Portfolio Of Options Research Articles

Are real options a missing piece in the diversification-value puzzle?

This paper examines the impact of corporate diversification on a firm's market value in terms of changes in its mix of value sources between growth options and assets-in-place. We argue that the traditionally assumed replicability of corporate diversification benefits by individual investors might not be as feasible when diversification implies acquiring new growth options as when it only involves assets-in-place investments. We further explain why a different effect of diversification on a firm's mix of value sources can occur, therefore leading to a mediating role of growth options between diversification and market value. Using a panel sample of U.S. firms from 1998 to 2010, we find that a firm's growth options portfolio helps explain the effect of diversification strategy on its market value.

Do CEO Bonus Plans Serve a Purpose?

Given the substantial stock and option portfolios held by most CEOs, much recent literature on CEO incentives regards cash-based bonus plans as largely irrelevant. This begs the question of why nearly all CEO compensation plans include such bonuses. We re-examine the financial incentives provided by bonuses and their role in executive compensation packages. Using detailed data on bonus-plan performance measures, we document that the pay-performance sensitivity of CEO cash compensation is much greater than prior estimates and that cash-based pay provides a substantial portion of many CEOs’ total financial incentives early in their tenure. However, we find little evidence that boards adjust bonus plans over time in response to CEO-specific characteristics, such as the evolution of CEO equity holdings or liquidity needs. This “stickiness” results in growing disparity between the magnitudes of cash- and equity portfolio-based incentives over a typical CEO’s tenure. At the same time, we find evidence that bonus plans appear to consider liquidity and incentive issues for lower-level executives, leading us to conclude that cash-based plans are designed mainly for the overall management team, as well as perhaps new CEOs.

How can palliative care specialists best integrate into multidisciplinary oncology care for patients with metastatic breast cancer?

182 Background: Current evidence for palliative care/oncology integration derives from cancers with either very short prognoses or relatively limited treatment options (e.g. pancreas). Little is know about the role of palliative care in metastatic breast cancer, where prognosis may be measured in years and the treatment option portfolio is continuously expanding. Methods: The Cancer Support Community Metastatic Breast Cancer Experience Registry is a voluntary, patient-reported, online registry of patient experiences with cancer. We evaluated data reported by patients from March 2013 to March 2014. The registry includes demographic information and data regarding physical, emotional, social, and financial distress measured using Likert scales. We calculated descriptive statistics and Pearson’s chi-squared. Results: We evaluated 599 patients. The sample median age was 56; 93% were White; 61% had a bachelor’s degree or higher Median time from diagnosis of metastatic cancer was 3 years. Regarding physical distress, over 50% reported “moderate” or higher issues with sleep, nutrition and eating, and fatigue. Depression and anxiety prevalence increased by 15% and 20%, respectively, from pre-treatment to post-treatment. Among social distress, 25% felt alone, 62% worried about burdening their family, and over 50% limited contact with others. 30% or higher desired more assistance with: diagnostic and treatment information, making decisions, managing symptoms and emotions, and managing disruptions to family and work life. Respondents were more likely to have been asked about distress if they received part or all of their care at an academic or comprehensive cancer center (p < 0.001) or treatment through a clinical trial (p = 0.012). Conclusions: We identified a high prevalence of unmet needs across several supportive care domains. These areas of distress should be a targeted focus of palliative care and oncology integration to improve the care of patients with metastatic breast cancer.

Engaging farmers on climate risk through targeted integration of bio-economic modelling and seasonal climate forecasts

