Mitigating the Global Food Crisis

There are 860 million people (~13% of the world's population) who are suffering from chronic hunger. 90% of these people, reside in developing countries i.e: mostly in Africa, Parts of Asia, South America and Eastern Europe.

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According to the agenda of the June 2008 HIGH-LEVEL CONFERENCE ON WORLD FOOD SECURITY (centered on THE CHALLENGES OF CLIMATE CHANGE AND BIO-ENERGY):

• 'During the first three months of 2008, international nominal prices of all major food commodities reached their highest levels in nearly 50 years, while prices in real terms were the highest in nearly 30 years!' Over the last year, the global mean price of food has risen by 56%, with wheat rising by 92% and the average price of rice rising by 96%.

• The global food crisis 'is provoking social unrest across the developing world'. For instance in Somalia, where thousands rioted during the first week of May 2008; protesting for food. Food riots have also occurred in Indonesia, Haiti, the Philippines and Ethiopia.

It is clear that the escalating prices (of food commodities) threaten to plunge millions into deep poverty. If unchecked, this crisis has the potential to trigger a chain of apocalyptic events: it may draw us closer to extinction...

That's how serious it is!

Below is a graphical illustration showing real and nominal average food prices between 1961 and 2008:

Source: HIGH-LEVEL CONFERENCE ON WORLD FOOD SECURITY: THE CHALLENGES OF CLIMATE CHANGE AND BIOENERGY AGENDA. For more information see conference materials

Explanation of the graphical illustration: The vertical axis shows prices and the horizontal axis shows time in years (between 1961-2008). The navy-blue trajectory shows nominal price movements (of food commodities) between 1961-2008 and the lime-green trajectory shows price movements (of food commodities) in real terms, between 1961 and 2008. From the illustration you can see that real prices and nominal prices of food are equal in 2003. Between 2003 and 2008, both real and nominal prices increase at a pace that was last witnessed in 1974! In 2008 the nominal price of food is at its highest and the real price of food is at the same level it was in 1978.

...What's causing food prices to soar?

World Bank Agricultural Economist, Don Mitchell believes that bio-fuels are the chief cause of the upsurge of food prices. According to Mitchell, the growing use of food crops as raw materials for bio-fuel generation, combined with falling grain stocks, speculation in commodity markets and food export bans; contributed to approximately 75 percent of the 140 percent rise in food prices between January 2002 and February 2008. He also attributes 65 percent of the 140 percent increase in food prices, to the depreciating U.S. dollar, increasing energy prices and associated increases in fertilizer costs. Another factor that's fueling the price escalation, is climate change (caused by global warming). Climate change generally has an adverse effect on agricultural yields.

The above-cited factors generally have a 'reducing-effect' on the global supply of food, which generally causes food prices to increase (assuming constant food demand).

Below is a supply and demand model that illustrates the effect of the aforementioned factors on global prices of food:

Explanation the Supply and Demand Model: The vertical axis represents the global averages of food prices. The horizontal axis represents quantity of food demanded globally and quantity of food supplied globally. The downwardly sloping lime-green line represents the global quantity of food demanded, at various prices. Global supply of food (at various prices) before the bio-fuel revolution is represented by the upwardly-slopping navy-blue line labeled S1. The global supply of food after the bio-fuel revolution has started, is illustrated by the upwardly-slopping navy blue line labeled S2. Point b (Q1;P1) is the point of equilibrium between demand and supply of food, before the bio-fuel revolution. Point a (Q2; P2) is the point of equilibrium between demand and supply of food, after the bio-fuel revolution has started. The bio-fuel revolution reduces the supply of food from S1 to S2 and the point of market equilibrium shifts from Point b to Point a. At point a the aggregate quantity of food supply is Q2 at an increased price denoted by P2.

...How do we mitigate the crisis?

Answer: By increasing food supply (which in turn reduces food prices) through any, or a combination of the following:

• Channeling an increasing proportion of bio-fuel feedstock to the food industry. However, this may undermine the productivity of bio-fuel projects, which would adversely impact Kyoto Protocol-sanctioned pollution-reduction initiatives. In the diagram below, the increase in food production from a reduction in bio-fuel production is illustrated by a movement from Point a to Point b.

