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Cost of Funds Index (COFI) Definition

 The cost of fund index, COFI, refers to the interest rate's weighted average that banks compensate on savings accounts held by their clients and their financial creditors. The interest charged by banks are determined by the banks cost of fund index.

A Little More on What is the Cost of Funds Index

The interest rate a borrower of mortgage or loan pays is partly calculated by the index rate the bank applies. Banks have to use COFI to ascertain what to charge in interests to compensate the interests they pay out together with margin. Even though COFI has continuously become out of date, it is commonly used to calculate the variable rate loans' cost, The COFI is determined both regionally and federally.The indexes are printed when it's approaching the month end and can be adjusted again until the subsequent issue. That indicates that the interests rates attached to the cost of funds index gap after the rate tied to other indexes, occasionally by many months. Although, similarly to other indexes, the COFI rate is most probably directly proportional to the interest the customers pay. For instance, if the COFI rate moves up, borrowers will most likely pay more interests and vice versa.Cost of funds index exampleInterest rates rose sharply in January 2010 at the peak of the Great Recession. This was attributed to the extraordinary leap in COFI rates.The rise resulted from the Wells Fargos acquisition of Wachovia, which reduced Wachovias low borrowing rates from the COFI formula because Wells Fargo was never a member. Due to the rise in COFI rate, borrowers remained to utilize extra dozens every month in interest rate payment on their variable rate mortgages. COFI rate has only reduced gradually as from that time despite the rise resulting in a temporary spike.

References for COFI (Cost of funds index)

• http://www.businessdictionary.com/definition/cost-of-funds-index-COFI.html
• https://en.wikipedia.org/wiki/Cost_of_funds_index
• https://www.bankrate.com/glossary/c/cost-of-funds-index/

Academic Research on for COFI (Cost of funds index)

