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Saturday, September 13, 2025

The "Certainty System": How I Use Math to Rebalance My CDP Dividend Portfolio | Lin Cangyan



According to data from DBS Bank’s net worth planning tool (digiWealth), my owner-occupied property (a three-room HDB flat) currently accounts for approximately 12.35% of my total assets. Over the years, I have consistently regarded my property as living infrastructure rather than an investment asset. My long-term asset allocation and capital management are conducted primarily through Singapore Real Estate Investment Trusts (S-REITs) and retail unit trusts offered by DBS Bank.

My current asset allocation is as follows:

Owner-occupied property: 12.35%

This allocation reflects a deliberate separation between living infrastructure and capital infrastructure within the CYSM framework. It embodies my long-standing financial strategy: housing serves as essential living infrastructure, while the investment portfolio functions as the primary engine for capital growth and cash-flow generation.

I decided to retire on March 1, 2024, before reaching the age of 58, seven years earlier than the official retirement age of 65, which was originally scheduled for 2030. My basic monthly salary before retirement was SGD 3,114. In hindsight, SGD 3,114 was not an income milestone, but a system signal. It marked the point at which my financial and living infrastructure had matured sufficiently to support time sovereignty. CYSM does not interpret numbers as achievements; it interprets numbers as indicators of system state.

My CPF investments have maintained a profitable return on investment so far. On March 16, 2024, having reached the FRS, I decided to close my CPF investments account and withdraw all my CPF investments, allowing me greater flexibility and convenience in managing my retirement assets.

The value of investment funds fluctuates with global economic developments, so the timing of fund redemptions is crucial. Past returns, which can be found online, are for reference only. The following is my CPF Investment portfolio before closing, please feel free to refer to it:

73.56% — FSSA dividend advantage fund
6.84% — Mapletree Pan Asia Cm reit
5.67% — Frasers log & co tr
3.79% — Sasseur reit
3.67% — Lendlease gl co reit
3.53% — Capitaland ascendas reit
2.92% — Aims apac reit

Achieving retirement officially opens the door to my money working for me. I no longer work for money and become fully committed to controlling my finances and my time. The next step is to reduce investment risk, increase sustainable investment returns, and properly manage my retirement assets.

The first formula below estimates the actual amount of cash invested in my CDP fund, using my Amova Singapore Dividend Equity Fund (ASDE) as a benchmark. It provides a standardized way to track relative performance.

Estimated CDP Cash Invested Principal = (ASDE Principal x CDP Market Value) / ASDE Market Value

The second formula below tells me the actual dividend yield of my CDP portfolio, adjusted for invested capital. I regularly update this data in Excel to monitor whether my portfolio remains within my target yield range of 4-8%.

Annual CDP Dividend Return % = (Total Annual CDP Dividends Received x 100) / Estimated CDP Cash Invested Principal

The above formula provides a data-based estimation method to measure the performance of my CDP portfolio by projecting potential paper gains or losses. You can also use the above formula to benchmark your CDP fund against an index fund or ETF. Maintaining no more than 10% of your entire fund in any single stock is generally quite safe. 


Data source: SGX

[Empirical Evidence of Non-Deliberate Operation at the Capital Layer]

As of 30 September 2026, the top ten holdings in my CDP portfolio accounted for approximately 50.3%, while the remaining holdings—around 90 securities—accounted for 49.7%.

Some may assume that I deliberately maintain the “Others Securities” portion at around 48–49% to achieve diversification. In reality, this was never a target I set.

I established only two basic structural constraints: no individual holding should exceed 10%, and the portfolio should remain diversified across roughly 100 Singapore-listed securities.

Once these constraints operate over time, the portfolio naturally develops a relatively stable distribution. The top ten holdings cannot simply occupy the entire portfolio, while the long tail of smaller positions fills much of the remaining space.

I do not calculate or adjust this ratio every day. I set the structure, and then let time operate within it.

