CAPITAL STRUCTURE, CATASTROPHE FUTURE AND OPTIONS, COMMODITY FUTURES VOLATILITY

 

Capital Structure

Capital structure is the mixture of securities issued by a company to finance its operations.

Companies need real assets in order to operate. These can be tangible assets, such as buildings and machinery, or intangible assets, such as brand names and expertise. To pay for the assets, companies raise cash not only via their trading activities but also by selling financial assets, called securities, financial instruments or contingent claims. These securities may be classified broadly as either equity or debt (though it is possible to create securities with elements of both). Equity is held as shares of stock in the company, whereby the company’s stock holders are its owners. If the company’s trading activities are sufficiently successful, the value of its owners’ equity increases. Debt may be arranged such that repayments are made only to the original holder of the debt, or a “bond” may be created which can be sold on, thus transferring ownership of future repayments to new bondholders.

Capital structure can be changed by issuing more debt and using the proceeds to buy back shares, or by issuing more equity and using the proceeds to buy back debt. The question then arises: is there an optimal capital structure for a company? The solution to this question, for the restricted case of “perfect markets,” was given by Franco Modigliani and Merton Miller (1958), whose fame is now such that they are referred to in finance textbooks simply as “MM!” A perfect market is one in which there are neither taxes nor brokerage fees and the numbers of buyers and sellers are sufficiently large, and all participants are financially sufficiently small relative to the size of the market that trading by a single participant cannot affect the market prices of securities. MM’s “first proposition” states that the market value of any firm is independent of its capital structure. This may be considered as a law of conservation of value: the value of a company’s assets is unchanged by the claims against them. It means that in a perfect and rational market a company would not be able to gain value simply by recombining claims against its assets and offering them in different forms.

Modigliani and Miller (1961) likewise deduced that whether or not cash was disbursed as dividends was irrelevant in a perfect market. MM’s first proposition relies on investors being able to borrow at the same interest rate as companies; if they cannot, then companies can increase their values by borrowing. If they can, then there is no advantage to investors if a company borrows more money, since the investors could, if they wished, borrow money themselves and use the money to buy extra shares of stock in the company. The investors would then have to pay interest on the cash borrowed, as would the company, but will benefit from holding more equity in the company, resulting in the same overall benefit to the investor.

An analogy which has been used for this proposition is the sale of milk and its derivative products (see Ross et al., 1988). Milk can be sold whole or it can be split into cream and low cream milk. Suppose that splitting (or recombining) the milk costs virtually nothing and that you buy and sell all three products through a broker at no cost. Cream can be sold at a high price in the market and so by splitting off the cream from your milk you might appear to be able to gain wealth. However, the low cream milk remaining will be less valuable than the original, full cream milk – a buyer has a choice in the market between full cream milk and milk with its cream removed; offered both at the same price, he would do best to buy full cream milk, remove its cream and sell it himself. Trading in the perfect market would act so as to make the combined price of cream and low cream milk in the perfect market the same as the price of full cream milk (conservation of value). If, for example, the combined price dropped below the full cream price then traders could recombine the derivative products and sell them at a profit as full cream milk.

What was considered perplexing, before Modigliani–Miller, is now replaced by a strong and simple statement about capital structure. This is very convenient because any supposed deviations can be considered in terms of the weakening of the assumptions behind the proposition. Obvious topics for consideration are the payment of brokers’ fees, taxes, the costs of financial distress and new financial instruments (which may stimulate or benefit from a temporarily imperfect market). New financial instruments may create value if they offer a service not previously available but required by investors. This is becoming progressively harder to achieve; but even if successful, the product will soon be copied and the advantage in the market will be removed. Charging of brokers’ fees simply removes a portion of the value and (as long as the portion is small!) this is not a major consideration, since we are concerned with the merits of different capital structures rather than the costs of conversion.

Taxes, however, can change the result significantly: interest payments reduce the amount of corporation tax paid and so there is a tax advantage, or “shield,” given to debt compared with equity. When modified to include corporate taxes, MM’s proposition shows the value of a company increasing linearly as the amount of debt is increased (Brealey and Myers, 1991).

