Credit Downgrade of USA and Triple A Whining

As a person trained , deployed and often asked to comment on macroeconomic shenanigans- I have the following observations to make on the downgrade of US Debt by S&P

1) Credit rating is both a mathematical exercise of debt versus net worth as well as intention to repay. Given the recent deadlock in United States legislature on debt ceiling, it is natural and correct to assume that holding US debt is slightly more risky in 2011 as compared to 2001. That means if the US debt was AAA in 2001 it sure is slightly more risky in 2011.

2) Politicians are criticized the world over in democracies including India, UK and US. This is natural , healthy and enforced by checks and balances by constitution of each country. At the time of writing this, there are protests in India on corruption, in UK on economic disparities, in US on debt vs tax vs spending, Israel on inflation. It is the maturity of the media as well as average educational level of citizenry that amplifies and inflames or dampens sentiment regarding policy and business.

3) Conspicuous consumption has failed both at an environmental and economic level. Cheap debt to buy things you do not need may have made good macro economic sense as long as the things were made by people locally but that is no longer the case. Outsourcing is not all evil, but it sure is not a perfect solution to economics and competitiveness. Outsourcing is good or outsourcing is bad- well it depends.

4) In 1944 , the US took debt to fight Nazism, build atomic power and generally wage a lot of war and lots of dual use inventions. In 2004-2010 the US took debt to fight wars in Iraq, Afghanistan and bail out banks and automobile companies. Some erosion in the values represented by a free democracy has taken place, much to the delight of authoritarian regimes (who have managed to survive Google and Facebook).

5) A Double A rating is still quite a good rating. Noone is moving out of the US Treasuries- I mean seriously what are your alternative financial resources to park your government or central bank assets, euro, gold, oil, rare earth futures, metals or yen??

6) Income disparity as a trigger for social unrest in UK, France and other parts is an ominous looming threat that may lead to more action than the poor maths of S &P. It has been some time since riots occured in the United States and I believe in time series and cycles especially given the rising Gini coefficients .

Gini indices for the United States at various times, according to the US Census Bureau:[8][9][10]

  • 1929: 45.0 (estimated)
  • 1947: 37.6 (estimated)
  • 1967: 39.7 (first year reported)
  • 1968: 38.6 (lowest index reported)
  • 1970: 39.4
  • 1980: 40.3
  • 1990: 42.8
    • (Recalculations made in 1992 added a significant upward shift for later values)
  • 2000: 46.2
  • 2005: 46.9
  • 2006: 47.0 (highest index reported)
  • 2007: 46.3
  • 2008: 46.69
  • 2009: 46.8

7) Again I am slightly suspicious of an American Corporation downgrading the American Governmental debt when it failed to reconcile numbers by 2 trillion and famously managed to avoid downgrading Lehman Brothers.  What are the political affiliations of the S &P board. What are their backgrounds. Check the facts, Watson.

The Chinese government should be concerned if it is holding >1000 tonnes of Gold and >1 trillion plus of US treasuries lest we have a third opium war (as either Gold or US Treasuries will burst)

. Opium in 1850 like the US Treasuries in 2010 have no inherent value except for those addicted to them.

8   ) Ron Paul and Paul Krugman are the two extremes of economic ideology in the US.

Reminds me of the old saying- Robbing Peter to pay Paul. Both the Pauls seem equally unhappy and biased.

I have to read both WSJ and NYT to make sense of what actually is happening in the US as opinionated journalism has managed to elbow out fact based journalism. Do we need analytics in journalism education/ reporting?

9) Panic buying and selling would lead to short term arbitrage positions. People like W Buffet made more money in the crash of 2008 than people did in the boom years of 2006-7

If stocks are cheap- buy. on the dips. Acquire companies before they go for IPOs. Go buy your own stock if you are sitting on  a pile of cash. Buy some technology patents in cloud , mobile, tablet and statistical computing if you have a lot of cash and need to buy some long term assets.

10) Follow all advice above at own risk and no liability to this author 😉


Sub Prime Crisis: A Risk Analyst view from the Trenches

Pricing of Future Securities and Derivatives Based on Mortgage Assets are all about projecting delinquency rates , and it depends on the analysts to be either conservative in projecting a high rate or optimistic in a low rate.

Based on these projections , the assets are priced, packed up in SPV’s or collateralized, and options priced. Now Senior Management gets a big bonus if they sell off their balance sheet like this, and business is able to use cash generated to create higher loans….. so they lean on the analyst to Continue reading “Sub Prime Crisis: A Risk Analyst view from the Trenches”

Keynes and Milton Friedman

The current economic situation is as follows –

1) Growth is high – at 8-9 % p.a

2) Inflation is even higher – at 11 % p.a

3) Inflation i s high for fuel , a huge importer (despite subsidies) and essential food items (a big importer.

4) Non -food credit growth is high (as per the Central Bank ..the Reserve Bank of India,RBI)

5) There is a general election next year , hence inflation is the top concern

6) Economy is dependent on services , and is sensitive to dollar depreciation. Inflow of investment and export dollars is almost matched by outflow for oil imports (nearly 70 %)

7) Equity markets are in a slump (down 25 % this year)

This has led to the RBI doing the following – clamp down on monetary supply by hiking key rates.