This is what non-deliberate operation means in CYSM: when the underlying structure is properly aligned, stability does not have to be maintained through constant willpower or manual intervention. It can emerge naturally from the way the system operates over time.

The 49.7% was not a target. It was an emergent property of the system.




[Empirical Evidence of Non-Intentional Operation: My Career] 

By the time I formally retired on March 1, 2024, my career had accumulated approximately 25 years of employment, including part-time work. This was not the result of deliberate planning.

Some may assume that I intentionally pursued 25 years of service or a long multinational-company career. In reality, neither was a planned objective.

I simply operated under two underlying constraints:

  1. After National Service, I consistently worked in roles related to maintaining system reliability—from electrical and testing systems to building and automated systems.
  2. After developing glaucoma, I became increasingly aware that the time available to enjoy a healthy life is one of life's greatest forms of wealth. I therefore chose retirement rather than entering a third period of unemployment.

Once these two constraints were in place, my career gradually converged into its present structure:

  • Multinational experience: NEC, IVP, ST Electronics, Sanmina-SCI, ST Aerospace, and APM, totaling more than 20 years.
  • Periods of unemployment: June 1999–May 2002 (2 years 11 months) and September 2009–June 2012 (2 years 9 months). These were not empty gaps, but periods of recalibration while the system responded to broader economic conditions.
  • Part-time transition: NTUC FairPrice (2002–2006), which helped keep the system operational during a lower-demand period.

I did not deliberately try to avoid unemployment, nor did I deliberately try to accumulate years of service.

I simply maintained the underlying structure: work in system-reliability roles, wait for suitable opportunities, and avoid rushing into work that was structurally misaligned.

Then I allowed time to do its work.

This is what CYSM means by non-intentional operation:

When the underlying structure is aligned, stability does not have to be maintained by willpower. It can emerge naturally from the way the system operates.

My father’s devotion to Guan Yu instilled in me a fundamental sense of alignment that served as a psychological buffer. It is precisely this mindset of going with the flow that has enabled me to truly operate without forced effort in both my investments and my career.

I did not deliberately build a 25-year career.

I simply allowed time to amplify a stable structure.



📖 Financial Transparency as System Validation

To pursue the Advanced Degree in Life Engineering (CYSM), I made public my portfolio of liquid assets and monthly expenses. This is something many people cannot bring themselves to do. Transparency in financial modules is not about showing wealth, but about demonstrating the operational stability of the system. CYSM is not a theory on paper—it is a life protocol validated by real-world constraints.

The true difficulty, however, is not merely in making a portfolio public. The real challenge lies in allowing a theory to be tested against reality. Many are willing to share ideas, philosophies, or methods, but few are willing to disclose actual asset allocation, cash flow structures, spending levels, or risk-bearing strategies. Once such data is revealed, a theory shifts from opinion to verifiable structure.

By publishing key operating parameters—liquid asset allocation, REITs, ETFs, SSBs, cash buffers, living expenses, the SGD 667 low-energy engine, and the 5.61% yield engine—CYSM moved beyond abstract discourse. Readers can now observe not only what CYSM says, but how CYSM runs.

This transparency aligns with CYSM’s guiding principle: Theory may guide, but systems must run. Once data is public, time becomes the strictest examiner. Only long-term stability proves resilience. In this sense, publishing asset configurations is not the “degree” itself, but rather the submission of experimental data. The true test of CYSM lies in whether the system can continue to operate stably under the constraints of Signal × Time × Stability.




Personal Narrative Signals: Sparrows, Moths, and Dreams

The following content does not fall under the "evidence framework" of CYSM. These are external and internal narrative signals recorded during the long-term operation of my system; they claim no causality and constitute no verification. They serve merely as observational records within the calibration process.

