Which Bedokian Portfolio Combination Is Suitable For You?

In my eBook I had touched on three different Bedokian Portfolio variations¹, each broadly suited for investors of different age groups and/or risk profiles. Let us revisit what are the three:

• Young investor aged 21-35 / Aggressive investor: 40% equities, 40% REITs, 10% bonds, 5% commodities, 5% cash (we call this Portfolio 1).
• Middle-aged investor aged 36-55 / Moderate investor: 35% equities, 35% REITs, 20% bonds, 5% commodities, 5% cash (also known as the balanced Bedokian Portfolio, which I use most of the time as an example)(Portfolio 2).
• Retiree investor aged 56 and above / Conservative investor: 20% equities, 20% REITs, 40% bonds, 10% commodities, 10% cash (Portfolio 3).

What would be the performance of these three portfolio combinations? Using U.S. market data from the Portfolio Visualizer (www.portfoliovisualizer.com), let us assume a U.S. Bedokian Portfolio investor with an initial amount of USD 10,000 and does annual rebalancing. Since the site’s earliest data on REITs was from 1994, we shall use the period of 1994-2018, a 25-year span. We will also include the S&P500 ETF as a benchmark, since this roughly represents the U.S. equity market as a whole.  

Fig.1 – Portfolio returns, table view, 1994-2018. Inflation is not factored in.

Fig.2 – Portfolio returns, graphical view, 1994-2018. Inflation is not factored in.

Let Us Compare

Looking at the whole thing, it is no doubt that investing in the S&P500 for 25 years will trump every Bedokian Portfolio combination out there, even the most aggressive one (Portfolio 1). Yes, the results are there and I do not dispute it. However, this just highlights the fallacy that most investors would tend to fall for, and that is looking at just the returns.

If we run a similar test, but making 2009 as the end year, the results would be vastly different:

Fig.3 – Portfolio returns, table view, 1994-2009. Inflation is not factored in.

Fig.4 – Portfolio returns, graphical view, 1994-2009. Inflation is not factored in.

And in 2009, naturally the returns-only investor would proclaim that the aggressive Bedokian Portfolio was the best.

Returns are very subjective and will change from time to time, depending on what you are invested in and when you are looking at your investments. A well-known way to have good returns all of the time would be tactical asset allocation, where you adjust the weightage of the asset classes, sectors and/or individual companies to capture the best returns. Problem is, this meant a very sound grasp of what is coming, and I can say not even the best investor or fund manager can do it 100% of the time.

Risk And Returns

There are two ‘Rs’ in investing, one is returns and the other is risk, specifically market risk. These two attributes form the very basic premise of the Modern Portfolio Theory (MPT), where investors build portfolios to optimize returns based on a given level of risk, and it also advocates the advantages of diversification.

There are a few ways to measure risk. One is to use standard deviation, which measures the past volatility of an asset class or security. The higher the standard deviation, the more volatile the asset class/security is (and thus, more risky). Another is the Sharpe ratio, where it is the measure of the excess returns above the risk-free rate over the standard deviation. The higher the Sharpe ratio, the better it is.

Lastly we have the Sortino ratio, which is similar to the Sharpe ratio, but it uses only the downside standard deviation instead. Like the Sharpe ratio, the higher the Sortino ratio, the better it is.

Let Us Compare Again

Reevaluating the numbers in Fig.1 and Fig.3, taking risk and returns in mind, Portfolio 3 stood out as the best with a lower standard deviation, and higher Sharpe and Sortino ratios. This concludes the suitability of Portfolio 3 for the conservative and/or retiree Bedokian Portfolio investor.

The results also highlight a common adage in investing; higher returns typically require higher risks. In Fig.1, the S&P500 ETF gave the highest returns, but also the highest risk based on the three risk measurements. But in Fig.3, Portfolios 1 and 2 gave the higher returns with lower risk than the S&P500 ETF (hence my bold on the word ‘typically’). This reinforces the importance of diversification at the asset class level, where risk is tapered and correlation may bring higher positive returns and lower losses.

Still, I acknowledge every person’s personality and characteristics are different, and so is the respective person’s risk appetite and investment style. The usual disclaimer applies and of course, the phrase: "past performance does not indicate future returns".

