The very place puts toys of desperation,
Without more motive, into every brain
That looks so many fathoms to the sea
And hears it roar beneath.

Shakespeare, Hamlet, Act 1, Scene 4

This is my one hundred and nineteenth monthly portfolio update. I complete this regular update to check progress against my goal.

Portfolio goal

My objective is to maintain a portfolio of at least $3,250,000. This should be capable of producing an annual income from total portfolio returns of about $112,000 (in 2026 dollars).

This portfolio objective is based on an assumed safe withdrawal rate of 3.45 per cent.

A secondary focus will be maintaining the minimum equity target of $2,600,000.

Portfolio summary

Vanguard Lifestrategy High Growth Fund	$1,004,357
Vanguard Lifestrategy Growth Fund	$49,593
Vanguard Lifestrategy Balanced Fund	$83,563
Vanguard Diversified Bonds Fund	$88,234
Vanguard Australian Shares ETF (VAS)	$674,483
Vanguard International Shares ETF (VGS)	$1,166,059
Betashares Australia 200 ETF (A200)	$346,462
Gold ETF (GOLD.ASX)	$252,185
Bitcoin	$1,219,097
Plenti Capital Notes	$84,000
Financial portfolio value (excluding Bitcoin)	$3,748,936 (-$24,538)
Total portfolio value	$4,968,033 (-$133,507)

Asset allocation

Australian shares	28.5%
Global shares	32.6%
Emerging market shares	1.1%
International small companies	1.3%
Total international shares	35.0%
Total shares	63.5% (-16.5%)
Australian bonds	2.6%
International bonds	3.5%
Total bonds	6.0% (+1.0%)
Gold	5.1%
Bitcoin	24.5%
Gold and alternatives	29.6% (+14.6%)

Presented visually, the pie chart below is a high-level view of the current asset allocation of the full portfolio.

Comments

The total portfolio value fell by $134,000 or 2.6 per cent this month, effectively returning the portfolio to its headline value at the end of January.

This fall was primarily driven by a lower price for Bitcoin holdings, which fell by around 8.2 per cent this month. Losses extended into the narrower financial portfolio as well, however, with this contracting by around $25,000.

The chart below sets out the performance of both the full and ‘financial assets only’ portfolios since the commencement of the journey.

Within the portfolio, Australian shares were steady across the month, however, gold fell by around 5.2 per cent. International equities also fell by around 1.7 per cent, as yields from US and other developed country bonds continued to advance. Bonds marked out a small gain across the full month, despite this, advancing around 0.8 per cent.

This month, once again, a small new investment was made in global equities (through the Vanguard exchange traded fund VGS), in accordance with the decision to regularly reinvest excess distributions and cash holdings.

Finalisation of third quarter portfolio distributions

Third quarter distributions were received across this month, totalling around $21,000 in direct payments.

These were around 6 per cent higher than projections, due in particular to higher than average payments from Australian equity ETFs. These third quarter distributions are up around 17 per cent on the equivalent payments last year.

As the chart below shows, since the movement to quarterly payments from the Vanguard retail funds, third quarter distributions have reached a material level, and have the same multiple sources as the June and December quarter payments.

The trend in third quarter payments is a particularly smooth upward movement. Excepting the impact of an anomalously high diversified bond fund payment in 2017, the upward trend has been unbroken.

The third quarter distributions have tended to be structurally lower than the first two quarters, but ahead of the December quarter. Over time, however, it appears that they are likely to stabilise at the level of around $20,000 per annum, absent significant new investments.

Their relative stability and low variance is observable on the chart below.

The finalisation of third quarter distributions allows an estimate to be made of the full calendar year distributions. Currently, using projected average fourth quarter distributions these look to be consistent with the past two years, rising slightly to around $95,000 (and around $102,000 when Plenti income returns are added).

In other words while third quarter distributions have been strong, there has been an underlying continuity and stability in the calendar year results that they contribution to.

