BoomBustBlog Research Performance for 2008

By: Reggie Middleton | Sat, Jan 10, 2009
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A week and change into the new year and I finally get around to tabulating the performance results for 2008. They were quite impressive, until December, when the market rally forced me to disgorge a significant amount of my unhedged profits. I made a conscious decision not to take full profits in late November when I knew the market was going to go into its oversold/overbought momentum game. Alas, I did not take profits and my proprietary numbers took a hit. The bright side to this is that both my blog's static research model (+106.3%) and my proprietary results (+335%) are the best that I know of.

Barry Ritholz's Fusion Analytics posted positive results for the year (between 8% and 20%, depending on your perspective), which is damn good compared to most other services. It's not nearly as good as the BoomBust, but hey, I am the one of the cutest investors around - it's hard to compete. For those interested in his work or the difference between his service and mine, see his research site and blog. I don't know him personally, but he is often on CNBC, and is one of the most grounded pundits that they have. I have received permission to release his results and have made them available for download here:
fusion_analytics_recommendations_2008 09/01/2009,11:49 67.60 Kb.

Now, let's walk through my results for the year in detail. I'll start by comparing my results to that of the big name brands, just to illustrate where the real performance is to be found. For those in the press and the mainstream media (MSM), take note of this - you guys are interviewing the wrong people! As you peruse this year end report, be sure to conceptualize what would happen if all of the talking heads on TV were to have their performance results streamed across the bottom of the screen as they spoke! Below is what I believe to be the most comprehensive year end performance report of any blog or publicly available investment site, not to mention one of the most impressive.

BoomBustBlog vs Wall Street Brokers

I had my team choose the most prominent brokers, bankers and sell side research houses to compare with my results, and the final verdict for all of 2008 is...

Stock Return of Blog's
forensic /drill
down analysis
Brokers (Holding period return)
Citi GS JPM MS For
len 113.3% 0.0% 50.8% -95.3%    
hov 155.0% -77.7%   -75.9%    
phm 47.5% -1.0% -15.6% -15.0%    
ctx 108.5% -17.2% -52.6% 49.9%    
dhom 140.4%   No coverage      
bzh 165.6%   -81.6% 87.4%    
rdn 146.0%   No coverage      
mtg 164.6%     -44.6%    
dhi 87.5% 215.7% -38.6% -45.0%    
tol -5.5% 5.1% 6.7% 3.9%    
bsc 181.0%   No coverage     181.0%
cfc 150.4%   No coverage     150.4%
mbi 175.1%   14.7% -83.0%   175.1%
abk 188.6% -28.0%   -89.9%   188.6%
wm 193.0%   99.5%     193.0%
ryl 27.7% -7.8% -10.1% -44.9%   27.7%
ms 119.3% -71.9% -70.9% -71.3%   119.3%
ggp 182.6% 58.4% -95.9% -95.3%   182.6%
bac 125.9% -72.3% -58.5% -73.3% -36.2% 125.9%
kbh 72.1% -17.7% -41.9% -67.5%    
lehmq 195.2%   -99.9%     195.2%
ago 79.8% 0.0% -47.2% -32.4%   79.8%
key 125.6% -76.0% -67.9%   17.8% 125.6%
ffhs     No coverage      
ms 112.6% -71.9% -70.9% -71.3%   112.6%
c 137.9%   19.1% -80.1% -49.3% 137.9%
wfc 33.4% -14.0%   -30.4% -25.6% 33.4%
gs 99.4% -58.2%   -56.2% -51.2% 99.4%
mer   -81.6% -78.6% -84.3% -63.3%  
wb 163.8%   No coverage     163.8%
bsc 183.7%         183.7%
kfn 157.2% -85.1%   -78.9%   157.2%
jef     -35.5%     0.0%
pnc 55.5% -24.5% -23.2%   -35.3% 55.5%
bpop     No coverage      
sti 97.6% -45.3% -57.9% -63.3% -61.2% 97.6%
snv   -42.6%   -45.1% 36.6%  
mi   -47.5% 47.7% 68.7% -47.5%  
asbc         -43.6%  
fctr     No coverage      
mtb 86.9% -30.1% -9.0% -12.8% -41.0%  
hban 44.5% 21.7% 43.8%   -64.4%  
bbt   -14.0% -30.7% -43.4% -51.9%  
jpm   -41.7% -36.1%   -42.1%  
usb   30.4% -31.9% -32.9% -35.7%  
cof 70.1%   -34.8%     70.1%
nara     No coverage      
sasr     No coverage      
hnbc     No coverage      
cvbf     No coverage      
gbci     No coverage      
fhn   -54.4% 46.1% -43.6% 44.3%  
ncc   -88.1% -83.5% -89.5% -53.9%  
WAMUQ 195.5%   52.2%     195.5%
cfc 15.4%   No coverage     15.4%
rf   -40.2% -67.1% -67.4% 0.0%  
zion   -32.0% -66.5% -69.1% -51.3%  
tcbk     No coverage      
fitb   -73.1% -42.4% 76.9% 13.8%  
sov   -71.1%        
ge 85.6% -58.7% -61.4% -61.4%   85.6%
axp 91.1%   -54.6% -56.8%   91.1%
hbc 80.4%     45.9%   80.4%
nav 82.5%     -41.8%   82.5%
wire -1.5%   No coverage     -1.5%
sfd 66.0%     -44.1% -12.4% 66.0%
hig 69.9%         69.9%
mac 107.7%         107.7%
110.5% -28.9% -29.3% -41.4% -29.7% 106.3%