Seasonal climate forecasts (SCFs) can be used to identify appropriate risk management strategies and to reduce the sensitivity of rural industries and communities to climate risk. However, these forecasts have low utility among farmers in agricultural decision making, unless translated into a more understood portfolio of farm management options. Towards achieving this translation, we developed a mathematical programming model that integrates seasonal climate forecasts to assess ‘what-if?’ crop choice scenarios for famers. We used the Rayapalli village in southern India as a case study. The model maximises expected profitability at village level subject to available resource constraints. The main outputs of the model are the optimal cropping patterns and corresponding agricultural management decisions such as fertiliser, biocide, labour and machinery use. The model is set up to run in two steps. In the first step the initial climate forecast is used to calculate the optimal farm plan and corresponding agricultural management decisions at a village scale. The second step uses a ‘revised forecast’ that is given six weeks later during the growing season. In scenarios where the forecast provides no clear expectation for a dry or wet season the model utilises the total agricultural land available. A significant area is allocated to redgram (pigeon pea) and the rest to maize and paddy rice. In a forecast where a dry season is more probable, cotton is the predominant crop selected. In scenarios where a ‘normal’ season is expected, the model chooses predominantly cotton and maize in addition to paddy rice and redgram. As part of the stakeholder engagement process, we operated the model in an iterative way with participating farmers. For ‘deficient’ rainfall season, farmers were in agreement with the model choice of leaving a large portion of the agriculture land as fallow with only 40ha (total area 136ha) of cotton and subsistence paddy rice area. While the model crop choice was redgram in ‘above normal and wet seasons, only a few farmers in the village favoured redgram mainly because of high labour requirements, and the farmers perceptions about risks related to pests and diseases. This highlighted the discrepancy between the optimal cropping pattern, calculated with the model and the farmer's actual decisions which provided useful insights into factors affecting farmer decision making that are not always captured by models. We found that planning for a ‘normal’ season alone is likely to result in losses and opportunity costs and an adaptive climate risk management approach is prudent. In an interactive feedback workshop, majority of participating farmers agreed that their knowledge on the utility and challenges of SCF have highly improved through the participation in this research and most agreed that exposure to the model improved their understanding of the role of SCF in crop choice decisions and that the modelling tool was useful to discuss climate risk in agriculture.

The Fundamental Theorem of Derivative Trading - exposition, extensions and experiments

When estimated volatilities are not in perfect agreement with reality, delta-hedged option portfolios will incur a non-zero profit-and-loss over time. However, there is a surprisingly simple formula for the resulting hedge error, which has been known since the late 1990s. We call this The Fundamental Theorem of Derivative Trading. This paper is a survey with twists on that result. We prove a more general version of it and discuss various extensions and applications, from incorporating a multi-dimensional jump framework to deriving the Dupire–Gyöngy–Derman–Kani formula. We also consider its practical consequences, both in simulation experiments and on empirical data, thus demonstrating the benefits of hedging with implied volatility.

The Fundamental Theorem of Derivative Trading - Exposition, Extensions, and Experiments

When estimated volatilities are not in perfect agreement with reality, delta hedged option portfolios will incur a non-zero profit-and-loss over time. There is, however, a surprisingly simple formula for the resulting hedge error, which has been known since the late 90s. We call this The Fundamental Theorem of Derivative Trading. This paper is a survey with twists of that result. We prove a more general version of it and discuss various extensions (including jumps) and applications (including deriving the Dupire-Gyongy-Derman formula). We also consider its practical consequences both in simulation experiments and on empirical data thus demonstrating the benefits of hedging with implied volatility.

An improved framework for approximating option prices with application to option portfolio hedging

As the price of the underlying asset changes over time, delta of the option changes and a gamma hedge is required along with delta hedge to reduce risk. This paper develops an improved framework to compute delta and gamma values with the average of a range of underlying prices rather than at the conventional fixed ‘one point’. We find that models with time-varying volatility price options satisfactorily, and perform remarkably well in combination with the delta and delta-gamma approximations. Significant improvements are achieved for the GARCH model followed by stochastic volatility models. The new approach can ensure significant improvement in modelling option prices leading to better risk-management decision-making.

Bayesian MCMC Analysis on R&D Investment of Biotech Start-up in the ‘Valley of Death’

