Category Archives: Dividend Growth Investing

Performance Tracking January 2017

For calculation methodology see earlier post

2017 started with a bang — precious metals performed well even though it was looking to retest the 2015 lows at the end of last year. Since PMs are the main drivers in the “tracking error” (I hate that term!), my portfolio did well relative to the overall market. The S&P also had a good month, gaining 1.79% while the bonds gained 0.21%, meaning the benchmark 60/40 portfolio picked up 1.16% for the month.

Passive Portfolio

The total passive portfolio gained 2.11%, the portion outside of the 15% allocation to PMs gained 1.34%. In this post, I outlined my plan to increase the equity allocation by 5%. I’m about half way done. Funds has already come out of TBM but has not been added to equities just yet. The market has been directionless for a long time. Since the model has a low in February and I know it can’t be timed perfectly, I have already started to transfer funds slowly. I can only access the emerging market index fund, VEMAX, in a Roth IRA at Vanguard and the space is limited. Hence I had to dial down its allocation by 1% and shift to VTIAX. The allocation for the rest of 2017 looks like this:

Active Portfolio

The overall active portfolio gained 2.37% despite the drag from DGI whose main culprits were victims of presidential tweets and Target. Large changes are being made in FI: reducing muni CEFs in taxable and adding to taxable CEFs in taxed advantaged. I’m using this opportunity to cull back certain dividend stocks.

Plan and Forecast

Transition to my AA is straight forward and should be completed by the end of February. In the active portfolio, the goal is to maximize tax advantaged space for taxable CEFs. Consequently, dividend stocks will all end up in taxable. Tax considerations alone forces me to favor stocks with high dividend growth over high current payout. Currently, the blended payout ratio for my DGI stocks is 2.74% vs. 2.03% for SPY and 2.93% for VXUS. I expect this ratio to come down further. I’ve also started positions in MKL, aka “the baby Berkshire”. It doesn’t pay any dividends so doesn’t count towards DGI. I’m taking my time to buy the taxable CEFs as they have all been on a good run — patience is definitely a virtue. This process may continue well into March or April.

Portfolio Changes 2017

A new year is always a time for reflection and planning for the future. This is especially true for one’s investments. My investment policy statement (IPS) allows for a once-a-year plan review and gradual changes in my passive allocation. Those changes don’t have to be implemented right away and can subject to a range of dates or pre-conditions. The important thing is to keep a record of them and hold myself accountable.

2016 Results

I was quite happy with the portfolio level gains in 2016: 10.87%. It was calculated with the Simple Dietz method which meant contributions were properly accounted for. One of my pet peeves for many personal finance blogs is the co-mingling of contributions and investment returns. Another widely used formula is (end value – start value – contributions)/start value. It’s generally fine except when the contribution is large. The simple Dietz method adds half of the contribution to the denominator to approximate the time-weighted return. The 10.87% figure was calculated on an annual basis, more accurate would be to chain link monthly figures. Unfortunately the official record for this blog was only started in August. I’ll have much more data to work with in the future.

AllocateStartly had a summary of various allocation strategies for 2016. The Golden Butterfly portfolio which I drew inspirations from was the top dog at 10.79%, while the benchmark 60/40 portfolio returned 7.71%. So it doesn’t seem I have much to complain about. Though in all fairness I took on more risk — I have silver/miners in my PM sector, my equities are higher and cash position lower. Conversely, the equity slice-and-dice to include international hurt my returns. The timing of the start of this blog was unfortunate as July was the high watermark in terms of percentage gains. I gave back more than 3 points in the 2nd half of the year while the S&P was going gang-busters, so the results from August look rather poor. I’m an unabashed market timer, so that’s definitely something to improve on.

A New X

I have no plans to disclose actual dollar amounts — I hope it doesn’t detract from the ideas discussed here. At times I have spoken about the portfolio value in terms of X, where X is my non-inflation-adjusted, no-mortgage, target annual pre-tax retirement income. More recently, after some thought about desired life-style and future medical expenses, I’ve decided to increase X by about 10%. I don’t foresee any further changes to this figure.

Current investible assets stand at 17X after a contribution of 1.3X and a gain of 1.6X in 2016. I define “financial independence” as 25X plus a paid-for primary residence. There is still 4.5X left on the mortgage. Being naturally conservative I’ll probably keep working until reaching 30-35X. This amount will also include any future financial support for my daughters. There’s definitely some margin of safety in X, such that I call investible assets at 20X “financial independence lite” even without paying off the mortgage. It’s tantalizingly close, with luck may even be reached in 2017.

Passive Allocation

My guiding assumptions for the next couple of years are based on an equity pricing model I have been following. So the plan is to increase the equity allocation slightly after a drop in the market in the first quarter.

I’ll maintain the 50/50 split between US and international and increase the overall equity allocation by 5% which comes out of TBM. No changes in PMs.

