Uncertain Prices Research Articles

An Unfair Option Game: The Effects of Asymmetric Government Subsidy to Innovators and Imitators

This article develops a model of real option game to analyze effect of asymmetric government subsidy on the investment thresholds of private investors who compete with each other in the same market with uncertain price. The optimal investment thresholds of innovator and imitator are derived, and the effects of some key variables, such as inflation rate, interest rate, and degree of intellectual property protection, on those thresholds were analyzed. With the help of our model and a numerical example of sewage treatment industry, we demonstrate that subsidy to both innovator and imitator reduces optimal investment thresholds, while subsidy only to innovator raises the investment thresholds rather than reducing them. Based on the results of our study, we suggest that the government should offer subsidy to both of innovator and imitator indiscriminately, raise the overall level of IP protection, and reduce the financial cost for private investors in order to motivate them to invest in PPP projects.

Protecting against Loss: Protective Put Strategiesversus Stop-Loss Strategies

The authors compare the effectiveness of two popular strategies for managing risk at the individual stock level: stop-loss orders and long put option positions. They find that the protective put generally produces higher returns than the stop-loss order. This result is consistent across a variety of different market conditions, with the protective put’s higher returns most prominent in high-volatility stocks and winner stocks. The authors consider two possible sources for the difference in returns: the greater precision in exit price provided by the protective put and the opportunity cost of stop-loss activation. They find that the difference in performance can be explained entirely by the greater precision in exit price provided by the put strike price relative to the more uncertain price provided by the stop-loss order.

Hedging with Regret

This paper investigates corporate hedging under regret aversion. Regret-averse firms try to avoid deviations of their hedging policy from the ex post best policy, an intuitive consideration if one has to justify one's decisions afterward. The study presents a model of a firm that faces uncertain prices and seeks to hedge both profit risk and regret risk with derivatives. It characterizes optimal hedge positions and shows that regret aversion leads to stronger incentives to hedge downside price risk than standard expected utility theory. In the profit region of the price distribution, however, regret aversion reduces the hedging of price risk to avoid large regret in the case of increasing prices. The results show that regret aversion has a strong effect on the choice of the hedging instrument and provides a preference-based explanation for the use of options in corporate risk management.

Compliance choice analysis for India's thermal power sector in the market-based energy efficiency regime

India has recently introduced a market-based scheme―Perform, Achieve, and Trade―to realize emission reduction by enhancing energy efficiency. In the case of thermal power plants, investment in energy efficiency projects, using clean coal and buying energy saving certificates are the available compliance options for complying with the scheme. These options are associated with specific forms of cash flows that depend on the uncertain price of energy saving certificates and clean coal premium. This paper uses a Monte Carlo-based decision tree approach to find the optimal compliance options for an efficient and a less efficient thermal power plant. The decision tree evaluates different sequences of compliance options in three consecutive PAT cycles by using the discounted cash flows and their associated probabilities. The study shows that investment in energy efficiency is optimal in the first PAT cycle for the inefficient plant only. The threshold certificate price for the efficient plant is substantially higher than the inefficient plant, implying that the real efficiency improvement is likely to take place in the low-efficiency plants. The study also indicates that the investment in high-efficiency plants is not optimal over a wide range of certificate prices and the incremental cost of clean coal.

Techno-Economic Forecasts of Lithium Nitrates for Thermal Storage Systems

Thermal energy storage systems (TES) are a key component of concentrated solar power (CSP) plants that generally use a NaNO3/KNO3 mixture also known as solar salt as a thermal storage material. Improvements in TES materials are important to lower CSP costs, increase energy efficiency and competitiveness with other technologies. A novel alternative examined in this paper is the use of salt mixtures with lithium nitrate that help to reduce the salt’s melting point and improve thermal capacity. This in turn allows the volume of materials required to be reduced. Based on data for commercial plants and the expected evolution of the lithium market, the technical and economic prospects for this alternative are evaluated considering recent developments of Lithium Nitrates and the uncertain future prices of lithium. Through a levelized cost of energy (LCOE) analysis it is concluded that some of the mixtures could allow a reduction in the costs of CSP plants, improving their competitiveness.