• Development and wide-scale implementation of yield enhancing technologies. This would boost global food output. Effective yield enhancing technologies have the likelihood of emerging from the field of Biotechnology (specifically genomics and proteomics) in the form of; high yielding, nutrient-rich, pest resistant, 'all-weather' crops. In the diagram below the increase in food production that accrues from technological development is illustrated by a movement from Points a and b to either Point d or Point e.

• Development of 'food alternatives'. Recent advancements in the field of nanotechnology have given us the power to manipulate matter--at it's most basic level--with great precision. We could use this technology to create chemical substance equivalents of food, that mimic real food in terms of; taste, appearance, nutrition, texture and smell: I believe that in the near future, we'll be able to harness the power of light energy, carbon dioxide and synthetic chlorophyll; to create edible nutrient rich carbohydrate foods in labs (at a lower cost and at a faster speed than nature)... Also, currently, stem-cell technology is used to grow cartilage and skin (for medical patients who need replacements) in petri-dishes. We can use that technology to grow meat (parts of cows, fish, chicken etc) in labs. This will help conserve grain (and land), that would otherwise have been used as an input for animal husbandry projects (which are generally 'grain-intensive'). This would avail more grain for human consumption. (Side Note: Sounds like a florid, quixotic statement; embedded in deep romanticism? Wait and see! The passage of time will validate my assertion). In the diagram below this increase in food supply from food alternatives. is illustrated by a movement from Points a and b to either Point d or Point e.
  

Explanation of the graphical illustration: The illustration above is a Production Possibilities Frontier (transformation curve) model showing the maximal combinations of bio-diesel and food, that the global economy could efficiently produce during a specific time period, with the use of scarce resources. The vertical axis represents various quantities of bio-diesel and the horizontal axis represents various quantities of food. A northward movement from any point on the graph, means that more bio-diesel is being produced, whereas an eastward movement from any point on the graph, means that more food is being produced. The two concave slopes are called transformation curves. They show the various maximal combinations of food and bio-diesel that the global economy can produce efficiently. Each respective transformation curve represents a different level of technology utilization; with the navy-blue trajectory showing the maximal combination of bio-diesel and food that can be produced with the current level of technology. The green trajectory shows the maximal combinations of food and bio-diesel that can be produced if a technological advancement occurs. Point f lies lower than the navy blue trajectory; a movement from Point f to point either Point a or b, means that producers have scaled-up their operations--using the current level of technology--to (efficiently) produce maximal combinations of food and bio-diesel. A movement from Point a to b means that producers who are already producing maximal combinations of food and bio-diesel (using the current levels of technology), are increasing food production at the expense of bio-diesel production. A movement from Points a and b, to either Point d or e means that farmers are using new yield enhancing technology to (efficiently) produce greater quantities of food and bio-diesel.

...How do governments; channel an increasing proportion of bio-fuel feedstock to the food industry, facilitate development and wide-scale implementation of yield enhancing technologies, facilitate development of food alternatives?

I think that the Food and Agriculture Organization of the United Nations should encourage its membership to set voluntary, legally binding food production targets: a food production treaty. The treaty should be an adapted (to food security) 'reverse-engineered' model of the Kyoto Protocol, that among other things, sets specific targets and deadlines for food production. A treaty of this kind will provide the moral impetus for tackling the global food crisis.

A carrot and stick approach has to be implemented to encourage parties to the treaty to comply i.e reward compliance and punish non-compliance. Financial penalties should be set to punish signatories who don't meet targets, and, tradeable 'Food Production Credits' (similar to carbon credits) should be awarded to parties that increase food production beyond a set benchmark.

'Food production credits' have the added benefit of inspiring research into yield enhancing methodologies, and, will encourage producers to adopt yield enhancing technologies rapidly i.e 'food credits' will reduce the 'bottleneck' between (yield-enhancing) technology creation and (yield-enhancing) technology adoption.

And so on, and so on, etc, etc :-) . The academics can takeover from here.

Media Elasticity of Stock Prices

This article alleges that Bear Stearns' collapse was concocted by diabolical 'invisible forces'... It would be improper to comment on the Bear Stearns debacle before SEC investigations are concluded, so I reserve all comments (on this conspiracy theory) until then!

