Portfolio Of Options Research Articles

The Intersection of Wastewater Treatment Plants and Threatened and Endangered Species in California, USA Watersheds

AbstractA changing climate and often unregulated water extractions have exposed over 2 billion people to water stress worldwide. While water managers have explored a portfolio of options to reduce this stress, supply augmentation through reuse of treated municipal wastewater is becoming increasingly attractive. Wastewater treatment plants protect water quality and prevent sewage from contaminating waterways. Increasingly, this resource is utilized for numerous human (e.g., irrigation, drinking water, groundwater recharge) and conservation (e.g., stream and river recharge) needs in water stressed regions. To understand the role treated municipal wastewater plays in impacting conservation objectives we identified the intersection of wastewater treatment plant locations and occurrences of threatened and endangered (T&E) species in California and compared the permitted contribution of effluent to baseflow quantities of the receiving waterbody to assess the degree to which changes in effluent could affect instream waterbodies. We found a positive correlation between the presence of treatment plants and T&E species in California watersheds—a quarter of species have 100% of their range in watersheds with at least one treatment plant. This correlation is greatest for species associated with terraces and riparian habitat, followed by aquatic habitat and aquatic emergent vegetation. One‐third of watersheds in our analysis can receive most of their cumulative watershed baseflow from effluent and are characterized by dense urbanization or agriculture. Our analysis demonstrates that the fates of T&E species and effluent are interconnected in ways important for water policy, suggesting that species conservation goals should be considered when making decisions about effluent reuse.

Valuing photovoltaic power plants by compound real options

Meeting electricity demand with renewable generation requires spending trillions of dollars in investments exposed to financial risk. Renewable projects have multiple strategic real options to manage investment risk, but they are usually priced separately in isolation. This paper proposes a framework for valuing multistage decisions in a grid-scale photovoltaic (PV) power plant under uncertainty. The project is modelled as a compound portfolio of American sequential and mutually exclusive options to defer, expand and relocate. The compound options are jointly priced by a hierarchically nested least-squares Monte Carlo algorithm. The framework incorporates uncertainties related to decreasing costs in solar technology and the emergence of more profitable renewable tariffs elsewhere. The results show that the value of the compound option portfolio significantly exceeds the value of the single deferral option commonly considered in practice. Ignoring expansion and relocation flexibilities may lead to underinvestment by mispricing the value of PV projects. Incorporating these options encourages early commitment of the PV investment. Moreover, summation of individual option prices may not be a good approximation of the true portfolio value, as interactions among options exist. These findings may improve allocation efficiency of renewable investments, accelerate energy transition and benefit investors, funding agencies and regulators.

Optimal economic and environmental design of multi-energy systems

Designing decentralized energy systems in an optimal way can substantially reduce costs and environmental burdens. However, most models for the optimal design of multi-energy systems (MESs) exclude a comprehensive environmental assessment and consider limited technology options for relevant energy-intensive sectors, such as the industrial and mobility sectors. This paper presents a multi-objective optimization framework for designing MESs, which includes life cycle environmental burdens and considers a wide portfolio of technology options for residential, mobility, and industrial sectors. The optimization problem is formulated as a mixed integer linear program that minimizes costs and greenhouse gas (GHG) emissions while meeting the energy demands of given end-users. Whereas our MESs optimization framework can be applied for a large range of boundary conditions, the geographical island Eigerøy (Norway) is used as a showcase as it includes substantial industrial activities. Results demonstrate that, when properly designed, MESs are already cost-competitive with incumbent energy systems, and significant reductions in the amount of natural gas (92%) and GHG emissions (73%) can be obtained with a marginal cost increase (18%). Stricter decarbonization targets incur larger costs. A broad portfolio of technologies is deployed when minimizing GHG emissions and integrating the industrial sector. Environmental trade-offs are identified when considering the construction phase of energy technologies. Therefore, we argue that (i) MES designs and assessments require a thorough life cycle assessment beyond GHG emissions, and (ii) the entire life cycle should be considered when designing MESs, with the construction phase contributing up to 80% of specific environmental impact categories.

Vol, Skew, and Smile Trading

We show how a three-strike option portfolio can be used to either trade the difference between the instantaneous variance rate and the implied variance rate, the difference between the instantaneous covariation rate and the implied slope, or the difference between this instantaneous variance rate of volatility and the implied convexity. We label each one of these strategies as vol, skew and smile trades. Our results yield precise financial interpretations of particular measures of the level, slope, and curvature of a BMS implied variance curve. We provide empirical evidence that the average returns of the vol and smile (skew) trades are negative (positive) and that the returns of the skew and smile trades cannot be explained by the CAPM.

