Why you should not buy an endowment plan.

To my fellow fresh graduates, congratulations on getting that degree scroll. 

By now, some of you would have secured your job and started bringing the dough home. As we accustom ourselves to the post-college life, many of us are entrusted with a newfound responsibility - managing our finances. How you control your spending and manage your savings will determine whether you can meet your financial goals in life. It is high time for us to maximize our dollars. 

Fortunately (or unfortunately), financial advice are aplenty both online and on the streets. We young tender looking fresh graduates in our office wear are probably one of the prime targets of the preying insurance agents. Buzzwords like 'returns', 'savings', 'beating inflation', and 'miserable banks' interest rate' resonate with your interest. Endowment plans, which are often marketed as a low-risk tool to help you meet financial goals while providing some insurance protections, may hit the sweet spot of many. The guaranteed cash value at maturity also entices the risk averse. 

Barring all the commissions and other fees and charges, endowment is inherently not a bad concept. This got me pondering whether I can build my own endowment using financial products that are highly accessible, while cutting out the unnecessary costs.

Structure of an Endowment

To do so, we need to understand the underlying structure of an endowment plan. An endowment can essentially be broken up into 3 parts, the guaranteed cash value, the non-guaranteed cash value, and insurance protection (usually death and total and permanent disability). In a very simplified sense, we can think of the premiums you paid as being channeled to each of the respective parts in an endowment. The premiums (after deducting all the commissions and fees) are allocated such that a significant portion of it will be used to buy low-risk-low-yield bonds to generate the guaranteed cash value. A small portion of the premiums will be used to pay for the cost of insurance. And finally, the remaining premiums will be invested in higher risk equities. 

The DIY-Endowment

In order to replicate an endowment, I will be combining 3 financial products that are highly accessible to the general public. They are: (1) the Singapore Saving Bonds (SSB); (2) the STI-ETF from POSB Invest-Saver; and (3) a direct term from NTUC income that covers death and TPD. Using this 3 products, I will try to replicate and compare it against the RevoSave (3-Pay-10). The RevoSave is a 10-year endowment plan with a $30k guaranteed cash value at maturity. Three $10k premiums are paid over the first 3 years of the policy.

To ensure the quality of comparison, I have included all the transaction fees for SSB and POSB Invest-Saver. STI-ETF are brought using the dollar cost averaging approach over 3 years at a monthly interval. The projected annualized return of STI-ETF is 9.2% (this takes guidance from the annualized return of STI between 2002 to 2013). The returns of SSB follows the interest schedule as shown on the SSB official page. The cost of insurance is $55 p.a. with a $50k coverage on death and TPD. 

Below is the benefit illustration of RevoSave for a 23 yo female non-smoker.

At 4.75% projected return, the RevoSave would generate a  projected return of $9689 at maturity with an average coverage of $39,158.40 over the 10-year period.

On the other hand, the DIY endowment yield superior performance compared to the RevoSave. The death and TPD is fixed at $50k throughout the 10 years. The non-guaranteed return is $11029.14, while the guaranteed return is $30000.03.

For those who are interested, the code for calculating the figures is pasted here.

insurance = 55
bonds = 8111
stocks = 10000 - insurance - bonds

bonds_returns1 = 1.0241
bonds_returns2 = 1.0234621
bonds_returns3 = 1.022956
stock_returns = 1.092

guranteed = (bonds-2)*bonds_returns1^10 +
    (bonds-2)*bonds_returns2^9 +
    (bonds-2)*bonds_returns3^8 - 4
non_g = stocks/12*0.99*sum(stock_returns^((1:12)/12))*
    (stock_returns^2 + stock_returns^1 + stock_returns^0)
for(i in 1:7){
    non_g = (non_g-55)*stock_returns
}

Is the assumption of 9.2% annual return from STI-ETF a fair comparison against the projected return of 4.75% in the endowment? 

We must note that the 9.2% is the return from equities. On the other hand, the 4.75% from RevoSave is the return from an investment mix of both equities and other low yielding instruments. As of 31 Dec 2014, the participating fund of RevoSave is make up of 23% equities, 67% fixed income, and 10% of cash/loans/properties. Assuming the low yielding instruments yield an annualized returns of 3% to 3.5%, this means that RevoSave assumes their equities can generate a return of 8.9% to 10.6%. The higher equities exposure (18% in my diy-endowment vs 23% in RevoSave) also means higher risk exposure in RevoSave.

All in all, the diy-endowment is likely to yield better returns, offers higher protection for 9 out of 10 years, able to provide a guaranteed principle, lesser risk exposure, and greater flexibility to customize to your needs.