As I was reading that article, I experienced a flash of insight: Speculative negative media coverage adversely affects a firm's stock price, regardless of what the firm's fundamentals say. I knew that of course, but I now understand this from a Mathematical (and Economic) perspective. I term this 'mathematical frame' (negative) media elasticity of stock prices . The concept that underlies the paradigm is not new, it has been discussed extensively in academic circles.

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In his research paper titled: Market and Individual Investors Reactions to Corporate News in the Media, Philipp Schmitz states that:

• '...The incorporation of information in prices is fairly fast. The main price reaction occurs on the day of the arrival of the new information.This price jump is especially large if the news coverage in the media is accompanied by ad hoc announcements made by the corporation itself. While there is only a very short-term post-event drift after good news, prices tend to drift for several days after bad news. The post-event trading volume is significantly higher than before the news for several days for good as well as bad news'.

This implies that negative media coverage has a sharper effect (than positive media coverage) on a firm's share price.


...The media can break a firm... And it can do this easily

Sustained negative (and baseless) media coverage can have a catastrophic effect on a firm's share price. To illustrate how: Baseless negative media coverage 'discounts' a firm's share price; which attracts a greater degree of speculative negative media coverage; which in turn causes a firm's share price to 'dive deeper' and so on. This self-reinforcing chain of causation continues to feed and magnify itself until:

• the media speculation is disproved or invalidated by changing macro environmental trends or by widely publicized developments in the underlying firm, or,
  

• it is curtailed by government intervention, through the use of legislative instruments, or,
  

• the media's speculative perspective becomes deeply ingrained within a society's collective consciousness; i.e society begins to take the negative media speculation as FACT. At this point, the firm's fundamentals begin to increasingly validate (previously baseless) media speculations i.e there starts to be a convergence of baseless media speculation and reality. When this happens, the firm's brand capital is increasingly decimated; its goodwill falls exponentially and the firm's financial health deteriorates rapidly. I don't know whether or not a firm can survive past this point, or,
  

• it just runs out of momentum because of an incomprehensible factor! (Irrational markets)

...Negative media elasticity of a stock price

Negative media elasticity (NMESP) of a stock price is the responsiveness of a firm's stock price to negative media coverage (of the firm).

A share price's NMESP is never fixed, it varies in response to changes in a firm's:

• Micro environment: These are factors that a firm has influence over, including its culture; its capital structure; its brand capital; its human resource mix; its public relations policy and its level of efficiency in general (to name a few). To lower its NMESP, a firm would have to 'improve' (..for lack of a better word) its micro factors.
  
• Macro environment: These are factors that a firm has very little to no influence over, including market volatility; societal openness; the elite media's editorial policy; the level of media technology the average person utilizes; and the number, level of activity & size of stock market participants.

A firm's NMESP is a function of its micro and macro environmental factors. Mathematically this can be expressed as:

NMESP = f(Ma; Mi)

Where :

NMESP is the negative media elasticity of a firm's stock price
f means a function of
Ma represents a firm's macro environmental factors
Mi represents a firm's micro environmental factors

...How does a firm's share price relate to negative speculative media coverage (in general)?

A firm's share price is inversely related to negative speculative media coverage i.e as negative speculative media coverage increases, a firm's share price decreases.

Below is a graphical illustration that shows an inverse relationship between a firm's share price and negative media coverage.

Explanation of the illustration above: The vertical axis represents a firm's share price movements and the horizontal axis represents percentage increases of (speculative negative) media coverage a firm receives. The inwardly curving navy-blue line represents the inverse relationship between a firms share price and the % increase of speculative negative media coverage it receives. From point a to b, the firm's share price falls very rapidly, a small increase in speculative negative media coverage causes a large decrease of the firm's share price. Between points b and c, speculative negative media has a reduced influence on the firm's share price. From point c to d, the firm's share price is no longer responsive to an increase in speculative negative media coverage, evidenced by the flat gradient between point c and point d.

To mathematically express the relationship between a firm's share price and the % increase of speculative negative media coverage it receives:

ShP = k/NSP

Where:

Shp is the firm's share price
k is a constant number
NSP is the % increase of speculative media coverage the firm receives

...To calculate a firm's Negative media elasticity of its stock price
(NMESP)

NMESP = % change of a share price divided by the corresponding percentage increase of negative media coverage the firm receives within a defined chronological period

Now I need to figure out how to use those equations to generate cash flows!