For a detailed addendum that show the supporting data for these calculations, see
Blog vs. Broker Analysis - supplementary material (1.09 MB 2008-10-24 14:43:34). The individual posts behind each ticker can be found here: "In the Actionable Research post". Here you can find the first post made regarding every ticker in this table above. Plenty of reading for those who are interested.

The last report has inadvertently been excluded from this analysis (FRO). PFG was not included as well, but was also not a full blown analysis, thus did not belong in the 2008 results column. I will be following up on PFG for there may be further opportunity there (I have already included addenda on FRO). Both of these tickers would show underwater, but would have a minimum effect on the return numbers posted here.

To be as fair as possible, I included unlevered returns below in order to compare with raw brokerage recommendations. Since nearly all of my research resulted in bearish opinions, shorts and puts were the order of the day (umm, year?!). Most cannot go short in a cash account, so leverage must be calculated, but to compare on an apples to apples basis, we created a watered down cash index of my recommendations in order to compare directly with the brokerage firms. The results are the pretty much the same.

Stock BoomBustBlog's
Holding period
(with leverage)
BoomBustBlog's HPR without
margin and commissions
Return of Blog's
drill down
len 113.3% -42.6% 16.7% 60.0% 113.3%
hov 155.0% 44.5% 68.9% 80.9% 155.0%
phm 47.5% -18.2% 16.6% 27.1% 47.5%
ctx 108.5% -2.9% 25.3% 57.6% 108.5%
dhom 140.4% 16.7% 16.7% 73.6% 140.4%
bzh 165.6% 50.0% 79.5% 86.2% 165.6%
rdn 146.0% -20.2% 13.7% 76.4% 146.0%
mtg 164.6% -7.7% 55.7% 85.7% 164.6%
dhi 87.5% -22.0% 36.8% 47.1% 87.5%
tol -5.5% 3.7% 12.5% 0.6% -5.5%
bsc 181.0% 3.3% 30.4% 93.9% 181.0%
cfc 150.4% 0.0% 0.0% 78.5% 150.4%
mbi 175.1% 38.3% 65.8% 90.9% 175.1%
abk 188.6% 50.6% 82.4% 97.6% 188.6%
wm 193.0% 22.5% 98.9% 99.9% 193.0%
ryl 27.7% -10.8% 18.7% 17.0% 27.7%
ms 119.3% -4.6% 55.4% 62.4% 119.3%
ggp 182.6% 44.0% 92.2% 93.8% 182.6%
bac 125.9% 42.7% 58.9% 65.5% 125.9%
kbh 72.1% 10.0% 31.7% 38.4% 72.1%
lehmq 195.2% 21.9% 99.7% 99.9% 195.2%
ago 79.8% -18.8% 31.4% 42.2% 79.8%
key 125.6% 37.1% 36.8% 65.1% 125.6%
ffhs 62.9% 6.7% 30.8% 33.6%  
ms 112.6% -4.6% 55.4% 58.4% 112.6%
c 137.9% 48.8% 63.5% 71.1% 137.9%
wfc 33.4% 23.9% 17.1% 18.8% 33.4%
gs 99.4% 4.1% 49.0% 51.8% 99.4%
mer 153.0% 38.5% 58.9% 78.6%  
wb 163.8% 13.4% 67.8% 84.0% 163.8%
bsc 183.7% NA NA 48.4% 183.7%
kfn 157.2% 39.1% 57.7% 80.5% 157.2%
jef 25.4% 8.0% 18.7% 14.6%  
pnc 55.5% 28.4% 7.8% 29.5% 55.5%
bpop 100.9% 24.2% 16.0% 52.2%  
sti 97.6% 32.5% 10.5% 50.5% 97.6%
snv 84.3% 34.3% -6.9% 43.8%  