1 – The Bedokian Portfolio, p72.

Assumptions on Portfolio Visualizer Data

Asset class representations used in the data: Equities = U.S. Stock Market; Bonds = Total U.S. Bond Market; REITs = REIT, Commodities = Gold; Cash = 1-month Treasury Bills. All dividends are reinvested and transaction costs (e.g. commissions) are not included.

Results

To see the results in its entirety for the 1994-2018 period in Portfolio Visualizer, click here.

To see the results in its entirety for the 1994-2009 period in Portfolio Visualizer, click here.

References

Standard Deviation – https://www.investopedia.com/terms/s/standarddeviation.asp

Sharpe Ratio – https://www.investopedia.com/terms/s/sharperatio.asp

Sortino Ratio – https://www.investopedia.com/terms/s/sortinoratio.asp

MacBooks and Starbucks

I had mentioned about MacBooks and Starbucks in a one-liner here.  How this came about was my tendency to count the number of Apple MacBook users whenever I visited a Starbucks store. Out of 10 visits, on seven occasions I would see that MacBook users form the majority (>50%) of all laptops.

I posed this phenomenon to a few of my friends and colleagues, and one of them gave me a very interesting answer; MacBook users tend to be young adults, and Starbucks is considered a hipster joint, so these two things compliment each other. Short of carrying out a nationwide (or global wide) survey and research, from a presumptive point of view, it kind of makes sense.

So is there a positive correlation between MacBooks and Starbucks?

Good thing that the two companies, Apple and Starbucks, are publicly listed, so I can find out their market correlation using the Portfolio Visualizer (www.portfoliovisualizer.com). I will take the period of January 1993 to December 2018 for calculating the correlation, since Starbucks was listed somewhere in 1992, and the first MacBook (called the PowerBook) was released in 1991, to give a fair comparison.

Based on annual returns, the correlation is 0.16¹. While this number is positive, it is positive on the low end, and usually we see this correlation score between distinct asset classes.

So, does this mean my observations are wrong?

Short answer is, it depends.

It Depends #1

Both companies are in different businesses. Apple is in technology while Starbucks is in food and beverage. Also, in 2018 Mac computers (comprising of Mac desktops and MacBooks) formed only 8.9% of Apple’s total revenue², as compared to Starbucks whose primary product is coffee. These reasons could explain why the correlation is low between them.

It Depends #2

On another note, my observation settings may be skewed. It is not wrong to look purely at MacBooks in Starbucks, since I am comparing these two variables. To make it more complete, we could see if MacBook users form the majority in other cafes or outlets that serve local coffee, or we could find out if MacBook users are at other non-café places such as fast food restaurants or the library.

It Depends #3

Back to the numbers game, we go by the law of averages and assumptions, and find out some interesting statistics. Assuming:

• Average Lifespan of An Apple Device: 4 years³
• Number of Macs sold between 2015 and 2018 (to fulfill the above 4 years): 76.53 million⁴
• Assumed number of Macs sold that are MacBooks: 76.53 x 49.11%⁵ = 37.58 million
• Total number of Starbucks outlets: 29,324⁶

If all MacBook users gather at Starbucks at the same time, there would be 37.58 million / 29,324 = approximately 1,281 per outlet!

Thus to form a majority, you would need 1,280 people or less using non-Mac laptops within each Starbucks. This is just “wow”. Of course, the last answer was given in a hypothetical situation which, in all probability, near to impossible to realize.  

What I had gone through above is a very simple exercise in fact finding based on figures and observations, which I could classify them as quantitative and qualitative data, respectively. 

So why am I mentioning this?

Simple. It is a way of doing fundamental analysis (FA).

You will encounter these two types of data when you conduct your FA; facts and opinions in the news, financial statements and management messages in annual reports, etc. Quantitative data is difficult to refute (aside from “figures fudging”) as they are past or “as at” data. Qualitative data is a bit on blurred grounds because it is obtained by non-quantified methods, such as observations, trend spotting and opinions. Biases from different individuals’ personalities and experiences could also play a part in qualitative analysis.