Carl Icahn's Battle Against Yahoo! Board

For the Open Letter to Yahoo! Shareholders click here
For the Definitive Proxy Statement click here

Lets see what happens....

How do you identify weak companies - Part 2 (stocks to short-sell)?

In the post titled How do you identify weak companies (stocks to short-sell)?, I stated that a corporation's fiscal stability can be ascertained through examining the relationship between its capital structure and its (micro and macro) environmental risks. If a corporation is 'fiscally stable', its risk in capital structure varies inversely with its (micro and macro) environmental risks.

In this post, I'm going to discuss how to use Multiple Discriminant Analysis (MDA modeling) to assess a firm's insolvency risk. The MDA indicator I'll discuss is a statistical harmonization of five weighted financial ratios--derived from a firm's balance sheet and income statement--called Altman's z-score.

So what is Altman's z-score?

It is a multivariate formula developed by Edward Altman to 'measure' a corporation's financial 'soundness'. Altman's z-score is a highly effective diagnostic tool, that helps to forecast a corporation's probability of entering bankruptcy within a two year period. This model has an accuracy rate ranging between 72%-80%, and studies show that it is universally applicable!

The five weighted inputs for Altman's model include:

1. Return on Assets ratio (ROA): which is equal to earnings before interest and taxation divided by total assets (EBIT/Total Assets). This ratio gauges how efficiently a corporation generates revenues from its assets.
2. Sales to Assets ratio: which is equal to sales divided by total assets (Sales/Total Assets). This ratio measures the efficiency of a corporation's sales and marketing function.
3. Equity to Debt ratio: which is equal to market value of equity divided by book of value debt. (Market Value of Equity/Book Value of Debt). This ratio measures a firm's level of leverage and is a general indicator of its capital structure. Note: The book value of debt gives an inflated picture of a firm's true leverage. For an accurate picture of a firm's leverage, use the market value of long term debt i.e the discounted present value of debt interest and principal payments.
   
4. Retained Earnings to Total Assets: which is equal to retained earnings divided by total assets (Retained Earnings/Total assets). This ratio shows the degree to which assets have been paid for by company profits.
5. Working Capital to Total Assets: which is equal to working capital divided by total assets (Working Capital/Total Assets). This ratio tests for financial distress.

Computing the z-score

Z= 3.3x1 + 0.999x2 + 0.6x3 + 1.4x4 +1.2x5

Where:

Z is the z-score
x1 is the Return on Assets ratio
x2 is the Sales to Assets ratio
x3 is the Equity to Debt ratio
x4 is the Retained Earnings to Total Assets
x5 is the Working Capital to Total Assets

From the equation you can see that the Return on Assets Ratio receives the highest weighting and that the equity to debt ratio receives the lowest weighting.

Interpretation of the z-score:

• If a firm has a z-score that is greater than 3, it is safe
• If a firm has a z-score that lies between 2.7 and 2.99, it is financially weak
• If a firm has a z-score that lies between 1.8 and 2.7, it has strong changes of entering into bankruptcy within a year
• if a firm has a z-score that is less than 1.8, it is in the danger zone
  

You've taken your sample of mis-financed firms [which have risk in capital structure doesn't vary inversely with the firms' respective (micro and macro) environmental risks] calculated their z-scores, then whats next?

I then take all the z-scores that are less than 2.7, categorize them into very narrow ranges and plot the normal distribution of the scores.

You'll have something that looks like this:

The normal distribution will ALWAYS be positively skewed. I suspect that this is because bankruptcy (for listed companies) is a rare occurrence. I then focus my attention on everything that lies to the left of the mean--the green zone on the graphical illustration. That's where the 'gold' is!

Possible effects of Sovereign Wealth funds' diversification into portfolios of common stock

"...Fox mentions that sovereign wealth funds are diversifying out of bonds and bank bailouts and into broad portfolios of common stocks..." Source: CNN Money Story on Ken Heebner of Capital Growth Management

This (the quote above) begs the question of effects this 'diversification' may have (in general)...

...Firstly (for the benefit of the uninitiated), what is a Sovereign Wealth Fund (previously called 'stabilization fund')?