Situation is almost the same as the US except that the US has lower growth , nearly a recession , a distressed credit and mortgage market, and has big war expenditures.

Unfortunately  by clamping down on rates ,inflation is less likely to come down because both oil and food expenses are not discretionary expenses.By making capital goods more expensive, the manufacturers will likely pass the increased price to customers leading to demand slowdown first and price slowdown much later if at all. Oil and food will continue to be managed price items hence the subsidy bill on government is going to be higher thus leading to slower investment growth.It might just lead to a mortgage crisis in India as adjustable floating rates are now likely to touch 12 %.
By blindly following Friedman ‘s economic monetary policies of money control, the central banks are ignoring the fundamentals of the current crisis in which essential commodities are having increased prices, and growth is threated by global and financial market failures. Ironically these are conditions that have taken place almost 79 years ago in the macro economic event called Great Depression. A return to Keynesian economics and using the huge bulk up of stored dollars in foreign exchange funds to drive growth  rather than shrink money supply should be the way forward. It is necessary to grow out of this crisis rather than shrink and try and dodge it.

This will however require political leadership in driving long term infrastructure programs rather than short term monetary handouts and subsidies.

Need for Economists in Corporate India

Corporate India has been caught on surprise on many counts recently and most of them are macro economic events.

These have been namely credit rate hikes, inflation due to oil prices (consequent demand for better salaries and attrition) , market entry of new players and above all the rupee appreciation that shave off nearly 1000 basis points off the profitability of unhedged exporters.

Add to this the uncertainty in stock markets over remote events in the sub prime mortgage market in the United States that has actually led to many corporates getting below expectation results in their listing or Initial Public Offerings despite good fundamentals.

All these point to need for better corporate planning and strategizing for economic changes and events especially in a networked world.

Table 1-Top Macro Economic Events that caught corporate India by surprise and their impact

? Credit Policy Hikes by RBI 2006-2007 leading to expensive debt.
? Rupee Appreciation and RBI steps including curbs on ECB.
? Oil Prices and Inflation.
? US Mortgage Market, Effect on Global Equity Markets including India.
? SEZ Policy and impact on communities (this is more of socio-economic topic)

The primary impact of this has been exporters like Infosys missing their earnings guidance due to rupee appreciation, corporates like WNS having lower listed prices ,rising credit costs including for banks , and considerable rework of SEZ plans for corporates like Tatas and Reliance.

These are the biggest names in India, so the impact of lack of econometric planning and forecasting on smaller players is likely to be more.

Most corporates in advanced economies have business intelligence units and economic strategy and planning units. They are used mainly for forecasting sales using scientific quantitative methods like base driver models, time series models and regression models to predict and anticipate demand and align corporate supply and demand chains accordingly.

The usual audience for them is at CXO or Board level advisory positions.

In India while many corporates have started creating these units they are yet to gain the credibility and respect that they would have got in Western Companies.

Main reasons for these are as follows –
depth of Indian academia in application oriented research and their ability to adjust to corporate demands,
skepticism regarding modeling techniques most of which are complex for end users and corporate audiences ,
lack of investment in forecasting soft wares (like SAS , SPSS and even Excel/Solver ) and human resources in these units.

Most Indian corporates would rather hire five more sales managers than invest in two economists who would help create a much better forecast to help plan the corporate strategy.

This is partly due to historic mindsets and partly due to cultural risk aversion, as corporates engage in cost cutting, sales is looked upon as revenue units and planning units are cost centers. An additional complicating factor is that many companies still believe in push based sales, rather than pull based demand targets.

Table 2
Examples of Business Intelligence Units / Planning Units in Indian Corporates.

Muruguppa Group

Examples of Business Intelligence Units / Planning Units in other countries.

General Motors
British Telecom

An alternative for corporates unwilling to go into full fledged economics planning units is to become subscribers for customized content providers by third party providers.

This content could be in the form of business research, market research and segmentation studies, predictive models or even economics newsletters. The chief drawback to this is that due to the outsourcing and Knowledge Process Outsourcing boom, sales margins for third party content providers is much more when catering to the global market.

However even for the outsourcing sector it would be advisable to keep a foot in the domestic market, keeping in mind long term growth plans of Indian corporates and the ability to build domain expertise much better while catering to onshore Indian clients rather than offshore global clients. In the short term, these would be lower margins but it would help in building the domain expertise necessary for them to move up the value chain.

As the Indian economy is poised for sustained growth, the size and scale of this domestic demand for economics content would likely scale up manifold. Indian corporates should actually benchmark their demand planning and economic units from international players and partners

Butterfly Effect and Butterflies in my stomach

Chaos in the Markets – How a home loan default in America hurts investors in India

The recent crisis in global equity markets as a result of the sub prime mortgage meltdown in the United States has caught many investors by surprise. Economic fundamentals of most global markets had no major changes yet the disturbances were severe enough to erode and nullify recent rallies in the market. The subsequent panic caused in world currency and equity markets were severe enough to raise multiple levels of concerns in central banks, governments and the investors. What analysts worldwide called a re-rating of risk appetite has led to severe loss of appetite for many investors.

