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This blog is in response to many readers comments about jobs moving overseas.

Example 1: A friend losing his job.
We have a friend here in Colorado who works for a services company. He has been asked by his American management to train his replacement in the Philippines and when that is completed he will be laid off. The conventional perspective is that many jobs are moving to India & China, but in this example my friend’s job is moving to the Philippines.

Lesson 1: The problem is with us. This example illustrates that the real problem is not the BRIC or other countries. It is that many American managers have found it easier to remain profitable by procuring cheaper overseas talent than expensive local talent.

Example 2: ICL in the 1970s.
Let me give another example. In the 70s, ICL was a very big computer company in the UK. They were losing money and brought in someone from Texas Instruments to turnaround the company. I forget his name. He did a good job and increased the profitability of the company, but in doing so he dropped ICL’s internally developed chip and replaced it with a Fujitsu chip.

After completion of the turnaround ICL shareholders wanted to sell the company. They found that even though the company was very profitable nobody but Fujitsu would consider buying the company. Why? Because ICL was dependent on Fujitsu chips, and from the perspective of value creation it was no long an independent company but an extension of Fujitsu.

Lesson 2: We are handicapping the value of our business: So all this outsourcing of talent is in reality working against the long term advantage of the shareholders, because who wants to buy a company with many expensive senior managers, many technology boxes and most of the talent 6,000 miles away? This in my opinion is short sightedness. But people have the right to make mistakes. Unfortunately these mistakes can be very expensive for other people, their employees.

Lesson 3: We cannot legislate good business decisions.

Example 3: Texas Instruments (TI) Daily Factory Starts (DFS) team in the 1990s.
I was the architect of Texas Instruments’ Daily Factory Starts (DFS) factory scheduling system. This program was TI’s worldwide top ranked project for 1991 and 1992. This system, built from scratch on a theoretical basis not found in other ERP systems, revolutionized capacity allocation in a 3,000 SKU factory capable of producing up to 6,000 SKUs. It reduced work-in-progress from 5 day to 3 days or a savings of $8.2 million for TI Malaysia and TI Philippines.

What happened? The only three people who designed, developed and implemented this project left within 12 months of completion. Imagine that! All 3 of us left. Needless to say even TI made some mistakes. TI did not sufficiently recognize any of us for the ingenuity & work we had put in. And because we reported to a third country management team, corporate had little say in the matter. I am told that the project was folded in 1994.

Lesson 4: Program discontinuity risk: One very substantially increases the risk of program discontinuity when talent is procured from third party companies, and even more so when procured from overseas. Unless you are a big company like Microsoft, GE, or IBM who can have multiple teams concurrently working on similar programs, procuring talent from outside the company is something you have to think through very carefully.

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Disclosure: I’m a capitalist too, and my musings & opinions on this blog are for informational/educational purposes and part of my efforts to learn from the mistakes of other people. Hope you do, too. These musings are not to be taken as financial advise, and are based on data that is assumed to be correct. Therefore, my opinions are subject to change without notice. This blog is not intended to either negate or advocate any persons, entity, product, services or political position.

Contact: Ben Solomon, Managing Principal, QuantumRisk

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Here is another positive. My blog post TARP’s Possible Role in Jobs Growth was published by the syndicated news service RiskCenter.

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Disclosure: I’m a capitalist too, and my musings & opinions on this blog are for informational/educational purposes and part of my efforts to learn from the mistakes of other people. Hope you do, too. These musings are not to be taken as financial advise, and are based on data that is assumed to be correct. Therefore, my opinions are subject to change without notice. This blog is not intended to either negate or advocate any persons, entity, product, services or political position.

Contact: Ben Solomon, Managing Principal, QuantumRisk

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I am very pleased to see that Michael Corkery of the Wall Street Journal’s Deal Journal has similar views to a blog I posted TARP’s Possible Role in Jobs Growth.

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Disclosure: I’m a capitalist too, and my musings & opinions on this blog are for informational/educational purposes and part of my efforts to learn from the mistakes of other people. Hope you do, too. These musings are not to be taken as financial advise, and are based on data that is assumed to be correct. Therefore, my opinions are subject to change without notice. This blog is not intended to either negate or advocate any persons, entity, product, services or political position.

