Removal of regulatory loan and tax impediments

In the UK, the removal of regulatory and tax impediments revealed the tax efficiency of property derivatives over direct investments. In 2002, the Financial Services Authority (FSA) decided to allow life insurance companies to include real estate swaps and forward contracts as admissible assets in the computation of their solvency ratios. Further, the inland revenue legislation from September 2004 established a regime for taxation of property derivatives, thereby removing tax as a barrier to trading property derivatives. Key points were that no stamp duty is levied, be it land tax or reserve tax, on the issue or transfer of property derivatives. This gave rise to an immediate benefit over purchasing property, as stamp duty of up to 4% of the property value is saved.

UKregulators ruled that property derivatives are taxed under derivatives contracts legislation, which broadly taxes all profits and losses as income. There are some exceptions for property derivatives. The taxation of income and capital gains will depend on what type of entity enters the derivatives transaction. The law defines two categories of institutions:

Derivatives as a primary business. In such a case, the gains and losses are treated, and taxed, as income.

Derivatives not as the primary business of the respective company. In this case the capital element will be subject to capital gains and the income element will be charged by a corporation tax.

Capital losses arising on contracts can be carried back against capital gains on similar derivatives arising in the previous two accounting periods. In general, capital gains may also be offset against other existing capital losses. Property Index Certificates (PICs), some of the earliest property derivatives in the UK, are treated as loans for tax purposes. Often, the PIC is split for accounting purposes into a loan and an embedded derivative. The latter is taxed separately under the derivative contracts legislation. The new collective investment scheme “Sourcebook COLL” allows authorized retail and nonretail funds to hold property derivatives. Two key legislative changes have cleared the way for a commercial property derivatives market in the UK. To summarize, companies can include property derivatives in their solvency calculations and capital losses can be offset against tax.

Equity and debt in the form of a bond

We start with a company with a simple capital structure consisting of equity and debt in the form of a bond. When the bond matures the bond investor normally gets the nominal value of his investment back. In case the company is not able to repay the bond, the company’s asset will be liquidated and paid out to the bondholder. The value of the corporate bond (C) is therefore the minimum of the debt (D, equivalent to nominal value of the bond) and the value of the assets of the company (A). C = min(D, A) = D + min(A – D, 0).

If we look at the nominal debt value as the strike price and the value of the assets as the value of the underlying, the equation above can be rewritten as C = D – max(D + A, 0). Thus a corporate bond is a combination of a risk-free bond and a short put on the company’s assets. The risk of default can be extracted from the price of the put. The put price in turn depends on the asset value of the firm (price of the underlying) and its debt (strike price of the option), interest rate, maturity of the debt and the volatility of the company value. This is where the link between implied volatility and corporate spreads originates, as the implied volatility of the stock can help to estimate the volatility of the firm’s asset value. Based on this relationship Galai and Masulis (1976) derive a formal link between the degree of debt financing and equity risk.

With constant operational risk, equity risk rises when debt financing goes up. This link was confirmed in a number of studies and extended to operational leverage, the fact that fixed costs cannot be reduced very fast when demand turns weak, as Schwert (1989), Ferguson (1994) and Franks and Schwartz (1988) point out.

Handling the different credit risk sources

In an active approach, forecasts influence the management process. Return expectations play a minor role in this asymmetric risk management. The focus is clearly on risk forecasts. Expectations on volatilities and correlations are used to finally arrive at a portfolio structure which allocates risk to various risk factors (equity market risk, interest rate risk, idiosyncratic risk, etc.) in order to be compensated by earning risk premia, but strictly within the bounds of the current risk budget of the portfolio. But, in contrast to a traditional, forecast-based management approach, disciplined risk control dominates forecasts, even risk forecasts. The approach is flexible enough to easily factor in subordinate goals and restrictions. Because it is active in a nonmechanistic sense, it is also capable of handling the different risk sources present in a corporate bond portfolio.

Issuers with a lower credit quality

credit quality

However, the study by Desclée and Rosten (2002) also finds that correlations of bonds from one issuer, but in differing currencies, significantly depend on spread levels. The bonds of companies with a lower credit quality and higher spreads like Ford (F), tend to show a high degree of comovement across currencies, as previous posts illustrate. Despite the noise that results from using daily observations the correlation of the daily spread changes of the two selected Dollar and Euro bonds was a highly significant 0.80. For a typical low spread name like General Electric (GE) we obtained a correlation of 0.00, meaning we were not able to detect any comovement between the daily spread changes of Dollar and Euro bonds, as can be seen from our experience. If we conclude that the spread changes of low spread names typically are not significantly correlated, the empirical results suggest that issue-specific characteristics tend to have more influence on spread changes than issuer-specific information for low spread names.

Conversely, the spread changes of issuers with a lower credit quality seem to depend on issuer-specific information, and thus are significantly correlated across currencies.

On the sector level, Desclée and Rosten (2002) obtained similar results. Whereas the spread changes of low spread credit sectors like agencies, foreign sovereigns or supranationals are rather uncorrelated across currencies, utilities, financials and particularly industrials exhibit positive correlations.

Changes in the payday risk premium

payday risk

Another central result from the above-mentioned study is that the average bond-by-bond correlations are higher within markets than across currencies. Investors obviously tend to compare spread levels of an issuer’s bonds rather in one currency than across currencies. This suggests that there is a certain degree of segmentation in international credit markets, and that the different investor bases at least temporarily may have differing views on one name. Kercheval et al. (2003) argue that credit spread changes in a market largely reflect changes in the risk premium required by investors to hold securities from a certain sector and with a given credit quality. Fluctuations of the credit spread therefore should be primarily due to changes in overall economic and political conditions, which can differ substantially across markets. This explanation is consistent with their empirical observations of a high correlation across sectors and ratings within a single market.