Active Portfolio

The active and overall portfolios don’t follow a set allocation, although I do check it for risk management purposes. The overall equity allocation may grow to 55% by the end of 2017 from 50%. I expect the DGI portfolio that is heavy in consumer staples to under perform the broader market but don’t plan to make any major changes. Additions to the DGI will likely be old tech (MSFT, QCOM, CSCO), or a high-growth, low payout name like V. I plan to add more to growth stocks, currently at 7% of the active portfolio, and bring it up to 10%.

Option writing was a reasonably successful endeavor last year but my activity tapered off as job responsibilities increased. It’s still something I plan to continue this year, although I don’t have a target in mind. It is reassuring to know that if I ever lose my job I can generate some income this way. I do plan to use more synthetic equities (buy call, sell put) as a means to increase leverage. More details will follow when I open such positions.

DGI Portfolio Sept 2016

The dividend growth investing (DGI) portfolio is the largest component of my active portfolio. DGI is considered an active strategy where the active part comes from stock selection rather than short term trading. As a matter of fact the intended holding period is normally very long, or even for everem> as Warren Buffet is known to prefer. I believe DGI offers the individual investor the best odds for achieving superior returns – both absolute and risk-adjusted, benchmarked to an investible index ETF such as SPY, although there may be some foreign stocks worthy of consideration. A statement like that needs to be justified of course, and “best odds” is by no means a guarantee. In this post I’ll describe why I believe DGI has this potential and the way I choose to practice it. Not everyone can copy what I do, two of the largest roadblocks being position size and skill/willingness to use options to enhance returns.



Diversification is necessary to remove idiosyncratic single stock risk so that at the portfolio level only (mostly) market risk remain. This paper does a good job explaining the research despite the unfortunate title. I care more about the standard deviation (SD) than the variance (as indicated by r-squared). SD speaks to the portfolio value whose downside volatility I want to minimize. I don’t care to have a portfolio with a high r-squared fit to the market because that will also remove extra sources of return (see discussion on factors below). At any rate, it takes only dozens not hundreds of stocks to reap the vast majority of the benefits of diversification. Note also the dates cited in the article were from the end of 1990’s. If anything, the correlation between stocks have increased due to the growing popularity of indexing. In a “perfectly efficient” market – which will probably never materialize – every stock will have the same risk-adjusted, expected return (source). In a market where all participant are indexers – which is even less likely to materialize – every stock will move in synchrony and provide identical returns. Both gedankenexperiments point to less number of stocks needed to approximate the diversification of the entire market as efficiency increases.

My own DGI portfolio is a work in progress. It contains about 30 stocks right now with an eventual goal somewhere around 50 stocks. The chart below shows the current sector weighting vs. S&P 500 market weighting that is more of a guide than a target. There is a concentration in consumer staples which are the classic stable, unglamorous, capital un-intensive compounding machines. The S&P site doesn’t yet include the newly independent REIT sector. It’s not an issue as I don’t have any REITs anyway (I have them in my passive portfolio). The portfolio yield is 3%, respectably above the 2% yield for SPY but not outrageously high. Indeed current emphasis is on the “growth” part of DGI and I consciously avoid the classic dividend stocks with high yield and low growth such as telecoms. I also make a point to put the high growth, low yield stocks like Disney ($DIS) and Nike ($NKE) in taxable and high yield stocks in tax-advantaged.


Dividends and Share Buybacks

The much venerated Economist magazine recently ran a series called “Six big ideas”, the first of which was information asymmetry and signaling. My very rough summary goes like this: there is information asymmetry in markets such as in used cars where the seller knows the true condition of the car but the buyer doesn’t; or the job market where the applicant knows his true abilities but the potential employer doesn’t. The solution is for the seller to provide an additional “signal” to the buyer as an indication of quality. In this perspective, job applicants use their degrees as “signals” of their dedication and talent, which is contrary to what education is normally thought of: a means to benefit society to make workers more productive. OK fine, I recall saying to myself as I was reading this, until I came to this “Aha” moment:

Signalling explains all kinds of behaviour. Firms pay dividends to their shareholders, who must pay income tax on the payouts. Surely it would be better if they retained their earnings, boosting their share prices, and thus delivering their shareholders lightly taxed capital gains? Signalling solves the mystery: paying a dividend is a sign of strength, showing that a firm feels no need to hoard cash.

There is plenty of evidence that an above average dividend yield (better yet a dividend grower, but not too high a yield which could indicate a recent stock price crash or an unsustainable dividend) correlates with above average returns.