One interesting contributing factor to this overall stability is the strong focus since 2020 broadly, and mid-2025 in particular on global equity investment. This has the impact of reducing the growth of distributions due to dividend yields on foreign equities being generally lower than Australian equities, and embedding that growth in the form of capital gains.

Distributed volatility? Measuring relationships within distribution segments

Another factor to consider is whether there is any ‘diversification’ or volatility reduction effect operating, due to a negative correlation between distributions of the equity-exposed Vanguard retail funds, and the equity ETFs owned, viz Vanguard Australian Shares (VAS), Betashares A200 (A200) and Vanguard’s Global Shares ETF (VGS).

This is an effect I have often pondered, but this month I have put this hypothesis to the test, with some AI data assistance, to identify: what are the systematic, measurable relationships between the distributions of the ETFs held, and the three Vanguard retail funds (High Growth, Growth, and Balanced)?

Or to put it more simply, do ETF distributions tend to be higher when Vanguard retail fund distributions are lower, or vice versa, or is there simply no pattern?

It should be noted that the extent of any such benefit would rest not just on the correlations measured, but also the relative size of each holding.

A further fact to consider is that the simple act of adding a steadier stream of income from the ETFs to a more volatile series will reduce the volatility of the new combined stream. This effect is not to be underestimated. From some analysis conducted as part of the discussion below, it potentially comprises about three-quarters of the volatility reducing impact of introducing the ETFs overall.

Finally, it should be remembered that distributions are not the same as dividend or income returns, since they can have a significant capital gains component, as discussed last month. The Vanguard retail funds, in particular, do frequently pay out significant capital gains.

Isolating the effect of negatively correlated distribution patterns

With these caveats in mind, the remaining question to isolate is whether there is some discernible negative correlation between Vanguard retail fund distributions and those of the ETFs, either individually, or collectively.

The approach taken has been to map the correlations between payments at the annual level between different components of the distribution producing segments of the portfolio that include some equity exposure. One would expect distributions from bond funds, for example, to be non-correlated with equity ETFs or funds, due to asset differences.

The annual measurement approach avoids picking up spurious correlations arising from the timing differences of particular structures and their individual accounting or taxation management strategies, but has the disadvantage of reducing the number of data points.

As a result of this, it should be emphasised that the majority of the results do not pass the ‘statistical significance’ threshold. This test is that if there was truly no relationship, this result would show up less than 5 per cent of the time. The available record of distribution payments I have, stretching between 8 and 11 years depending on the fund, simply does not permit greater granularity.

Separating chance from fate: initial findings on correlations

The chart below sets out the findings of this analysis, showing in the right hand side the degree of rank correlation between examined combinations of the equity portfolio.

Each dot indicates the level of rank correlation on the scale of -1 to 1, and the grey bars indicate the range of results that might be due to pure random chance, to about a 5 per cent level of statistical significance. In other words, results in the grey bands may be tendencies, but not clear observations with statistical force.

Figure 1: Rank correlations between annual distributions: equity portfolio components (I)

An alternative way to look through the data analysis is the chart below, which summarises the analysis, the threshold for statistical significance, and provides an initial assessment of this significance.

Figure 2: Rank correlations between annual distributions: equity portfolio components (II)

As this table highlights, in most examined relationships listed, we are unable to say there is a clearly established, statistically significant negative correlation, even as the raw numbers suggest a tendency in that direction. Relationships between A200 and any other investment are particularly difficult to asses due to limited data (8 years).

Looking at ‘the big three’ cross-relationships: High Growth, VAS and VGS

Some of these possible or absent correlations matter more than others, clearly, due to portfolio size and structure.

For example, the correlation between the three largest holdings, being the Vanguard High Growth fund (approximately $1.0 million), VGS (approximately $1.16m) and VAS (approximately $0.67 million) clearly matter more for the shape of distributions. Together, they constitute over 80 per cent of the financial assets producing regular distributions.

