“How To Generate $XX Per Month From Your Portfolio”

Occasionally there will be blogposts and social media videos teaching how to generate an amount of income per month (or year) from one’s portfolio, which I find it a good thing as they give expectations on the approximate sizing of portfolio and yield required.

Picture generated by ChatGPT

While it is a relatively simple theoretical exercise involving percentage mathematics, it works when everything else is static, i.e., on a ceteris paribus basis (assume all other things are equal). However, executing it would be slightly difficult as market conditions do not really listen to what the theory was supposed to espouse. For instance, the yield or yields from the various asset classes and securities do not remain at that fixed number throughout, and so does the portfolio size that the yield(s) is based on.

Admittedly we do come out with such calculations for retirement/step-down planning for our portfolios, but we would also take in variables that may boost or hinder this model of determining monthly income. Of course, the first thing to do would be to derive the overall annual yield across the asset classes using the asset class allocations and their average yields, which goes something like this as an example (Figure 1):

 

Asset Class	Allocation (%)	Average Annual Yield (%)	Weighted Yield (Allocation x Average Yield)  (%)
Equities	35	5	1.75
Real Estate Investment Trusts	35	6.5	2.275
Bonds	20	2.5	0.5
Commodities	5	0	0
Cash	5	1	0.05
Overall Annual Yield			4.575

 

Fig.1: Overall annual yield of the balanced Bedokian Portfolio using assumed average yield per asset class.

The average yield could be obtained from a few sources, like from one’s own portfolio numbers, figures from finance sites showing the current yield, etc. Do note that the term "average" is used; yield figures have been sourced from multiple references and consolidated to present a mean value. The advantages of using the average are two-fold: the result gives a benchmark value if the actual portfolio is below it, or a buffer if the actual portfolio is above it.

If one is still not comfortable with the average number, a margin of safety can be introduced, corresponding to an imagined portfolio value drop; if one is prepared for a 30% drop of capital, he/she could adjust the expected yield number by 30% to 3.2%, and then plan the spend on the reduced income amount. This conservative approach would have the psychological effect of viewing amounts above the yield to be “windfall” and thus using them as savings and/or further capital to invest (and grow more yield).

AI Eats Software’s Lunch (Or Is It?)

It was coming; the feared disruption of artificial intelligence (AI) into the domain of software, which was already hanging around like the Sword of Damocles, came crashing down onto the markets the past week, accelerated by the introduction of Anthropic’s Claude large language model (LLM) legal tool. 

 

 Picture generated by Meta AI

 

Share prices of software companies such as Microsoft and Salesforce took a beating, down by 9% and 11% respectively the past 5 trading days. On the sector front using the iShares Expanded Tech-Software Sector ETF (IGV), it dropped close to 14% during the same timeframe.

 

Delving deeper on the situation, the number of inroads, potential or real, that AI made has been tremendous, and we are seeing a lot of these in the past few years. Though most leisure users utilise AI for generating pictures and summarizing homework, it is getting real with job-replacing tasks and applications being introduced for business purposes (e.g. Databricks, Base44, etc.). A serious threat to software, indeed.

 

However, if an investor steps back and relook at the whole picture, he/she may notice that there is another narrative being bandied about just recently, and that is about the threat of an AI bubble bursting. Logically the investor would be asking, “if AI eats software’s lunch, then how is it that AI is having this bubble?”. This paradox is a legitimate question.

 

However, amidst the bloodbath happening in the markets, a rational investor would see this as a good buying opportunity. With lowered share prices across the software and technology sector (the latter was a result of a spillover effect from the former), the next thing would be to look for companies that have strong moats and the strategic and financial ability of coming back (think Alphabet).

 

Think not of panicking but view it as a (probable) sale worth waiting for is now on.

 

Disclosure

The Bedokian is vested in Alphabet, Microsoft and Salesforce.

 

Related posts

The Great Search AI Race

Market (Over)Reactions 

 

Disclaimer

Possibilities And Probabilities

Although these two words may be similar to each other, both are different in meanings. Possibilities are occurrences that can happen, whereas probabilities are the likelihood of the occurrences happening. Using a lottery as an example, it is possible to win the top million-dollar prize, but the probability would be very small given the odds of winning it (literally at least a one-in-a-million chance).

Picture generated by Meta AI

The reason that I brought up these two things was from my encounters with other investors over the years, particularly on the issue of risk. While I had met some who totally disregard risks (so-called the “boom or bust” or “all-in and hope for the best” investors and traders), there were many others who did consider the different aspects of risks in their investments, to whom I give my praises to. Among the latter group, however, were some individuals who treated all possibilities with equal concerns; in other words, all potential risk happenings were given the same probable treatment by the person(s).