William Megginson, author of the research paper titled: The Financial Impact of Sovereign Wealth Fund Investments in Listed Companies, defines a Sovereign Wealth Fund as; 'a pool of domestic and international assets owned and managed by governments to achieve a variety of economic and financial objectives, including the accumulation and management of reserve assets, the stabilization of macroeconomic effects and the transfer of wealth across generations'

SWFs originated from government investment vehicles established for revenue stabilization. The governments that set-up these 'stabilization investment entities' invariably depended on revenue streams from one underlying commodity e.g OIL.

According to Andrew Razanov's paper titled: Who Holds the Wealth of Nations (Central Banking Journal, Volume XV, Number 4), governments that set-up SWFs essentially aim to:

• 'insulate their budgets and economies from excess volatility in revenues'
• 'sterilize unwanted liquidity'
• 'build up savings for future generations'
  

Below is a graphical illustration showing the investment strategy (whether it's active/passive), transparency, source of reserves under management and size of the world's major SWFs:

From the graphical illustration above, you can see that there are 20 major SWFs in the world; 60% of which manage revenues originating from commodities; and that SWFs generally rank low on transparency.

SWFs manage an estimated USD2-3.5 trillion; 2% of the total size of equity and bond markets globally. In his paper titled: How Big Could Sovereign Wealth Funds Be by 2015?, Stephen Jen (Morgan Stanley Research Global), estimates that the AUM held by SWFs will grow at the rate of USD40 billion per year and that the total pool of assets managed by SWFs could reach USD12 trillion (10% of the current total of Global Financial Assets) by 2015. In my opinion, Jen's estimates are extremely conservative: the rapidly appreciating price of oil (and other commodities) could fuel an annual growth rate (in AUM) of at least USD50 billion per annum.

...On effects

In his research paper titled: The Financial Impact of Sovereign Wealth Fund Investments in Listed Companies, William Megginson suggests that the involvement of SWFs in listed companies is something to be worried about because (and this is according to his findings):

• 'SWFs are particularly likely to impose agency costs on acquired firms, since as state-owned funds their motives might not always be consistent with risk-adjusted profit maximization. In addition, by virtue of their lack of transparency, they could impose agency costs simply because of the uncertainty associated with their behavior as shareholders. Additional agency costs would then lead to a decrease in the value of equity'.

I believe that he may have arrived at the wrong conclusions because: 1) His research is based on a very small sample, 75 SWF transactions to be exact, and it is very unlikely that the analysis of a sample this small would produce statistically valid conclusions 2) He tracks the abnormal returns of SWFs for a period of 2 years; which I believe is too short a period. I believe that a period of at least 5 years would reflect the true impact of SWF investment.

In my opinion SWF investment into common stock can have the following effects:

1) Stabilizing markets:

Investment by SWFs in (public) equity markets may increase the stability (reduce volatility) of equity markets: Sovereign wealth funds typically 'go long' on sizeable chunks of shares, and, hold onto those shares for longer periods of time than most investor classes. These enormous share-purchases reduce the number of shares available for active trading--in the short to medium term--on the markets, which limits the extent to which share-prices fluctuate (upwards or downwards) in the short-term to medium term. Otherwise stated: this reduces share price volatility.

Secondly, SWFs typically invest large amounts of capital in times of acute market turmoil (they like buying cheap): which helps to moderate financial market downturns. For instance: during the 2007-2008 credit crisis, SWFs blunted--by replenishing eroded capital--the effects of the 2007-2008 credit crunch on financial service firms (and their share-prices): Citigroup raised about USD$20 billion from a consortium of SWFs from Abu Dhabi Kuwait and Singapore; UBS received a capital injection of around USD$10 billion from a Singaporean SWF fund; Merrill Lynch received a USD$11 billion capital injection from consortium SWFs from Kuwait, Singapore and South Korea.

Gopal Ramanthan KPMG’s Global Head of Transaction Services supported this viewpoint when he said:

“I don’t think the SWFs have been given full credit for the supportive role they played during the credit crunch. They helped prop up the financial services sector with some timely investments. They refused to be panicked into exiting their share-dealing positions and they were similarly resolute about their real estate holdings at a time when other investors were looking for an exit route. Admittedly, the potential business benefits mean that their reasons were not entirely altruistic but their investment strategies have arguably diminished the full effects of the credit crunch. No-one could have simply ‘solved’ the credit crunch but the SWFs went some way to making it a less uncomfortable journey than it could have been.”