mi 93.4% 32.4% -11.0% 48.4%  
asbc 66.9% 19.8% -21.6% 35.2%  
fctr -2.2% 0.0% 0.0% 0.6%  
mtb 86.9% 39.9% -11.3% 45.2% 86.9%
hban 44.5% 27.1% -19.0% 23.9% 44.5%
bbt 56.0% 33.8% -13.9% 29.7%  
jpm 70.1% 33.2% -2.6% 36.8%  
usb 57.2% 23.6% 8.0% 30.3%  
cof 70.1% 21.9% 13.2% 36.8% 70.1%
nara 64.4% 25.8% 1.3% 33.9%  
sasr 31.6% -0.6% -15.7% 17.5%  
hnbc -13.0% -1.5% 6.6% -4.8%  
cvbf -15.5% 12.7% -12.2% -6.0%  
gbci 33.0% 18.3% 7.6% 18.2%  
fhn -30.2% 11.9% -4.5% -13.4%  
ncc 134.3% 28.5% 50.2% 68.8%  
WAMUQ 195.5% 22.5% 98.5% 99.5% 195.5%
cfc 15.4% 0.0% 0.0% 9.4% 15.4%
rf 115.2% 33.8% -7.0% 59.3%  
zion 94.5% 45.9% -33.6% 48.9%  
tcbk -80.8% 4.3% -27.4% -38.7%  
fitb 115.5% 29.9% 29.9% 59.5%  
sov 127.6% -7.1% 71.0% 65.5%  
ge 85.6% 16.4% 32.4% 44.3% 85.6%
axp 91.1% 29.2% 30.8% 46.6% 91.1%
hbc 80.4% 20.6% 22.5% 41.3% 80.4%
nav 82.5% -3.5% 43.0% 42.4% 82.5%
wire -1.5% 4.3% -7.4% 0.1% -1.5%
sfd 66.0% -28.8% 46.1% 33.9% 66.0%
hig 69.9% -13.5% 74.7% 35.6% 69.9%
mac 107.7% 32.4% 57.0% 54.5% 107.7%
92.9% 15.6% 28.3% 47.9% 110.5%

Speaking of CNBC, James Cramer is probably one of the most renown TV and cable investment pundits. He's an entertainer, for sure, but he still bites the BoomBust! To see the entire study comparing this blog to his flagship "Action Alerts Plus" service (which ain't cheap), see Reggie Middleton on James Cramer: Marked to Market!. Don't get me wrong, I like Cramer, and in small doses he really makes me laugh. I don't want to disparage him in any way, but like I said earlier... Let's put it this way, his performance was better than JP Morgan's, and he did a little worse than the S&P, that is until you factor in expenses and taxes. Then you would have been better off simply watching him for entertainment rather than following his advice.

BoomBustBlog vs Cramer

James Cramer's Action Alert Plus Performance  
Average holding period in months 6.23
Cramer's average holding period return -15.07%
Cramer's return 01/01/2008-Present -39.48%
Cramer's average yearly return since 01/01/2002 -15.29%
Broad Market Indices  
S&P 500  
S&P 500 01/01/2008-Present -29.90%
S&P 500 average yearly return since 07/01/2007 -33.60%
Reggie Middleton's  
Average holding period in months 10.09
S&P 500 01/01/2008-Present -29.90%
S&P 500 average yearly return since 07/01/2007 -33.60%
Cramer's average holding period return -15.07%
Cramer's return 01/01/2008-Present -39.48%
Cramer's average yearly return since 01/01/2002 -15.29%
BoomBustBlog research average holding period return 110.55%
BoomBustBlog research average yearly return since 01/01/2007 106.3%

The slight differences in performance are due to the calculation variations made to create an "apples to apples" comparison, ex. holding period, etc.