A Real Option Analysis applied to the production of Arabica and Robusta Coffee in Ecuador

The coffee market is distinguished for being volatile and uncertain in terms of domestic and international prices. Arabica and Robusta coffee are produced in 23 provinces of Ecuador. A decade-long decline of coffee production prompted the Ecuadorian government to launch a public program for replanting coffee trees towards the end of 2011. A grower’s decision to enter, remain in or exit the coffee sector is based on fluctuating profits from each year’s harvest sale. We analyzed the hypothesis whereby the coffee grower’s decision to leave the sector is explained by volatile and uncertain prices. This paper aimed to evaluate the coffee sector with an application of Real Option Analysis for the period 2002-2012. We also defined entry (H) and exit (L) prices for Arabica and Robusta coffee for the analyzed period. Our findings revealed high H and L prices encourage growers to leave the sector for the most part of the analyzed period. High H and L prices resulted from high variable cost due to increasing wages for farm workers. The Ecuadorian government is developing a policy to help growers make production more efficient, encouraging them to remain in the sector in the long run.

Valuation of convertible bond under uncertain mean-reverting stock model

Different from the classical method of pricing convertible bond under stochastic stock model, we investigate the valuation of convertible bond under uncertain mean-reverting stock model which is described by an uncertain differential equation. Within the framework of uncertainty theory, we proposed the uncertain pricing method, and present the price formulas of the convertible bond and the callable convertible bond.

THE EFFECTS OF ENTREPRENEURIAL ACTIVITY AND PREFERENCE FOR AVOIDING UNCERTAINTY ON NATIONAL ECONOMIC GROWTH

Entrepreneurs play an important role nowadays as well as in the history of economic thought - entrepreneur used to be the one bearing the risk of buying at certain prices and selling at uncertain prices, protagonist of economic activity and innovating so the new combinations of inputs are used in order to create new output. Nevertheless, relationship between entrepreneurial activity and national growth is not so straightforward. This study aims to contribute to the stream of research that tries to uncover the ultimate results of entrepreneurship. This paper seeks to explore influence of TEA in countries that belongs to different categories regarding ‘uncertainty avoidance’ cultural dimension. Our results could not confirm that entrepreneurial activity increases with increase of per capita income. We argue that entrepreneurial activity could contribute to GDP growth regardless of current level of development. We find that the entrepreneurial activity can increase or decrease GDP growth rates depending on level of preferences for uncertainty avoidance. We argue that TEA in countries with lower and higher preferences for uncertainty avoidance will negatively influence the GDP growth. Possible explanation is that less innovative ventures are created in countries with lower preference for uncertainty avoidance thus no considerable influence on GDP could be expected while more ventures fail as the entrepreneurs starts riskier business in the countries with higher preferences for uncertainty avoidance. Countries in the middle of these two extreme values can expect positive effect of TEA on GDP growth since preference for uncertainty is neither too high nor too low. Nevertheless, these results should be taken with caution since not all results were statistically significant. The main limitation is lack of data on entrepreneurial activity for all countries so instead of using TEA in the period preceding the GDP growth, average TEA for 2010-2011 was used.

Comparing the profitability of a dairy business with alternative investments

In the present study, the profitability of a dairy-farm case study evaluated over the period 2003–2004 to 2014–2015 was compared with the performance of other dairy farms and other non-agricultural investments over the same time. Investments are generally made on the expectation that a net return will be earned that justifies using capital in one particular way rather than an alternative way. The expected, and actual, returns from capital invested in different assets will differ according to the risks involved. Investors choose an investment, and mixes of investments, that align with their goals, preferences for risk and anticipated returns over time. Dairy farming involves investing in assets, such as land and improvements, water, livestock, plant and equipment, and people, which are managed to produce milk and ultimately to earn a competitive return on capital. With uncertain seasonal conditions, fluctuating costs and prices, declining terms of trade, wide ranges of equity and management abilities, and a steady decline in the number of commercial farm businesses, it may be tempting to presume that investing in farming, and dairy farming in particular, is a hard road, leading to lower and more variable returns than investing in non-agricultural investment opportunities in the economy. This need not be the case. Analysis of how a dairy business in northern Victoria performed from 2003–2004 to 2014–2015 showed that this farm did well compared with (i) other dairy businesses in Victoria and (ii) alternative investments, such as shares, bonds and property, over the same time. Compound annual return to capital for the dairy farm over the 12 years studied was 12.4% (real, before tax). Over half the return came from the farming operations and the remainder came from owning assets that appreciated in value, particularly in this case, water. The dairy business that was studied was well managed and earned higher annual average returns than the average returns of investments with similar risk elsewhere in the economy, such as shares, and matched it with the best performing of these alternative investments.