In addition to many need-pull innovations, a type of rare basic-research-push innovation is biopharmaceutical development. In reflecting next generation innovation, the NASDAQ Biotechnology Index (NBI) is actually moving stronger in comparison with other indicators. From the industry’s high dependence on basic research, biotech start-up, which is more excellent in combing breakthrough technologies and niche markets than the mass market and low risk-oriented large pharmaceutical companies are expected as a major driver of the innovation chain. However, from the prolonging period of pharmaceutical development, expansion of necessary investment, low possibility of success, and severe resource constraints, a drug discovery-based biotech start-up must endure the ‘Valley of Death’ as a long-term deficit state in addition to the high bankruptcy rate. Why can a biotech start-up that suffers from long-term deficits even in the financial crisis continue research and development investment? If so, what kind of criteria for investment can be utilized? Biotech start-up is defined as the portfolio of real options. As methodologies, this paper applies the real options concept to the assessment of the stockholders’ equity as technological potential and Bayesian MCMC to the parameter estimation between the net income, shareholders' equity value, and R&D costs of representative 30 companies in the NBI. Keywords: Biotech start-up, Valley of Death, R&D investment, real options analysis, Bayesian Markov Chain Monte Carlo.

Households transport-home energy conservation strategies in response to energy price policies: A stated adaptation experiment based on portfolio choices and cross effects designs

abstractThis article explores consumer investment choice in long-term energy conservation technology and assesses trade-offs in energy saving behaviour between the housing and transportation domains. The long-term energy conservation choice problem is conceptualized as a portfolio choice problem. Consequently, to measure trade-offs between investments in housing and transport options, a cross effects choice design is developed in which respondents were shown one or more alternate ways to reduce their current energy consumption: (1) investing in new technology in the house, such as solar panels; (2) exchanging the current car for a more energy efficient car; (3) buying a new energy-efficient car, such as EV or solar car; (4) moving house to reduce current travel distances. To help respondents linking these options to their current energy consumption, a new Web-based survey system (SINA) to implement and administer stated adaptation experiments was developed. The system was used to collect two sets of data. First, data about out-of-home and in-home energy consumption, together with detailed time use data, was collected. Second, using a cross effects design, respondents were asked to select a portfolio of energy-saving strategies in response to different energy pricing policy scenarios. Results reported in this paper are based on 572 respondents who completed the survey and responded to seven adaptation questions based on their current energy expenditures. A random parameters logit model is estimated to predict the probability of choosing a particular portfolio of energy-saving options. Estimation results indicate that individuals from different socio-demographic groups exhibit varied preferences. The saving option characteristics, especially cost related characteristics have significant effects on individuals' preferences. Moreover, the results also showed significant effects of choice set composition on energy saving options. Further, the energy pricing policies had showed mixed effects on individual's preferences.

Price Dislocations and Risk Management: Lessons from a Large Options Trading Loss

On May 8, 2007, the largest trading loss thus far reported in Sweden was announced by Carnegie Investment Bank, caused by a revaluation of the bank’s options portfolio. Among consequences, the bank’s CEO was forced to resign, the bank was fined a maximum penalty from the Swedish FSA, and three option traders were accused of market price manipulations and exploitation of inefficient internal procedures. Using unique data from the Swedish Economic Crimes Bureau, this paper provides a hands-on account of how market price were dislocated and shows the actual trading patterns behind the dislocations. Internal procedures at the bank failed and the paper provides some important lessons regarding operational risk management practices.

Selecting climate change mitigation strategies in urban areas through life cycle perspectives

Urban governments globally have generated climate change mitigation plans in recent decades. With greenhouse gases (GHG) being emitted from far-ranging anthropogenic sources, selecting mitigation alternatives from a portfolio of options can be highly challenging, particularly when capital budgets and life cycle costs are considered. This research combines life cycle assessment (LCA), life cycle cost accounting (LCCA), and mathematical formulation methods to select ideal alternatives for a case study city. We utilize LCA and LCCA to determine the environmental and economic costs associated with 15 different GHG emission abatement alternatives in four different infrastructure systems: lighting, transportation, buildings, and energy. These abatement alternatives are also assessed for high, medium, and low emission reduction scenarios. For this problem we propose two mathematical formulations to apply to the LCA and LCCA results. The first mathematical formulation is for a single-phase implementation of all selected solution design alternatives; the second mathematical formulation applies to the implementation of alternatives done in three phases. The modeling results reveal the selection differences that occur when capital budgets are varied for both single and multi-phase planning. This unique approach to urban GHG abatement planning can effectively aid policy makers in efficiently selecting best practices in climate change mitigation when balancing environmental and economic perspectives.

