Please take the following poll. I am interested in your thoughts on these pairs. I have included the score generated by the model for each pair. This poll is setup to allow multi choice. You can pick up to 3 pairs. It is also setup to allow comments.

Please leave your own suggestions, and I will generate the score for it, for any posts in comments.

Thanks,

Jack H Barnes Jr.

The model scoring results are available here for the watch list.

I then took the same pairs, and built a quick and dirty backtest of the results since Jan. 1, 2012. The following is how they have performed YTD. This is just a comparison of the pairs based on the closing price Dec. 31, 2011.

This is for comparison purposes only, and is in no way a suggestion to buy or sell any of these pairs specifically.

This post is about the Sub-Sector Scoring Engine (SSSE) and how it will be incorporated into the model. This is the key module toward generating future trading pairs in the model that are not currently deployed.

The SSSE is reviewing over 6,000 stocks, divided into 217 sub-sectors, and updates its data daily about one hour after market close from www.finviz.com, allowing us to track changes over time.

The engine was designed and coded by my friend, Samir, at investexcel.net to generate each of the sub-sectors in U.S.-based equity markets. He was kind enough to add new features to his original Stock Screener model available here.

The SSSE gives a mean score for each of the 40+ factors we use in the model to track changes between two stocks. It generates an easy-to-use strategy for reviewing large numbers of nearly identical companies.

We can then take the comparisons and rank each of the underlying stocks, so we have a best- and worst-case score for each of them.

We then can compare and contrast the performance of these pairs, to see which have been trending away from each other at the highest rate of speed.

The screen capture above is the REIT Residential group, which has 26 equity selections in it. The model will compare and rank each of these stocks based on their average score in the sub-sector.

The obvious premise is we want to have the SSSE highlight the most divergent pairs to combine. It’s one thing for a model to have unique pairs that generate results; it’s completely another thing to have the model actively seeking to find the next best pairs to be used.

The SSSE gives us the ability to dive into the equity markets and find the most logical Long/Short stock pairs based on their ongoing results. The data is updated daily, as fundamentals & technical factors change through time.

Again, our long-term goal is moving these proof-of-concept Excel files to an industrial database that allows us to track each stock’s score against the others in its sub-sector.

We’ll be able to track historical performance and results between stocks to find the best performing pairs. If you have any suggestions on how to improve this model, please do so in comments.

Jack H Barnes Jr.

CEO & Founder
jack@jhbcapital.com
www.jhbcapital.com

1 (800) 658-7572 Phone
1 (888) 370-7610 Fax

Let’s dive right in and take a look at what stocks we have in the model, why they are in there, and what is driving the thoughts behind the process of selecting them.

I have set up this test model with a number of intentional failures, to see how it would treat these events on its own. Let’s review those trades, and see how the model is coping with them.

The model is reporting three false readings on its stable trade checkpoint. These would trigger the removal of the trade from the basket, and a new replacement trade being plugged in to redeploy the capital.

I am using .75 as the hard cut-off for a trade that is flirting with an equal ratio. In each of the test cases, the model would reject the trades, while two of the three are profitable trades.

As is obvious, the model caught the Coke versus Pepsi trade and would have put it on in the reverse direction. This was a planned test, and I was glad to see it. Coke has overperformed Pepsi YTD, and while the model is exposed to it from a test point of view, it would never have been put on or kept in.

The test model has a false positive trade embedded with its love of Ford over GM, while the equity markets have sold Ford and bought GM in comparison to each other YTD. This trade is listed as a true trade, but is in fact underwater as will be seen below. The trade would be allowed to stay in, due to its positive reading. It would get rejected if its losses reach 1.5% of the portfolio AUM.

The following model snapshot was taken end of yesterday during the writing of this article.

The only real failure in the model selection process is JPM versus Wells Fargo in the battle of the TBTF.

JPM is up YTD more than WFC is, and even with the model saying to reverse this trade I would instead pull it and watch. The model is trying to put on a losing trade YTD here.

