Our Tactical Asset Allocation (TAA) model selects up to four assets from a diversified basket of asset classes on the final trading day of each month. Below is the new allocation for today’s close. Click to read more about the TAA model.

I eat my own cooking, so I’ve devoted a healthy share of my own net worth to the TAA model (read why). On the last day of each month I share my new allocation (see above) and real-time performance (see below).

The model underperformed its benchmark in December, returning (as of yesterday’s close) -1.9% vs 1.3%.

The portfolio was dragged down by the abysmal performance of gold in December. Gold and Treasuries are both up nicely today so returns for the full month should end near flat.

For January, the model will add a small position in real estate (ETF VNQ). Normally I would say this is a conservative allocation, but given gold’s recent shenanigans, I think this is a moderate allocation.

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Happy Trading,
ms

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I want to retool the Map, but I’ve been busy the last month or so on other projects.

The large vs small cap map has been performing exceptionally well, but that’s not the one most folks are using.

Most readers are interested in the main long/short map, and while it has outperformed simple buy and hold, I think it has room for improvement.

So look for more on that shortly. In the meantime, no monthly seasonality map will be issued this month.

Happy Trading,
ms

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First the (misleading) numbers…

From this 30,000 foot view, January has solidly outperformed the average month, with almost twice the average and median return (at less volatility).

But averages can be misleading because they say nothing about how consistent an observation has been or whether it’s waxing or waning, so below I’ve assumed a trader was only long the S&P 500 in January (red) versus the average month (grey) each year since 1930.

[logarithmically-scaled, growth of $10,000]

The graph shows that January consistently outperformed the average month over the last 80+ years. But the graph also shows that that outperformance has waned more recently. Note the dip in the equity curve over the last decade or so.

The next graph makes this more clear. Below is the rolling 10-year average excess monthly return in January versus the average month. Positive values indicate January outperformed over that decade, and negative values indicate that it underperformed.

January has not impressed over the last decade.

Like all seasonality plays, this one has by no means been a sure thing and doesn’t by itself justify a trade, but because January bullishness has been on the wane, I’m calling the calendar month bias for January NEUTRAL.

Happy Trading,
ms

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Our Tactical Asset Allocation (TAA) model selects up to four assets from a diversified basket of asset classes on the final trading day of each month. Below is the new allocation for today’s close. Click to read more about the TAA model.

I eat my own cooking, so I’ve devoted a healthy share of my own net worth to the TAA model (read why). On the last day of each month I share my new allocation (see above) and real-time performance (see below).

The model outperformed its benchmark in November, returning (as of yesterday’s close) -1.4% vs -1.6%.

The model was positioned mostly in cash in November, so despite holding the worst performer of all the asset classes I track (real estate) it still managed to eke out a small win over the benchmark. With both gold and real estate rallying today, the model should end the month near flat.

For December the model is dropping that small real estate position in favor of a large (low vol) position in Treasuries. This is an even more defensive allocation than November.

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Happy Trading,
ms

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That post showed that December has historically been bullish for the stock market. Ed asked whether this bullish seasonality was affected by the market’s performance in the preceding 11 months, Jan – Nov (which would make sense given “tax loss selling” and all that jazz).

In short, yes it is. To illustrate…

The table above shows December results when Jan-Nov was either up (left column) or down (right).

From this 30,000 foot view, December returns in years when Jan-Nov was up have been hugely bullish, and when Jan-Nov was down, flat.

How consistent has this observation been?

In the graph below I’ve assumed an investor was long the S&P 500 in December when Jan-Nov had been up (green) or down (red) since 1930.

I’d call that pretty darn consistent.

We’re dealing with a very small number of observations here (so be extra wary that this is all just noise) but the stark contrast between the two is hard to argue with.

By my calculation we stand at about a -3.5% loss YTD, so we’re right on the cusp of the cutoff point. In any case, the important takeaway is that the much touted bullish December seasonality might not be so strong this year.

Note: I’m sure that none of this is new and other folks have blogged about this observation before. But it’s all new to me, so meh. P.S. Thanks Ed!

Happy Trading,
ms

Geek note: returns are dividend-adjusted. Dividends interpolated from quarterly data before 1988. S&P 500 TR index used 1988 and beyond.

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First, the numbers…

December has significantly outpaced the average month over the last 80+ years across all metrics, particularly the one I think matters most: average return / std. dev. of returns. From this 30,000 foot view, December has been far and away the most bullish month of the year.

But averages can be misleading because they say nothing about how consistent an observation has been or whether it’s waxing or waning, so below I’ve assumed a trader was only long the S&P 500 in December (red) versus the average month (grey) each year since 1930.

The graph appears to show December consistently outperforming the average month since (at least) 1930. To confirm, below I’ve shown the rolling 10-year average excess return in December versus the average month.

Note mostly consistent outperformance since at least 1930.

Like all seasonality plays this one has by no means been a sure thing and doesn’t by itself justify a trade, but I’m calling the calendar month bias for December as BULLISH.

See the monthly seasonality map for daily seasonality predictions in December.

Happy Trading,
ms

Geek note: returns are dividend-adjusted. Dividends interpolated from quarterly data before 1988. S&P 500 TR index used 1988 and beyond.