Hybrid Power Generation Supply Chain Financing and Purchasing Strategies with Option Hedging against Disruption

Environmental pollution has stimulated cleaner and sustainable energy (CSE) resource consumption which fuels low-carbon electric-power growth. This consumption is particularly affected by two factors. One of them is the power grid’s capital size in the electricity supply chain (ESC) and the other is the carbon emission reduction level elasticity of electricity consumption. Further, the financial strategy directly exerts quantifiable influence on one of the factors of capital size, while the procurement strategy plays a role in another factor. However, the impact of strategic behavior on all participants in the ESC remains unexplored. Thus, we construct a game model for the ESC consisting of two heterogeneous power plants and a strategic power grid with financial constraints, in order to analyze the purchasing and financing strategies for low-carbon electric-power consumption and examine the profit scenario from the credit and option hedging. We find that for the power grid, high self-owned funds level or affluent credit line encourages procurement. And when considering the power grid funds are uniformly distributed on or are constant, this funds property variation surely imposes influence on the wind electricity purchases. We find price elasticity of demand shows monotonic on the purchase when the power grid funds are constant but not necessarily when funds are uniformly distributed. The two power plants pursue the most favorable scenario for profit-maximizing by means of credit interest rate. Whether the power plants increase the financial credit interest is contingent upon option portfolios, the grid’s fund property, and wind yield conditions. We also find whether the relations between the two power plants are competitive or complementary depending on the wind yield rate. Numerical study shows that when the power grid funds are uniformly distributed, executing the double option seems to be the most profitable choice for the power grid and the traditional energy power plant, whereas with the uniform distribution of the grid’s funds, executing the call option but abandoning put is the most profitable to the traditional energy power plant. Moreover, under the grid’s fund of uniform distribution, it can both motivate power user consumption for clean energy generation and expand the power grid’s capital size.

On the Nature of (Jump) Skewness Risk Premia

Market skewness risk is priced, but the components of its premium are not fully understood. We propose new trading strategies decomposing the skewness risk premium into jump and leverage effect components, and we analyze the skewness risk premia in the market for S&P 500 index options. We find that the skewness premium is higher when markets are closed than during trading hours, consistently with uncertainty resolution patterns by non-U.S investors; that it increases after left-tail market events; and that it is distinct from the variance premium. Moreover, during trading hours, the skewness premium is dominated by priced jump risk. This paper was accepted by Kay Giesecke, finance. Funding: P. Orłowski acknowledges financial support from the Doc.Mobility program of the Swiss National Science Foundation [Project P1TIP1_161875 “Option portfolio returns and dispersion”]. P. Schneider acknowledges financial support from the Swiss National Science Foundation [Projects 169582 “Model-free asset pricing” and 189086 “Scenarios”]. F. Trojani and P. Orłowski acknowledge financial support from the Swiss National Science Foundation [Project 150198 “Higher order robust resampling and multiple testing methods”] and the Swiss Finance Institute [Project “Term structures and cross-sections of asset risk premia”]. F. Trojani gratefully acknowledges support from the AXA Chair in Socioeconomic Risks of Financial Markets at the University of Turin. Supplemental Material: The data files and online appendices are available at https://doi.org/10.1287/mnsc.2023.4734 .

The effect of optimal investment by stock options incentive under economic policy uncertainty

ABSTRACT This study shows that executive stock options are an effective compensation policy that takes corporate investment to the optimal level in the presence of unpredictable risk from economic policy uncertainty (EPU). We aim to explore whether stock options provide incentives for executives to choose a project that the optimal investment needs to be implemented. We use delta and vega as a proxy for price sensitivity and compensation sensitivity, respectively, to examine the interaction between executive stock options portfolio and EPU. We use delta for price sensitivity and vega for compensation sensitivity, respectively, to examine the interaction between executive stock options portfolio and EPU. Our analysis shows that a well-designed compensation structure motivates executives to maintain the optimal investment level when faced with unpredictable risks.