While it may turn out to be correct, the vagaries of bank balance sheet reporting are such that I would suggest the model is only as good as the data being put into it. I believe, in all cases, a model should still have a human reviewing the individual trades.

The third false trade reading in the test model is based around XOM versus Chevron. These two companies are almost identical, and while the market prefers XOM over CVX, the model would reject this trade and book the profits. The Ratio strength level has hit a point that would generate a sell.

In Review

At this time, the model should have the PEP versus KO trade kicked out due to false ratio before .75, along with the XOM versus CVX trade and the JPM versus WFC. This would leave in the F versus GM trade due to it only being underwater, but is expected to turn around due to its current model score.

In reviewing the rest of the Model Portfolio, the additional trades, specifically CLR versus PBR, SRE versus EQT, AAPL versus GOOG, DVN versus CHK, and MSFT versus ORCL are positive trades, with a positive score in the selection process.

I will return to discuss the successful trades and the sub-sector scoring engine in future articles in this series.

Jack H Barnes Jr.

CEO & Founder
jack@jhbcapital.com
www.jhbcapital.com

1(800)658-7572 Phone
1(888)370-7610 Fax

While the model is replicable and other shops likely use similar ones, ours is focused on extremely liquid strategy. I don’t mind discussing the nuts and bolts of how it operates in the wild.

This was built around the Excel file made available by InvestExcel, a copy of the original file before I modified it is here.

Below you will find a snap shot of the Stock Comparison Scoring Engine. Using 40 different items to compare and contrast two like stocks, it generates a unique relative score of 1 or 0 per line compared. These are then combined to give us the relative score between any two stocks compared against each other.

Below is the score for Exxon & Chevron, as compared against each other using yesterday’s data.

The relative score will change in value as new information is available. The idea is to run the model daily and build a database of the rolling scores for each paired trade of interest.

The model will track the trend in the pairs, giving us insight into historical divergent and expected mean reversion estimates.  In addition, it generates the best timing of the pairs themselves.

While Alfred Jones, who founded the first hedge fund, had his organization track a form of volatility and weight their pairs based on a volatility-rated value, we are going to take a different approach. We will use equal dollar weighting on same sub-sector pairs.

I prefer to use what I think of as natural pairs. If they belong to the same business sector, and preferably sub-sectors, that makes a lot more sense than using cross-sector pairs. I don’t believe in the lowering of risk, just because historically if the volatility or rate of change between two stocks has been X, it will stay X.

The model uses a fundamental bias structure, so it looks to capture the change between two competitors.  We are only focused on the rate of change between two nearly identical stocks. This strategy is designed to be as uncorrelated with the index as possible.

While a relative paired score is nice to have, a baseline is needed so I’m working on adding that to the model. Below is a snap shot of the Sub-Sector Comparison Engine.

The next step will be to recode this to generate a sub-sector score for all stocks.

This helps us identify the best natural pairs in a sector. I will post on the Sub-Sector Comparison Engine, once I have it polished and generating sector-wide scores.

The model being discussed in these blog posts is an example model only. Clients of JHB Capital will see a new, and completely different set of paired trades in their own account’s once the model is in operation.

This is an example of a copy of the model only. This model has three intentionally constructed trades out of nine pairs that are designed to test the models outputs.

As such, do not invest in this model or its results blindly. You should consult  with your adviser before investing in anything you find on the internet for free. Everything in this post is for example only.

If you have any comments or thoughts about how I can improve on this design please join me in the comments section of this or the first article in the series.

Jack H Barnes Jr
CEO & Founder
JHB Capital LLC

A new client recently approached me with an interesting mandate I’ll explain, and hope readers will discuss in comments to help me improve the strategy.

He cashed out of the market near the top in January 2008 and has watched the last few years with his nest egg safe but sidelined. He realizes if his nest egg is going to remain one, he needs to put his capital back to work. Given current market status, he expects a pullback and finds himself torn between market risk and market exposure. I have spent the last month working on a solution for these investment requirements.