This would suggest that companies should try to operate with as much debt as possible. The fact that very many companies do not do this motivates further modifications to theory: inclusion of the effect of personal tax on shareholders and inclusion of the costs of financial distress.

Miller (1977) has argued that the increase in value caused by the corporate tax shield is reduced by the effect of personal taxes on investors. In addition, the costs of financial distress increase with added debt, so that the value of the company is represented by the following equation, in which PV denotes present value: value of company = value if all equity-financed +PV (tax shield) – PV (costs of financial distress)

As debt is increased, the corporate tax shield increases in value but the probability of financial distress increases, thus increasing the present value of the costs of financial distress.

The value of the company is maximized when the present value of tax savings on additional borrowing only just compensates for increases in the present value of the costs of financial distress.

One element of financial distress can be bankruptcy. It is generally the case throughout the world’s democracies that shareholders have limited liability. Although shareholders may seem to fare badly by receiving nothing when a company is declared bankrupt, their right simply to walk away from the company with nothing is actually valuable, since they are not liable personally for the company’s unpaid debts. Short of bankruptcy there are other costs, including those caused by unwillingness to invest and shifts in value engineered between bondholders and shareholders, which increase with the level of debt.

Holders of corporate debt, as bonds, stand to receive a maximum of the repayments owed; shareholders have limited liability, suffer nothing if the bondholders are not repaid and benefit from all gains in value above the amount owed to bondholders. Therefore, if a company has a large amount of outstanding debt it can be to the shareholders’ advantage to take on risky projects which may give large returns, since this is essentially a gamble using bondholders’ money! Conversely, shareholders may be unwilling to provide extra equity capital, even for sound projects. Thus a company in financial distress may suffer from a lack of capital expenditure to renew its machinery and underinvestment in research and development. Even if a company is not in financial distress, it can be put into that position by management issuing large amounts of debt. This devalues the debt already outstanding, thus transferring value from bondholders to shareholders. Interesting examples of this are to be found in leveraged buyouts (LBOs), perhaps the most famous being the attempted management buyout of R. J. R. Nabisco in the 1980s (Burrough and Helyar, 1990). Top management in R. J. R. Nabisco were, of course, trying to become richer by their actions – an extreme example of so-called agency costs, whereby managers do not act in the shareholders’ interest but seek extra benefits for themselves.

There is, finally, no simple formula for the optimum capital structure of a company. A balance has to be struck between the tax advantages of corporate borrowing (adjusted for the effect of personal taxation on investors) and the costs of financial distress. This suggests that companies with strong, taxable profits and valuable tangible assets should look towards high debt levels, but that currently unprofitable companies with intangible and risky assets should prefer equity financing. This approach is compatible with differences in debt levels between different industries but fails to explain why the most successful companies within a particular industry are often those with low debt. An attempt at an explanation for this is a “pecking order” theory (Myers, 1984). Profitable companies generate sufficient cash to finance the best projects available to management.

These internal funds are preferred to external financing since issue costs are thus avoided, financial slack is created, in the form of cash, marketable securities, and unused debt capacity, which gives valuable options on future investment, and the possibly adverse signal of an equity issue is avoided.

 

Resources For Capital Structure:

Brealey, R. A. & Myers, S. C. (1991). Principles of corporate finance. 4th edn, New York: McGraw-Hill.

Burrough, B. & Helyar, J. (1990). Barbarians at the gate: The fall of R. J. R. Nabisco. London: Arrow Books.

Myers, S. C. (1984). The capital structure puzzle. Journal of Finance, 39, 575–92.

Ross, S. A., Westerfield, R. W. & Jaffe, J. F. (1988). Corporate finance. 3rd edn, Chicago, IL: G. S. B. Chicago, University of Chicago. 434–35.

 

Catastrophe Futures and Options

Catastrophe futures and options are derivative securities whose payoffs depend on insurers’ underwriting losses arising from natural catastrophes (e.g. hurricanes).

Specifically, the payoffs are derived from an underwriting loss ratio that measures the extent of the US insurance industry’s catastrophe losses relative to premiums earned for policies in some geographical region over a specified time period. The loss ratio is multiplied by a notional principal amount to obtain the dollar payoff for the contract. The Chicago Board of Trade (CBOT) introduced national and regional catastrophe insurance futures contracts and the corresponding options on futures in 1992.