Intelligent option portfolio model with perspective of shadow price and risk-free profit

Since Markowitz proposed modern portfolio theory, portfolio optimization has been being a classic topic in financial engineering. Although it is generally accepted that options help to improve the market, there is still an improvement for the portrayal of their unique properties in portfolio problems. In this paper, an intelligent option portfolio model is developed that allows selling options contracts to earn option fees and considers the high leverage of options in the market. Deep learning methods are used to predict the forward price of the underlying asset, making the model smarter. It can find an optimal option portfolio that maximizes the final wealth among the call and put options with multiple strike prices. We use the duality theory to analyze the marginal contribution of initial assets, risk tolerance limit, and portfolio leverage limit for the final wealth. The leverage limit of the option portfolio has a significant impact on the return. To satisfy the investors with different risk preferences, we also give the conditions for the option portfolio to gain a risk-free return and replace the Conditional Value-at-Risk. Numerical experiments demonstrate that the intelligent option portfolio model obtains a satisfactory out-of-sample return, which is significantly positively correlated with the volatility of the underlying asset and negatively correlated with the forecast error of the forward price. The risk- free option model is effective in achieving the goal of no drawdown and gaining satisfactory returns. Investors can adjust the balance point between returns and risks according to their risk preference.

GAMIFICATION IN URBAN PLANNING - EXPERIENCING THE FUTURE CITY

Virtual Reality (VR) systems have been commonly used in the game and entertainment industries and are also increasingly explored in architecture and urban planning. They assist designers to communicate design ideas to a wider public and can engage them in the design processes. In this paper, we explore gaming environments to allow users to learn about smart city applications, such as innovative mobility approaches, urban farming, drone delivery, etc. The project is part of a real-world project for a future city for 50,000 inhabitants in the European side of Istanbul, Turkey. VR technologies can offer a testing ground for testing ideas, simulating performance, crowdsourcing ideas, before building the actual city physically. Gaming incentivizes citizens to participate in the design process, and the data collected provides a significant feedback loop to shape the city of the future. Citizens can immerse themselves in the VR environment, and experience the design via four circulation modes, e.g., walking, biking, driving, and flying. They allow users to explore novel circulatory approaches within new and innovative city arteries. Indeed, the design of the city accommodates a portfolio of mobility options, and the gamification allows testing pioneering designs, e.g., parallel streets for pedestrians, vehicles, etc. Furthermore, the game allows users to collect points when engaging in smart city topics, such as urban farming, solar energy usage, carbon neutrality, etc. Feedback loop that helps to iterate on the design. The project consists of three phases, a. an immersive VR version of the city experienced on head-mounted-displays, b. edutainment and the gamification of the city, and c. the integration of the digital version of the city into Meta’s multi-user space. In the paper, we present early findings of the project, the methods/tools explored, and discuss the utility of VR technologies in the design processes of architecture and urban planning.

Option Return Predictability with Machine Learning and Big Data

Abstract Drawing upon more than 12 million observations over the period from 1996 to 2020, we find that allowing for nonlinearities significantly increases the out-of-sample performance of option and stock characteristics in predicting future option returns. The nonlinear machine learning models generate statistically and economically sizable profits in the long-short portfolios of equity options even after accounting for transaction costs. Although option-based characteristics are the most important standalone predictors, stock-based measures offer substantial incremental predictive power when considered alongside option-based characteristics. Finally, we provide compelling evidence that option return predictability is driven by informational frictions and option mispricing. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

МОДЕЛЮВАННЯ ІНВЕСТИЦІЙНОГО ФОНДУ АКЦІЙ ІЗ ЗАСТОСУВАННЯМ СТРАТЕГІЙ КЕРУВАННЯ ФІНАНСОВИМИ ДЕРИВАТИВАМИ ТА ХЕДЖУВАННЯ

The article is devoted to the investigation of determining an effective method of modeling investment and option portfolios, as well as creating a software product that can automate the process of achieving such goals. In times of economic instability, the critical goal for investors is to reduce the risk of losing profits. Before creating your investment portfolio, you need to determine its management strategy's specific goals and objectives, priorities in choosing stock assets for investment, and to form the proportions of investment resources in different types of portfolios. The most used portfolio strategies factors of market volatility, therefore, it is advisable to modify existing models and use newer methods to form a strategy for managing the investment portfolio to reduce risk. During the work, various methods of forecasting market stock prices were investigated, a model was developed to determine the optimal investment portfolio and its value. After that, this algorithm was automated as a developed software application. The result of the investigation is the creation of a combined model of portfolio management, which predicts the development of used stock assets and creates a strategy for managing them on the basis of the obtained forecast data. The model also calculates the expected profit and investment strategy in case of unexpected changes in the market. The effectiveness of the model is tested on the forecast and actual historical data for the period under review. The modeling examined 7 stocks, including Tesla, Netflix, Amazon, Alphabet Inc., Facebook, Restoration Hardware Holdings, and EPAM. The model adapts to the types of stocks under consideration and adjusts its forecasts to obtain a minimum error from the actual ones. At the output, the model issues a portfolio management strategy for the next month, based on basic forecast data.

