An analytic derivation of the cost of deposit insurance and loan guarantees An application of modern option pricing theory

It is not uncommon in the arrangement of a loan to include as part of the financial package a guarantee of the loan by a third party. Examples are guarantees by a parent company of loans made to its subsidiaries or government guarantees of loans made to private corporations. Also included would be guarantees of bank deposits by the Federal Deposit Insurance Corporation. As with other forms of insurance, the issuing of a guarantee imposes a liability or cost on the guarantor. In this paper, a formula is derived to evaluate this cost. The method used is to demonstrate an isomorphic correspondence between loan guarantees and common stock put options, and then to use the well developed theory of option pricing to derive the formula.     

The incompatibility of achieving a fully specified linear model with assuming that residual dependent-variable variance is random

The residual dependent-variable variance in experiments is not “random error”, as it is often assumed to be, but merely “unaccounted for variance”, because what is random is inexplicable in terms of any possible set of independent-variables and this is something that ultimately is only empirically determinable. So, if there is any unaccounted for dependent-variable variance, an experiment’s set of independent-variables is certainly under-specified and perhaps mis-specified because of the confounding of variables included in this set by causally relevant variables not included in the set. Thus, the proper first empirical test of any linear model is whether it leaves any residual dependent-variable variance, and if it does then none of its independent variables can yet logically justifiably be claimed to predict or causally explain any of the dependent-variable variance whatsoever.     

Associational versus correlational research study design and data analysis

Scientific human psychology (SHP) is an international public enterprise responsible for promoting the optimization of humanity’s experienced quality of life by means of the various psychological crafts, such as parenting, teaching, supervising; winning a debate or election, achieving a good enough sale or purchase, benefitting oneself by threatening, taunting, seducing or by protecting oneself through avoiding, escaping, or counteracting threats, taunts, seduction, entrapment; meditating, praying, exercising. Etc. Optimizing their practice for achieving this requires a research methodology that most cost-effectively facilitates doing so and therefore requires centrally coordinated programmatic research devoted to fully enough dimensionally specifying each of these crafts and their effects and to validly measuring on all these dimensions. Linear model (covariational) statistics presume too much about how causes and effects are inter-related to rely on for adequately informing such research, so SHP needs a less presumptive and more data sensitive form of study design and data analysis, the associational model.     

THE HISTORY OF FINANCE: AN EYEWITNESS ACCOUNT

In this account of the evolution of finance theory, the “father of modern finance” uses the series of Nobel Prizes awarded finance scholars in the 1990s as the organizing principle for a discus‐sion of the major developments of the past 50 years. Starting with Harry Markowitz's 1952 Journal of Finance paper on “Portfolio Selection,” which provided the mean‐variance frame‐work that underlies modern portfolio theory (and for which Markowitz re‐ceived the Nobel Prize in 1990), the paper moves on to consider the Capi‐tal Asset Pricing Model, efficient mar‐ket theory, and the M & M irrelevance propositions. In describing these ad‐vances, Miller's major emphasis falls on the “tension” between the two main streams in finance scholarship: (1) the Business School (or “micro normative”) approach, which focuses on investors ‘attempts to maximize returns and cor‐porate managers’ efforts to maximize shareholder value, while taking the prices of securities in the market as given; and (2) the Economics Depart‐ment (or “macro normative”) approach, which assumes a “world of micro optimizers” and deduces from that assumption how the market prices actually evolve. The tension between the two ap‐proaches is resolved, and the two streams converge, in the final episode of Miller's history–the breakthrough in option pricing accomplished by Fischer Black, Myron Scholes, and Rob‐ert Merton in the early 1970s (for which Merton and Scholes were awarded the Nobel Prize in 1998, “with the late Fischer Black everywhere ac‐knowledged as the third pivotal fig‐ure”). As Miller says, the Black‐Scholes option pricing model and its many successors “mean that, for the first time in its close to 50‐year history, the field of finance can be built, or…rebuilt, on the basis of ‘observable’ magnitudes.” That option values can be calculated (almost entirely) with observable vari‐ables has made possible the spectacu‐lar growth in financial engineering, a highly lucrative activity where the prac‐tice of finance has come closest to attaining the precision of a hard sci‐ence. Option pricing has also helped give rise to a relatively new field called “real options” that promises to revolu‐tionize corporate strategy and capital budgeting. But if the practical applications of option pricing are impressive, the op‐portunities for further extensions of the theory by the “macro normative” wing of the profession are “vast,” in‐cluding the prospect of viewing all securities as options. Thus, it comes as no surprise that when Miller asks in closing, “What would I specialize in if I were starting over and entering the field today?,” the answer is: “At the risk of sounding like the character in ‘The Graduate,’ I reduce my advice to a single word: options.”