Contradicting as it may sound, we need both quantitative and qualitative data and information in order to give a more rounded picture in FA. I have always said that guesstimates (or calculated guesses) are better than pure wild-stab-in-the-dark guesswork, and these can be used for further analysis.

Sounds like hard work? Maybe for the first few times, but once you get the hang of it, it is easier. While you are at it, go grab a cup of coffee and enjoy it at the same time.

1 – Portfolio Visualizer. Asset Correlations. AAPL, SBUX. https://www.portfoliovisualizer.com/asset-correlations?s=y&symbols=AAPL%2C+SBUX&endDate=12%2F31%2F2018&timePeriod=4&numTradingDays=60 (accessed 21 Feb 2019)

2 – Statista. The Mac’s Waning Relevance to Apple. https://www.statista.com/chart/8817/mac-sales-as-a-percentage-of-apples-revenue/ (accessed 23 Feb 2019)

3 – MacRumors. Average Apple Device Lifespan Estimated at Just Over Four Years by Analyst. https://www.macrumors.com/2018/03/02/average-apple-device-lifespan/ (accessed 24 Feb 2019)

4 – Statista. Global Apple Mac sales in the fiscal years from 2002 to 2018 (in million units). https://www.statista.com/statistics/276308/global-apple-mac-sales-since-fiscal-year-2002/(accessed 23 Feb 2019)

5 – GlobalStat StatCounter. Desktop vs Mobile vs Tablet Market Share Worldwide. Jan 2018 – Jan 2019. http://gs.statcounter.com/platform-market-share/desktop-mobile-tablet(accessed 24 Feb 2019)

6 – Statista. Number of Starbucks locations worldwide 2003-2018. https://www.statista.com/statistics/266465/number-of-starbucks-stores-worldwide/ (accessed 23 Feb 2019)

Revisiting The Three REIT ETFs

A while ago, I had written about the three locally listed REIT ETFs here, so this post is some sort of a follow-up. To recap, the three REIT ETFs are the (my short form in brackets) Philip SGX APAC Dividend Leaders REIT ETF (Philip APAC), the NikkoAM-Straits Trading Asia ex Japan REIT ETF (Nikko-Straits Trading) and the Lion-Philip S-REIT ETF (Lion-Philip).

For this blog post, we shall see what would be the weightage of individual REITs and the sectors if we decide to buy all of the REIT ETFs, in equal share numbers, for our investment portfolio, based on the latest fund information.^1,2,3

REIT	Philip APAC	Nikko-Straits Trading	Lion-Philip	Overall Weightage
CAPITALAND MALL TRUST	3.68	10.20	10.00	7.96
ASCENDAS REIT	4.65	10.00	8.20	7.62
CAPITALAND COMMERCIAL TRUST		8.70	9.90	6.20
MAPLETREE COMMERCIAL TRUST		6.40	9.80	5.40
MAPLETREE LOGISTICS TRUST		6.20	5.90	4.03
MAPLETREE INDUSTRIAL TRUST		5.10	6.90	4.00
MAPLETREE NORTH ASIA COMMERCIAL TRUST		4.90	4.80	3.23

Fig.1 – Weightage of individual REITs (in %). REITs that are common in at least two REIT ETFs and among the top 10 holdings are selected.

Sector	Philip APAC	Nikko-Straits Trading	Lion-Philip	Overall Weightage
RETAIL	37.78	38.00	29.20	35.08
INDUSTRIAL	17.37	21.30	23.90	20.82
DIVERSIFIED	27.64	17.00	8.40	17.67
OFFICE	13.53	17.90	19.30	16.89
HOTEL & RESORT	0.96	2.30	8.10	3.78

Fig. 2 – Weightage of REITs by sector (in %). Only top 5 sectors are shown.

Based on the above two tables, we can see that, if the three REIT ETFs are combined into one, Capitaland Mall Trust is the highest holding at 7.96%, with Ascendas coming in second at 7.62%. The biggest component, which is the retail sector, is slightly above 35%, with industrial coming in second at around 21%. However, this status does not remain stagnant as the weightages do change from time to time, though mostly not by that much. If you know some “Google-Fu”, you can check out the weightages from past fund information documents.

