distributions.

The record of portfolio distributions is set out below. In my earlier post Wind in the Sails – A History of Portfolio Distributions I set out some similar data on a financial year basis, however this figure below is on a calendar year basis in 2017 dollars, to enable the incorporation of the most recent half year data (with again green denoting the period covered by the blog).Figure 4 - Dist

Trends in portfolio distributions

Measured on a monthly basis these distributions started at less than $100 per month, and grew steadily until 2007, where they declined substantially due to some large cash funds receiving interest which were used in a house purchase. The global financial crisis in 2008 affected distributions across into 2009 , but some of that effect was also attributable to falling interest rates during that time, and it was a temporary reduction.

Portfolio distributions, aside from some variations flowing from irregular capital distributions, were largely fairly stable through 2011 to 2015, averaging a between $20 000 and $25 000. After this, in 2016, portfolio distributions began to become extremely significant in their own right.

The distributions in 2017, and part of 2018, have contained significant realised capital gains from Vanguard funds, and like the results in 2006 and 2011, may not be repeated for some time. At the time, these high distributions led me to ponder whether I had actually already achieved ‘Credit Card FI’.

Overall distributions have made a significant contribution to my journey to date. In real inflation adjusted terms these past returns constitute around 30 per cent of the current portfolio value. In nominal terms, they have added over $375 000 to the portfolio total.

Consistent with the growth in the size of the portfolio and impacts of compounding, this contribution has been highest in the last few years. Over half of the total distributions the portfolio has ever generated  over the past 19 years has occurred in just the past 4 years, and over 75 per cent within the past eight years.

Changing mix of distributions

The changing portfolio has also led to marked shifts in what makes up the distributions. Prior to 2007, high interest savings account (such as ING Direct, Bankwest) made up the most significant part of the level of distributions recorded, often over two-thirds. Over the period since 2007, falling interest rates, a shift towards more equity investments, and lower invested amounts in fixed interest and cash have led to a decline in this area. Even as recently as 2014, however, these sometimes made up as much as one third of total distributions.  With the slow withdrawal from Ratesetter to meet asset allocation goals, this can be expected to keep falling.

The current constituents of the most recent half yearly distributions are set out below.

PIPieChartDec18

From this it can be seen that Ratesetter interest make up only 10 per cent of total portfolio distributions, while passive Vanguard funds and ETFs, overwhelmingly weighted towards equity assets, now make up over 80 per cent of net distributions.

Reflections on the waypoints

The conscious journey to financial independence has stretched back at least a decade. Progress has mostly been achieved by increasing my spending by less than my income, and investing the difference.

Knowledge, and a willingness to try out different assets and vehicles and continue to learn were also markers in the journey. They pushed me beyond simple and unrealistic savings targets, to find the habits and open mind that allowed embarkation on this exploration. They also left me with a more complicated portfolio than I would recommend for others, but which nonetheless is quite diversified.

Much of the journey was quiet and not memorable, although a weekly habit of tracking my net worth since 1998 provided a regular focal point to account for progress and lay future plans to take the next step. Much of the time I allowed automatic deductions to slowly average into the market.

The waypoints continue to mark down a diminishing distance towards the destination of my first FI goal. More time has passed than lays ahead for the portfolio in growth terms, but of course history continues to happen. As the distance counts down, I strain forward to see the shape of this undiscovered country.