Contact: Ben Solomon, Managing Principal, QuantumRisk

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QuantumRisk is having a one-day event:

Event: Answer Your Business Questions
Topics: Strategy, Re-engineering, Financial & Risk Modeling
Price: No Charge
Date: December 14, 2009
Time: 9:00 am to 5:00 pm Mountain Standard Time
Venue: Over The Phone 303-618-2800

Email me (benjamin.t.solomon@QuantumRisk.com) your contact information and a brief summary prior to your call so that I have some idea of who you are and why you are calling.

If you don’t get through (lines are busy) and you have emailed your contact information, and I will call back on the next available business day.

We are doing this to celebrate the end of the recession, Christmas and New Year.

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Disclosure: I’m a capitalist too, and my musings & opinions on this blog are for informational/educational purposes and part of my efforts to learn from the mistakes of other people. Hope you do, too. These musings are not to be taken as financial advise, and are based on data that is assumed to be correct. Therefore, my opinions are subject to change without notice. This blog is not intended to either negate or advocate any persons, entity, product, services or political position.

Contact: Ben Solomon, Managing Principal, QuantumRisk

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To get jobs growth going, maybe what is required is a business solution and not an economic solution.

The exceptions are people like Ben Bernake who did a marvelous job of reducing the severity of this recession. Even then Bloomberg reports (05/29/09) that Bernanke’s efforts to bring down borrowing costs to revive the housing market and help the economy are stalling.

Let’s review TARP to find some answers. TARP, issued as preferred stock in the banks’ balance sheet, is tax payers’ public funds used to cushion private shareholders bank balance sheets so that the difference between the banks’ assets and liabilities does not fall below a specific value (at best) or go negative (at worst); because Assets – Liabilities = Equity.

As reported by the Washington Post (07/20/09), the special inspector general overseeing the government’s financial rescue program said that “many of the banks that got federal aid to support increased lending have instead used some of the money to make investments, repay debts or buy other banks”.

What TARP was meant to do was to give banks time to fix the Asset side of the Balance Sheet. If banks had to mark to market, my guess would be that their Assets were about 25% smaller than on July 2007. This suggests that at the worst period during the recession some banks would have had an insignificant or negative equity on the Balance Sheets.

With hind sight this inference makes sense for 2 reasons. (1) There was a huge outcry around April 2009 by the banking industry to move away from mark-to-market rule. (2) The special inspector general report mentioned earlier.

Therefore, we see that the role of TARP was to ensure that bank Equity would remain positive and above a specific Asset % and nothing more.

Now what the banks did with TARP makes business sense too, because TARP increased some banks’ Equity in such a manner that they needed to adjust the Asset – Liabilities side of the equation; that meant reducing Liabilities or “repay debts” and increasing Assets or “make investment” and “buy other banks”.

Could we blame the banks for making “good” business decisions to secure their own safety having received so much cheap money with no strings attached? Let’s flip sides, would you as a banker give free money to your customers?

Let’s think about this some more. The only way banks are going to stay profitable in an underperforming economy is to (1) shed more banking jobs, (2) close more branches, (3) foreclose more properties & (4) reduce risk of lending by reducing lending. All are undesirable outcomes. I suspect that even banks forget that they too need a functioning economy to be profitable.

It appears that the previous Treasury Secretary Paulson’s primary objective was to save the banking system, not the economy, and therefore did not attach any conditions to the TARP funds. I believe the thinking was that this was to be a financial transaction only, to save some banks.

By the time Secretary Geithner took over, some of the initial panic had subdued. There did not seem to be the need to push for more conditions. Even if one wanted, what additional conditions would one attach to the TARP funds? This was a new situation and everyone was learning on the job.

Looking back we can clearly see that TARP’s weakness lay in not aligning the banks’ interests with the tax payers’ interests. Banks are the primary source of credit for a functioning economy, and if after they were rescued, they continued to withdraw credit from the economy then something is amiss. Fed’s Non Revolving Credit Outstanding shows that until recently non-revolving credit had been shrinking. But the recent blimp could be due to the clunkers and other such programs and not so much a revival in bank lending.

Do you remember “what is good for GM is good for America”? We should not make that mistake with the banks either.  Now this is our challenge, aligning banks’ interest with America’s.