• ARM wrestling: Valuing adjustable rate mortgages indexed to the eleventh district cost of funds, Stanton, R., & Wallace, N. (1995). Real Estate Economics, 23(3), 311-345. This paper examines the adjustable rate mortgages (ARMs) by Eleven District Cost of Fund Index (EDCOFI). The pattern of EDCOFI was studied over 1981-1993. Adjustments to this index lag significantly behind term structure variations. Besides, the seasonality and days-in-the-month impacts recognized by previous authors are signs of a January influence. The pricing formula enables ascertainment of endogenously the best prepayment method for mortgage holders and finally the number of their payment choices. The dynamics of EDCOFI adds important value to this option, typically about 0.5% of the reduced principal on loan.
• Econometric models of the eleventh district cost of funds index, Passmore, S. W. (1993). The Journal of Real Estate Finance and Economics, 6(2), 175-188. The paper states that Eleven District Cost of Fund Index, COFI, is a popular index for pricing adjustable-rate mortgages. COFI is determined from the interest expense incurred by the prudence when sourcing funds. It is a combination of existing and the past interest rates on different financial instruments. COFI can be molded better with a simple econometric model. Frequently used, simple COFI prototypes are matched using a method established by Hendry (1989). Once a robust econometric model is taken, the lagged adjustment of COFI variations in interest rates can be included in the mortgages pricing models.
• Can retail depositories fund mortgages profitably?, Passmore, W. (1992). Journal of Housing Research, 305-340. The paper illustrates how the cost of funding a mortgage with deposits are broken down into costs relating to interest-rate-risk hedging, repayment, credit risks and deposit collection by use of a model of the profit-maximizing bank. Financing mortgages with retail deposits will be an effective method when using retail deposits reduces the cost of hedging against the interest rate risks. Cost of accumulating retail deposits together with the regulatory capital requirements for banks results in mortgage lending is the loss-making activity for banks. Profits can be improved by securing mortgages and not widening mortgage lending past existing retail funds.
• Mortgage Securities Research: Adjustable Rate Mortgages: The Indexes, Roll, R. (1987). Housing Fin. Rev., 6, 137. The paper states that the coupon rate of adjustable rate Mortgage (ARM) varies with time because it is attached to an index which is an issued number quantified in the original contractual contract of the mortgage. Most ARMs are associated with constant maturity U.S. Treasury return indexes or thrift institution cost of Funds Index (COFI). The coupon of ARM is determined by the addition of a margin to the index, subject to the limitation on the maximum and minimum coupon during the mortgage life or the highest and the lowest changes during a particular period.
• Temporal relationships among adjustable-rate mortgage indexes, Crockett, J. H., Nothaft, F. E., & Wang, G. H. (1991). The Journal of Real Estate Finance and Economics, 4(4), 409-419. The paper examines the association among the six ARM indexes for the period from 1978-1989. Granger's direct casualty test is used in studying their associations within the rolling regression framework. The flexible features of every index and the chosen pair of indexes are determined by use of the marginal root and cointegration tests. The practical outcome confirmed their association has varied over this period and short-term rates top the eleventh cost of funds index. The effects of empirical outcome from the borrowers angle (ARM option), lenders (pricing), and investors (security assessment) are also examined.
• The pricing of adjustable-rate mortgage contracts, Sa-Aadu, J., & Sirmans, C. F. (1989). The Journal of Real Estate Finance and Economics, 2(4), 253-266. The paper ascertains the structure of ARM agreements and pricing of their factors characteristics. By perception of ARM as a compound package, Contrasting previous experiments, which generally focused on option-based simulation method, our examination stipulates a microeconomic model of the lender as a profit-maximizer which is then evaluated using company-specific data. The empirical results which are consistent with the microeconomic model, indicate that the lender behaves like a profit-maximizing company in ping the characteristics of ARM agreements. Therefore, theoretical and practical ARM pricing models should consider other characteristics of the agreements in addition to the cap factors.
• Caps on adjustable rate mortgages: Valuation, insurance, and hedging, Schwartz, E. S., & Torous, W. N. (1991). Financial markets and financial crises (pp. 283-304). University of Chicago Press. The paper outlines that federally chartered thrift organizations were allowed to develop adjustable rate mortgages in April 1981. Before this, thrifts mainly developed long-term stable rate mortgages. Therefore, being that mortgages are funded by short-term deposits, a gap between their assets and liabilities maturities arose thereby subjecting the thrifts to significant interest rate risks. Adjustable rate mortgage developers were left subject to interest rate risks as a result of many contractual characteristics of a regular adjustable rate mortgage leads to imperfect variations of its coupon to variations in thrift cost of funds.
• Mortgage valuation models at Prudential Securities, Ben-Dov, Y., Hayre, L., & Pica, V. (1992). Interfaces, 22(1), 55-71. In the previous four years, Prudential Securities Inc. (PSI) has developed a premier mortgage-backed securities (MBS) department. Because of the complexity of the securities, standard fixed income valuation tools are not sufficient for MBSs. The establishment of a rational and effective model has been a central part of the growth. These models use various management science methods that include; regression analysis, probabilistic modeling, Monte Carlo simulation, and programming. The models enable the companies to value speedily and perfectly, therefore, trade, complex MBSs, to properly hedge MBSs in inventory, and to structure clients groupings to achieve targets while remaining within the constraints range.
• Adjustable rate mortgages: Valuation, Berk, J., & Roll, R. (1988). The Journal of Real Estate Finance and Economics, 1(2), 163-184. The paper employs a simulation method to quantify adjustable rate mortgages. It is used for pricing two types of instruments: an ARM connected to Treasury interest rate and an ARM connected to Cost of Funds Index. Contractual requirements like margin over the index cap and floors on the ARM's rate or the monthly advances, reset frequency, and the teaser rate is studied for their effects on the amount.
• Cost of funds indexed mortgage contracts with government-backed catastrophic insurance (COFI-Cats): A realistic alternative to the 30-year fixed-rate mortgage?, Hancock, D., & Passmore, W. (2016). Journal of Economics and Business, 84, 109-130. This paper examines the practicability of an adjustable rate model product linked to a nationwide cost of fund index COFI which is given by the total interest divided by the total liabilities of all domestic commercial banks. Due to banking institutions having a cost of funds that commonly vary with each other, mortgage-backed securities based on groups of COFI-Cat mortgages possibly offer much needed geographic divergence, mainly for smaller U.S. banks, while still being relatively simple to hedge related to fixed-rate and other adjustable-rate mortgages. Investors, like asset managers, banks, and central banks, COFI-Cat MBS can offer profitable opportunities for constant profits.
• A preliminary inquiry into the causes of the Credit Crunch, Murphy, D. (2008). Quantitative Finance, 8(5), 435-451. The paper states that the entire US. Prices of residential properties grew 96% in eight years from January 2000 to 2008. While they have previously fallen from the historical peak, the decline is only 13%. The author pauses a question on why the decline presages the massive write-down of mortgage-backed and other securities, huge recapitalization of financial institutions, nonpayment of off-balance-sheet vehicles and extraordinary and central bank involvement in the markets. The outlines the major factors which led to the credit crunch, some of the major market activities are described, their causes proposed and rules to counteract future crunches are studied.