He asked me to build a model that would be less volatile than the indexes, with an absolute return strategy for his account. He could underperform a bull market but wants nothing to do with a 20% pullback.

The turtle approach to alpha. Said differently, how do you generate alpha without beta?  I went to work and developed a lower beta model generating index-beating results.  In doing research, I looked back to the work of Alfred Jones, the father of the modern hedge fund. He was a reporter who was studying the market, and decided to pair two styles together. When combined, his strategy generated market-neutral results.

The Jones Hedge Fund Strategy was in business for 32 years, with 29 of them profitable. The company is still around as a fund of funds using hedged equity as its strategy. In 1968 Institutional Investor published this piece on the first hedge fund shop.

“The logic of the idea was very clear. It was a hedge against the vagaries of the market.”

He used a hedged pair strategy. The idea is you go long a quality stock and short an equal dollar amount on a like stock that has worse fundamentals. A hedged pair of like stocks should be market-neutral.

That is, if the equity markets go up 100 S&P points, or down 100 S&P points, the only difference in account value is the change in value between the pairs. The pair can go up in value together, or down in value together, or bifurcate in their returns, you only care about the rate of change between the pairs. This is the basis I have expanded on with my new model.

The JHB Capital Long/Short Market-Neutral Strategy.

The strategy is built around the idea of using natural pairs – Long Coke/ Short Pepsi or Long UPS/Short FedEx. The idea is to capture the spread between two similar stocks. Historically, the failure of hedged pairs has been hedges that didn’t work when most needed.

The premise behind the model is to select highly liquid pairs of stocks that move with the market noise as one, while slowly diverging away from each other. This generates a portfolio with little correlation to the market indexes as a whole.

The model is currently built using Excel files.  Samir, of www.investexcel.net, has graciously allowed me to have access to his own work, to morph it into what I needed it to do. He has built a number of excellent, free, and easy to use Excel tools which I highly recommend to anyone.  I have used two already for this project and hope to move the model to a serious database to track the ratings changes over time.

The model currently uses a “Stock Comparison” spreadsheet available at the link. I modified the sheet to incorporate a two-stock evaluation, generating a unique score based on the comparison of the Fundamental & Technical Analysis data.

In simple terms, I am comparing two stocks, and on each line item the model generates a 1 or 0 value. The pairs are compared via 40 different evaluations, some of which are true fundamental evaluations and others which are technically focused on the strength of the stock in question.

This gives us a dual view of both types of evaluations and generates a quant-based factor score for each item. Once added up, this gives each pair a moving ratio score which will be used to generate exits from the portfolio as well as hitting gain targets or stop losses.

The score will be compared against a sub-sector baseline generated from the “Stock Screener” available at the link which will be used to generate a mean score for each of the stocks in each sub-sector. This gives us a baseline to compare our individual company scores with the paired trades, to generate the best pairs of like stocks.

The portfolio will use a built-in exit on any pairs that have lost 1.5% of the account’s AUM. The portfolio will also take profits at specific return levels in a pair, allowing new pairs to be plugged in to redeploy the capital in question. Finally, one of the strategy’s goals is to evaluate the pairs allowing for a change in them, if the internals have changed significantly since the pair was initiated.

While I’m still developing the model, it’s advancing nicely and has begun generating some interesting results. Here is a snapshot of the current model, as backtested to close of market on December 31, 2011.

This draft of the model has deployed only 49.3% of its capital, with the balance in cash.

These results are for a basket of 9 paired stocks with equal dollar value on entry. The model has not generated any profit or loss sales yet. I’m still working on incorporating the paired value scores, which I will document in a follow-up post in a few weeks when the next upgrade to the model is deployed and generating results.

I would like to thank both Matt Busigin (@mbusigin) and Ryan Prociuk (@ryanprociuk) who were both generous in helping me with the proof of concept pieces necessary to build a working version.