A lot of discussion points can be generated based on the above numbers, ranging from the superficial (e.g. which ETF to go to for an all-rounder sector coverage) to the complex that involves looking deeper at various degrees and from different dimensions (e.g. the high concentration of retail REITs in the ETFs, and how shopping habits and the impact of electronic commerce could erode their returns). I would stop at here for now, and I hope at least the above numbers can spark some analysis of your own.

1 – Philip SGX APAC Dividend Leaders REIT ETF. Product Info Sheet. December 2018. https://www.phillipfunds.com/uploads/funds_file/201812_Phillip_SGX_APAC_Dividend_Leaders_REIT_ETF_Product_Sheet.pdf (accessed 8 Feb 2019)

2 – NikkoAM-Straits Trading Asia ex Japan REIT ETF. Factsheet. 31 December 2018. https://www.nikkoam.com.sg/files/documents/funds/fact_sheet/axj_reit_etf_fs.pdf?v20170630 (accessed 8 Feb 2019)

3 – Lion-Philip S-REIT ETF. Fund Information. December 2018. https://lgi.nextview.com/doc/uploads/documents/index.php?type=FS&fid=LEPF&lang=EN (accessed 8 Feb 2019)

SPDR GLD ETF Lot Size Change

OK, I may be “WOLS” (internet-speak for being slow on the news), but I would like to highlight that from 14 Jan 2019 onwards, you are able to purchase the State Street Global Advisors SPDR Gold Trust (or better known as the SPDR GLD ETF) in lot size of 5 shares, down from the previous lot size of 10.

According to an announcement by State Street Global Advisors on 10 Dec 2018¹, this reduction allows “…more Singaporeans, including Central Provident Fund (CPF) Investment Scheme members, to efficiently invest in gold…”. It also emphasized that gold “…historically acted as a portfolio diversifier, particularly during times of market volatility”, which I agree as I am a believer of diversification.

So what does this mean for The Bedokian Portfolio investors? There are two issues which I will mention here.

Issue #1: Bedokian Portfolio Starting Amount

In my eBook, I used the SPDR GLD ETF as the basis to determine the starting amount for The Bedokian Portfolio². Taking the ETF closing price of United States Dollars (USD) 124.69³, and the exchange rate between USD and Singapore dollars (SGD) of 1.3085⁴(both information as at 1 Feb 2019), one SPDR GLD ETF share is about SGD 163.16. If you have decided to allocate 5% of your Bedokian Portfolio to commodities, under the old 10-share lot, you would need to fork out SGD 32,632 (SGD 163.16 x 10 x 20) to start the portfolio (before any transaction costs and commission fees).

However, with the new 5-share lot size, your starting portfolio can be halved to SGD 16,316 (SGD 163.16 x 5 x 20). 

Issue #2: “Overshooting/Undershooting” Risk

My eBook also mentioned about the deviation tolerance of the asset class allocation⁵. For asset classes with 5% to 10% allocation, a deviation of 2.5% is acceptable. So in this case, if you allocate 5% to commodities, rebalancing is not necessary unless it goes below 2.5% or above 7.5%.

Depending on the size of your portfolio, when your commodities allocation goes below (or above) the thresholds stated in the previous paragraph, rebalancing with a larger lot size may mathematically cause the portion to go beyond the other limit. For example, if your commodities portion is at, say 2% of your portfolio, and by purchasing 10 SPDR GLD ETF shares, the allocation may go up to above 7.5%. A smaller lot size would reduce this “overshooting/undershooting” risk.

One More Thing…

The above two issues are based on the investor’s preference to start off and rebalance with the SPDR GLD ETF listed in the Singapore Exchange. However, these issues will be moot if you decide to get the SPDR GLD ETF from other markets. Yes, it is the same ETF, and it is listed not just in Singapore, but also in the United States, Mexico, Japan and Hong Kong⁶. Again as stated in my eBook⁷, you can buy one SPDR GLD ETF share in the United States market, thus bringing down your portfolio starting amount to a very affordable level. In addition, the overshoot/undershoot problems during rebalancing will be greatly reduced.