While on one hand it points to the increasingly close knit network of the world financial economy with all its subsequent gains in efficiency and capital investment, it also points to a new area in evaluating equity valuations in varying times of global risk. It is thus necessary for the Indian investor to understand not only those markets in the world are now strongly co related but also the macro economic drivers that affect various markets including hedge funds , sub prime markets, and the US federal bank’s unparallel influence beyond its borders.

Introducing the Butterfly Effect- The butterfly effect is a concept in chaos theory. It refers to the idea that a butterfly’s wings might create tiny changes in the atmosphere which could lead to a tornado appearing somewhere else. Thus changes which apparently seem random are actually caused by small changes in the initial system. The flapping of wings represents a small change in the initial condition of the systems.

Similarly the loosening of credit in the United States sub-prime mortgage system partly due to the increased liquidity in the system and collateralization of loan based collaterals to financial intermediaries has caused the widespread chaos in the worldwide financial systems. Simply put, there was too much money in the market that mortgage companies could easily borrow, and transferring risk was also easy due to securitization of these loans. As a result, while financial discipline was lost while lending to a booming real estate market, the risk was systematically transferred and in fact hidden during the collateralization process to the whole financial system.

Quite notably, the about turn by the United States Federal Bank also caught the market by surprise. By cutting the inter –bank lending rateand the later the key Fed rate, the Fed ,led by Bernanke in it’s first crisis since the post Alan Greenspan era, effectively did a volte-face on it’s previous stand of waiting and watching. Indeed markets in Alan Greenspan’s time used to talk of the Greenspan put – basically a concept that is asset prices tumbled too far the Federal bank would step in to take control.

Note: This has important lessons for even Indian lender. In the United States median house prices almost doubled from 1993 to 2005, while incomes rose just 49 percent. In India, the real estate boom has been even faster and thus the increased danger of the bubble bursting.

The recent crisis also pointed to the fact that Indian Markets continue to be sensitive to downward global cues, to the point of ignoring value investing. The concept of value investing was created by Graham –Dodd and most successfully used by Warren Buffet. It said that it was better to concentrate on the fundamentals of the company and expected cash flows rather than try and anticipate its future price. The metric used was the long term rice to earnings ration of a particular stock. Thus the ups and downs of the market have actually taught both the retail and the institutional investor the fundamentals of investing on actual value rather than be caught up in bearish or bullish swings.

At this point, the recent record fund raising by mutual funds is also an increased area of concern. The regulators led by AMFI, SEBI and the RBI should focus that mutual funds are sold transparently with easy to understand tables of disclosures, and adequate amounts of effort is spent on educating the common man, who is the worst affected in any stock market bust.

Predictive Forecasting in Commercial Applications

Most organizations tend to have a sales plan or forecast for the next 1 year.This is done for internal planning as well as give guidance to financial investment analysts covering the listed company.

However a lot of organizations use simplistic linear models of

1) either growth based on previous history (Last year Sales * Factor of forecast (e.g 10 % growth in sales) -TIME SERIES APPROACH


2) growth based on macro economic causal factors (e.g economy is in recession hence sales will grow by 3 %) REGRESSION BASED APPROACH and

3) A consensus of industrial factors (We have spare capacity of 10 % so we will likely slash prices and have sales growth of 2 % but profit growth of -3%) DELPHI BASED APPROACH (this is also based on bottoms up market feedback and top down sales pressure).

A better approach is to combine all these approaches in one or different models .

This can help build a much more robust forecasting model for organizations using nothing more than simple combination of excel cells.

The following model assumes only seven factors and tries to build a stable and relatively easy to understand forecast model.

Forecasted Sales for this quarter =

Historic Sales for this quarter last year *A1

+ Historic Average Sales for this quarter for past three -five years (based on industry cycle ups -downs)*A2

+ Historic Sales for this quarter/Actual Sales of Last Quarter( for seasonal factors )*A3

+Causal Factor 1 ( Eg. Outsourcing is likely to grow by 15 % in this year) *A4

+Causal Factor 2 (Foreign Exchange Movement.Dollar is likely to depreciate by 10 %)*A5

+ Causal Factor 3 (Our bench strength is likely to grow by 3 % in this quarter)*A6

+ Percentage Error Factor *A7 (There will always be +-5 to15 % error in forecasts.Capturing this error also helps provide a feedback loop for planning).

Here A1- A7 are constants

In order to get actual values of A1-A7 , run this a regression (use the add-in and tools menu in excel) on actual data for past three years quarters (keeping last six months seperate)

Then run the actual equation on last two quarters and check for actual error. If error exceeds the comfort level (+-3 % for critical industries and +-15 % for harder to predict industries) . Iterate the last two steps till you get a good equation.

Then substitute in the 7 factor predictive model to build your simple and robust sales plan for this quarter.

Happy forecasting !!!

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