I will be following this post, with others that focus on either the design or the results of the model.

Links

• Alfred Jones
• on the first hedge fund shop
• www.investexcel.net

Files

• Stock Screener here
• Stock Comparison link

I like a paired trade here. I would go long the common shares in Continental (Quote: CLR) and a short an equal dollar value in Petrobras (Quote: PBR).

Here is why.

This boils down to Onshore incremental growth story vs Offshore incremental growth story. Both company’s have stated their plans (CLR Presentation & PBR Presentation) on growing at a high rate via internally driven organic growth.

Since each is growing rapidly, via the drill bit, we can compare them to each other on a cost to develop each flowing barrel of equivalent oil. We have some commonality between like stories.

We can take that commonality, and compare and contrast the cost structures to produce them. However, for this simple blog post, lets just look at the quick and dirty facts that are obvious.

Let’s compare two scenarios. The first is an onshore vs offshore drilling strategies.

In the case of onshore production, it is a lot cheaper to haul in standardized completion hardware, and build out the necessary production capacity incrementally. That is one well at a time, with the new production put on stream as take off capacity becomes available.

Onshore has very little learning curve left, in regards to unlocking new on shore oil & gas fields. The development of on shore fields has reached the turn key level in the US. The greatest issues today in onshore development is if there is enough takeoff capacity to get your product to a refinery cheaply. If not, can you still produce the well using temporary transportation means like trains, trucks and localized demand.

Offshore however, the newest & largest fields are in locations that have never been produced before. Typically, there are no pipeplines to tap into. Everything has to be installed in some of the most challenging locations in the world. Hundreds of miles from shore.  This causes off shore to have to design and build expensive technology that doesn’t exist yet, to solve new and original issues.

It’s not uncommon that a field is so far from shore that a dedicated floating facility will have to be created from scratch for that specific field. It may not have any use after this field. The new equipment is custom tuned to the specific demands of producing that oil at sea safely. While converted tankers can be used on smaller projects, historically a major field development needs a custom design for it.

The off shore tanker portion of the field FEED design requires years of expensive lead time, to build and break in the new production capacity. This process doesn’t always go according to plans.

A single mistake like what happened at Thunder Horse can cost billions of dollars in lost production, and redevelopment of new equipment.

Continental is rolling out an onshore building program focused on lowering incremental costs, while expanding production in lower risk drilling strategies like shale, where the formation presence is already known.

Petrobras is developing the most expensive and technically some of the more challenging oil fields in the world. It is never cheap to develop new technology. The challenges to bring on new production in the deep salt offshore markets isn’t fully factored into the equity price in my opinion.

What it means

In simple terms, I would prefer to invest in a lower risk onshore developments, then to invest capital into higher risk capital intensive projects that will need to design new custom hardware, to work.

If you agree or disagree, tell me what you think in the comments section below.

Disclosure: Jack Barnes does not have a position in any stock mentioned in this article, at the time of this being published. This blog post is an example of the type of investment I will be looking to place in my funds under management, once compliance clears my new business for client accounts.

Pondering Some of the Global Markets

When I look at the capital markets in the United States, and for that matter the world, a new view is becoming clearer. What was weak is stronger and what has been the dominant story of growth is no longer driving demand as it was.

The U.S. economy is growing at a slow but steady rate. The bifurcation of the U.S. work force has been absorbed, with former workers now regularly falling off of the government unemployment indices. The new reality is based around growth sectors in the economy again.

North Dakota has almost no unemployment. If you want to work, you just have to be willing to live in a trailer until you can afford to have a house built. The rate of growth in jobs in the region is staggering.

This has all been driven by the unlocking of abundant energy sources in the near term.  The State of North Dakota has seen its oil production increase from 342k boepd, to 546k boepd from Jan 2011 to jan 2012.