Insurers/re-insurers can use catastrophe futures and options to hedge underwriting risk engendered by catastrophes (see Harrington et al., 1995) For example, when taking a long position, an insurer implicitly agrees to buy the loss ratio index at a price equal to the current futures price. Accordingly, a trader taking a long catastrophe futures position when the futures price is 10 percent commits to paying 10 percent of the notional principal in exchange for the contract’s settlement price. If the futures loss ratio equals 15 percent of the notional principal there is a 5 percent profit. Conversely, if the settlement price is 5 percent at expiration, the trader pays 10 percent and receives 5 percent of the notional principal for a 5 percent loss. The CBOT catastrophe futures contracts have a notional principal of US$25,000.

Prior to the expiry of the contract, the futures price reflects the market’s expectation of the futures loss ratio. As catastrophes occur or conditions change so as to make their occurrence more likely (e.g. a shift in regional weather patterns), the futures price will increase.

Conversely, if expected underwriting losses from catastrophes decrease, the futures price will decrease. Given that the futures price reflects the futures loss ratio’s expected value, an insurer can take a long futures position when a contract begins to trade at a relatively low futures price. Then, if an unusual level of catastrophe losses occur, the settlement price will rise above the established futures price and the insurer will profit on the futures position and thus offset its higher than normal catastrophe losses.

Call and put options on catastrophe futures contracts are also available. A futures call (put) option allows the owner to assume a long (short) position in a futures contact with a futures price equal to the option’s exercise price. For example, consider a call option with an exercise price of 40 percent. If the futures price rises above 40 percent, the call option can be exercised which establishes a long futures position with an embedded futures price of 40 percent. If the futures price is less than 40 percent at expiration, the call option will expire worthless.

Catastrophe futures and options are an innovative way for insurers to hedge underwriting risk arising from catastrophes. In essence, the catastrophe derivatives market is a secondary market competing with the reinsurance market for trading underwriting risk.

 

Resources For Catastrophe Futures and Options:

Harrington, S. E., Mann, S. V. & Niehaus, G. R. (1995). Insurer capital structure decisions and the viability of insurance derivatives. Journal of Risk and Insurance, 62, 483–508.

 

Commodity Futures Volatility

The definition of a commodity (by the Commodity Futures Trading Commission) includes all goods, articles, services, rights, and interest in which contracts for future delivery are dealt.

However, another approach extracts the financial instruments (interest rate, equity, and foreign currency) leaving those assets more commonly referred to as commodities, that is agricultural (such as grains and livestock), metals (such as copper and platinum), and energy (such as crude oil and natural gas).

Early studies of commodity futures identified several factors that have an impact on volatility, including effects due to contract maturity, contract month, seasonality, quantity, and loan rate.

For the contract maturity theory, Samuelson (1965) suggested that futures contracts close to maturity exhibit greater volatility than futures contracts away from maturity. The intuition for this idea is that contracts far from maturity incorporate a greater level of uncertainty to be resolved and therefore react weakly to information. On the other hand, the nearer contracts tend to respond more strongly to new information to achieve the convergence of the expiring futures contract price to the spot price.

The seasonality theory is also grounded in the resolution of uncertainty, but is approached by Anderson and Danthine (1980) in the framework of the simultaneous determination of an equilibrium in the spot and futures markets based on supply and demand. As explained by Anderson (1985), during the production period, supply and demand uncertainty are progressively resolved as random variables are realized and publicly observed. Thus ex ante variance of futures price is shown to be high (low) in periods when a relatively large (small) amount of uncertainty is resolved. For agricultural commodities, particularly the grains, crucial phases of the growing cycle tend to occur at approximately the same time each year leading to a resolution of production uncertainty that follows a strong seasonal pattern.

Seasonality on the demand side is explained on the basis of substitute products, which also exhibit production seasonalities. Under the general heading of ”seasonality” are various studies of such aspects as month-of-the-year effect, day-of-the-week effect, and turn-of-the-year effect.