The banks’ balance sheets provide an answer as to how to align the banks’ interest with America’s interests. Monitor banks’ business loans and mortgage assets and implement an additional TARP condition that banks cannot return their TARP borrowings until their business loans and mortgage assets have increased by 25% (or some percentage the economist feel safe with). By this rule the government does not tell the banks how to run their business. It tells the banks that the government only recognizes that the banks are healthy functioning members of the economy when they have shown that they can increase these critical assets by 25%.

This rule will immediately stop banks from adjusting their balance sheets by raising capital without growing their business. Raising capital is equivalent to substituting TARP dollars for private money and does not prove that banks will avoid previous mistakes. This rule will (1) cause banks to focus on their critical role of credit provider for the economy. (2) Buoy home prices because spatial correlations dictate less foreclosures will put less downward pressure on neighboring home prices. (3) Facilitate a greater tolerance for mortgage delinquencies for those who have lost their jobs for reasons beyond their control, and therefore fewer foreclosures.

We need to take into consideration that most banking practices are derived from experience in a functioning economy, when everything else is going good. This recession is the exception to those practices and needs to be viewed in a different light.

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Disclosure: I’m a capitalist too, and my musings & opinions on this blog are for informational/educational purposes and part of my efforts to learn from the mistakes of other people. Hope you do, too. These musings are not to be taken as financial advise, and are based on data that is assumed to be correct. Therefore, my opinions are subject to change without notice. This blog is not intended to either negate or advocate any persons, entity, product, services or political position.

Contact: Ben Solomon, Managing Principal, QuantumRisk

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Someone on LinkedIn brought this to our attention. Hope you enjoy it.

It is just amazing that there are so many ways to ‘calculate’ an answer in a consistent manner. Even the ‘wrong’ way provides a consistently ‘right’ answer, and therefore must be ‘right’? Makes you wonder what else are we doing wrong that looks right!

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Disclosure: I’m a capitalist too, and my musings & opinions on this blog are for informational/educational purposes and part of my efforts to learn from the mistakes of other people. Hope you do, too. These musings are not to be taken as financial advise, and are based on data that is assumed to be correct. Therefore, my opinions are subject to change without notice. This blog is not intended to either negate or advocate any persons, entity, product, services or political position.

Contact: Ben Solomon, Managing Principal, QuantumRisk

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I recently had a discussion with a respected colleague of mine. It got me thinking about the many differing points of view in finance. My colleague accepts that regime change is a correct phenomenon in financial time series, and you will find many published articles in respected journals proposing how to deal with this regime change. I might also add the many quants accept regime change.

And here we differ. I do not accept regime change. I know from past experience building time series forecasting models that regime change is model misspecification. Let me show you 3 graphs that support my point of view. Clearly Fig 1 is a linear trend.

Figure 1: Time Series from Period 245 to Period 300

Figure 2: Time Series from Period 0 to Period 1000

However, when we expand the range of the time series to between 0 and 1,000 (Fig 2) the linear trend of Fig 1 now becomes a regime change from a level around 0 prior to period 200 to a new level of about 7 after period 350. This must be proof of regime change. No? But wait.

Figure 3: Another time series.

Figure 3 is another example of regime change. Prior to period 150 the level is around 0, between periods 170 and 270 the level is about 110, and between periods 290 and 400 the level is about 230. This would be considered an example of two regime changes.

Because I generated both data sets I can inform you that Figure 3 was generated by Normally distributed random noise and nothing more. Figures 1 & 2 were also generated by Normally distributed noise and with a trend inserted between periods 250 and 300.

First lesson. A continuous function time series can present itself as a regime change when it is not, but in real life we cannot ‘rerun’ the time series to test if regime change will recur.

Second lesson. Statistical tests will affirm that regime change did occur when no regime change was present.

Third lesson. Figure 1 is a subset of Figure 2. Therefore, our interpretation of the data depends on our perspective.

Fourth Lesson. Therefore, my experience with time series would suggest that regime change is model misspecification.

Fifth Lesson. Even though economics & finance borrows heavily from the scientific method it is still an art.

Take care,

Ben

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Disclosure: I’m a capitalist too, and my musings & opinions on this blog are for informational/educational purposes and part of my efforts to learn from the mistakes of other people. Hope you do, too. These musings are not to be taken as financial advise, and are based on data that is assumed to be correct. Therefore, my opinions are subject to change without notice. This blog is not intended to either negate or advocate any persons, entity, product, services or political position.