The hydraulic fracking is changing the fundamental picture for energy in the US. The U.S. is the world’s largest producer of natural gas again and has been growing its oil production year-over-year. Refined energy products leapfrogged every other export to lead the U.S. in total dollar value per product exported. Domestic gasoline consumption is significantly down from before the financial crisis.

With natural gas at decade lows, entire transportation fleets are quietly being converted to run on compressed natural gas and propane. The U.S. is adapting, and with it, a new economy is starting to grow.

The era of cheap Chinese labor is ending, with double-digit salary raises built into yearly expectations of Chinese corporations. In the States, cheap energy supplies are driving new capital investments.

When it comes to U.S. manufacturing, says Kristina Hooper, head of portfolio strategies at Allianz Global Investors, “It’s time to stop looking in the rearview mirror and start looking ahead.”

The warm winter has left the U.S. with extra supplies of natural gas in storage, which will impact the price until winter, as storage capacity won’t be able to absorb the new supplies coming online.

Australia appears to be the poster child for future economic pain, as the most levered nation to China’s previously insatiable need for raw inputs. Chinese demand for endless Australian commodities will wane and, when it does, the turn in their domestic capital markets will be interesting to watch.

The impact of slower compounded growth targets will change how Australia and China approach the future. Australia is going to have a China-sized hangover from relying too heavily on commodity exports to them.

This was obvious when Australia invited the U.S. Government to station U.S. Marines near Darwin. The base gives the U.S. a prime location in the region from which to stage additional assets on demand. The Australian Defense Minister, made this clear when he greeted U.S. Marines this week.

“The world needs to essentially come to grips with the rise of China, the rise of India. The move is strategic and political and economic influence to our part of the world.”

Brazil, another of China’s largest trading partners, has seen its economic growth rates drop from emerging to developed market rates. Particularly, China has relied on imports of Brazilian iron ore.

Brazil’s relationship to China is the same as Australia’s – both nations have found themselves in a raw-to-refined product market relationship.  China has developed a colonial relationship with Brazil just as it has Australia. One particular example is Vale, the world’s largest iron ore producer.

Vale has found itself paying China to build the world’s largest ships. These vessels are so large, China won’t allow them to ship iron ore to China. This has depressed the value of the ships, before they have been put into service.

Vale paid $133.3 million each for another 12 ore carriers under construction in China that are now worth $63.7 million apiece, according to VesselsValue.com data.

A second major issue for Brazil is their previously seeming offshore oil and gas miracle. It has become an interesting battle ground, as Brazilian Federal Prosecutors appear to be focused on stopping the near-term development of the energy sector.

Charges brought against Chevron and Transocean are part of an intentional strategy to stop current development plans. While Brazil is attempting to start a world-class energy development sector, as is Houston, arresting contractors is not a smart strategy.

While Brazil has stated it would pour $225 billion into its oil and gas sector by 2015, it seems the nation has announced a growth strategy that is larger than its capacity to fund. Consider that preparations for  hosting the next World Cup and Olympics are behind schedule and Brazil looks even worse.

The great collapse in Europe was averted when the European Central Bank rolled out its own quantitative easing labeled Long Term Recapitalization Operation (LTRO). While LTRO was not designed to explicitly end the crisis, it has provided the European Union banking sector with enough balance sheet liquidity to calm the crisis waters for now.

The ugly truth is that Greece has played its role perfectly. The markets no longer have any expectation of a real fix. Europe now talks about how the International Monetary Fund needs to increase its bailout fund, so it can help match the EU increase in their bailout funds.

When you have a global drive to build up new bailout funds from the same financially stressed sources of capital, you start seeing  socially driven moment of cognitive dissonance.

Issuing debt to refund debt that can’t be marked to market will not work as a viable long-term solution.

Historically, when Europe becomes this fractured over its economic agenda, a military event is not so far away. The players may change names and the borders may move, but the results rarely deviate.

A Middle East military conflict now, while China growth is slowing down, could cause real inflationary events in Europe. What is the real price of oil in Europe, if the Euro drops while the U.S. dollar returns to a safer haven status?