Reggie Middleton's Proprietary Trading Account

These are the results for my personal trading. I have decided to disclose some of my trading strategies with the institutional level subscribers starting next week, when I release the global macro research featuring a Spanish bank. Be aware that this is not necessarily for beginners.

The proprietary trading account differs from the static blog research model in that it is actively traded and managed (although I do very, very little trading and exhibit bare minimum churn) while the blog research model is static - assuming the reader simply attains a position when the research is released and closes the position at or around the valuation band indicated in the research or follows the direction of continuing opinion. This is in essence, a passive/static model, although it has outperformed practically every this year and last year. The result of the difference between the two is that what I perceive to be the more profitable opportunities are concentrated, and profits are active taken while losses are actively cut. In addition, I do some tax management as well, which tends to skew the pre-tax performance numbers, often to the downside.

Below are the raw, absolute returns for my proprietary account. These returns are calculated by calculating the difference between my starting point and ending point, and is the number that I use for comparison (since it is the number that shows how much money I actually made).

  Reggie's gross
avg. return
S&P return
For all 2007 (6 months) 42.93% -8.23%
For Q1 2008 50.03% 0.68%
For Q2 2008 53.46% -8.66%
For Q3 2008 32.40% -8.30%
For all 2008 196.11% -8.69%
Since inception 481.04% -35.72%
2008 absolute return 335.42%  
Correlation to S&P 500 -61.02%  
Correlated Beta -2.26  

The numbers below are average monthly numbers. They are posted for the sake of uniform comparison.

As can be plainly seen, we have absolutely trounced all of the hedge fund indices, both for the year and since inception.


• Reggie Middleton Proprietary Account has outperformed the S&P 500 - 19 month Outperformance: 273.06%

• Reggie Middleton Proprietary Account has outperformed the Barclay Hedge Fund Index - 19 month Outperformance: 245.82%

• Reggie Middleton Proprietary Account has outperformed the Barclay Event Driven Index - 19 month Outperformance: 243.7%

• Reggie Middleton Proprietary Account has outperformed the Barclay Equity Long Bias Index - 19 month Outperformance: 258.52%

• Reggie Middleton Proprietary Account has outperformed the Barclay Equity Long/Short Index - 19 month Outperformance: 238.81%

• Reggie Middleton Proprietary Account has outperformed the Barclay Market Neutral Index - 19 month Outperformance: 226.52%

• Reggie Middleton Proprietary Account has outperformed the Barclay Equity Short Bias Index - 19 month Outperformance: 166.37%

• Reggie Middleton Proprietary Account has outperformed the Barclay Fund of Funds Index - 19 month Outperformance: 244.79%

• Reggie Middleton Proprietary Account has outperformed the Barclay Global Macro Index - 19 month Outperformance: 218.61%

• Reggie Middleton Proprietary Account has outperformed the Barclay Multi-Strategy Index - 19 month Outperformance: 243.33%

What about Risk???

Most year end performance tabulations fail to take risk into consideration, even the year end reports from the multi-billion dollar hedge funds that take 22% of you money and basically act as an overpriced levered mutual fund. Don't get me wrong, I'm all for the hedge fund business, but as the Bernie Madoff fiasco illustrates, sometimes you have to look past name brands, fancy literature and the "I know a guy, who..." type of relationships. Hey, listen up. I am a blogger, and if my disclosure, research and transparency is greater than the money management and brokerage guys that you give your money to, let that be considered the writing on the wall (street)! You've been forewarned (again), and as we all now know after the (BoomBustBlog forewarned) failure of the big investment banks, monolines, mortgage insurers, commercial banks and thrifts, etc. - The Revolution will not be televised! It will probably be BLOGGED though!

Trusting a money manager, broker, bank or custodian that posts reward without posting the risks taken to obtain the reward is akin to buying up a lot of items on a shopping spree without bothering to ask the prices of the items. Risk IS the price of reward, period! Trust me, many of you are probably overpaying.

Notice the correlation numbers. This is why everybody is leaving, these are just pricey mutual funds with barely better performance and 14 times the price.