This is akin to an investor viewing the possibility of a company’s share price going down to zero and that of a brokerage firm absconding with his/her securities with the same probability lens. Hence, a typical interaction with this group would be peppered with many “what ifs”, like “if I buy overseas securities, what if the custodian ran away with my money?” or “what if A invaded B, resulting in the share price of the company located in B going down to zero?”, and so on.

For investors with this line of thought, a little bit of self-critique is necessary to slightly wean off from the equal-probability bias. After acknowledging a risk possibility, the first question to ask oneself would be how often it happened. If it was many times, assign a higher probability to it; if not, treat it as an event that one may not see again in his/her lifetime, and then go on and assess the next risk happening. After going through the possible risks, a probability scale of sorts is formed. Though in strict sense, probabilities are quantifiable and calculations are required to give them a number (e.g. percentage or odds), but having a simple probability scale should suffice for one to have a clear picture.

In an ironic twist that even myself adhere to, it is good to have a contingency plan for even the lowest probability risk event, and most are surprisingly easy to implement. Afraid of a custodian brokerage running away? Open an account on another one (what are the chances of two custodian brokerages going rogue at the same time? Very remote). Scared of a company’s share price going to zilch? Diversify one’s holdings. Most of these can be mitigated, but there are several events where one (or almost everyone) cannot prevent, like a total global market collapse, or an asteroid 10 kilometres in size hurtling towards Earth at 60,000 kilometres per hour. For this, should it really happens, it has been nice knowing everyone.

Suntec Distribution Up 13.6% Year-On-Year: The Beginning Of The Beginning?

Screenshot from Suntec REIT Financial Result cover slide.

Suntec REIT reported its FY2025 results with a 13.6% year-on-year increase in distribution per unit (DPU), despite slight declines in committed office occupancies across Singapore (-0.5%), Australia (-0.3%), and the UK (-2.6%). The retail side, mainly led by Suntec City Mall, saw a 1.2% rise in retail occupancy, boosting gross revenue by 2.9% and net property income by 2.1%. 

On the capital management front, the REIT reduced its aggregate leverage from 42.4% to 41.5%, increased its interest coverage ratio from 1.9x to 2.1x, and lowered all-in financing costs from 4.06% to 3.71%, aided by lower Q4 2025 interest rates. Net asset value declined slightly from SGD 2.05 to SGD 2.03 due to lower Australian property valuations.

The Bedokian’s Take

Although lower finance costs were not the primary factor, they still contributed noticeably to the rise in DPU. Reviewing the statements of total return, post-tax returns increased by approximately SGD 44,141,000 between FY 2024 and FY 2025 (from SGD 136,154,000 to SGD 180,295,000). Out of this, around SGD 22,625,000 (from SGD 154,588,000 to SGD 177,213,000) was linked directly to reduced finance costs.

The impact of declining interest rates is gradual because much of the debt was taken out when rates were higher. With an overall decrease in Suntec REIT's finance costs of about 35 basis points, it seems we are starting to see the initial effects of the rate reductions initiated by the U.S. Federal Reserve in September 2024. Depending on the nature of their debt structures—whether fixed or floating—other REITs may experience increased DPUs when they release their financial results in the near future. This trend could indicate the beginning of a broader REIT recovery.

Disclosure

The Bedokian is vested in Suntec REIT

Disclaimer

All figures are derived from Suntec REIT Financial Result for 2H and Financial Year ended 31 Dec 2025 (dated 22 Jan 2026).

Using ChatGPT To Review Our Bedokian Portfolio

Out of curiosity, we asked ChatGPT (free version) to review our Bedokian Portfolio, after reading up online on what other investors had done. With the exception of removing our holdings list, the answers were “as is” from ChatGPT (though from the replies you could catch a glimpse of what we are holding). 

Picture generated by ChatGPT

The prompted question was: Please analyse the following portfolio. Numbers denoting quantity of securities of the ticker. Only the counter names and number of securities were provided to ChatGPT.

I will give my take at the end of the post. Meanwhile, enjoy the ChatGPT review!

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Below is a structured, portfolio-level analysis based on your holdings and quantities. I’ll focus on asset allocation, concentration, risk profile, income vs growth balance, and key strengths/risks, then end with practical suggestions(not advice).

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1. High-Level Asset Allocation (by asset type, not market value)

Because prices aren’t provided, this is qualitative weighting based on number of holdings and intent.