A bottom-up approach for demand response aggregators’ participation in electricity markets

This paper proposes a bottom-up model for demand response (DR) aggregators in electricity markets. This model enables a DR aggregator to consider the technical constraints of customers in developing an optimal trading strategy in the wholesale electricity market. In the bottom level, DR options, called load shifting, load curtailment and load recovery are comprehensively modelled in a stochastic programming approach. Each DR program is mathematically formulated in such a way that practically models the constraints of customers. Further, the proposed model considers the customers’ behaviour in participating in the given DR program through a scenario-based participation factor. On the other hand, the upper level proposes trading the DR outcome in day-ahead and balancing markets with uncertain prices, as well as in forward contracts with a predefined price. The overall bottom-up problem is formulated as a stochastic profit maximization model for the DR aggregator, in which the risk is taken into account using the Conditional Value-at-Risk (CVaR) measure. The feasibility of the given strategy is assessed on a case of the Nordic market.

Analyst information acquisition and the relative informativeness of analyst forecasts and managed earnings

Mixed empirical evidence exists on whether equity analyst forecasts complement (‘interpretation role’) or rather substitute for (‘information role’) the informativeness of corporate earnings. This paper develops a theoretical model in which an analyst acquires costly information to forecast the fundamental information contained in a subsequently released and strategically manipulated earnings announcement. The manager is assumed to manipulate earnings such that his objectives – an uncertain price interest and meeting-or-beating the analyst forecast incentives – are optimized. The model shows that the manager’s incentives are the source of the two roles of the analyst information in the valuation of earnings. In a theoretical regression of share price on earnings and the analyst forecast, it can be shown that a positive forecast response coefficient, and thus the dominance of the information role of analyst forecasts, is only obtained if the analyst’s information acquisition costs are sufficiently low.

Uncertain Price Competition in a Duopoly With Heterogeneous Availability

We study the price competition in a duopoly with an arbitrary number of buyers. Each seller can offer multiple units of a commodity depending on the availability of the commodity which is random and may be different for different sellers. Sellers seek to select a price that will be attractive to the buyers and also fetch adequate profits. The selection will in general depend on the number of units available with the seller and also that of its competitor - the seller may only know the statistics of the latter. The setting captures a secondary spectrum access network, a non-neutral Internet, or a microgrid network in which unused spectrum bands, resources of ISPs, and excess power units constitute the respective commodities of sale. We analyze this price competition as a game, and identify a set of necessary and sufficient properties for the Nash Equilibrium (NE). The properties reveal that sellers randomize their price using probability distributions whose support sets are mutually disjoint and in decreasing order of the number of availability. We prove the uniqueness of a symmetric NE in a symmetric market, and explicitly compute the price distribution in the symmetric NE.

Robust energy procurement strategy of large consumers

Summary This paper presents a risk-constrained model for large consumers to determine the optimal energy acquisition framework and the participation level in load-reduction programs based on the real-time pricing scheme. Additionally, the proposed pricing framework for the load-reduction enables the system operator to control the consumers' load reduction levels, according to energy prices. In competitive electricity markets, the uncertainty of hourly energy prices is the main problem faced by large consumers. Therefore, the information gap decision theory approach is addressed to manage the financial risk arising from uncertain prices. In this work, instead of profit maximization, the optimal robust framework is specified in a way that guarantees the desired profit. The robustness of the optimal procurement strategy is demonstrated by determining the variation interval of uncertain prices such that the profit associated with this strategy will be more than an acceptable threshold, which is defined by consumers. The performance of the presented model is analyzed via a case study. Copyright © 2015 John Wiley & Sons, Ltd.

Polymerization of epoxidized triglycerides with fluorosulfonic acid

ABSTRACTThe use of triglycerides as agri-based renewable raw materials for the development of new products is highly desirable in view of uncertain future petroleum prices. A new method of polymerizing epoxidized soybean oil has been devised with the use of fluorosulfonic acid. Depending on the reaction conditions, one can get a viscous oil or a solid as the reaction product. The reaction mechanism has been studied through a systematic examination of the fluorosulfonic acid-initiated reaction of epoxidized methyl oleate and epoxidized methyl linoleate. Through 13C NMR spectroscopy, the major species derived from fluorosulfonic acid-initiated polymerization of epoxidized soybean oil have been determined. The effects of temperature, initiator dosage, and reaction time have been studied and shown to affect the nature of polymer products obtained and the distribution of different chemical species present.

Uncertain pricing decision problem in closed-loop supply chain with risk-averse retailer

This paper considers a pricing and remanufacturing problem in closed-loop supply chain which includes one dominant manufacturer and one retailer under uncertain environment. The remanufacturing cost, market demand, and collection cost are characterized as uncertain variables. The firms’ optimal strategies are obtained by uncertainty-theory-based and game-theory-based models. Besides, the impacts of the risk sensitivity on the performances of the closed-loop supply chain members are given by the comparison of different degrees of the retailer’s risk aversion and numerical studies. It is found that only the manufacturer makes more profits when the retailer is more risk sensitive but this condition in the closed-loop supply chain still leads to better performance of the total system.