The chart below sets out a scatterplot of the financial year distributions of the Vanguard High Growth fund and VAS distributions over the past decade.

Figure 3: Comparing Vanguard High Growth and VAS annual distributions

In this chart, a slightly negative tendency can be observed. Of note, FY2021 saw low VAS distributions, while the Vanguard High Growth fund paid out at historically high levels. The very next year, this pattern largely reversed, with exceptionally large VAS distributions combining with moderate High Growth fund payouts.

In other words, the apparent negative relationship is real enough to show up in the statistical test, but it is based on a very small number of observations and appears heavily influenced by several individual years.

The chart below provides the equivalent scatterplot of distributions of the Vanguard High Growth fund and VGS distributions over the past decade.

Figure 4: Comparing Vanguard High Growth and VGS annual distributions

As can be noted, here there is vertical spread in the observations, but no particular horizontal pattern, indicating a weaker relationship, potentially one due to chance alone.

Assessing the impact of investment structure on experienced distribution volatility

Earlier it was highlighted that part of the positive impact, in terms of volatility in distribution payments over recent years may arise not from negatively correlated ETF and fund payments, but from a generally smoother pattern in ETF payments.

One way to capture this effect is to pose the hypothetical: what would distributions look like over the past ten years, if instead of the current mix of funds and ETFs, all the holdings had been placed in either the three funds, or ETFs, to achieve the same asset allocation.

This is an approximate and illustrative exercise, due to data limitations.

The chart below shows the result, calibrated to approximate current day financial asset holdings. In the chart, the blue line represents a scenario in which no ETFs were held, and all funds were split between the Vanguard retail funds. The orange line is a different scenario in which ETFs (in this case, VGS and VAS) were held exclusively over the period – i.e. funds currently in the Vanguard retail funds were instead held exclusively in these ETFs. The dotted grey line represents the current split between ETFs and funds.

Figure 5: Comparing alternative investment structure scenarios

The scenarios keep the current product mix within each group and change only the ‘wrapper’. They are not identical in asset allocation, since the retail funds hold some bonds and the ETFs here are all equities, though the High Growth fund alone, which is closer to the ETFs, gives a very similar resul

What this relatively crude exercise illustrates is the higher and more volatile levels of cash distributions that would have resulted from a ‘retail funds only’ approach. This is summarised in the result table below, which looks at the three structures side by side, and separates the source of the reduced volatility.

Figure 6: Comparing the volatility of scenarios compared to the current mix

The swings in cash distributions are far higher under the funds (at 43 per cent standard deviation compared to the scenario’s average payouts) than they would be under the ETFs only scenario (at an equivalent 23 per cent standard deviation). As a point of comparison, the equivalent standard deviation of the current funds and ETF mixed approach is only slightly lower – at 21 per cent.

In other words, most of the reduction in distribution volatility comes from replacing the more volatile retail fund distribution stream with the smoother ETF stream, rather than from any negative correlation between the two.

A final limitation on such ‘backcast’ scenarios should also be noted.

The ‘all in ETFs’ line is a more theoretical scenario, rather than an alternative possible history, given the relevant ETFs only started being introduced around a decade after the Vanguard retail funds were first invested in. This means that adopting an ‘all ETF’ strategy from FY2016 onwards would have actually involved substantial sales of retail fund holdings, and consequent tax implications.