What are your thoughts about the global macro market of today?

Sources:

WSJ: The Great Reversal: Playing the U.S. Manufacturing Boom

NPR: U.S. Marines in Australia, what’s the message?

Bloomberg: Vale Ore Ships plunge 36 percent in value

LAHT: Brazil’s Petrobras Approves $225 Billion Investment Plan Through 2015

What a long, strange trip it’s been.

Over these last 18 months, I’ve had the distinct pleasure of writing the “Buy, Sell or Hold” column for Money Morning courtesy of Mike Ward and Bill Patalon, Publisher and Executive Editor respectively. From the first column, Mike and Bill gave me carte blanche to write what I thought, when I thought it. Such freedom is rare, and I believe it contributed to the column’s success.

My love of writing about markets, I’ve recently admitted to myself, no longer outweighs my love for markets. Hell, my first investment was charging my kid sister interest on her allowance! I’ve had enough of looking at real waves – I’m getting back in the financial ocean with them.

Today, I’m proud to announce JHB Capital LLC will be opening for business. I’m getting relicensed so I can provide Separately Managed Accounts (SMAs) to investors again.

If you are interested in my services in the future drop me a line at info@jackhbarnes.com and I will get in touch.

Unfortunately for Money Morning “Buy, Sell or Hold” readers, there is no way I can legally continue writing the column and will sincerely miss doing so. The gracious team I’ve worked with agreed to release me from my contract at the end of March, so I can focus on clients’ expectations again.

Again, thank you to Mike and Bill for the opportunity. Thank you also to loyal readers, who I hope continue reading what I’ll be publishing here and interacting with me in the future. You’ve given me more than you’ll ever know.

Every place to stop is also a place to start.  Another trip begins.  I hope you’ll join me.

The energy industry has the appearance that it is about to undergo a major shift in pricing structures again. We saw it lately with the spread between crude and NG blowing out. We have seen signs of it happening in Brent and WTI before, and I expect we will see new signs of it again.

To be clear, we could see extremely expensive Brent oil, as international supply fears increase with tension in Iran. This would be happening while the price of WTI, a lighter sweeter standard, crashes in U.S. terms due to its own oversupply and lack-of-demand issues.

This would all be happening under a backdrop of world markets bidding for refined products from a U.S. export-happy refining complex. This would lead to U.S. gasoline prices hitting all-time highs, while refinery complexes in the U.S. Midwest would have the highest profit margins in their history.

The U.S. Midwest is growing its own domestic sources of oil, while its own capacity to ship the oil out is limited. This causes a bottleneck in exports in the region. This is causing the price locally to crash.

The planned refinery work in the Midwest has lowered the take-off demand for Bakken oil. This is happening inside of a window of time while the Bakken production sets all new records every month.

This is causing the price of oil in the Midwest to crash in localized markets, as the take-off capacity does not equal the supply of new barrels. The region is buried in supply, all of which is now seeking a path to the Houston refining complex.

The price difference of an equivalent grade of oil in Bakken Terminals & Louisiana terminals is now $40. This imbalance in like qualities will generate a short term arbitrage trucking bonanza, as the profit per trip approaches silly levels.

I expect to hear about a fleet of white trucks driving loads of crude oil from the Midwest to the refining complexes with accessible pipelines capacities. You don’t have to drive it all the way there, to deliver it.

I wish I had a fleet of modern fluid haulers right now. There is more oil supply in the Bakken than local demand, and that won’t change much when the refinery’s turn around. The Bakken supply is still growing every month, and will for a while.

The growth in rail take-off capacity will not keep up with the growth in new oil production in the near to intermediate term. This will lead to price differentials that will last longer than people expect. There is always a profit to be made when these events happen. It will be interesting to see who ends up owning those fleets of white trucks.

Just like the old gold rush stories of stores making more than people digging for gold, there just might be more money made in shipping the oil by truck, than there is in producing or refining it. As they say, this could get interesting in the near-term.