Hedging an option portfolio with minimum transaction lots: A fuzzy goal programming problem

Options are designed to hedge against risks to their underlying assets such as stocks. One method of forming option-hedging portfolios is using stochastic programming models. Stochastic programming models depend heavily on scenario generation, a challenging task. Another method is neutralizing the Greek risks derived from the Black–Scholes formula for pricing options. The formula expresses the option price as a function of the stock price, strike price, volatility, risk-free interest rate, and time to maturity. Greek risks are the derivatives of the option price with respect to these variables. Hedging Greek risks requires no human intervention for generating scenarios. Linear programming models have been proposed for constructing option portfolios with neutralized risks and maximized investment profit. However, problems with these models exist. First, feasible solutions that can perfectly neutralize the Greek risks might not exist. Second, models that involve multiple assets and their derivatives were incorrectly formulated. Finally, these models lack practicability because they consider no minimum transaction lots. Considering minimum transaction lots can exacerbate the infeasibility problem. These problems must be resolved before option hedging models can be applied further. This study presents a revised linear programming model for option portfolios with multiple underlying assets, and extends the model by incorporating it with a fuzzy goal programming method for considering minimum transaction lots. Numerical examples show that current models failed to obtain feasible solutions when minimum transaction lots were considered. By contrast, while the proposed model solved the problems efficiently.

Pricing D-Dimensional Real Portfolio Options Effect of Many-Valued Logic on Optimal Investment

In this work, I develop an option pricing framework for an American option on multiple real investment portfolios, which have price processes, for which the martingale assumption does not hold. Taking recourse to the philosophical theory of many-valued logic, the paper shows how this framework can serve as an aid for decision makers, who are confronted with interval-identified underlying value estimates rather than point estimates. I use a non-parametric version of the Longstaff and Schwartz (2001) numerical option pricing algorithm to assess the optimal stopping times, which are embedded in the option pricing problem. Against the theoretical expectation, high levels of tolerance with respect to contradictory underlying price process information in the decision maker’s information processing do not lead to superior investment decisions.

Analyzing manufacturers' impact on green products' market diffusion – the case of electric vehicles

Electric vehicles are often seen as a promising way for rationalizing the use of fossil energy in the automotive sector. So far, however, their market success and thus their impact on reducing fossil fuel consumption are rather limited. In this article, the automotive market simulator (AMaSi) is applied to analyze the leverage of manufacturers to support the market diffusion of electric vehicles. This is done by parameterizing the model for the German car market and simulating different product portfolio options regarding the timing of the introduction and the elimination of vehicle models; an aggregated industry as well as an individual manufacturer's perspective is taken into account. The results indicate that manufacturers' portfolio decisions have a strong influence on the market development of electric vehicles and can be used to gain a competitive advantage. Thus, manufacturers should proactively strive to shape the electric vehicle market instead of adopting a waiting position. For policymakers these findings imply that instruments to steer manufacturers' behavior are just as important as those targeted at consumers. The paper broadens the discussion on the levers for the market diffusion of electric vehicles by providing a simulator to analyze manufacturers' portfolio decisions in a competitive setting and by illustrating the necessity to include portfolio decisions when designing mechanisms to foster the market diffusion of electric vehicles.

Tail Protection for Long Investors: Trend Convexity at Work

The performance of trend following strategies can be ascribed to the difference between long-term and short-term realized variance. We revisit this general result and show that it holds for various definitions of trend strategies. This explains the positive convexity of the aggregate performance of Commodity Trading Advisors (CTAs) which -- when adequately measured -- turns out to be much stronger than anticipated. We also highlight interesting connections with so-called Risk Parity portfolios. Finally, we propose a new portfolio of strangle options that provides a pure exposure to the long-term variance of the underlying, offering yet another viewpoint on the link between trend and volatility.

