Category Archives: Performance Tracking

2017 Review

Now that 2017 is in the books it’s time to have a more in-depth review of our investment activities. With more monthly returns available, we can also make more meaningful comparisons to the benchmarks. Accurate return analysis is a critical part of self-evaluation: if we were better of putting our money in index funds then we would need to face up to that fact.

Let’s start with our overall FI progress. I track our total invested (total portfolio reported here + 529s + a small pension) in the table below. The values are shown as a multiple of X: our projected future annual retirement spend. There is some slack in X, such that I consider 20X financial security: a softer form of financial independence where we can sustain a bare-bones standard of living indefinitely. My goal of reaching financial security by the end of 2017 was reached two month earlier. In fact, we reached 22X before 2017 ran out. The next milestone is 25X and mortgage-free which is the canonical definition of financial independence. Assuming the mortgage is still around -4X, it implies a total invested value of 29X or about a 30% gain plus additional contributions from here. My (somewhat dated) stretch goal for reaching FI was EOY 2019. If the market cooperates, we may reach this goal by mid 2019 or even the end of 2018.

The table below describes the increase in the total invested amount in the last two years. My compensation from work was leaner than usual in 2017 hence the reduced contribution vs. 2016. In addition, I exited the majority of my cryptocurrency positions in December, incurring tax liability which was deducted from the contribution amount. Nonetheless, the investment gain of 5.07X more than made up for the lack of contributions. For reference, the gain outstrips my W2 income even in a good year. The return rate of 30.01% was calculated using the Simple Dietz formula applied to the year as a whole: return = (End Value – Start Value – Contributions)/(Start Value + Contributions/2). It assumes all contributions are made at the middle of the year which is a decent enough approximation: I tend to make Roth and 529 contributions early in the year, the bonus and RSUs hit late in the year, and 401K/HSA contributions are made evenly throughout.

Of the dollar amount gained from investments, cryptocurrencies contributed the most, about 1.4X, followed by 0.9X from options. Other sources of outperformance were individual stocks and closed-end funds. Precious metals related positions were a net detractor. In 2018, I expect the majority of the speculative gains to be from options.

Counting back to blog inception there are 17 monthly return data points (see the December update). The first figure below plots the monthly returns for my passive, active accounts, the total portfolio, $SPY and the 60/40 portfolio; while the second figure shows the normalized cumulative value. Immediately after blog inception, losses in both PMs and the muni CEFs put my accounts “in the hole”. They clawed back slowly, and started accelerating in June’17 when I started building up leverage through options. Currently both active accounts and total portfolio are above their benchmarks (total portfolio vs. 60/40, active accounts vs. 80) by a significant amount. The results of the portfolio shuffle at the start of 2017 where I revamped both the individual stocks and the CEFs were not as visible on these charts but were present, e.g. the individual stocks were about +3.7% vs. SPY since April.

The final two figures compare my monthly returns vs. the benchmarks in the same way that CAPM extracts the alpha/beta parameters. We can make some qualitative statements based on these figures: the slopes are positive indicating broadly positive correlation to stocks, the slope is greater than 1 for active and less than 1 for passive indicating respective risk orientation, the low R^2 indicating lack of correlation/presence of other return drivers, etc.

Lastly I want to comment on risk and volatility. Cryptos were a huge return driver but also highly volatile, with a daily STD around 5%. My rule of thumb was to limit monthly exposure to 2% or a 5% allocation assuming they can lose up to 40% in a month. This allocation was briefly exceeded in December before I exited 90% of the position. I may engage in more short term trading in 2018 but do not expect crypto to be as big a return driver or contributor to volatility. My equity exposure has hovered between 110% to 130% in the last couple of months, around half provided by options where the leverage ratio was up to 40 at times. In 2017 the Sharpe ratio of my total portfolio almost exactly equals that of $SPY, although much of the volatility for my portfolio was from the large gains in Q4. 2017 was a historically low volatility year. In general, I’m comfortable with an annual STD around 10% but in the end it’s all about realized returns. My main risk control method is market timing, and I expect hedging based on my equity pricing model to kick in around the middle of 2018.

17 months is still a very short amount of time to draw any conclusions about my portfolio management skills. Professional fund assessment usually needs at least 3 years of data. However, the returns so far has been encouraging and the out-performance more than justified the amount of time I put into active management. I can’t promise this level of performance will continue but I can promise to keep tracking them as I have been.

Performance Tracking December 2017

This is a quick review for December. A more in depth review for 2017 will follow.

For calculation methodology see this post.

