Understanding modern retirement calculators

August 31, 2014

In today’s post I want to explain and demonstrate how modern retirement calculators work. There are two basic ways to calculate how much you can safely withdraw from your portfolio in retirement; looking backwards using historical data for past retirees and looking forward using possible future investment returns. On this blog I’ve pretty much only described the historical safe withdrawal rate (SWR) approach. That’s where the 4% SWR number comes from that you hear talked about all the time. Modern retirement calculators do not use this approach. They use a forward looking approach called Monte-Carlo analysis to come up with their SWRs. Lets see how these calculators work.

What’s wrong with using historical data to come up with SWRs? The problem is history only represents one outcome of all the possible future paths from that previous point. If you were back in 1966 looking forward to a 30 year retirement the actual outcome of your 30 year retirement period, which happened to become the worst in history, was only one of many possibilities. Modern retirement calculators eliminate this drawback by looking at many many possible future retirement outcomes. That’s the fundamental difference. The rest is calculation details. How do they do this? They assume that future investment returns follow some probability distribution, since the future is fundamentally indeterminate and probabilistic. So, for example, they assume that future investment returns are normally distributed (they also use some really fancy distributions like multi-variate log normal but the results are similar), i.e. follow a bell curve. They then randomly generate a time series of investment returns and use those investment returns to calculate what the SWR would be in each of those random series of returns. Since they can’t do this for the infinite variety of possible returns they usually stop at a sufficiently large number that generates statistically robust results. The generally accepted large enough number for these retirement calculators is 10,000 trials.

Now, here is the catch with these retirement calculators. They still involve some kind of bias or human forecasting under this seemingly unbiased random robust scientific method. For those assumed normal distributions  you still need to pick a mean and a standard deviation to generate those random investment returns. And you still need to forecast inflation as well. You can’t model all possible potential future outcomes. Confused yet?

It’s really pretty simple, it’s just the calculations that get intense. I put together a simple retirement calculator in excel to illustrate how this is done. In one excel file I generated 1,000 random series of 30 year investment returns (note: every time you open, save, or make any changes to this file the random numbers change, unless you turn off automatic calc in options). I generated stock and bond returns independently. I then copied these results to another excel file where I did the work of calculating the SWR for those 1,000 random simulations. In this first pass I use the historical mean and standard deviations for US stocks and US 10 year government bonds from 1929 through 2013. I also used historical inflation. And this leads to the next important observation regarding retirement calculators. All of them define a successful SWR to one that has an 80% to 85% success rate. In a 10,000 trial simulation that means 1,500 to 2,000 of the possible time series of investment returns result in failure, i.e. running out of money. It’s just that those cases are lower probability events. Yet still possible. Using an 85% success rate my simple model yields and SWR of 3.92% for a 50/50 stock bond allocation. Pretty close to the historical SWRs for such a simple model.

But none of the modern retirement calculators I’ve seen use historical returns in their calculators. They all use a return forecast that is significantly lower than historical returns have been. I think the simplest and best retirement calculator is the one from Vanguard. I like it because there is no need for a ton of inputs on the user’s part. It just generates the SWR based on the retirement period and one of three asset allocations. All the gory details are behinds the scenes. Their future return assumptions are updated once a year and explained in the Vanguard Capital Markets Model. It’s well worth the read. Basically, they use diversified portfolio returns of 3-5% real going forward, less than returns have been in the past. For a 30 yr retirement period and a moderate asset allocation their model yields and SWR of 3.8%. I used these lower future expected returns in my simple model and that yielded an SWR of 3.30%. You can access those files here and here.

At the end of all this fancy analysis we have a tool that tells us that future SWRs will be lower than the past because we are forecasting future returns to be lower than historical returns. And specifically lower than the 30 year retirement period that started in 1966 which is what gave us the worst case historical SWR to begin with. Seems kind of obvious when you put it that way. So, basically this all relies on a forecast of the future which are notoriously inaccurate. But its the best tool we have. From today’s valuation levels and interest rates it is possible the SWRs will be slightly to a good deal lower than 4%. But they may not be.

That pretty much sums up how modern retirement calculators work. Now you can at least use these tools with an understanding of what’s under the hood. You can even generate your own models if you want.

Note: the T Rowe Price retirement calculator is another very popular one. I find the added inputs and complexity unnecessary.


SWRs from 100% US TIPs portfolio update

August 21, 2014

Contrary to the overwhelming consensus at the beginning of the year, bonds have done remarkably well year to date. With that in mind I wanted to update the SWRs for the 100% US TIPs retirement portfolio I presented last year. With rates down, SWRs will be down as well but lets see by how much.

The updated SWRs from a 100% US TIPs bond ladder are shown below. I also compare them to the SWRs from my previous analysis plus the SWRs from various risky portfolios.