Narrative Signal: On the evening I updated this section of the blog describing the deliberate separation between living infrastructure and capital infrastructure within the CYSM framework, a black moth unexpectedly entered my room. After guiding it out, I later discovered that, in traditional folklore and symbolic interpretations, a moth entering the home is often seen as a symbol of transition, fortune, emotional connection, or subconscious awakening. Within the CYSM framework, I interpret this event not as superstition, but as a narrative signal — similar to the sparrow incident in 2025 — a reminder that real-world experiences often echo the system’s ongoing calibration. Just as external signals are filtered, abstracted, and integrated into CYSM, this symbolic encounter reflects the convergence of rational asset allocation with subconscious transformation. A black moth is not a causal omen but a narrative signal. It symbolizes the constraints and transitions that invite recalibration of the life system. Whether interpreted as misfortune or transformation, its meaning lies in how the individual integrates the observation into structural stability.


This comparative chart visualizes two narrative signals — the sparrow of 2025 and the moth of 2026 — illustrating how real‑world encounters can be observed as part of CYSM’s long‑term calibration. Each event occurred about one year apart, forming a natural rhythm of observation rather than prediction, and showing how symbolic experiences can coexist with rational system updates.

Narrative Signals in CYSM In the CYSM framework, certain real-world events are recorded not as proof of theory but as narrative signals — emergent observations that surface during long-term system operation. These signals, such as the sparrow in 2025 and the moth in 2026, are documented as part of ongoing calibration. They represent the overlap between external occurrences and internal system states. While each event is objective in itself, its long-term significance can only be validated through continued operation, feedback, and structural convergence.

Narrative Evidence in CYSM The comparative chart of the sparrow (2025) and the moth (2026) illustrates how narrative signals emerge as part of long‑term calibration. Their one‑year interval filters random events into meaningful observations, aligning external encounters with internal system states. The contexts—retirement transition and infrastructure reflection—map directly onto two stages of system evolution. By juxtaposing quantitative data with symbolic experiences, CYSM demonstrates that stability is achieved not only through numbers but also through the disciplined recognition of signals that surface over time. In CYSM, narrative signals are not decorative metaphors—they are recorded observations that inform calibration, without asserting causality.


This framework illustrates the four layers of evidence in CYSM — quantitative, operational, narrative, and structural — showing how the system evolves from data to long-term stability.

Note: Narrative Evidence differs in kind from the Quantitative, Operational, and Structural layers — it is not independently verifiable, reproducible, or causal. It records events surfaced during long-term system operation; its value lies in whether it is consistently incorporated into calibration, not in whether the event itself is objectively true. The four-layer table reflects the completeness of CYSM's recording system, not equal evidentiary weight across layers. Validation here refers to whether signals are consistently integrated into the system, not whether the events themselves are proven true.

CYSM also incorporated the dream—occurring at midnight on July 28, 2026, and representing the subconscious—into the narrative signals. Within CYSM’s semantic framework, "black moths" and "sparrows" constitute external narrative signals—environmental events that serve to observe the system's interaction with the outside world. Dreams, conversely, are internal narrative signals—reflecting the system's internal psychological or cognitive state.

In CYSM, narrative signals are not decorative metaphors—they are recorded observations that inform calibration, without asserting causality. The distinction between the two lies in:



This approach aligns perfectly with the CYSM methodology, clarifying how external events serve as system inputs and internal experiences act as feedback within its long‑term calibration framework.


Conclusion CYSM demonstrates that true stability is not designed once, but sustained through transparent data, disciplined operation, and continuous calibration over time.

Time sovereignty ultimately provides the operational freedom required for long-term system calibration, allowing CYSM to evolve through continuous observation rather than continuous urgency.



All images above provided by Microsoft Copilot. Pie charts were created using VS Code IDE and Google Sheets respectively
The personal information above was analyzed and interpreted by Google Gemini, DeepSeek, ChatGPT and Microsoft Copilot, editorial review by Claude

Regarding naming philosophy →  please refer to"The Use of White Space in Names"


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