$SPY gained a very respectable 1.21% and the 60/40 benchmark 0.90%. My total portfolio and active accounts had a third consecutive record month, gaining 5.56% and 8.83% respectively. For the whole year, $SPY gained 21.71% and the 60/40 14.13%, dividends included. My passive, active and total portfolio gained 13.59%, 46.75% and 30.94%, respectively. I’m more than pleased with the performance — the extra returns were greater than my W2 income for the year and more than justified the hours spent actively managing and trading.

The passive account without PM returned 14.33%, slightly above that of the 60/40, indicative of both the extent of the PM under-performance and the out-performance from slicing-and-dicing: in this case from international and emerging markets in 2017. Passive without PM had outstanding risk-adjusted metrics, due to a combination of lower equity percentage and the lack of correlation between US and international equities.

I was thrilled with the performance from my active accounts. Of the 46.75% annual gain, cryptocurrencies provided about 18%, with another 11% from various options positions, leaving the combination of individual stocks and CEFs about 3.5% over that of 60/40. I have exited 90% of my cryptocurrency positions by the end of 2017. In 2018, I expect the options positions to generate the bulk of the speculative profits. The standard deviation was over 9%, in-line with historical stock market averages but doubled that of $SPY which had a record low-volatility year. Granted much of the volatility was from the enormously positive Q4, indeed, YTD Sortino ratio is undefined since returns were positive for each month.

Transactions: added $CEF (Central Fund of Canada) which is a CEF (closed end fund) to my passive account. $CEF holds gold/silver bullions and is treated as a PFIC for tax purposes. It was purchased in my Roth IRA account to sidestep the annual QEF election issue. I also added to $GDX and $NAC this month. Annual re-balance started in the last few days of 2017 and is expected to be completed in mid January along with backdoor Roth and 529 contributions for 2018.

End of Month Portfolio Composition

PMs were at 11%, equities 54.6%, fixed income 24%, cash 7% and other 3.5%. The “Other” category was composed of cryptos 0.8%, 3X ETF 0.4%, and (market value of) options 2.3%. Exposure from options equaled 63.2% of the total portfolio, or a leverage ratio of 28X. Total portfolio equity exposure was at 118%.


AllocateSmartly tracks over 40 different tactical asset allocation strategies. The top December return was 1.78% and the top annual return was 26.67%, both below my total portfolio at 5.56% and 30.94%, respectively. With the exit of the majority of the cryptocurrency positions I anticipate reduced volatility to a certain extent — the PM and options positions will still provide plenty of juice.

Performance Tracking November 2017

For calculation methodology see this post.

November was an even better month than October which was a mild surprise to me. I had expected a small pull back but the market roared back with $SPY gaining 3.06% and the 60/40 1.77%. My portfolio had been outperforming significantly but gave back ground in the last couple of days when the FANG’s retreated. Still the total portfolio and the active accounts gained 4.08% and 6.29% respectively. Both were new records 2nd month in a row. The YTD returns have further distanced from that of $SPY, while the active accounts have overtaken $SPY since blog inception.

Breaking down individual components: cryptos again were the star of the month contributing about 1.6% as BTC climbed over the $10k mark; options delivered another 1.1% or so; the individual stocks lagged SPY, 2.9% vs. 3.06%, due to the large cap tech stocks; fixed income CEFs faced some difficulty, however adding at the bottom and partial recovery resulted in a positive month, 0.05% vs. -0.15% for $AGG. PMs continue to be lack luster which I now expect to deteriorate into the end of January.

Transactions that haven’t been covered in weekly wraps include closing the tiny $SOGO position received in its IPO, and closing Gilead to add to $JNJ. The latter was really about reducing the total number of individual stocks, which currently stands at 26, and having a larger position in each.

End of Month Portfolio Composition

PMs were at 9.5%, equities 56.1%, fixed income 22.7%, cash 5% and other 6.6%. The “Other” category was composed of cryptos 3.9%, 3X ETF 0.4%, and (market value of) options 2.3%. Exposure from options equaled 66% of the total portfolio, or a leverage ratio of 28X. Lower leverage ratio was a result of gains in $QQQ and closing $GILD positions. Total portfolio equity exposure was at 122%.


AllocateSmartly tracks over 40 different tactical asset allocation strategies. In November my total return of 4.08% would have trounced the pack whose highest return was 3.06%, matching that of $SPY. YTD the first and second ranked strategies are at 24.72% and 20.25% respectively, vs. 24.05% and 34.84% for my total portfolio and active accounts. My portfolio remains leveraged long equities and I expect the out-performance to continue as long as this bull market lasts.