For those of you who have something better to do than study archaic finance terms, I have provided a handy dandy glossary of terms used in this article. My next article (other than updating the oil shipper research) will address the significance of the significant drop in wealth amongst the upper and upper middle classes in this country, Europe, Asia and the middle east, and what that social mobility means. Of course, those that read this blog should have actually moved up a notch in absolute terms, which probably means they moved up about 1.4 notches in relative terms. Blog on, my loyal readers and have a happy new year!


n 20 Monthly periods in the sample set, annualized.
arithmetic mean 0.115 Simple average of Reggie Middleton Returns, net of fees
standard deviation 0.234 Standard deviation is applied to the annual rate of return of an investment to measure the investment's volatility. Standard deviation is also known as historical volatility and is used by investors as a gauge for the amount of expected volatility. For example, a volatile stock will have a high standard deviation while the deviation of a stable blue chip stock will be lower. A large dispersion tells us how much the return on the fund is deviating from the expected normal returns.
skewness 0.324 Skewness is extremely important to finance and investing. Most sets of data, including stock prices and asset returns, have either positive or negative skew rather than following the balanced normal distribution (which has a skewness of zero). By knowing which way data is skewed, one can better estimate whether a given (or future) data point will be more or less than the mean. Most advanced economic analysis models study data for skewness and incorporate this into their calculations. Skewness risk is the risk that a model assumes a normal distribution of data when in fact data is skewed to the left or right of the mean.
kurtosis -0.684 Used generally in the statistical field, kurtosis describes trends in charts. A high kurtosis portrays a chart with fat tails and a low, even distribution, whereas a low kurtosis portrays a chart with skinny tails and a distribution concentrated toward the mean. Higher kurtosis means more of the variance is due to infrequent extreme deviations, as opposed to frequent modestly-sized deviations.
beta -2.255 The Beta coefficient, in terms of finance and investing, is a measure of volatility of a stock or portfolio in relation to the rest of the financial market. An asset with a beta of 0 means that its price is not at all correlated with the market; that asset is independent. A positive beta means that the asset generally follows the market. A negative beta shows that the asset inversely follows the market; the asset generally decreases in value if the market goes up. Correlations are evident between companies within the same industry, or even within the same asset class (such as equities), as was demonstrated in the Wall Street crash of 1929. This correlated risk, measured by Beta, creates almost all of the risk in a diversified portfolio. The beta coefficient is a key parameter in the capital asset pricing model (CAPM). It measures the part of the asset's statistical variance that cannot be mitigated by the diversification provided by the portfolio of many risky assets, because it is correlated with the return of the other assets that are in the portfolio. Beta is calculated for individual companies using regression analysis.
Sharpe ratio 0.488 A ratio developed by Nobel laureate William F. Sharpe to measure risk-adjusted performance. The Sharpe ratio is calculated by subtracting the risk-free rate - such as that of the 10-year U.S. Treasury bond - from the rate of return for a portfolio and dividing the result by the standard deviation of the portfolio returns. The Sharpe ratio tells us whether a portfolio's returns are due to smart investment decisions or a result of excess risk. This measurement is very useful because although one portfolio or fund can reap higher returns than its peers, it is only a good investment if those higher returns do not come with too much additional risk. The greater a portfolio's Sharpe ratio, the better its risk-adjusted performance has been. A variation of the Sharpe ratio is the Sortino ratio, which removes the effects of upward price movements on standard deviation to measure only return against downward price volatility.
Sortino ratio 1.240 The Sortino ratio measures the risk-adjusted return of an investment asset, portfolio or strategy. It is a modification of the Sharpe ratio but penalizes only those returns falling below a user-specified target, or required rate of return, while the Sharpe ratio penalizes both upside and downside volatility equally. It is thus a measure of risk-adjusted returns that some people find to be more relevant than the Sharpe. Thus, the ratio is the actual rate of return in excess of the investor's target rate of return, per unit of downside risk.
Omega 3.576 A risk-adjusted performance measures that attempts to mitigate the difficulty in calculating risk adjusted returns for short intervals - based on the Sharpe ratio methodology.
maximum drawdown 25.17% The measure of the decline from the historical peak in the cumulative profit of the financial trading strategy.
Information ratio 49.61% The Information Ratio measures the excess return of an investment manager divided by the amount of risk the manager takes relative to a benchmark. It is used in the analysis of performance of mutual funds, hedge funds, etc. Specifically, the information ratio is defined as excess return divided by tracking error. Excess return is the amount of performance over or under a given benchmark index. Thus, excess return can be positive or negative. Tracking error is the standard deviation of the excess return. An alternative calculation of Information ratio is alpha divided by tracking error, although it is preferable to use pure excess return in the calculation. The ratio compares the annualized returns of the Fund in question with those of a selected benchmark (e.g, 3 month Treasuries). Since this ratio considers the annualized standard deviation of both series (as measures of risks inherent in owning either the fund or the benchmark), the ratio shows the risk-adjusted excess return of the Fund over the benchmark. The higher the Information Ratio, the higher the excess return of the Fund, given the amount of risk involved, and the better a Fund manager. The Information ratio is similar to the Sharpe Ratio, but there is a major difference. The Sharpe Ratio compares the return of an asset against the return of Treasury bills, but the Information Ratio compares excess return to the most relevant equity (or debt) benchmark index.
Stutzer index 6.142 The possibility of an investment outperforming a benchmark over a given time horizon, with an equivalent unit of risk.
Upside potential ratio 176.65% A measure of a return of an investment asset relative to the minimal acceptable return. The measurement allows a firm or individual to choose strategies with growth that is as stable as possible for a given minimum return.
Calmar ratio 45.76% The absolute value of the ratio of the annual compounded return divided by the largest drawdown incurred to date. It is also quite commonly referred to the MAR ratio. Calmar or MAR ratio's of 1 are very rare in real world trading for an extended period of time. From this we can infer that if we are striving for a compounded annual return of 20% than we can expect our largest drawdown to be at least -20%.