Contact: Ben Solomon, Managing Principal, QuantumRisk

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When I was at Texas Instruments, we were told that nobody is indispensable. If Dimon leaves JP Morgan and the bank’s share drop, then he did not do a good enough a job at succession planning at the bank.

The real issue is the rumored replacing of Tim Geithner. We need to ask ourselves why the rumor. It is because unemployment has exceeded 10% and still increasing, and this can allegedly be a liability to the Obama Administration in the coming elections.

However, if we look at history, neither the Democratic nor the Republican Administrations have in the past recovered from a similar unempolyment spike at an average rate better than 0.06% per month. Therefore, what is required is a collective change to historically untried policies rather than a change in personalities.

The problem then is if Dimon cannot solve this unemployment problem (and he won’t if he does not do something radical), who are the Democrats going to blame next?

 

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Disclosure: I’m a capitalist too, and my musings & opinions on this blog are for informational/educational purposes and part of my efforts to learn from the mistakes of other people. Hope you do, too. These musings are not to be taken as financial advise, and are based on data that is assumed to be correct. Therefore, my opinions are subject to change without notice. This blog is not intended to either negate or advocate any persons, entity, product, services or political position.

Contact: Ben Solomon, Managing Principal, QuantumRisk

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There is a nice story developing in the $16.7 billion Kraft bid for Cadburys’. There are possibly four players in this deal to be, Cadbury, Hershey, Kraft and Ferrero.

And there are some big time names advising the players, Akeel Sachak of Rothschild, Byron Trott of BDT Capital Partners.

In my opinion Hershey does not have what it takes to out bid Kraft so Hershey would need to develop alternative strategies. Second, Cadbury & Hershey don’t mix, not yet anyway. They tried in 2007 and failed.

This is the case of the small fish swallowing the big fish as Hershey’s market capitalization is $8.3 billion, Cadbury’s $18.1 billion and Kraft’s is $39.4 billion.  So that tells us quite a few things:

1. Hershey views the Kraft’s Cadbury bid as a threat to its long term independence. That is if Hershey does not succeed it will soon be bought out by someone else.

2. Hershey’s does not have the global reach that Kraft and for that matter even Cadbury has. Hershey generates 93% of sale in North America, while Cadbury has 16%.

3. A Kraft purchase of Cadbury would turn Cadbury from friend to foe overnight, and one with a formidable distribution network in the United States.

4. Hershey’s 93% North American sales says that Hershey cannot compete overseas. Hershey needs Cadbury more than Kraft needs Cadbury. Don’t get me wrong. This is not about distribution networks even though that is important. If, like me you have lived on both sides of the Atlantic, you know American chocolates don’t cut it when compared to European chocolates. Hershey needs the branded recipe.

Hershey needs Cadbury and will pay more.

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Disclosure: I’m a capitalist too, and my musings & opinions on this blog are for informational/educational purposes and part of my efforts to learn from the mistakes of other people. Hope you do, too. These musings are not to be taken as financial advise, and are based on data that is assumed to be correct. Therefore, my opinions are subject to change without notice. This blog is not intended to either negate or advocate any persons, entity, product, services or political position.

Contact: Ben Solomon, Managing Principal, QuantumRisk

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Many unintended consequences in business & finance occur because upside (profitability) and downside (loss) risk have very different characteristics.

Background
In 2007 I sifted through 330,000 RMBS (Residential Mortgage Backed Securities) assets or loans with the purpose of developing a default & loss econometric model that would enable my then employer differentiate between good and bad RMBS bonds.

I had to do a lot of data structuring and clean up to standardize incoming data from about 20 different servicers. I should say data structuring and data scrubbing. And after that sift through this asset data set to filter out the bad data. So you can imagine the amount of work that went into this.

My strategy to identify the loss quality of a bond was to use the origination and close data to forecast future losses. Why? Because once you have purchased the bond you are stuck with whatever losses that unfold.  If this was possible we could very quickly eliminate the poor quality bonds, and use cash flow methodologies (more on this in a later blog) to evaluate the better quality bonds. We did not want to expend effort valuing poor quality bonds.