Observations on the findings

Several observations can be made about this data, in the case of my portfolio’s specific experience:

• Investment structure and greater distribution volatility in the Vanguard retail funds cash distributions is the largest effect: The retail funds payouts are simply more volatile through time, due to investment structure differences, and result in greater payouts of capital gains, which dominates as an effect.
• The current mix of Vanguard funds and ETF helps reduce distributions volatility: Against an alternative ‘backcast’ scenario, where ETFs were not used at all, the volatility of overall distributions would have been approximately halved.
• ETFs and retail fund distributions do tend to move in different directions: Years of higher than average Vanguard fund distributions do tend to coincide with lower than average ETF distributions, and vice versa. The tendency is a directionally negative correlation, but mostly cannot be distinguished from chance.
• There is only one clearly established fund-ETF relationship : The only fund-ETF relationship which clearly passes the ‘statistical significance’ test is between distributions of the three Vanguard funds and VAS.
• For the one Vanguard fund with large distributions, the relationship with ETF payouts is negative, but not clearly established: For the largest Vanguard retail fund holding – the High Growth fund – the data shows the weakest link of the three funds. Its best result, against VAS, sits right on the border of statistical reliability (a rank correlation of about -0.6) and primarily arises from data points of FY2017, FY2018 and FY2021.
• The distributions of the global equity ETF moves independently: The Vanguard Global Shares ETF distributions show no reliable relationship with any of the funds. VAS and VGS distributions also tend to move independently of each other. This is likely due to its distribution drivers being different from domestic equity ETFs, and equivalent assets forming only part of some of the retail funds.
• Distributions from the Vanguard retail funds move closely together: The three funds distributions move together (at a rank correlation of 0.9), as might be expected given their common holdings (in different proportions)

This analysis should not be mistaken for a claim that these tendencies or relationships would be present over different sample periods, or that they will remain the same going forward.

To be clear, this is not intended to be a generalised, or generalisable observation applicable to other funds, or ETFs, or to inform decisions about portfolio design. Rather, it is a simple empirical observation around historical experience with the data to hand, in the context of my personal portfolio distributions.

Likewise, on its face, it could be argued that the negative tendency in the relationships found could serve a useful stabilising or diversifying role around distributions. In a limited sense, this might appear be true, in my specific circumstances.

Yet it must be considered that part of this apparent diversification effect is simply the playing out of different structures, fund accounting, capital gains realisation and turnover effect, for example. It is less clear, however, that it would be worth constructing a portfolio with this deliberately in mind if one was at the start of the investing journey. True risk-reducing diversification of income or investment returns is something quite distinct from these types of factors, and relates to the underlying nature of the assets and their performance in different market conditions.

Over the long term, minimising ongoing management fees and picking the most appropriate mix of low cost passive ETFs suitable for one’s own risk capacity and tolerance would likely be the mathematically superior approach in my view than deliberately choosing to mix in the retail funds I happen to hold for this perceived stabilising ‘benefit’. As an example, on average, ETF structures are likely to be more tax efficient, and result in less lumpy exogenously driven capital gains payouts within distributions.

The answer, then, is somewhat different from the hypothesis this analysis started with.

There is some evidence that the different structures have tended to produce distributions in opposite directions, but the statistical evidence for this is generally weak. The much clearer finding is that the ETF distributions themselves have historically been less volatile, and that this structural difference—not negative correlation alone—accounts for most of the reduction in distribution volatility.

Trends in average distribution, portfolio income and expense measures

Each month I examine the trends across average distributions, notional portfolio income and total expenses, with the analysis below focusing on the financial portfolio only, consistent with previous updates.

The chart below measures distributions (the blue line) against an estimate of total expenses (the red line).

The total expenses figure is based on actual credit card spending, with the addition of a regularly updated notional monthly allowance for other large fixed expenses.

The chart also has a series of ‘safe’ portfolio income (in green). This is calculated as the product of the financial portfolio (i.e. the portfolio excluding Bitcoin) and the selected safe withdrawal rate of 3.45 per cent.

This value can be viewed as the notional ‘safe withdrawal income’ currently provided by financial assets in the portfolio. It is estimated on a three-month moving average basis.

This month average total expenses remained steady again at around $9,000 per month, while total estimated annual expenses also stayed at around $108,000.

Meanwhile the three year moving average of distributions (the blue line) has continued to be level at around $8,200 per month.