TIPS Model Aug 2014

As the bottom table shows, the SWRs for a 100% US TIPs bond ladder went down from 4.37% to 4.20% for a 30 year retirement period. This still compares very well to the historical SWRs from the risky portfolios. Although you almost never see this option discussed as retirement portfolio option (no one can make a lot of fees off this model), the results could be very compelling for the most risk adverse retirees.

Note: I’ve uploaded my detailed spreadsheet model here for anyone that is interested. You need to be familiar with Excel’s solver function to run the analysis for yourself.


Trending value performance update (Aug 2013 port)

August 15, 2014

This is a simple house keeping post on a quant portfolio from last year. In the comments section of my post last year on the Trending Value portfolio I linked to a Trending Value portfolio I created as of Aug 9 2013 to help some readers compare holdings in their versions of trending value portfolios. The link to that portfolio in Google sheets is here. The portfolio I reference here is the TV2 FCF NA 50 tab. Below I update the one year performance for that portfolio.

First, the snapshot at the close on Aug 9 2014 from my FINVIZ tracking portfolio is below.

Trending Value Aug 9 2013 One Year Performance Aug 2014

First thing to note is that the portfolio lost 3 holdings during the year. It started with 25 stocks. There were 3 mergers/acquisitions during the year; SPRD, CGX, and ASI. Those need to be added back in to the portfolio at the merger or sell prices.

Second, and the most important portfolio change throughout the year was in ESI. On Feb 26, 2014 the US gov’t announced an investigation into ESI. That breaks rule #2 of the quant portfolio rules and the stock should have been sold from the portfolio. I waited a few days to do some investigating and sold ESI at $30.95, for a 4% gain. If the stock had been held  in the portfolio the loss would have been -71% as shown above.

Lastly, dividends need to be added to the capital gain returns shown above. The portfolio has a dividend of 1.24%.

I’ve added all these changes and return calculations to the original link for the portfolio.

All changes incorporated, the portfolio had a gain for the year of 17.7%, handily beating its closest benchmark the Russel 2000 which had a return over the same period of 9.8%. The SP500 returned 16% over the period.


Yes, you are trying too hard

July 7, 2014

“True wisdom comes to each of us when we realize how little we understand about life, ourselves, and the world around us.” Socrates

When I read the Socrates quote above I can’t imagine what he would have said about today’s world. We live in a highly complex non-linear world with access to way more information than even massive computers can process. And yet we try and get by with our relatively poor information processing brains that simply cant deal with the onslaught of data and are subject to slews of behavioral biases which affect our decision making. No where is this more true than investing where there is the added complexity of trying to predict the future under in such an environment. I was reminded of this recently by a white paper from one of my favorite quantitative investment researchers Wes Gray titled Are you trying too hard? In the paper he makes the case for systematic decision making, i.e. quant investing. It’s a compelling case that all investors should consider. I’ll highlight some of the gems in the paper but by all means read it all and try a take a few minutes from the information hose to digest what it could mean for you.

First, lets start with the basic summary of the white paper;

Because we recognize our frequent irrational urges, we often seek the judgment of experts, to avoid becoming our own worst enemy. We assume that experts, with years of experience in their particular fields, are better equipped and incentivized to make unbiased decisions. But is this assumption valid? A surprisingly robust, but neglected branch of academic literature, has studied the assumption that experts make unbiased decisions for over 60 years. The evidence tells a decidedly one-sided story: systematic decision-making, through the use of simple quantitative models with limited inputs, outperforms discretionary decisions made by experts.

The evidence is overwhelming. He understates his case. And its even worse than he makes out as investors even underperform the experts they are paying to underperform the market by chasing returns. The solution lies in relying on models and focusing our precious limited bandwidth on choosing said models and evaluating their performance.

Students of decision-making break the decision-making process into three components (see Figure 3):

  1. Research and development
  2. Implementation
  3. Assessment

I would argue that human experts are required for the first and third phases of a decision-making process, which are the research and development phase and the assessment phase, respectively. The crux of my argument is that human experts should not be involved in the second phase of decision-making, or the implementation phase.

Exactly. Focus on the model and how it performs. This need not be a complex quant model. Standard allocation and Buy and hold indexing is a model. A model that can work quite well for most investors over the long term. The IVY portfolios whether buy and hold or the trend following ones are models. So are all the quant portfolios I’ve discussed on the blog. Once you decide to go on a path to more systematic decision making, the question becomes which one is right for you. Buy and hold is just fine if you can handle the drawdowns in bad years. Many can’t. Then what? Choose a different model.

What’s even more enlightening is that even experts armed with proven  models under perform the model. How’s that for human fallibility. Turns out the models represent a ceiling on performance.

