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Analysis of Information Options offers new tools for evaluating investments in research, mineral exploration, logistics, energy transmission, and other information operations. With Information Options, the underlying assets are information assets and the rules governing exercise are based on the realities of the information realm (infosphere). Information Options can be modeled as options to “purchase” information assets by paying the cost of the information operations involved. Information Options arise at several stages of value creation. The initial stage involves observation of physical phenomena with accompanying data capture. The next refinement is to organize the data into structured databases. Then bits of information are selected from storage and synthesized into an information product (such as a management report). Next, the information product is presented to the user via an efficient interface that does not require the user to be a field expert. Information Options are similar in concept to real options but substantially different in their details, since real options have physical objects as the underlying assets and the rules governing exercise are based on the realities of the physical world. Also, while exercising a financial option typically kills the option, Information Options may include multiple exercises. Information Options may involve high volatility or jump processes as well, further enhancing their value. This chapter extends several important real option applications into the information realm, including jump process models and models for valuing options to synthesize any of n information items into any of m output assets.

In this chapter we develop and implement a method for maximum simulated likelihood estimation of the continuous time stochastic volatility model with the constant elasticity of volatility. The approach does not require observations on option prices, nor volatility. To integrate out latent volatility from the joint density of return and volatility, a modified efficient importance sampling technique is used after the continuous time model is approximated using the Euler–Maruyama scheme. The Monte Carlo studies show that the method works well and the empirical applications illustrate usefulness of the method. Empirical results provide strong evidence against the Heston model.

This paper uses contingent claims analysis to evaluate the implicit government guarantee to Fannie Mae and Freddie Mac prior to their placement into conservatorship. The main findings of the paper indicate that the expected value of the guarantee was in line with the size of capital injections under the Treasury Preferred Stock Purchase Agreement and that the market expected the government to cover nearly all expected losses on senior debt. However, simulations reveal that the eventual total cost to recapitalize the GSEs may be significantly higher than provided for under the original terms of the conservatorship.

On May 18, 2014, AT&T Inc., the second-biggest U.S. mobile-phone carrier, agreed to acquire DirecTV, a satellite-television company, for $49 billion in cash and stock. However, the merger’s conditions and terms are complicated as the stock exchange ratio is contingent on the volume-weighted average AT&T stock price over a 30-day period that is three trading days prior to the date when the merger becomes effective.

Using a contingent claims pricing approach, we model DirecTV’s theoretical value based on the merger’s conditions and terms. It is shown that the theoretical DirecTV stock value is analogous to the sum of the present value of a cash offer, plus owning shares of the AT&T stock, and short volume-weighted average price (VWAP) call spreads. Using three different option-pricing models, DirecTV’s stock valuation model is tested with the market data. Empirical results show that on average, DirecTV’s stock was consistently priced at a discount during the sample period, and Funahashi and Kijima’s (2017) VWAP option model works better than Black and Scholes’ (1973) plain vanilla option model and Levy’s (1992) average-price option model.

The effects of price limits and market illiquidity are crucial for pricing derivatives based on some underlying assets traded in the markets with a price limit rule and an illiquidity phenomenon. We develop models to value options for the cases of either the underlying assets encountering price limits and market illiquidity, or when the underlying assets are imposed with price limits and the options themselves show market illiquidity in this paper. The Black–Scholes (1973) model, the Krakovsky (1999) model, and the Ban, Choi, and Ku (2000) model are presented as special cases of our model. Our numerical results show that both the price limit and market illiquidity significantly affect the option values.

We describe some recent contingent capital securities (CoCos) and explore the issues that confront their development. We take the view that bank CoCos should be designed to maintain confidence in a bank before a crisis begins because once a crisis commences it is difficult to see how a bank can assure the capital market without the support of state aid. With this overriding objective in mind we find that, in at least some respects, existing examples of bank CoCos have got the ‘right’ design. Existing bank CoCos are unfunded as they should be as there is no need to structure these securities to provide additional liquidity. If funding turns out to be necessary then a liquidity crisis is already underway and the CoCo has already failed in its attempt to maintain confidence in the bank. Moreover, existing CoCos use the simpler single trigger that we favour rather than dual trigger structure recommended by some.

This paper explores the role of institutional objects in the constitution of institutional logics. Institutional objects depend for their objectivity on the goods produced through those objects, such as economic models, passports, or sacred texts. The authors theorize institutional logics as grammars of valuation that institutionalize goods through institutional objects. The authors identify four value moments through which goods are objectified: institution, the instituting of a good, a belief and an imagination of its objective goodness; production, how the good is produced, what practices are productive of the good; evaluation, how good is the good, the practices and objects through which worth in terms of that good is determined, and territorialization, the domain of reference of the good, to what objects and practices a good can and does refer in its instantiations. The authors assess the adequacy of our model through an institutional object based on the good of “market value” – i.e., an options pricing model. The authors discuss the implications of these findings for institutional logical theory and the sociology of valuation.