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Our Tactical Asset Allocation (TAA) model selects up to four assets from a diversified basket of asset classes on the final trading day of each month. Below is the new allocation for today’s close. Click to read more about the TAA model.

I eat my own cooking, so I’ve devoted a healthy share of my own net worth to the TAA model (read why). On the last day of each month I share my new allocation (see above) and real-time performance (see below).

The model underperformed its benchmark in October, returning (as of yesterday’s close) +0.2% vs +5.5%.

The model was positioned very defensively in October. Given how epicly equity-related asset classes rallied for the month, eking out any gain was fortunate. With Treasuries up today, the portfolio should end the month with a respectable gain.

For the upcoming month the model is dropping the large Treasuries position in favor of a small position in real estate (16%) and a large cash position (59%). This is, like last month, a very defensive allocation.

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Note that last month I began including the Permanent Portfolio mutual fund PRPFX as an alternative benchmark (see below). Click to read more about PRPFX.

PRPFX has performed well over the last decade (and poorly prior to that) as a result of its large allocation to defensive assets like gold and Treasuries and relatively small allocation to risk assets like equities.

My $0.02 is that PRPFX is a very good portfolio built for a very specific type of market (namely one with a high degree of uncertainty like we’re in now) but that given enough time, TAA wins the day. 

Risk comes in and out of favor and PRPFX doesn’t have the ability to adjust to that (which is why performance was so poor in the 1990′s). But for now, in this specific market, PRPFX is a tough benchmark to beat.

Happy Trading,
ms

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Below is a map of potentially strong/weak days for the US stock market in November based on historical seasonality patterns. Read more after the image.

Scorecard: since launching in April 2010, the monthly seasonality map has called the closing direction of the S&P 500 correct 49% of the time with winning predictions 1.2x losing ones (outperforming 55%/0.9x for buy & hold).

The large vs small cap map (see below) has, since launching in January 2011, called large caps relative to small caps correctly 57% of the time with winning predictions 1.1x losing ones (outperforming either neutral pair).

Click for a more detailed look at the real-time performance of the Map.

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About the Monthly Seasonality Map

One of the unexpected side effects of keeping this blog is I’ve become a proponent of seasonality (i.e. bullish/bearish biases around certain times of the month, year, etc). The Map forces me to tie my seasonality studies together every month.

The studies included are: (a) the turn of the month, (b) the first and last day of the month, (c) the day-after options expiration, (d) the monthly W, (e) individual holidays, (f) scheduled Fed meetings, and (g) strong/weak calendar months.

To be clear, I do NOT think that seasonality alone is sufficient to justify a trade; however, all of the seasonality plays included in this report have been consistent enough that I do think they should be one of many tools in the trader’s toolbox.

Some observations have been stronger than others, so I’ve rated each from -100% (most bearish) to +100% (most bullish). Very low ratings (+/- 25%) indicate the play has been inconsistent and should be viewed with an extra skeptical eye.

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Large vs Small-Cap Seasonality Map

This year I’ve also begun issuing a monthly large vs small-cap seasonality map (click to zoom). Positive (negative) values indicate large cap (small cap) relative strength.

Note that these seasonality biases only exist after adjusting for differences in volatility between large caps and small caps (AKA “market neutral” or “beta neutral”) so they are only relevant to either (a) pairs trading, or (b) choosing between large and small caps after an investor already had a view on the market as a whole (read more).

The large vs small-cap studies included on this map are: calendar month, intra-month, intra-week and individual holiday seasonality.

Happy Trading,
ms

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First, the (misleading) numbers…

From this 30,000 foot view, gold has been uber strong in November, returning more than twice the average month’s return over the last 35 years.

But averages can be misleading because they say nothing about how consistent an observation has been or whether it’s waxing or waning, so below I’ve assumed a trader was only long gold in November (red) versus the average month (grey) each year since 1976.

[logarithmically-scaled, growth of $10,000]

Note that gold’s “outperformance” is really the result of 8 fortuitous years beginning in 2003. Eight years do not an observation make, and I have to assume the outperformance we saw in the numbers was simply noise.

Like all seasonality plays this one has by no means been a sure thing and doesn’t by itself justify a trade, but I’m calling the calendar month bias for gold in November as NEUTRAL.

Happy Trading,
ms

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This has been a rough month for our aggressive long/short YK strategy. Worse though is the fact that it comes after an extended period of uninspiring performance.

I think that YK will have more days in the sun, but I don’t feel comfortable directing new subscribers and managed accounts to the strategy until it’s able to demonstrate its ability to perform again.

What this means:

Starting at the end of this month, we’ll no longer carry YK as an active strategy at MarketSci.com.

I pride myself on our transparency, so like all of our retired strategies we’ll continue to report YK’s performance (ending EOM) on our website indefinitely.

I intend to continue allocating a portion of my own personal funds to YK. When the program gets back on its feet, I’ll roll it out to investors again (excluding this retired period so as not to be guilty of cherry-picking results).

So what’s next for MarketSci?

As mentioned before, volatility ETFs have begun to consume my own personal aggressive trading.

I plan to begin providing verifiable trading results next month at MarketSci.com and begin talking more about trading these products here at the blog.

I don’t plan to offer this strategy via subscription or managed account anytime soon, but I could see doing so in the distant future.

Until then, I’m perfectly happy with this blog just being a repository for my geeky ramblings.

Happy Trading,
ms

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