Application of fuzzy Malliavin calculus in hedging fixed strike lookback option

<abstract><p>In this paper, we develop a Malliavin calculus approach for hedging a fixed strike lookback option in fuzzy space. Due to the uncertainty in financial markets, it is not accurate to describe the problems of option pricing and hedging in terms of randomness alone. We consider a fuzzy pricing model by introducing a fuzzy stochastic differential equation with Skorohod sense. In this way, our model simultaneously involves randomness and fuzziness. A well-known hedging strategy for vanilla options is so-called $ \Delta $-hedging, which is usually derived from the Itô formula and some properties of partial differentiable equations. However, when dealing with some complex path-dependent options (such as lookback options), the major challenge is that the payoff function of these options may not be smooth, resulting in the estimates are computationally expensive. With the help of the Malliavin derivative and the Clark-Ocone formula, the difficulty will be readily solved, and it is also possible to apply this hedging strategy to fuzzy space. To obtain the explicit expression of the fuzzy hedging portfolio for lookback options, we adopt the Esscher transform and reflection principle techniques, which are beneficial to the calculation of the conditional expectation of fuzzy random variables and the payoff function with extremum, respectively. Some numerical examples are performed to analyze the sensitivity of the fuzzy hedging portfolio concerning model parameters and give the permissible range of the expected hedging portfolio of lookback options with uncertainty by a financial investor's subjective judgment.</p></abstract>

От филология към „нещо друго“ през погледа на студентите англицисти в ПУ „Паисий Хилендарски“

The text reflects on the dynamic changes that have occurred in the makeup and rationale of English Studies associated majors on offer at Plovdiv University Paisii Hilendarski (PU) as revealed through the views of students enrolled in three distinctive strands of programs. The contours of these developments are addressed by comparing cohorts of ES students at PU across time. Namely, the discussion relies on a comprehensive student survey that registered students’ views in 2008 and 2018, i.e. with a time lapse of a decade, against the background of broader contextual developments and narrowly institutional such (PU institutional policies) in the interim period. Within the institutional context of PU, the developments amount to diversifying the portfolio of BA degree options from traditionally philologically-oriented such to those following an applied linguistics model on one hand, and majors involving a degree of interdisciplinary “hybridization” on the other. These transformations appear further nuanced with a view to the distinctive features that come across the responses of three qualitatively different student cohorts. One, those pursuing ES degrees within a more conventional philological model; two, those engaged in ES related degrees following an Applied Linguistics model; and finally, those who study ES as a component in combinations with IT, Marketing and Business Administration. Even if limited to the institutional context of PU, the survey offers scope for considering the implications for the HE philological horizons of foreign language education from the perspective of the changing expectations, attitudes and career aspirations of the undergraduates involved in them.

Choosing Portfolios of Rival Risky Options: Evidence That Most People Violate the No Safety Schools Theorem

Choosing Portfolios of Rival Risky Options: Evidence That Most People Violate the No Safety Schools Theorem

APPLICATION OF THE FITRADEOFF METHOD IN A PORTFOLIO PROBLEM IN THE CONTEXT OF REVERSE LOGISTICS FOR WHOLESALE

The study investigates options to support the reverse logistics for wholesalers in a company. This big company, which do not have the name presented in this paper aims to improve the process of returning unsold items. At the moment, the process contained several rework-related losses. Hence, in this study two methodologies have been applied. The VFT has been used to structure the problem considering the multiple objectives presented by the Decision-Maker, in special those that are considered by sporting multinational. Also, the FITradeoff method has been used to identify the alternatives that should compose the portfolio of options concerning the reverse logistics. The portfolio problematic has been applied since it has been desired to obtain the subset of option to support the problem, constrained by monetary resources. Using the VFT, ten alternatives which were evaluated in ten criteria have been defined, and support by the FITradeoff method. As result, the alternatives five alternatives have been selected to compose the portfolio.