🏢 REITs & Property (Very Heavy)

~30–40%+ of portfolio (likely more by value)

Observations

• Strong Singapore REIT bias
• Diversified across industrial, retail, office, and data centres
• Heavy reliance on interest-rate direction and refinancing risk

Pros

• Stable income
• Inflation-linked rents (partial hedge)
• Familiar regulatory environment (SG)

Risks

• Rate-sensitive
• Geographic concentration (Singapore-centric)
• Structural office risk (Suntec, Lendlease)

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📈 Equities – Growth & Quality

~25–35%

Observations

• Strong tilt to US mega-cap tech
• Nvidia + ASML = high semiconductor cycle exposure
• Berkshire adds stability and capital discipline

Pros

• Long-term growth engine
• Currency diversification (USD exposure)
• High-quality franchises

Risks

• Tech valuation cyclicality
• Concentration risk (AI/semiconductor theme)

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🇸🇬 Singapore Equities (Non-REIT)

~10–15%

Pros

• Defensive, cash-generative businesses
• Dividends and balance-sheet strength

Risks

• Slower growth
• Small-cap liquidity (YHI)

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💵 Fixed Income / Bonds (Very Strong)

~25–30%

Observations

• Excellent capital preservation sleeve
• Laddered duration via SSBs
• High credit quality overall

Pros

• Stability
• Income buffer during equity drawdowns
• Strong SGD base

Risks

• Reinvestment risk if rates fall
• Lower real returns long term

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🌱 Thematic / Satellite ETFs

~5–8%

Pros

• Optionality and upside themes
• China exposure via A-shares (policy levered)

Risks

• Volatility
• Policy and regulatory risk (China, clean energy)

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🪙 Commodities / Hard Assets

~3–5%

Pros

• Inflation hedge
• Crisis insurance

Risks

• No yield
• Silver volatility

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2. Portfolio Characteristics Summary

Dimension	Assessment
Income Generation	⭐⭐⭐⭐⭐ Very strong
Capital Preservation	⭐⭐⭐⭐½
Growth Potential	⭐⭐⭐⭐
Geographic Diversification	⭐⭐⭐½
Interest Rate Sensitivity	⚠️ High
Currency Diversification	Moderate (SGD + USD heavy)

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3. Key Concentration Risks to Watch

🔴 1. Singapore REIT + SGD Risk

• REITs + SGD bonds + SG equities = macro concentration
• If SG property or rates move adversely, multiple assets correlate

🔴 2. Interest Rate Sensitivity

• REITs + bonds move inversely to yields
• A sharp rate spike would pressure both income sleeves

🔴 3. AI / Semiconductor Cycle

• Nvidia + ASML + S&P 500 exposure
• Fantastic upside, but cyclical drawdowns can be severe

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4. Strengths of This Portfolio

✔ Well thought-out income + growth barbell
✔ Strong use of ETFs for efficiency
✔ Conservative bond allocation cushions volatility
✔ Real assets + equities + bonds = true multi-asset structure
✔ Suitable for long-term wealth preservation with income

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5. Optional Refinement Ideas (Not Advice)

You may consider:

1. Reducing REIT concentration over time and reallocating to:
• Global infrastructure
• Global dividend ETFs
2. Adding non-US developed equities beyond EAFE (e.g. factor or dividend tilt)
3. Monitoring duration risk if rates fall sharply (bond reinvestment strategy)
4. Rebalancing AI exposure periodically due to valuation swings

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Bottom Line

This is a mature, income-anchored, institution-style portfolio with:

• Strong downside protection
• Sensible growth engines
• Some macro concentration risk that is manageable with rebalancing

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The Bedokian’s Take

We were somewhat surprised by ChatGPT’s analysis, yet we also found the results fairly consistent with our portfolio construction. Reviewing point 2, Portfolio Characteristics Summary, ChatGPT awarded a 5-star rating for income generation, a 4½-star rating for capital preservation, and a 4-star rating for growth potential. When considering the portfolio strengths mentioned in point 4, it became clear that our current Bedokian Portfolio aligns well with our expectations.

Looking at the drawbacks, the main issue was the portfolio's high sensitivity to interest rates. This had been anticipated since the Bedokian Portfolio allocates a significant portion (20% to 40%) to REITs. Although REITs serve as valuable sources of income, they are notably sensitive to interest rate changes—a trend we have observed from early 2022 to recent months.

In addition to the Singapore Dollar bias that ChatGPT identified (without prior information about its focus on Singapore-based investors), another risk highlighted was the considerable exposure to artificial intelligence and semiconductor sectors. This aspect of our Bedokian Portfolio includes stocks like ASML, Nvidia, Apple, Alphabet, and is further influenced by the technology-heavy S&P500 index. Such a composition was purposefully chosen for growth, as explained in this post, and to capture extra alpha as detailed in my previous blog entry.

Overall, this exercise was insightful and confirmed several objectives we set for the Bedokian Portfolio. We may consider providing more data to ChatGPT and other AI tools to gain further views on our investment approach.