1/29/2015 Sector Change

The Sector Model sold XLI and bought XLF.

1/27/2015 Sector Change

The Sector Model sold XLF and bought XLI.

1/23/2015 Sector Change

Sector Model sold XLI and bought XLF.

1/23/2015 Intraday Trade

The Full Model sold MRVL and bought AGCO with a better than 2% favorable intraday gap.

1/22/2015 Sector Change

Sold XLF; bought XLI.

1/21/2015 Sector Change

Sold XLI and bought XLF.

1/20/2015 Two Trades

Full model sold BBRY and bought GNW.

Sector model sold XLB and bought XLI.

1/18/2015 Two possible trades

Sector Model	XLF	1.21%
Large Portfolio	Date	Return	Days
ESI	8/4/2014	-40.18%	167
EDU	10/27/2014	-8.23%	83
UVV	12/2/2014	1.05%	47
JOY	12/8/2014	-17.89%	41
MRVL	12/10/2014	5.36%	39
RS	12/11/2014	-13.07%	38
BBRY	12/24/2014	-5.19%	25
MWW	12/29/2014	-7.94%	20
JNPR	1/5/2015	-3.65%	13
COG	1/12/2015	-3.36%	6
(Since 5/31/2011)
S&P	Annualized	11.82%
Sector Model	Annualized	23.97%
Large Portfolio	Annualized	19.40%

 

Rotation: selling BBRY; buying GNW.

Also, a reset of the Sector Model shows an edge on XLF over XLB, and so I will trade to XLF if there is a favorable gap in the morning.

All of this depends in part whether I’m able to even get out of bed in the morning.  I have the flu.

Tim

 

1/11/2015 Corrected Trade

CORRECTION:

On Monday the trade pair is to sell PLT and buy COG.

As always, a negative gap would prevent the trade.

1/10/2015 More Yearly Return Metrics

Sector Model	XLB	-0.92%
Large Portfolio	Date	Return	Days
ESI	8/4/2014	-36.34%	159
EDU	10/27/2014	-6.13%	75
PLT	11/6/2014	-0.98%	65
UVV	12/2/2014	0.54%	39
JOY	12/8/2014	-13.99%	33
MRVL	12/10/2014	8.68%	31
RS	12/11/2014	-6.73%	30
BBRY	12/24/2014	-3.89%	17
MWW	12/29/2014	1.93%	12
JNPR	1/5/2015	2.67%	5
(Since 5/31/2011)
S&P	Annualized	12.29%
Sector Model	Annualized	24.66%
Large Portfolio	Annualized	20.85%
S&P	Total	52.01%
Sector Model	Total	121.77%
Large Portfolio	Total	98.28%
Sector Model	Advantage	12.37%
Large Portfolio	Advantage	8.57%
	Previous	2015
S&P	53.06%	-0.68%
Sector Model	122.60%	-0.37%
Large Portfolio	101.13%	-1.42%

 

Rotation: selling BBRY (corrected on 1/11/2015) PLT; buying COG.

A careful reader noted that I had not included the rate of return for the Full Model last year.

I had a computer crash over the summer that eliminated some of my background data, but this is what I could reconstruct from the previous blog posts.

I’ve taken the annualized rates of return for the Full Model, the Sector Model, and the S&P for the posts on 1/1/2013, 1/5/2014, and 1/1/2015 to reproduce the total return from 5/31/2011 (when the models went live) on those dates.  Next, I reconstructed the return for the year from each date to the next.  Since one of the dates is 1/5/2014 instead of 1/1/2014, the returns will be off by a small amount.  But this is the best I could do from the blog itself:

From 5/31/2011
		Full	Sector	S&P
1/1/2015	Annualized	21.50%	24.97%	12.59%
1/5/2014	Annualized	28.75%	22.65%	12.61%
1/1/2013	Annualized	27.20%	16.22%	3.75%
1/1/2015	Total Return	101.17%	122.57%	53.06%
1/5/2014	Total Return	92.95%	70.07%	36.19%
1/1/2013	Total Return	46.62%	27.01%	6.03%
2014	Year Return	4.26%	30.87%	12.38%
2013	Year Return	31.60%	33.90%	28.45%

 

I’ll dig through my files in the next week or so to see if I can reconstruct 2012 as well.

The Full Model had a bad 2014, tied to an error in my Fundamental Correlation Matrix that I’ve since corrected.  It should catch back up to the Sector Model in 2015.

Also, Steve Cohen’s STAR fund at Folio Institutional returned 29% in 2014, which was an accurate track of the Sector Model.  A good start to our little fund.

To this I’ve added on the Full Model report the metrics that I keep on file.  The additional lines are not usually reported, because they don’t add value on a week by week basis, but I’ll include them in the future at least once a quarter.  On 12/31/2014 I took a snapshot of the total returns, which are used to calculate year to date returns.  Currently those are all down for the year.

The market pundits are screaming about bear markets and such, but I don’t time.  Even if I were 100% convinced of a bear market I would not time.  There is a reason behind that strategy, best elaborated in Taleb’s book Antifragile. The book is a sheer delight and covers an important topic about constructing systems that gain from disorder.

My own model isn’t quite “antifragile” in respect to the dollar, but its defensive nature makes it robust enough to appear antifragile in relation to the S&P.

To show how this works, here are the return rates against SPY for the Sector Model back-tests:

Date	SPY	SPY%	Sector	Sector%	Advantage
12/31/2014	205.54	13.46%	24833.09	36.12%	22.66%
12/31/2013	181.15	32.30%	18243.38	42.36%	10.05%
12/31/2012	136.92	15.99%	12815.31	28.95%	12.95%
12/30/2011	118.04	1.89%	9938.44	6.23%	4.34%
12/31/2010	115.85	15.06%	9355.89	17.54%	2.48%
12/31/2009	100.69	26.35%	7959.91	58.07%	31.72%
12/31/2008	79.69	-36.79%	5035.68	-16.37%	20.43%
12/31/2007	126.08	5.15%	6021.19	21.85%	16.70%
12/29/2006	119.91	15.84%	4941.50	17.82%	1.97%
12/30/2005	103.51	4.83%	4194.23	-0.49%	-5.32%
12/31/2004	98.74	10.70%	4214.90	30.96%	20.26%
12/31/2003	89.20	28.18%	3218.55	36.48%	8.30%
12/31/2002	69.59	-21.58%	2358.30	-7.58%	14.00%
12/31/2001	88.74	-11.76%	2551.61	25.68%	37.44%
12/29/2000	100.57	-9.74%	2030.29	18.47%	28.21%
12/31/1999	111.42	20.39%	1713.72	35.30%	14.91%
12/31/1998	92.55		1266.59

 

These can then be used to create the following forecast metric on expected returns in different market conditions:

SPY%	Sector%	Advantage%
50%	58%	8%
40%	50%	10%
30%	41%	11%
20%	33%	13%
10%	25%	15%
0%	16%	16%
-10%	8%	18%
-20%	-1%	19%
-30%	-9%	21%
-40%	-17%	23%
-50%	-26%	24%

 

The graph of these relationships shows that the worse the market gets, the better the model outperforms:

 

So, if there is a bear, I’ll lose money – but will be so far ahead of the market that I will recover at a much better advantage than I was before the chaos.

I have to keep reminding myself of this during these painful whipsaws we are having lately.  Losing money hurts, and it’s easy to get spooked and cash out at the bottom!

Tim