The contract month effect explained by Milonas and Vora (1985) suggests that an old crop contract should exhibit higher variability than a new crop contract due to delivery problems (squeezes) when supply is low.

Quantity and loan rate effects are an artifact of the government farm programs. Government involvement in price support and supply control in the grain market can have an impact on volatility as follows. A major component of price support is the loan, whereby a producer who participates may obtain a loan at the predetermined loan rate (dollars per bushel) regardless of the cash market price. If cash prices do not rise above the loan rate plus storage and interest costs, the producer forfeits the grain to the government to satisfy the loan. As a result, the program tends to put a floor on the cash and futures price near the loan rate and thus, as prices decline to the loan rate level, price volatility should decline. Additionally, when production and ending inventories are relatively large (quantity effect), the cash and futures prices have a tendency to be supported by the loan program, and once again, volatility should decrease.

Several empirical tests of these hypotheses have been conducted, of which we will mention only a few. First, Anderson (1985) tests the seasonality and maturity effects theories for nine commodities including five grains, soybean oil, livestock, silver, and cocoa. Employing both non-parametric and parametric tests, he finds that the variance of futures price changes is not constant and that the principal predictable factor is seasonality with maturity effects as a secondary factor. Milonas (1986) finds evidence of the contract maturity effect in agricultural, financials, and metals markets, which shows that the impact of a vector of known or unknown variables is progressively increasing as contract maturity approaches.

Gay and Kim (1987) confirm day-of-the-week and month-of-the-year effects by analyzing a twenty-nine-year history of the Commodity Research Bureau (CRB) futures price index. This index is based on the geometric average of twenty-seven commodities using prices from all contract maturities of less than twelve months for each commodity. Kenyon et al. (1987) incorporate four factors into a model to estimate the volatility of futures prices (seasonal effect, futures price level effect, quantity effect, and loan rate effect). Test results of the model in three grain markets support the loan rate hypothesis, while the quantity effect was insignificant. Once again, seasonality effects are supported.
A recent paper by Crain and Lee (1996) also studies the impact of government farm programs on futures volatility. The test period covers forty-three years (1950–93) with thirteen pieces of legislation and concentrates on the wheat market. Patterns of changes in futures and spot price volatility are linked to major program provision changes, such as allotments, loan rates, and the conservation reserve. Three sub-periods of distinguishable volatility magnitudes seem to exist with the discernible patterns explained as follows. Mandatory allotments contribute to low volatility, voluntary allotments and low loan rates contribute to higher volatility, and both market-driven loan rates and conservation reserve programs induce lower levels of volatility. Seasonality is also confirmed in this study, but the seasonality effects do not seem to be as important as farm program impacts. Additionally, there is evidence of changing seasonality patterns over the three defined sub-periods.

Another issue addressed in Crain and Lee (1996) concerns the price discovery role of futures markets. In particular, the wheat futures market has carried out this role by transferring volatility to the spot market. This is consistent with previous studies in other markets, such as equity, interest rate, and foreign exchange markets. Also, there is some evidence that the causal relationship has been affected by the farm programs.

 

Resources For Commodity Futures Volatility:

Anderson, R. W. (1985). Some determinants of the volatility of futures prices. Journal of Futures Markets, 5, 331–48.

Anderson, R. W. & Danthine, J. P. (1980). The time pattern of hedging and the volatility of futures prices. Center for the Study of Futures Markets. CSFM Working Paper Series 7.

Crain, S. J. & Lee, J. H. (1996). Volatility in wheat spot and futures markets, 1950–1993: government farm programs, seasonality, and causality. Journal of Finance, 51, 325–44.

Gay, G. D. & Kim, T. (1987). An investigation into seasonality in the futures market. Journal of Futures Markets, 7, 169–81.

Kenyon, D., Kling, K., Jordan, J., Seale, W. & McCabe, N. (1987). Factors affecting agricultural futures price variance. Journal of Futures Markets, 7, 169–81.

Milonas, N. T. (1986). Price variability and the maturity effect in futures markets. Journal of Futures Markets, 6, 443–60.

Milonas, N. & Vora, A. (1985). Sources of nonstationarity in cash and futures prices. Review of Research in Futures Markets, 4, 314–26.