Rather than a choice of either “total return” or DGI as some would have you believe, above evidence suggests DGI is a path to superior total returns. Now I understand that some may have a preference for share buybacks over dividends. The former does have advantages for taxable holdings. That’s why I prefer companies that do both. Share buybacks tend to be more volatile and will be cut first in tough times as companies defend dividends. To be more effective, share buybacks need to be counter-cyclical, tough to do but a sure sign of a management with capital allocation chops. Together dividends and buybacks make up shareholder yield which is a terrific indicator for the quality of a business. One of the main gripes I have about index funds is that I want to own more of the companies with high shareholder yield but the index fund takes that shareholder yield and distribute among the whole universe of companies. By owning the stocks directly, I don’t need to do anything in the case of buybacks; with dividends, DRIP, or let the dividends accumulate to buy another dividend paying stock are both possible. The latter is my preference since I want to have control over entry points and keep stocks in round lots.

Equal Weight and Inactivity

Supposedly a popular (long only?) hedge fund construction is the “50/50”: 50 stocks with 50% in the top 10. I don’t have the time to do the research to have that level of conviction so my default construction is equal weight as much as my desire for keeping round lots would allow. It is well known the equal weight S&P500 ($RSP) outperforms the cap-weighted $SPY, 10.88% vs. 8.75% annualized since May’03, despite higher expense ratio and turnover: 0.4%, 22% turnover vs. 0.09%, 2.77% turnover. Factor analysis (PortfolioVisulizer) shows $RSP having a market factor of 1.09, both size and value factors of 0.12, and a statistically insignificant alpha of 0.4%. Proponents of fundamental indexing would argued that anything but cap-weight avoids overweighting the recently-up-a-lot stuff.

On the impact of trading activity or lack thereof on performance, one stunning example of LONG TERM holding is the Voya Corporate Leaders trust fund (LEXCX, hat tip: Sure Dividend), a fund that started in 1935 with 30 blue chip stocks at equal number of shares (not exactly equal weight nor cap weight). It didn’t buy new stocks since inception and holdings only changed due to spin-offs or mergers. The result speaks for itself:


Source: Voya Investment Management

45 years (the data for the first 40 years is not available), no new purchases, the original 30 stocks turned into 22 and it handily beat both the Dow and S&P. In addition, a preponderance of academic studies suggest trading activity negatively affect mutual fund returns, mostly due the impact of trading cost (commission and slippage). My main take away is: weight quality stocks more or less equal (for sure not cap weight) and hold’em for a long, long time.

Factor Exposure

The MSCI paper Foundations of Factor Investing is a good intro to the topic. It defines a factor as “any characteristic relating a group of securities that is important in explaining their returns and risk”. Further, “the market can be viewed as the first and most important equity factor”. The paper went on to highlight value, size, momentum, low vol, yield and quality as the most important factors among the 300 or so that have been identified. Factors are important because they are sources of additional returns above that of the market. For some factors, such as value and size, the additional returns come with higher volatility so it can be argued that there is no advantage in risk-adjusted returns. But the low vol factor is certainly a slap in the face for CAMP. Academics refer to the factors that don’t fit their cherished theory as “behavioral” or “mis-pricing”. Also note that momentum which is one of the most robust and pervasive factors is totally contrary to the teachings of EMH. Still, you’ll see plenty of people in chat rooms who continue to regard CAMP and EMH the cutting-edge of portfolio theory. They are almost as bad as the academics who at first insisted it impossible to beat the market, then having found the factors, and then factors they had to call “behavioral” or “mis-pricing”, now use multi-factor analysis to RETROACTIVELY deny the existence of skill.

So much for the rant, the real point I’m trying to make is the typical DGI portfolio is likely positively loaded with value, dividend, quality and low vol factors; and slightly negative on size. If we take the new Nifty Fifty as representative of a DGI portfolio and compare them with the top stocks in $USMV, you’ll see plenty of overlap. Recent popularity of low vol and yield strategies probably means some future returns have been pulled forward, but to me it’s a confirmation of their long run advantage over the market.


Source: MorningStar

Option Writing

One reason I keep stocks in round lots is to be able to write options for income generation. I keep things basic: sell covered calls or cash/margin secured puts on stocks I’d like to own. Expirations are typically 3-6 weeks out when time decay is the greatest. My goal is to have the options expire worthless so I normally stay with Delta <0.2. The low commissions at IB ($0.7 per contract, no base fee) make it worthwhile even with a couple contracts at around 1% premium. Further more, I use technical analysis to select entry points: sell calls when upside momentum is nearly exhausted or puts conversely. Being selective limits the number of trades I’m in at any given time. So far that hasn’t been an issue as I’m targeting only a couple percent of additional gains annually unlike some aggressive premium sellers targeting 20% per year. Compounded over years though I expect this to be a significant source of alpha. It’s very reassuring to know that I can generate a steady income from the portfolio when planning for early retirement. For monthly reporting purposes, gains from option trades are not included in the returns for DGI.

In summary, each of the above considerations has potential to enhance returns with varying probability of delivering. I’m under no illusion that any level of performance is guaranteed but I’m also content in having maximized my chances. Time will tell what return I’ll get in the end. By then it would be too late to change course – such is the investor’s condition.