Source: Sovereign wealth funds, KPMG Article, 1 April 2008

The hypothetic graphical illustration below depicts the 'stabilizing effect' SWF investment has on a firm's share-price (during a financial market downturn)

Explanation of the graphical illustration: The illustration above shows a stock whose price is on a free-fall (due to turmoil in the underlying corporation's micro and macro environment). The vertical axis represents the price movement of the share, the horizontal axis represents the period of time that the price of the stock is tracked; from T1 to T2. The red trajectory shows the normal price fluctuations of the share i.e the price movement of the share without a SWF capital injection in the underlying firm. The green trajectory shows the price movement of the stock after a capital injection in the underlying firm by a SWF. In the diagram above, the share falls from point a to b until a SWF injects capital in the firm at point b (T1+1 : P3) . The share price then takes the green trajectory labeled b, f, g, h instead of the red trajectory labeled c, d, e. From the graphical illustration, you can see that the green trajectory has fewer peaks and dips; i.e it is more stable than the red trajectory. The most important thing to note is that prices on the green trajectory are generally higher than prices on the red trajectory. This implies that the SWF capital injection restored public faith in the firm and stopped the firms price from falling further.

To calculate the stabilizing effect of the SWF capital injection, you would have to:

• Calculate the gradient on the red trajectory between points c,d,e
• Calculate the gradient on the green trajectory between points b,f,g,h
• Find the difference between the gradients and express it as a percentage of the gradient between points c,d,e

To calculate the short-term financial effect (in a standard unit of currency eg dollars or euros) of the SWF's investment on the firm's share price:

Which reads the financial effect of a SWF's investment on a firm's share price is the total sum of; the difference between chronologically corresponding share prices on the green trajectory and the red trajectory; during the time period TI to T2

Where:

• Feff is the financial effect of a SWFs investment
• t is any time period between T1 and T2
• Pgt any share price on the green trajectory between the time period T1 to T2
• Prt any share price on the red trajectory between the time period T1 to T2

Side-note: someone asked me why I like to mathematicize everything. Answer: It helps me to link cause to effect better! I also include all mathematical models in my super predictive computer model --which gives me a competitive edge (enough said!)

Assuming that SWFs will replicate the investment strategy they employed in bank bailouts to the broad portfolios of common stock they are now diversifying into: it can be argued that their involvement will help to stabilize equity markets in the same way it stabilized the financial services sector during 2007-2008 credit crunch.

2) Negatively impact the provision of Social Goods:

The diversification of SWFs out of bond markets spells doom for most borrowers--especially the US government. SWFs were a major player in the markets for US government issued bonds; where they purchased bonds that most investor classes wouldn't touch. Their exit from (government issued) bond markets will make it cumbersome (if not impossible) for the US government to raise cost-effective funding through bond issues. Simply put: The US government faces the strong risk of failing to raise adequate funding for the provision of social goods. This implies that the social welfare of US citizens may be compromised by SWFs' diversification out of US bond markets.

How do you identify weak companies? (stocks to short-sell)

...The tale of the corporation that looks 'healthy'

I'm sure everyone has encountered at least one corporation that looks healthy, (with Liquidity ratios, Profitability ratios, Asset management ratios, Debt management ratios, Dividend and market value ratios that paint a picture of vibrancy and soundness) and then, suddenly gets wiped-out in a cyclical business slowdown.

How did that happen?

...It's the capital structure stupid (look beyond the ratios)!

There is no single correct, or universally applicable capital structure (X percent equity and Y percent debt); infinite optimum variations exist in different industries and economies. Ideally, a corporation's capital structure has to evolve in response to changes in the corporation's micro and macro environment.

A firm with a capital structure that isn't responsive (a firm that's mis-financed) to micro and macro environmental changes, will fail to survive in the long run: If a corporation has the best management in the world, the best market prospects and the wrong capital structure, it will fail to survive in the longterm.

...Before we go into identifying a corporation that's mis-financed, how do you identify a firm that's well-financed.