This leaves the monthly deficit between total expenses and average distributions at about $800.

The ‘SWR portfolio income’ measure again slightly increased to just above $10,800 per month, due to growth in the financial portfolio in the last three months.

As a result, this measure of income is around $1,800 per month higher than total expenses, meaning a further expansion in the positive ‘safety margin’. If notional income from superannuation investment assets is added to the estimate, this margin grows to around $5,700 per month.

Progress

Measure	Progress
Portfolio objective – $3,250,000	153%
Financial portfolio income as % of total average expenses (3 yr average) – $108,300 pa	119%
Target equity holding in portfolio – $2,600,000	121%
Financial portfolio income as % of target income – $112,000 pa	115%

Summary

Across this month there have been phases of close to full time project work, which has lent an accelerated quality to the passage of time, and meant perhaps less time thinking about finances and markets than on average.

Nonetheless, markets are at an intriguing, unique place. Equity markets continue to enjoy relatively historically strong valuations in the US. In Australian equity markets, there has been a period of overall stability, with narrowly positive total returns over the last twelve months, from dividends outpacing capital losses.

The focus, however, has been the resurgence of yields amongst sovereign bonds across longer terms, amongst developed countries. In some cases, as with events in France, added to this has been premiums representing diminished confidence in the capacity and willingness of governments to respond to explosive social pressures, and the compounding impact of rising financing costs on governmental budgets.

It has been particularly relevant, therefore, to be reading Robin Wrigglesworth’s A Fabulous Debt, a colourful historical rendering of the history since the Roman and Venetian states of the bond. What this history highlights is how the bond has adapted, waxed and waned and changed in form across different periods where the balance between lenders and the emerging state was in contest.

In periods of extremities, bond holders, or lenders in general, have found themselves systematically under-compensated in real terms by the state, through the operation of default, alteration of terms, or financial repression combined with inflation. It is difficult to review the build up of financing pressures on developed economy states, and forecast an optimistic resolution for lenders to sovereign states. Indeed, this judgement seems embedded in recent yield increases, even as inflationary pressures moderate in some major economies.

Typically in those times, bond returns were amongst the least important societal-level events occurring, even if the impacts of the fates of bond holders marked a significant historical passage in its own right. This observation has been part of the reason why, since around 2020, I have personally been unconvinced to maintain a significant exposure to bonds or fixed interest. This has slowly wound down from a – not very consciously or wisely chosen – peak exposure of about 28 per cent in 2014.

That does leave an exposure to equity and other risk assets, and under some monetary regimes (though not reliably), a greater bond allocation would have reduced volatility at the portfolio level, at least mildly. Importantly, however, were the world facing the type of societal-level developments, this protection would likely have failed in any case.

As it is, the full portfolio at a headline level is close to where it was in May 2025, and at the beginning of the year. The narrower financial assets portfolio is relatively close, however, to its all time highest values.

That, and particularly current US market valuations, does involuntarily induce a sense of precipitous altitude that the fearful night watch on the wall of the castle of Elsinore might recognise. The waves do roar in the sea below, bringing to mind the proclivity of all markets to fall victim the toys of desperation.

Note for readers

Over the past two years, there has been a noticeable degradation in the useability of my standard blogging interface. As an alternative, and because I am not interested in becoming a coder, plug-in or website management expert, I have created and maintain a mirror Substack which you can subscribe to and have imported past posts. The formatting of past posts may not be as tidy as here, but there are, with the assistance of AI, audio summaries of most new entries. Should the blog ever seem to ‘disappear’ or cease, it will likely just be a signal that I have switched entirely to Substack and started posting there.

Disclaimer

The specific portfolio allocation and approach described has been determined solely based on my personal circumstances, objectives, assessments and risk tolerances. It is not personal financial advice, or recommendation to invest in any particular investment product, security or asset, and investors considering these issues should undertake their own detailed research or seek professional advice.