In follow-on tests, the researchers gave the experts the output of the model and disclosed that the model has “previously demonstrated high predictive validity in identifying the presence or absence of intellectual deterioration associated with brain damage.” Using the model, experienced clinicians significantly improved their accuracy ratio from 58.3% to 75% and the inexperienced clinicians moved from 62.5% to 66.5%. Nonetheless, the experts were still unable to outperform the stand-alone model, which had already established the gold standard 83.3% success rate. This study suggests that models don’t represent a floor on performance; rather, models reflect a ceiling on performance, from which the experts detract. The “secret sauce” of human judgment ruins the beautiful simplicity of a calculation

What this tells me is that I need to accept that even after I make the conscious decision to use models I shouldn’t expect my performance to equal the model. Inevitably I will get in the way of the model and mess things up. That’s OK. We are not robots nor can we expect to become one but we should strive to adhere to the models and/or find ones that better fit our individual behavioral biases. This is not an easy switch to make.

Relegating your decision-making processes to systems requires a massive dose of humble pie.
Most—if not all—are unable to consume this dish. But to be a better decision maker we must eat our humble pie. As I have shown in this essay, in order for decision making to be effective, it must be systematic. And the only systematic thing about humans is our flaws. Therefore, it is best to leave the stock picking to Warren Buffett, and for the rest of us, who suffer from behavioral biases, which result in flawed decision making, we should stare into the mirror, and ask ourselves: Are You Trying Too Hard?

Yes, I was. And probably still am. My personal journey to quant investing started in 2005 when I bought two books that began a fundamental shift in investment thinking. The first book was Joel Greenblatt’s The Little Book That Beats the Market and the second was O’Shaughnessy’s What Works on Wall Street (links are to newer editions of the books). Then in 2009 it was The IVY Portfolio by Meb Faber which introduced me to ETF systems and risk reduction with trend following. That began a slow transition to quant investing and benchmarking myself against models. I’m now down to one individual discretionary stock holding and still a bit too discretionary for my bond holdings but I’m almost to where I want to be. My conclusion after all of this; even if I assume I can beat the models, which btw can beat the market, with above-average stock picking ability or market timing it’s not worth the time, work, or anxiety. I have better things I can do with my time and energy. You have probably been trying too hard too.


Technology is shaking up the investing landscape

July 4, 2014

There’s been couple of recent announcements in the portfolio management industry which show the extent of technology’s penetration into the industry. The announcements further continue the rise of such automatic investing companies like Betterment and Wealthfront which are using modern technology to automate and drive down investment costs for individuals.

First, Covestor announced a series of Core ETF Portfolios with zero management fees. Basically, this means you can get professionally managed buy and hold ETF portfolios for no management fees. The only fees are the underlying ETF fees and ETF transaction costs of approximately $20 per year. This is probably less than what it wold cost you to do it yourself but without having to make any decisions during the year. You just pick a certain allocation model, say the Balanced Core Portfolio (60% stocks, 40% bonds) and the rest is taken care of for you. See details here.

Second, with Motif Investing you can build your own portfolios of individual stocks or ETFs for a single one-way commission of $9.95. You can then change any individual position within your portfolio for $4.95 per transaction. Overall, this is lower than you can do on your own in any of the discount brokers that I am aware of. See details here. For example, think about implementing any of the quant models or IVY portfolios I’ve discussed on the blog with this transaction structure. You can pretty much beat the costs any broker or individual stock ETF with this model.

All of these technological developments could have huge implications for professional management, either passive or active. I believe there is a role for professional financial advice, as I discussed here, the question is how much are you going to pay for it? You think Vanguard is not aware of this trend? And why would you pay any more than 0.3% to Vanguard for any buy and hold advice? These developments also lower the bar to any active management of your portfolio and that active management of your portfolio should be leading to well documented investment outperformance and/or significant risk reduction (drawdowns, down years, etc…). If it’s not call Vanguard or do it yourself.

 


A year in the life of a trending value portfolio

June 4, 2014

It’s kind of hard to believe but almost a year ago I introduced the trending value quant portfolio. Since I’m coming up on a rebalancing and I’ll start work on the new portfolio this weekend I wanted to take a look back and see how last year’s portfolio performed. Also, I’ll point out some highlights and lowlights in the portfolio.

Lets start with performance. Below is a snapshot as of this morning of the performance of the trending value portfolio from June 14,2013.

Trending Value 1 year performance from June 14 2013updated june 4 2014

I use a $100K portfolio starting value because FINVIZ has a feature where it automatically calculates the individual share counts needed to make an equal weighted $100K portfolio for you. Makes life easier then I can scale the values as needed for my real portfolio in my brokerage account.

The Gain% column in the table shows the price only gain since June 14, 2013. The price only change is 20.8%. The portfolio had an initial dividend yield of 1.5% which brings the total return for the trending value portfolio to 22.3% with 10 days to go to complete the year. The closest benchmark to the trending value portfolios is the IWM ETF. In the same time frame IWM has a total return of 14.96%. And since everyone always likes to compare to the SP500, the SPY ETF is up about 19% in the same time frame. The performance of the trending value portfolio is right in line with its historical average.