Reggie Middleton

Author: Reggie Middleton

Reggie Middleton

Reggie Middleton

Who am I?

Well, I fancy myself the personification of the free thinking maverick, the ultimate non-conformist as it applies to investment and analysis. I am definitively outside the box - not your typical or stereotypical Wall Street investor. I work out of my home, not a Manhattan office. I build my own technology and perform my own research - in lieu of buying it or following the crowd. I create and follow my own macro strategies and am by definition, a contrarian to the nth degree.

Since I use my research as a tool for my own investing to actually put food on my table, I can stand behind it as doing what it is supposed too - educate, illustrate and elucidate. I do not sell advice, I am not a reporter hence do not sell stories, and I do not sell research. I am an entrepreneur who exists just outside of mainstream corporate America and Wall Street. This allows me freedom to do things that many can not. For instance, I pride myself on developing some of the highest quality research available, regardless of price. No conflicts of interest, no corporate politics, no special favors. Just the hard truth as I have found it - and believe me, my team and I do find it! I welcome any and all to peruse my blog, use my custom hacked collaborative social tools, read the articles, download the files, and make a critical comparison of the opinion referencing the situation at hand and the time stamp on the blog post to the reality both at the time of the post and the present. Hopefully, you will be as impressed with the Boom Bust as I am and our constituency.

I pay for significant information and data, and am well aware of the value of quality research. I find most currently available research lacking, in both quality and quantity. The reason why I had to create my own research staff was due to my dissatisfaction with what was currently available - to both individuals and institutions.

So here I am, creating my own research for my own investment activity. What really sets my actions apart is that I offer much of what I produce to the public without charge - free to distribute and redistribute, as long as it is left unaltered and full attribution is given to the author and owner. Why would I do such a thing when others easily charge 5 and 6 digits annually for what some may consider a lesser product? It is akin to open source analysis! My ideas and implementations are actually improved and fine tuned when bounced off of the collective intellect of the many, in lieu of that of the few - no matter how smart those few may believe themselves to be.

Very recently, I have started charging for the forensics portion of my work, which has freed up the resources to develop the site to deliver even more research for free, particularly on the global macro and opinion front. This move has allowed me to serve an more diverse constituency, which now includes the institutional consumer (ie., investment turned consumer banks, hedge funds, pensions, etc,) as well as the newbie individual investor who is just getting started - basically the two polar opposites of the investing spectrum. I am proud to announce major banks as paying clients, and brand new investors who take my book recommendations and opinions on true wealth and success to heart.

So, this is how I use my background and knowledge in new media, distributed computing, risk management, insurance, financial engineering, real estate, corporate valuation and financial analysis to pursue, analyze and capitalize on global macroeconomic opportunities. I have included a more in depth bio at the bottom of the page for those who really, really need to know more about me.

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