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Formula Method Definition
There are several methods for calculating termination payments, there is the Indemnification method, the agreement value method, and the Formula method as established by the International Swaps and Derivatives Association. The formula method is used for calculating termination payments on a prematurely ended swap. Termination payments are payments made to the party who was not responsible for the early termination of the swap
.What may lead to early termination of a swap are:
- Tax event
A Little More on What is the Formula Method
A swap agreement is a financial contract between two parties for a specific period of time. IT usually has an expiration date. The agreement will include a termination clause since an early termination can be triggered by several events. The termination clause will state which of the three methods will be used to determine the obligations of the parties.
The formula method is used to calculate the losses suffered by the party not at fault, this method is no longer in use in recent times, other better methods have been developed.
Other Methods for Early Termination of Swaps
Apart from the Formula method, there are still other methods namely;
- Indemnification Method
- Agreement Value method.
The Indemnification Method is when all the losses are being compensated by the responsible party to the other part based on the damage that resulted from the early termination of the swap. It is security against financial liability. This method has been overridden by the Agreement value method which put into consideration how to quantify the actual damages and interest rates.
The Agreement Value method is an extensive method for the calculation of termination payments. It is calculated based on the cost of a replacement swap transaction, the changes in market condition and interest rates are put into consideration.
Reference for “Formula Method”
Academics research on “Agreement Value Method”
Swaps: Codes, Problems and Regulation, Cunningham, D. (1986). Swaps: Codes, Problems and Regulation. Int’l Fin. L. Rev., 5, 26.
An Analysis of Interest Rate and Currency Swaps, Henderson, S. K. (1986). An Analysis of Interest Rate and Currency Swaps. NCJ Int’l L. & Com. Reg., 11, 497.
Tax Treatment of Interest Rate Swaps at Disposal: Should Swap Participants Have Their Cake and Eat it Too, Ferrer, E. Y. (1991). Tax Treatment of Interest Rate Swaps at Disposal: Should Swap Participants Have Their Cake and Eat it Too. USFL Rev., 26, 283.
Evaluation of instrument error and method agreement., Chatburn, R. L. (1996). Evaluation of instrument error and method agreement. AANA journal, 64(3), 261-268. Safely operating life support equipment and evaluating new technology both require some basic understanding of measurement theory. Measurement errors fall into two main categories: systematic errors (predictable problems usually due to calibration) and random errors (unpredictable). These two types of errors can be quantified by experiments involving repeated measurements of standards or “true” values. Systematic error (called bias) is usually expressed as the mean difference between measured and true values. Random error, called imprecision, can be expressed as the standard deviation of measured values. Total error can be expressed as an error interval, being the sum of bias and some multiple of imprecision. An error interval is a prediction about the error of some proportion of future measurements (e.g., 95%) at some level of confidence (e.g., 99%) based on the variability of the sample data and the sample size. Specifically, a tolerance interval gives an estimate of the true value of some variable given repeated measurements with an assumed valid measurement system. An inaccuracy interval predicts the validity of a measurement system with an estimate of the difference between measured true values (given that a standard or true value is available for measurement). An agreement interval evaluates whether or not one measurement system (e.g., a known valid system) can be used in place of another (e.g., a new unknown system). Statistical analyses such as correlation and linear regression are commonly seen in the literature, but not usually appropriate for evaluation of new equipment. Instrument performance evaluation studies should start out with a decision about the level of allowable error. Next, experiments are designed to obtain repeated measurements of known quantities (inaccuracy studies) or of unknown quantities by two different measurement systems (i.e., agreement studies). The first step in data analysis is to generate scatter plots of the raw data for review of validity (e.g., outliers). The next step is to make sure the data adhere to the assumption of normality. The third step is to calculate basic descriptive statistics, such as the mean and standard deviation. Finally, the data should be presented in graphic form with the differences plotted against the reference values and including numerical values for the calculated error intervals. The key idea to remember is that device evaluation and method agreement studies are based on the desire to know how much trust we should place in single measurements that may be used to make life support decisions.
Accounting information in private markets: Evidence from private lending agreements, Leftwich, R. (1983). Accounting information in private markets: Evidence from private lending agreements. Accounting Review, 23-42. This paper contains evidence of accounting measurement rules that are negotiated in private corporate lending agreements. The negotiated sets of rules differ from the regulated set of accounting rules (generally accepted accounting principles). Moreover, the differences between regulated and negotiated rules are systematic and consistent with the economic incentives of borrowers and lenders. Private parties in the market for accounting information are able to produce for themselves at least some of the information required for monitoring lending agreements. The evidence and analysis have implications for: 1. The voluntary choice of accounting rules, 2. The superiority of alternative accounting rules, and 3. The demand for a diverse set of accounting rules.