Efficient Management of Insecure Fossil Fuel Imports through Taxing Domestic Green Energy?

A small open economy produces a consumer good as well as renewable (green) and fossil fuel based (brown) energy. It imports fossil fuel at an uncertain price and suffers from carbon emission damages. Unregulated competitive markets are shown to be inefficient. The implied market failures are due to the agents' attitudes toward risk, to risk shifting, and the uniform price for both types of energy. Under the plausible assumptions that consumers are prudent and at least as risk-averse as the producers of brown energy, the risk can be efficiently managed by placing a tariff on fuel imports (which is equivalent to taxing carbon emissions in the model at hand) and taxing green energy. The need to tax green energy contradicts the widespread view that subsidization of green energy is an appropriate means to enhance energy security in countries depending on risky fossil fuel imports.

FFS - Small farmer vulnerability and climate risk: Index insurance as a financial fix

By its very nature, agriculture is a risky endeavor. Farmers not only face natural threats from pests, plant disease, and inclement weather, but many must also worry about fluctuating input costs, uncertain prices for their output, and, ultimately, their ability to repay debts and support their families. The growing incidence of extreme weather events and the rising volatility of agricultural commodity prices has greatly exacerbated the vulnerability of farmers since the turn of the century. This is especially the case for poor farmers in the global South who lack the assets and state protections that help to insulate their more fortunate counterparts.

A hybrid approach to select the best sourcing policy using stochastic programming

Supply contracts are known as the communication link among supply chain members. As sourcing of required goods is a challenging issue for supply chain members, different sourcing types for different market conditions have been presented in the literature. However, the uncertain price condition has not been much focused in the previous studies, and in the limited works on this issue the correlation between the periods has been ignored. In this paper, sourcing policies are analyzed in a multi-period system in which price and demand follow a Geometric Brownian Motion with drift. Wholesale contract, option contract, and purchase from the spot market are considered as the sourcing alternatives for the buyer. This paper applies the stochastic programming approach to model these three types of sourcing based upon price and demand uncertainties. Afterwards, a hybrid supply model of these sourcing types is developed. By a numerical example, the simulation results of the developed models reveal that each individual sourcing alternative can be selected as the best one in each price and demand behavior. The results also suggest that the proposed hybrid model dominates each of the individual sourcing types. Finally, the paper reports the effects of cost parameter alterations on the solution of the hybrid model through sensitivity analysis.

Decision-making framework for supplying electricity from distributed generation-owning retailers to price-sensitive customers

In this paper, a robust bi-level decision-making framework is presented for distributed generation (DG) owning retailers to supply the electricity to price-sensitive customers. Uncertainties about client demand and wholesale prices are the main difficulties faced by the electricity retailer. Clients can adjust their consumption according to the retailer's selling price. A higher selling price increases retailers' profit but decreases client consumption. Hence, the retailer faces a tradeoff between the price and sales. In the proposed model, the optimal selling price and the retailer's energy-supply strategy are modeled in the lower sub-problem. According to the proposed selling price, the optimal energy consumption of price-sensitive clients is determined in the upper sub-problem. To evaluate the financial risk arising from uncertain prices, the Information Gap Decision Theory (IGDT) approach is addressed in the lower sub-problem. Additionally, the risk-based optimization problem is formulated for risk-averse and risk-taker retailers via the robustness and opportunity functions, respectively. The robustness of the optimal solution against price variations is evaluated such that the associated profit will be more than the electricity retailer's acceptable threshold. The efficiency and performance of the decision-making framework are analyzed via a case study, and the numerical results are discussed.

Economic uncertainty, monetary uncertainty, and the demand for money in Thailand

Economic uncertainty reflected in the volatility of real GDP and monetary uncertainty reflected in the volatility of nominal monetary figure such as M2 are said to induce people to change their portfolio and reallocate their assets between cash and other financial assets. Either uncertainty could make public more cautious and therefore, hold more cash and less of other assets. On the other hand, to hedge against uncertain prices, public may hedge by holding more real less risky assets and less cash. We test these hypotheses by including a measure of output uncertainty and a measure of monetary uncertainty in the demand for money function in Thailand. Using bounds testing approach we find that both measures of uncertainty do have short-run as well as long-run effects on the demand for cash balances.