Dichotomy of Metrics
Well, at least that was the theory. What went wrong? In residential mortgages FICO scores are a major component, if not the primary driver for assessing future default behavior. I found that for residential mortgage FICO scores at origination were poor predictors of future defaults. How? Build two probability distributions of FICO scores. The first is a distribution of FICO scores of the borrowers at origination for all assets. The second is the distribution of the FICO scores at origination for defaulted assets only. You could not tell the difference between the two distributions!

Bewildering. Was there an analogy in other areas of finance? Yes. Company pro forma profitability analysis are good predictors of future profitability, but they are poor predictors of severe losses or bankruptcy risk. To get a handle on future company bankruptcy risk one requires a tool like Altman’s Z-Scores.

Here we observe a dichotomy in forecasting characteristics. On the one hand pro forma informs us of future profitability and on the other hand Altman’s Z-Scores informs on bankruptcy risk. We concluded that FICO scores behave like pro forma profitability, that they are good predictors of success but poor predictors of defaults.

I must add that unlike investment bankers and fund managers who are focused on upside risk or profitability, my career in financial services has been focused on downside risk. Therefore I did not test if FICO scores are good predictors of success.

When we recognized this dichotomy we abandoned RMBS bonds as a viable investment vehicle. But this story does not end here. I have an extensive business reengineering background and investigated how FICO scores are generated.

How Credit Cards Drive FICO Scores
From a business process perspective recent FICO scores are generated by your credit card issuer. Really. You the card holder use your card to transact purchases. In so doing you create debt. How much of this debt you pay down, how quickly, etc., is reported to the rating agencies. This reporting provides an insight into your debt payment characteristics which the rating agencies convert into FICO scores. FICO scores appear to predict defaults because they are adjusted downwards as your credit card payments deteriorate. That is, in my opinion, FICO scores have a limited window of about 90-days within which they work, but by then it is too late for the card issuer. Or no credit card visibility no FICO adjustments.

Here is the weak link in this whole business process. Without your credit card spending and payments reported by your card issuer, the rating agencies would not have a clue what your recent credit rating should be.

Take 2 people John & Jay. John has house and car payments and uses his credit card for all his purchasing transactions. Jay also has house and car payments, but he only uses cash for his purchasing transactions.

Now both have suffered a partial loss of income. They both continue to make house and car payments. Therefore the ratings agencies cannot tell from these payment that there has been a partial loss of income. Both reduce their spending to manage within their new realities. But John has now slowed his credit card payments. The rating agencies see this and are able to adjust John’s FICO scores accordingly but not Jay’s.

The use or not of credit cards provides asymmetric information to rating agencies. Now guess what happens as credit card companies ramp up interest rates, consumers pay down their card debt and stop using their cards.

Unintended Consequences
All manner of unintended consequences occur.

1. The banking industry loses it recent FICO information for a much larger proportion of the population.

2. Consumers do get penalized with lower FICO scores for not having recent payment histories.

3. First time home buyers will face higher rates because they don’t have sufficient recent history.

4. FICO scores are no longer as “effective” as they were “supposed” to be.

5. Because of this additional “FICO risk” for the same “risk” bonds with credit card debt should trade at a discount to bonds with residential mortgages which in turn should trade at a discount to CMBS bonds.

6. As I had stated in my Feb/02/09 post Risk-Reward is Non-Linear, increased rates will increase defaults. The unintended consequence of this is that banks that have rushed to increase rates to 30% before the new laws come into effect, will have locked themselves into a population demographics that experiences a higher default rate. Therefore we can expect to see an increase in credit card losses.

Summary
I’m sure there are a lot of very smart people in the credit card and rating industries, but… This situation is not dissimilar to what I observed as a management consultant reengineering manufacturing companies – one may have the best, the brightest and the most experienced managers but surprisingly when they come together at their management meetings they do strange things.

There needs to be a better way to address bank losses on credit cards and a better way to treat customers. Remember your customers are not your enemies.

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Disclosure: I’m a capitalist too, and my musings & opinions on this blog are for informational/educational purposes and part of my efforts to learn from the mistakes of other people. Hope you do, too. These musings are not to be taken as financial advise, and are based on data that is assumed to be correct. Therefore, my opinions are subject to change without notice. This blog is not intended to either negate or advocate any persons, entity, product, services or political position.
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