A Closed Form Model-Free Approximation for the Initial Margin of Option Portfolios

A Closed Form Model-Free Approximation for the Initial Margin of Option Portfolios

A Mathematical Formulation of the Valuation of Ether and Ether Derivatives as a Function of Investor Sentiment and Price Jumps

The purpose of this study was to create quantitative models to value ether, ether futures, and ether options based upon the ability of cryptocurrencies to transform existing intermediary-verified payments to non-intermediary-based currency transfers, the ability of ether as a late mover to displace bitcoin as the first mover, and the valuation of ether in the context of investor irrationality models. The risk-averse investor’s utility function is a combination of expectations of the performance of ether, expectations of cryptocurrencies’ transformative power, and expectations of ether superseding bitcoin. The moderate risk-taker’s utility function is an alt-Weibull distribution, along with a gamma distribution. Risk-takers have a utility function in the form of a Bessel function. Ether price functions consist of a Levy jump process. Ether futures are valued as the combination of current spot prices along with term prices. The value of spot prices is the product of a spot premium and a lognormal distribution of spot prices. The value of term prices is equal to the product of a term premium, and the Levy jump process of price fluctuations during the delivery period. For ether options, a less risky ether option portfolio offsets ether’s risk by a fixed-income trading strategy.

Counter-cyclical Margins for Option Portfolios

We propose a counter-cyclical initial margin model for option portfolios. Our model explores the intrinsic netting within a given portfolio of European options and outputs a constant upper bound of the maximum possible loss. This feature would allow option clearinghouses and regulators to gauge the tightest margin levels that are stable. We compare our model with the scenario-based SPAN model and the sensitivity-based SIMM model in terms of the netting efficiency and the procyclical property. Using the SPX options and the interest rate swaptions as examples, we quantify the minimum amount of additional margins needed to make them fully counter-cyclical. We then show how to strike a balance between risk-sensitivity and counter-cyclicality if needed by mixing our model flexibly with a prevailing risk-sensitive margin model.

Improving and Extending the Wu-Zhu Static Hedge

Without considering the underlying risk dynamics and jumps, Wu and Zhu (2016) recently proposed an ingenious approach of hedging options statically with an option portfolio. We improve their scheme in three ways. First, we theoretically make the Wu-Zhu approach more accurate by utilizing the Black-Scholes-Merton dual equation. Second, we propose a better error measure, the so-called “true hedge error,” that takes the initial cost of the hedge into consideration. Finally, we suggest two measures of percentage hedge errors to assess hedge performance more precisely. With extensive simulations under both the Black-Scholes-Merton and Heston models, we show that our proposal significantly improves the hedge performance, especially for in-the-money and at-the-money options. Importantly, we extend Wu-Zhu to options with a payoff of homogeneous of degree one.

Evaluation of climate variability on sustainability for transboundary water supply in Chihuahua, Mexico

Study regionThis is study of the Rio Conchos Watershed, Chihuahua, Mexico. Study focusThis study provides assessment of climate variability from analysis of instrumental climate and reservoir operations data, plus nearby tree-ring indices in Chihuahua, Mexico. Water demand include international treaty deliveries, growing agricultural land use, and intensified crop production. Analysis of climate cycles includes frequency analysis of local multidecadal instrumental hydrologic time series and multi-century tree-ring indices. In addition, tree-ring indices were compared with 14C content in tree rings to assess the presence of the millennial solar cycle. New hydrological insights for the regionMost of the climate variability within inter-annual to interdecadal periods are aligned with Pacific Decadal Oscillation (PDO)-like climate cycles. New multi-century climate cycles were discovered from tree-ring indices that have a profound impact on sustainability of food and water security. Historical droughts of 8-year average duration within PDO-like cycles that span longer (12–43 year) periods were newly identified which are longer than the 5-year delivery cycles used in the 1944 International Treaty of the Rivers. Mega-droughts were discovered to occur within multi-century climate cycles. Multi-century cycles identified in tree-ring indices were likely driven by solar luminosity changes from the millennial solar cycle and not just recent anthropogenic climate change. Climate variability and temperature increases will further amplify cycles of supply and demand and exacerbate sustainability, mitigation, and management strategies. Conjunctive use combined with reservoir operations will broaden sustainability portfolio of options, reducing demand effects as well as enhance supply options and replenishment effects.