Performance Tracking October 2017

For calculation methodology see this post.

Contrary to many top-callers, October was once again a great month for stocks, in fact it was the second best this year after February. $SPY picked up 2.36% for the month. Bond yields shot up after John Taylor was rumored to be Trump’s pick for the next Fed Chair. Both the rumor and yields settled down, leaving $AGG 0.1% higher for the month, and the 60/40 up a more than respectable 1.45%. Great as those numbers were, my portfolio performed even better. The total portfolio and the active accounts gained 3.8% and 6.04% respectively. Both were a record since blog inception.

Breaking down individual components: PMs were a drag for about a quarter of a point for the month in passive accounts. YTD passive w/o PMs returned 11.65% vs. 11.18% with PMs at much higher volatility. The absolute return was on part with 60/40 at 11.14%. Individual stocks gained 3.56% vs. 2.36% for $SPY, thanks predominantly to tech. CEFs had a down month. The taxable multi-strategy CEFs are recovering from the hit piece on SeekingAlpha while their NAVs continue to mover higher. The loss in muni CEFs had a more rational basis but I believe the distribution is safe and I’m ready to buy more if valuation becomes more attractive. Cryptos were a big contributor as bitcoin roared above $6400, but the real heroes were the options which were responsible for half of the gains.

End of Month Portfolio Composition

PMs were at 10.1%, equities 57.8%, fixed income 23%, cash 4.3% and other 4.9%. The “Other” category was composed of cryptos 2.6%, 3X ETF 0.8%, and (market value of) options 1.5%. Option delta times the underlying gave an equivalent value equal to 60% of the total portfolio, or a leverage ratio of 40X. Note that as I moved up the strike of the short put leg, the market value was reduced and the leverage ratio increased.

Potential Transactions before Year-End

Purchase gold bullion coins, TLH individual stocks, add to CEFs, and continue to manage option positions.


AllocateSmartly tracks over 40 different tactical asset allocation strategies. In October my total return of 3.8% would have led the pack whose highest return was 3.3%. YTD the first and second ranked strategies are at 23.42% and 16.86% respectively, vs. 19.18% and 26.85% for my total portfolio and active accounts. While my portfolio is currently at 120% long equities, knowing when to use leverage is part of art of the portfolio management. I expect to open up further distance with these strategies as well as the benchmark for the rest of this year.

Performance Tracking September 2017

For calculation methodology see this post.

Stocks had a very strong September with the SPY gaining 2.02%. Yields rose and the TBM declined -0.57% for the month, leaving the classic 60/40 portfolio still up a very respectable 0.98%. In contrast my total portfolio gained only 0.82% in September, the passive and active strategies returning 0.55% and 1.06% respectively.

Contrary to August when cryptos and PMs provided extra boost, in September they were laggards. Cryptos were responsible for a -0.8% decline. Approximately the same decline was due to PMs; however hedging (with 3X ETFs) mitigated the loss by 0.1%. I find it interesting that losses from cryptos and PM were evenly matched although that was the intent behind sizing the positions inverse to their daily volatilities, assuming all correlations were zero. I’m still amazed that it worked so well. The amount of decline gave a clue as to the maximum allocation I would give to cryptos from a monthly draw-down perspective: no more than 5-6%. At their lowest point this month the decline was about -1.2% overall from an end-of-August weight of just shy of 3%.

Other parts of the portfolio continue to perform well. The individual stocks had a banner month (+3.41%) and have returned more than 2% over that of SPY since April. The CEFs continue to deliver strong performance, up another 1.78% vs. a down month for AGG, my trimming down $PCQ this week notwithstanding. The option positions are starting to deliver as indices break out. The fact that cryptos and PMs were a drag this month is evidence that they’re serving as a portfolio diversifier as intended. For the remainder of the year, I expect cryptos to fully recover, and gold to bottom in late October before recovering, but the main performance driver will still be derived from equities.

AllocateSmartly tracks 40 different tactical asset allocation strategies. In September my total return of 0.82% would place it 14th; and the active account return of 1.06% 8th. YTD the first and second ranked strategies there have returned 19.91% and 14.44% vs. 14.82% for my total portfolio and 19.63% for my active accounts. I pay a lot of attention to the performance of my active accounts as that’s where I’ve devoted most of my energy but in the end the total portfolio is what will pay the bills. YTD it has delivered more than SPY at a standard deviation just above that of 60/40. It has also more or less caught up with 60/40 in total return from last August.