UPDATE (8 Nov 2015)
Sunday Times published an article titled Make (full) sense of insurance policies on 8 Nov 2015 that highlights important things to look out for before committing to  an endowment policy. The article provides a useful table which compares the investment returns on insurer's most representative participating funds for the past 7 years. Let's take a look at how they compare against my DIY endowment. (Note: I am assuming a risk-free product with similar return profile as SSB exists for the period of comparison)

A quick glance shows that the performance of all funds are comparable. But it is important to note that the returns of the insurer's participating funds are NOT the effective or net returns that policyholders will get. The returns have yet to consider the hefty distribution cost, management expenses, commissions, and cost of insurance. All these cost can easily shave off more than 1.5% of the returns.

Clearly, my DIY portfolio significantly outperformed many of the endowment plans based on past 7 years result. 

Last Academic Update AY2014/15 Sem 02

As the morning sun rose and crept into my bedroom, I sat in front of the desk, where I had spent countless hours grinding for the past 4 years, anxiously awaiting for the moment my phone vibrates and reveals the outcome. 

A blend of anticipation and trepidation engulfed me. The same cocktail of emotions which overcame me when I was still a freshie waiting for my Yr1 Sem1 result. But this time, more is at stake. I needed at least an A- for FYP in order to achieve the First Class Hons (FCH) I worked so hard for, and in turn, a FCH means quite a significant difference (+8.2%) in my starting pay.

The phone buzzed and there it was, ST4199 A-. Exuberance awash me as my efforts have bore fruit. It has been a long journey. When I first set foot in NUS, I worried about my ability to cope; then I started worrying about not being able to get an internship; I was quite depressed when my job applications were rejected repeatedly by Dept of Stats (Singstat); And my FYP was quite a mess, hence I was very worried about my grade. Luckily, things always turn out fine.

ST4199	Honours Project in Statistics	A-
ST4232	Nonparametric Statistics	A-
ST4242	Analysis of Longitudinal Data	B+
ST4245	Statistical Methods for Finance	A

MC	160
CAP	4.70

ST4232
The content is very light. The entire syllabus consists of approximatedly 70-80 pages worth of content. The materials taught are also quite easy. A/P Yu Tao likes to read off lecture notes, but his explanation generally helps to clear doubts. Assignments and final exam were manageable.

ST4242
The Content is heavy, and the module requires a lot of SAS coding which I am not very well-versed with. Spent a lot of time doing trial and error to get some output from SAS for my tutorials and I have no idea what's going for the most of the semester. Overall, I did not have a good experience with this module. Module was taught by A/P Li Jialiang.

ST4245
For people who have taken Financial Economics (EC3333), Applied Time Series Analysis (ST3233), and Linear Model (ST4233), there were not many new concepts introduced. As usual, Prof Xia Yingcun's midterm and final exams follow his tutorials closely. As long as you understand the tutorials, the exams will be manageable.

If anyone would like to get a softcopy of the lecture notes, tutorials for any of the modules I have taken, you may access them through this link: NUS Modules. Do note that, I don't have any secret study or access to pyp solutions. The files I share will contain only lecture notes, tutorials (+ solutions), assignments (+ solutions), and perhaps some pyp obtained from the library portal. Hence, asking me for materials towards the end of the semester is kind of pointless. The materials are meant for people who are keen to read ahead, or have a glimpse of the contents before they bid for the modules.

That's all for my last academic update. I am not sure if I will still be posting anymore academically related post in the future. I hope the series of module reviews and freshmen guides had help some of you. Feel free to contact me if you have any doubts related to the course, I will try to answer them to the best of my ability. Bye.

The End of a Chapter

How time flies.. 4 years had zoomed past, and my journey as a student has officially ended. When I was in JC, I have always had a knack for Statistics despite my distaste for Mathematics. Upon my JC graduation, I wanted a uni course which interest me, leverages on my strengths, and promise a certain level of career prospect. Statistics naturally fulfilled the first 2 criteria, but I was uncertain about the career prospect for a statistician or a statistics graduates, especially in Singapore's context. I did some research online then, but the relevant information were scarce. In the end, I took a leap of faith and accepted NUS Science with a very murky idea of the potential career opportunities. On hindsight, I am glad that I have chosen this course. 

The Programme

The statistics course in NUS is not going to be easy. Getting a First Class Hons will not be a walk in the park. With a significant number of foreigners who are brainy and hardworking, the competition is steep.

