An Optimal Rule for Switching over to Renewable fuels with Lower Price Volatility: A Case of Jump Diffusion Process

This study investigates the optimal switching boundary to a renewable fuel when oil prices exhibit continuous random fluctuations along with occasional discontinuous jumps. In this paper, oil prices are modeled to follow jump diffusion processes. A completeness result is derived. Given that the market is complete the value of a contingent claim is risk neutral expectation of the discounted pay off process. Using the contingent claim analysis of investment under uncertainty, the Hamilton-Jacobi-Bellman (HJB) equation is derived for finding value function and optimal switching boundary. We get a mixed differential-difference equation which would be solved using numerical methods.Demand and Price Analysis, Resource /Energy Economics and Policy,

Essays in public economics and mathematical finance

Abstract: Chapter 1 Why do some economies remain technologically backward even when technologies on the frontier are available for adoption, virtually freely? If institutions are fragile and property rights insecure, potential adopters of frontier technologies may be dissuaded if adoption leads to increased expost conflict over rightful shares to the higher returns. In such a setting, publicly-funded protection of private property rights may successfully support the adoption of best-available technologies as a Nash equilibrium. The movement to more-secure property rights may or may not be welfare-enhancing. Abstract: Chapter 2 In this chapter, valuation of a financial derivative, known as Stock Loan, is addressed when the underlying asset is subject to risk of bankruptcy. A stock loan is a financial derivative where the owner of an asset (a share of a stock) can obtain a loan from a lender (usually, a bank) using that asset as a collateral. The movements of the asset price is modeled to follow a geometric Brownian motion, with constant drift and volatility. Following the credit risk literature, risk of bankruptcy is introduced according to both structural and reduced form approaches. In the structural form modeling, default is introduced following the Black and Cox (1976) formulation, where the asset is declared as bankrupt as soon as the asset price falls below a pre-determined lower boundary. Modeling the lower boundary as a deterministic function of time, a closed form expression for the valuation of the financial derivative is obtained in terms of the probability distribution of the first passage time of Brownian motion and the valuation of the Down-and-out barrier option. The pricing formula in the structural form modeling is based on the celebrated Black and Scholes (1973) framework and therefore, is easy to implement. As a salient feature of structural form modeling, default time turns out to be a predictable stopping time. In the reduced form approach, bankruptcy is modeled to occur through a default intensity which is assumed to be a decreasing function of discounted stock price. The event of bankruptcy is modeled as a non-predictable phenomenon. In this formulation, the existence of an optimal exercise boundary is proved, which is of threshold type. This optimal decision threshold is crucially contingent on the policy variables that are treated as parameters of the system. We proceed further to use numerical methods to address the sensitivity analysis of the optimal exercise boundary. The results of our numerical simulation provide further insights into the linkage between optimal exercise boundary and the policy variables. We find that optimal exercise boundary is crucially contingent on the effective rate of return (defined as the difference between interest and lending rate) and exhibits a non-monotone relationship. We also find an interval where optimal exercise boundary shows a monotone increasing relationship with an increase in volatility. The sensitivity analysis in the reduced form modeling can be useful in recommending policy prescriptions in the valuation of mortgage backed securities

A nonradioactive assay method for determination of enzymatic activity of d-ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco)

A sensitive and nonradioactive assay method for activity determination of Rubisco is described. The method is based on thin-layer chromatographic separation of 3-phosphoglycerate (3-PGA) and d-ribulose-1,5-bisphosphate (RuBP). This assay method allows the quantitative determination of Rubisco activity. Rates of carbon dioxide fixation on RuBP determined by this method were comparable to those obtained independently by other methods. This assay method is reproducible and relatively free from interference

Biochemical engineering: cues from cells

Engineering principles are used in the exploitation of biocatalysts derived from cells. The purity of reagents, catalysts and maintenance of operation variables are extremely important for bioengineering systems. Any change in the purity of reagents or in operation variables usually leads to a dramatic decrease in productivity. Cellular systems, however, are able to work with relatively high impure conditions and increase their productivity in response to external signals. Thus the seemingly disordered ‘bag of juice’ or cytoplasm has more order and much higher order of integration than first appears. Learning the semantics of this paradoxical ability of order and integration would help bioengineers to understand and enhance productivity even using impure reagents

An Optimal Rule for Switching over to Renewable fuels with Lower Price Volatility: A Case of Jump Diffusion Process

This study investigates the optimal switching boundary to a renewable fuel when oil prices exhibit continuous random fluctuations along with occasional discontinuous jumps. In this paper, oil prices are modeled to follow jump diffusion processes. A completeness result is derived. Given that the market is complete the value of a contingent claim is risk neutral expectation of the discounted pay off process. Using the contingent claim analysis of investment under uncertainty, the Hamilton-Jacobi-Bellman (HJB) equation is derived for finding value function and optimal switching boundary. We get a mixed differential-difference equation which would be solved using numerical methods

Metabolic networks of microbial systems

In contrast to bioreactors the metabolites within the microbial cells are converted in an impure atmosphere, yet the productivity seems to be well regulated and not affected by changes in operation variables. These features are attributed to integral metabolic network within the microorganism. With the advent of neo-integrative proteomic approaches the understanding of integration of metabolic and protein-protein interaction networks have began. In this article we review the methods employed to determine the protein-protein interaction and their integration to define metabolite networks. We further present a review of current understanding of network properties, and benefit of studying the networks. The predictions using network structure, for example, in silico experiments help illustrate the importance of studying the network properties. The cells are regarded as complex system but their elements unlike complex systems interact selectively and nonlinearly to produce coherent rather than complex behaviors

Metabolic networks of microbial systems

Abstract In contrast to bioreactors the metabolites within the microbial cells are converted in an impure atmosphere, yet the productivity seems to be well regulated and not affected by changes in operation variables. These features are attributed to integral metabolic network within the microorganism. With the advent of neo-integrative proteomic approaches the understanding of integration of metabolic and protein-protein interaction networks have began. In this article we review the methods employed to determine the protein-protein interaction and their integration to define metabolite networks. We further present a review of current understanding of network properties, and benefit of studying the networks. The predictions using network structure, for example, in silico experiments help illustrate the importance of studying the network properties. The cells are regarded as complex system but their elements unlike complex systems interact selectively and nonlinearly to produce coherent rather than complex behaviors.</p