Climate change and indicators of probable shifts in the consumption portfolios of dryland farmers in Sub-Saharan Africa: Implications for policy

Several studies estimate the immediate impact of climate change on agricultural societies in terms of changes in crop yields or farm income, though few studies concentrate on the immediate secondary consequences of climate change. This synthetic analysis uses a set of indicators to assess the repercussions of predicted income reductions resulting from climate change on food consumption, nutrition, health expenditure, education, and recreation in Zimbabwe, Cameroon, South Africa and Ethiopia. We also assess the potential decline in human development potential among smallholder dryland farmers in these sub-Saharan African countries. In contrast to previous efforts, the current study directly integrates the uncertainties in estimations of income changes and secondary consequences through a weighting scheme. The results reveal moderate to high levels of secondary impacts which could lead to increased vulnerability to diseases, susceptibility to nutritional disorders, deprivation of educational opportunities, and ultimately to a reduction in human and societal development potential among the considered nations. The article concludes by proposing a portfolio of policy options for ameliorating the secondary impacts of climate change in these sub-Saharan African countries.

Outperforming benchmarks with their derivatives: theory and empirical evidence

Recent literature has demonstrated the existence of an unbounded risk premium if one combines the most important models for pricing and hedging derivatives with coherent risk measures. There may exist combinations of derivatives (good deals) whose pair (return risk) converges to the pair (+∞, −∞). This paper goes beyond existence properties and looks for optimal explicit constructions and empirical tests. It will be shown that the optimal good deal above may be a simple portfolio of options. This theoretical finding will enable us to implement empirical experiments involving three international stock index futures (Standard & Poor's 500, Eurostoxx 50 and DAX 30) and three commodity futures (gold, Brent and the Dow Jones-UBS Commodity Index). According to the empirical results, the good deal always outperforms the underlying index/commodity. The good deal is built in full compliance with the standard derivative pricing theory. Properties of classical pricing models totally inspire the good deal construction. This is a very interesting difference in our paper with respect to previous literature attempting to outperform a benchmark.

Form PF and the Systemic Risk of Hedge Funds: Risk-Measurement Precision for Option Portfolios

Form PF is the implementation of Congress’s post-crisis mandate for risk reporting by hedge funds to help protect investors and monitor systemic risk. The authors extend the methodology of Flood, Monin, and Bandyopadhyay to assess the risk measurement tolerances of Form PF for portfolios including options exposures. They generate a range of simulated portfolios of equities and equity options, wherein the weights are calibrated so that portfolios appear identical on Form PF. The authors assess the measurement tolerances of Form PF by examining the min–max range of actual risk exposures as measured directly from portfolio details. They find that the possible range of variation is significant. For portfolios that include options but do not report value-at-risk on Form PF, the range is especially large.

Form PF and Hedge Funds: Risk-Measurement Precision for Option Portfolios

The Securities and Exchange Commission’s Form PF is the implementation of Congress’s post-crisis mandate for risk reporting by hedge funds to help protect investors and monitor systemic risk. We extend the methodology of Flood, Monin, and Bandyopadhyay [2015] to assess the risk measurement tolerances of Form PF for portfolios including options exposures. We generate a range of simulated portfolios of equities and equity options, where the weights are calibrated so that portfolios appear identical on Form PF. We assess the measurement tolerances of Form PF by examining the minimum-maximum range of actual risk exposures as measured directly from portfolio details. We find that the possible range of variation is significant. For portfolios that include options but do not report value at risk on Form PF, the range is especially large.

Option pricing and coordination in the fresh produce supply chain with portfolio contracts

This paper studies a fresh produce supply chain that consists of a supplier and a retailer in a newsvendor framework. The supplier is the Stackelberg leader and the retailer is the follower. The retailer can obtain products from the supplier by wholesale price and call option portfolio contracts. The fresh produce incurs a circulation loss in quantity during its transportation. The retailer’s optimal ordering policy and the supplier’s optimal pricing policy are derived in the presence of portfolio contracts and circulation loss. It is demonstrated that, as the prices of option increase toward their optimal, the supplier’s expected profit increases whereas the retailer’s expected profit decreases, and the retailer is more sensitive to the price change. It is also found that the fresh produce supply chain can be coordinated by the portfolio contracts, and Pareto improvement for both chain members can also be achieved as compared with the non-coordinated contracts. However, when the supply chain is coordinated, the supplier cannot realize its optimal pricing strategy. Finally, it is shown that the supplier’s optimal option pricing policy is independent to the demand risk and wholesale price, and the circulation loss of fresh produce increases the management risks of the fresh produce supply chain.