A caveat though, if you wish to invest your CPF savings, you could only get the SPDR GLD ETF from the SGX, not from overseas markets, as per CPF regulations.

With all the talk on gold, and since it is a good omen topic in the coming festivities, The Bedokian would like to wish you a Happy and Prosperous Lunar New Year!

1 – State Street Newsroom. SPDR Gold Shares Halves Board Lot Size on Singapore Exchange. 10 Dec 2018. https://newsroom.statestreet.com/press-release/spdr-gold-shares-halves-board-lot-size-singapore-exchange (accessed 2 Feb 2019)

2 – The Bedokian Portfolio, p72-73

3 – Singapore Exchange. https://www2.sgx.com (accessed 2 Feb 2019)

4 – Exchange-Rates.org. US Dollars (USD) to Singapore Dollars (SGD) exchange rate for February 1, 2018. https://www.exchange-rates.org/Rate/USD/SGD/2-1-2018 (accessed 2 Feb 2019)

5 – The Bedokian Portfolio, p82

6 – GLD SPDR Gold Shares. https://www.spdrgoldshares.com (accessed 2 Feb 2019)

7 – The Bedokian Portfolio, p73 

Bond Yield Correlation And Use Of Macroeconomic Data

With the bond yield talk recently, I had done up a simple statistical research on the relationship between the United States (U.S.) 10-year treasury yield and our Singapore Government Securities (SGS) 10-year bond yield. Using annual average yields between the years 1998 and 2018, here are the results in Fig.1:

Fig. 1 – Annual average yields of U.S. 10-year treasury and SGS 10-year bond between 1998 and 2018^1,2.

Looks closely related, doesn’t it? To give the relationship a number, I had derived the correlation between them with all the data available, and that is 0.799.

So what does this mean? Statistically speaking, the U.S. 10-year treasury yield and the SGS 10-year bond yield are quite correlated with each other (close to 1.0), meaning that there is a positive relationship between them, though I have to stress that correlation does not imply causation.

So In What Way These Data Are Useful?

According to the Bedokian Portfolio’s fundamental analysis model, such macroeconomic data belongs to the economic conditions tier³. While all these data can be overwhelming, we can classify them as general knowledge that can be fetched from the back of our brains in an instant. 

For example, it is known that the US Dollar and gold have an inverse relationship, so when the price of gold goes up, we will know that the value of the US dollar will go down, and vice versa. Using the bond yield example, we can assume statistically, if we see a rise in U.S. 10-year treasury yield, we are expecting to see a rise in the SGS 10-year bond yield as well.

Though this “instant general knowledge” is useful, we have to take note of two related issues. The first is confirmation bias, which is interpreting information that confirms one’s preconceptions. A good way to mitigate this bias is to update yourself with new data, so as to check the relevancy of your general knowledge.

The second issue will be the ceteris paribus clause, which means “other things equal” in Latin. You could find out more on ceteris paribus in my post here.

1 – Macrotrends. 10 Year Treasury Rate – 54 Year Historical Chart. https://www.macrotrends.net/2016/10-year-treasury-bond-rate-yield-chart (accessed 19 Jan 2019)

2 – Singapore Government Securities. SGS Prices and Yields – Benchmark Issues. https://secure.sgs.gov.sg/fdanet/BenchmarkPricesAndYields.aspx (accessed 19 Jan 2019). 1998 is the earliest data available for the 10-year bond yield.

3 – The Bedokian Portfolio, Chapter 11 – Fundamental Analysis

Stay Focused, Stay Calm And Stay Invested

Speaking about volatility; just three weeks ago, there was talk of doom and gloom in the markets, with the Straits Times Index (STI) nearly touching the 3,000-point mark on Boxing Day. As of today, the STI closed at 3,198 points, almost a 7% increase.  Along the same time period, the S&P500 had recovered some 10%; from 2351 to 2587 (before the U.S. markets opened on 11 Jan 2019).

Looking back during the two weeks that straddled between 2018 and 2019, quite a number of fundamentally sound companies’ share prices were at a low, which meant buying opportunities. However, we are able to make this observation and conclusion on hindsight. If we were able to turn back the clock and time-travel back to that fateful fortnight, do you think we could still make the buy call confidently?