Firstly, you need to have great understanding of the firm, its business model, its competitive environment and the firm's broader; political, economic, social and technological environment. (that's the obvious part)

Then you also need to relate the risk in a firm's capital structure to risks in the firm's micro and macro environment. According to Michael Milken's essay titled, The Corporate Financing Cube; a financially strong firm's risk in capital structure varies inversely with (macro) volatility and risk in the basic business. What does this mean?

This means: as a firm's risk in basic business (and macro volatility) increases the risk in capital structure should decrease in proportion to the environmental risk increase. For example, the management of a firm with a debt to equity ratio of 3:2 (60% debt and 40% equity), which is experiencing the adverse effects of globalization (an increase market volatility) should:

• Generally reduce the firm's risk in capital structure by issuing more equity instruments and reducing debt (reducing leverage), to keep the firm financially strong.
  

To put Milken's statement--a financially strong firm's risk in capital structure varies inversely with (macro) volatility and risk in the basic business--into a mathematical context:

Rcs = k / (a + b)

Which reads: risk in capital structure is equal to a constant number divided by the total sum of; macro-volatility and risk in the basic business. Where:

• Rcs represents the risk in capital structure
  
• k represents a constant number
  
• a represents macro volatility
  
• b represents the risk in the basic business
  

Below is a graphical illustration (according to the above-introduced mathematical expression) of the ideal relationship between risk in the capital structure AND macro volatility and the risk in the basic business.

The Ideal scenario: an inverse relationship between capital structure and macro volatility + risk in the basic business

Explanation of the graphical illustration: The graph on top shows an inverse relationship between capital structure and macro volatility + business risk. The vertical axis represents risk in the capital structure. The horizontal axis represents macro volatility plus risk in the basic business. The navy-blue inwardly curving line illustrates an inverse relationship between between capital structure and macro volatility + business risk:

• A firm on point a with a risk in capital structure of Rcs 9 and volatility and business risk of V2; is a company that has a stable business model and revenues that are relatively unaffected by cyclical business slowdowns eg. a supermarket. Such a business can be leveraged with the highest debt to equity ratio (in comparison to firm's on points b and c)
• A firm on point c with a risk in capital structure of Rcs 1 and volatility and business risk of V20; is a company with very high business volatility and high competitive risk. It operates in an industry where cashflow is hard to predict e.g. an internet start-up. In such a business, the majority of the capital structure should consist of equity instruments; as it is difficult to predict with certainty if the firm will be able to generate sufficient cashflows to service debt.
  

...How to identify business that are mis-financed

Businesses that are mis-financed generally fall into two categories: 1) Businesses that are under-leveraged 2) Businesses that are over-leveraged

Graphical illustration of two dangerous types of mis-financing: over-leveraging and under-leveraging

The explanation of this graphical illustration can be found in the text below:

1. Under-leveraged corporations: To identify if a firm is under-leveraged, you have to look at the relationship between the firm's capital structure risk AND macro volatility + risk in the basic business. An under-leveraged firm 's risk in capital structure, has a negative direct relationship to its macro volatility + risk in the basic business. Mathematically this can be expressed as; Rcs = [-k *(a+b)] + c , where Rcs represents the risk in capital structure, k represents a constant number that lies between 0 and 1, a represents macro-volatility, b represents the risk in the basic business and c is a constant number that is greater than 1. In the graphical illustration above, the downwardly sloping red trajectory labeled J represents the relationship between risk in capital structure and macro volatility + risk in the basic business; of an under-leveraged firm. Such a firm usually has an undervalued share-price and has a strong likelihood of failing because of the mis-alignment of management's and shareholder's interests.
2. Over-leveraged corporations: To identify if a firm is over-leveraged, you have to look at the relationship between the firm's capital structure risk AND macro volatility + risk in the basic business. An over-leveraged firm's risk in capital structure, has a positive direct relationship to its macro volatility + risk in the basic business. Mathematically this can be expressed as; Rcs = k *(a+b) , where Rcs represents the risk in capital structure, k represents a constant number, a represents macro-volatility and b represents the risk in the basic business. In the graphical illustration above, the upward sloping green trajectory labeled K represents the relationship between risk in capital structure and macro volatility + risk in the basic business; of an over-leveraged firm. Such a firm faces the risk of insolvency and will suffer financially in when a cyclical business slowdown occurs. An over-leveraged company is very weak!

So whats the benefit of knowing all this? It helps you to identify possible 'short-selling candidates' :-)