Managing this portfolio throughout the year was relatively easy. If you compare the stock list above to that in the original post you will find a few differences. During the year, Arkansas Best Corp (ABFS) changed its name to Arc Best Corp (ACRB). You wouldn’t have needed to anything in your brokerage account. The change was automatic. You would just have changed your tracking portfolio like I did in FINVIZ. Next, DEG had a 4:1 stock split during the year. Again, nothing for you to do in your brokerage account. You would just need to update your initial share count and buy price or you would get an inaccurate gain calculation. Lastly, and always the most tricky are mergers. One of the stocks, First Financial Holdings (FFCH) experienced a merger during the year. SCBT merged with FFCH at the end of July 2013. FFCH shareholder received 0.4237 shares of SCBT for every share held of FFCH. All of this is handled automatically by your brokerage as usual, you just update your tracking portfolio to the ownership in the new company. Now, according to the quant portfolio rules, see here, if prior to the merger FFCH’s share price had come within 95% of the offer price we would have sold the shares and replaced the stock in the portfolio. Well, I totally missed this at the time and just stuck with SCBT in the portfolio.

Now, take a step back and look at the performance of some of the individual names. There are a couple of real dogs. HGG is down 46% over the year. It started out great, going from 16.88 to just over 20 and then cratered. It’s come back a bit, off 27% from the lows, but still not pretty. MX was another early star that has not done well since its initial run. And TA was a dog pretty much from the beginning as well. Of course, we have some real beauties on the other side of the ledger. GPRE lead the way with a 115% gain, followed by ArcBest with a gain of 113%., then GNW with a 61% gain. These three were pretty much straight up since the beginning. Then there are the stocks which pretty much no investor would touch on their own. There was a Greek shipping stock in the portfolio, two Argentinian stocks, and two hard drive companies. Do you remember the headlines surrounding some of these themes last year? Would you have been able to hold these names? Do you think you could have beat the portfolio by stock picking within this portfolio? Maybe, but history says no. Most investors can’t even make the initial investment in such a portfolio.

In short, a very good performance for the trending value portfolio from June of last year. Now on to next year.


The value of financial advice

May 31, 2014

I am a huge believer in do-it yourself investing. I believe that any one can learn to manage their own investments effectively given the time and the inclination. And it has never been easier or cheaper to manage your own investments. But there are many investors who do not have the time, nor the inclination to take on this task on their own. Or for whom the learning curve is too steep too quick. Or, maybe more importantly, need help managing their emotions during trying times. This post is for them. Technology and competition is making it easier and cheaper to get investment help.

Have you ever heard of a robo-advisor? This is the hot thing in the portfolio management world right now. Basically, a computer/robot does the grunt work of investment selection for you. After all, managing a buy and hold portfolio of diversified ETFs is an easy thing to do for computers. The two biggest companies in this space are Betterment and WealthFront. You create an account, answer a series of question to determine your investment personality, then are recommended an allocation with a portfolio of ETFs. And, of course, you don’t pay too much for this. Below is a comparison from a recent post on Mebane Faber’s site.

robo adivsor vs custodian fees may 2014

As the table shows the new robo advisors are really shaking up the landscape. Also, investors pay way too much money to have buy and hold portfolios managed for them. The industry average fee for managed portfolios is 1.32%, according to Vanguard. For buy and hold. On top of the underlying ETF fees. Seriously! Fidelity seems particularly egregious. Buy and hold should be cheap. If you have a great investment advisor who is doing advanced things like tax harvesting, active investing, risk management, etc, great they should be payed more for this added value but not anything more than 0.5% to 1.0% in my opinion. Anything above this and I would go somewhere else.

But there is more value in personal financial advice than just the mechanics of investing. To me the biggest value in financial advice is helping to manage an investor’s emotions. That is most investor’s biggest failing. Its why investors under perform even the mediocre returns of mutual funds. I all has to do with our behavioral biases.  And here is where a good advisor can really pay off. This image depicts the value of a financial advisor better than any words I can write.

Value of a Financial Advisor

**Image by Carl Richards, Buck’s Blog at the NYT. Check out the blog for more simple yet powerful investment messages.

And you know what? A lot of that great investment advice coming from a great advisor will be ‘I recommend we do nothing and stick to our plan’. Yeah, do nothing is often the best investment advice you will receive. So, there is a ton of value in financial advice you just shouldn’t pay a lot for it. Vanguard has really taken the lead here with their 0.3% annual fee. Combined with their industry leading low costs ETFs it makes for a powerful combination. If anything you should use them as a benchmark to the advice you are getting today.

In short, there can be a great deal of value in financial advice. And many investors need it. There is just no reason to pay lot for it.

 


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