This brings up the oft-mentioned trait about the financial markets which I harped on like a broken record, and that is no one is able to predict the future correctly. Sure, one can get it right some of the time, but no one can get it right all of the time. During the Christmas period and the run-up to the New Year, with the indices heading south, there were strong expectations that they could go further down, and very few would think they could go up. Some may had bought in, while others kept their reserves at hand, waiting to swoop at even lower prices; I guess the former group has won this round. To be honest, for myself I had only bought into one counter this round, and only after careful deliberation (and no, I did not buy in at a low).

To add, I had encountered some cases of panic selling, liquidating their shares, only to see it rising back up just days later. I guess the willing (and lucky) buyers were the ones that I mentioned in the previous paragraph.

So what is next? That is a very good question, but unfortunately I do not have a very good answer. I can give some good advice, though, and that is stay focused, stay calm and stay invested.

2018 Review, 2019 Preview and Bob

I had written something similar on the last day of 2017 (see here). I felt from now on, it would be a good tradition for me to write an annual review, preview and of course, about our dear friend Bob. So here it goes for this round.

2018 Review

If 2018 was a roller coaster, it would be a hell of a ride as compared to 2017 which was just a normal uphill climb. The S&P 500 Index fluctuated heavily between 2350s and 2920s this year¹. For the Straits Times Index, it went to as high as 3610s and as low as 2960s². A lot of factors had attributed to the volatility of the markets, but the main ones most people point to were tariffs and the related trade wars, and the rise of interest rates.

A year ago I had mentioned that I would look into cybersecurity, payment solutions and alternative energy. Using three United States (U.S.) based ETFs; HACK for cybersecurity, IPAY for payment solutions and ICLN for alternative energy, the year-to-date returns as at 31 Dec 2018 were +6%³, -0.12%⁴and -9.39%⁵respectively. They are still relevant in my opinion, as I foresee they are long-term trends rather than short-term fads (see here for my article on trends and fads). Do your due diligence and analysis before committing. 

2019 Preview

If using the trade wars and interest rate hikes as basis, I would expect 2019 to be less volatile than 2018, provided that full resolution is achieved between the United States (U.S.) and China on trade issues, and the U.S. Federal Reserve adhere to its two-rate-hikes as announced⁶. Overall, 2019 will be a challenging year for the financial markets, local and overseas, therefore it is advisable to adopt a diversified portfolio stance and be prudent in your fundamental analysis.

In my humble opinion (and educated guesses), technology will continue to make inroads, especially on the disruption, artificial intelligence and blockchain areas. If you wish to venture further into them, do perform analysis on which sectors/industries will benefit from their development. You could use my associative investing method (see here) as a guide.

Bob

Compared to 2017 (+12.13% XIRR), Bob’s Bedokian Portfolio did not fare well for 2018 (-1.94% XIRR), though he had collected SGD 909.64 in dividends. Bob knows that his investment horizon is long term, so this “down” is just a kink in the journey. On 2 Jan 2019 he will inject another SGD 5,000 to the portfolio, so watch out for this space in the next few days.

That’s it for me. Wish you a happy 2019!

1 – Yahoo Finance. S&P 500 Index. https://finance.yahoo.com/quote/%5EGSPC?p=%5EGSPC. (accessed 1 Jan 2019)

2 – Yahoo Finance. STI Index. https://finance.yahoo.com/quote/%5Esti/ (accessed 31 Dec 2018)

3 – ETFDB.com. ETFMG Prime Cyber Security ETF. https://etfdb.com/etf/HACK/. (accessed 31 Dec 2018)

4 – ETFDB.com. ETFMG Prime Mobile Payments ETF. https://etfdb.com/etf/IPAY/. (accessed 31 Dec 2018)

5 – ETFDB.com. iShares Global Clean Energy ETF. https://etfdb.com/etf/ICLN/. (accessed 31 Dec 2018)

6 –Transcript of Chairman Powell’s Press Conference, p2. 19 Dec 2018. U.S. Federal Reserve. https://www.federalreserve.gov/mediacenter/files/FOMCpresconf20181219.pdf(accessed 31 Dec 2018)