Comparing with economics modules, the workload of statistics mods tends to be heavier and requires more effort to understand. It is perfectly normal to leave a statistics lecture utterly confused, especially if  you did not skimmed through the reading materials before the lecture.  

Do a Double Major. 

For those who have the capacity to do more, consider a double major. 

The Statistics curriculum consists of one of the highest number of unrestricted electives (36MCs) compared to many other majors. This gives statistics students considerable flexibly to take on a second major without being heavily overloaded. For example, with careful planning, one can fit a second major in Economics into the programme requirement without additional coursework.

A double major do matters to the employers, and will enhance your employability. Apart from the intangibles like demonstrating your diverse interest and knowledge, your willingness and ability to do more than the minimum, certain combinations of majors are highly valued by employers. Combinations such as Statistics + Economics or Statistics + Computing are highly complementary, and for the latter, I foresee a rising demand for such graduates. Needless to say, a second major will also broaden your career options. Personally, a double major did opened up more opportunities for me, and I would not have secured my relatively-well-paying job offer without my second major. 

Career Paths

Majority of the statistics grads should not face much difficulties securing a job, especially for students who are graduating with honors. Many of my course mates managed to secure job offer(s) before the final exams. Some of the possible career paths available to statistics grads include:

Healthcare (Clinical Analytics) 

Biostatisticians with the various healthcare/research facilities and healthcare authorities 

Statisticians in the private and public sectors. 

Banking (risk, analytics, ops and tech) 

Actuary

Data Analytics

Market Research

However, some of these jobs have high barrier of entry, and so I would advise you to start preparing for your career as early as possible. Join networking session to find out what are the entry requirements for the job (pro. qualifications/exams, relevant internships, etc.). Get relevant experience through internships. Attend some career workshop conducted by NUS career center.

Let me end this section with a quote from Google's Chief Economist, Hal Varian, on statistics and data.

“I keep saying the sexy job in the next ten years will be statisticians. People think I’m joking, but who would’ve guessed that computer engineers would’ve been the sexy job of the 1990s? The ability to take data—to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it—that’s going to be a hugely important skill in the next decades, not only at the professional level but even at the educational level for elementary school kids, for high school kids, for college kids. Because now we really do have essentially free and ubiquitous data. So the complimentary scarce factor is the ability to understand that data and extract value from it.” – Hal Varian, Google’s chief economist

Modules Ranking

Finally, here's my personal ranking for the modules I have taken over the past 4 years. They reflect my interest, preference, strengths, and weaknesses. Therefore, my experience with these modules may be wholly different from yours. 

Most interesting mods

1. GEK1508 Einstein's Universe and Quantum Weirdness by Prof Phil Chan

2. EC3312 Game theory and Application to economy by Luo Xiao

3. EC3333 Financial Economics I by Lim Boon Tiong

For those who are intrigued by the movie Interstellar (2014), I highly recommend GEK1508. The module explores the intricacies of Relativity, Quantum Mechanics and strings. Prof Phil Chan is also an extremely passionate lecturer who makes the lectures an enjoyable experience. Easily the best module I have taken in NUS.  

Most Difficult ST mods

1. MA2108 Mathematical Analysis I by A/P Lee Soo Teck

2. ST3236 Stochastic Processes I by Sun RongFeng

3. ST3246 Statistical Models for Actuarial Science by A/P Lim Tiong Wee

Most Useful mods

1. ST2137 Computer Aided Data Analysis by Dr. David Chew

2. ST4231 Computer Intensive Statistical Methods by Alexandre Hoang THIERY

3. ST3239 Survey Methodology  by Dr. Chua Tin Chiu

Apart from the Most Useless modules listed below, many of the ST/MA lvl1000-2000 mods are useful for building up our foundation in understanding and applying statistics. The top 3 listed here are special mentions which I think are very useful in both industrial and academia. 

Mose Useless mods

1. MA2108 Mathematical Analysis I by A/P Lee Soo Teck

2.  ST3236 Stochastic Processes I by Sun RongFeng

I don't recall much from these two modules. Basically, they are just learn-and-dump mods as I have not applied anything from these two modules for any of my higher level modules.  

Most Difficult EC mods

1. EC3312 Game theory and Application to economy by Luo Xiao

2. EC3333 Financial Economics I by Lim Boon Tiong

Easiest EC mods

1. EC2101 Microeconomic Analysis I by Zhang Yang

2. EC3101 Microeconomic Analysis II by SNG Tuan Hwee

3. EC3361 Labor Economics I by Peter James McGee