Option Valuation Model Research Articles

Penerapan Model Harga Opsi Black Scholes dalam Penentuan Premi Asuransi Jiwa Dwiguna Unit Link

Unit-linked life insurance is one of the most popular insurance products. This product connects the element of protection with investment assets in a product. Regarding option pricing, the Black Scholes model is one method that can be used. The advantage of this model is that it is a call option valuation model and is in great demand among financial associations because the option rate obtained from the calculation of this model is an accurate value. This research aims to determine the premium value of unit-linked endowment life insurance by applying the Black Scholes option pricing model. This research begins by selecting the stocks used and completing the information needed, including the insured's age, gender, insurance period, and life expectancy based on TMI in 2011. The return value and stock volatility can be calculated based on the stock data used. Furthermore, applying the Black Scholes option pricing model on customer data with male gender, age 25 years, a selected interest rate of 5.75%, and an insurance period of 5 years obtained a unit link insurance premium value of Rp123,058,412. The results showed that the Black Scholes option price model is determined by stock prices, interest rates, insurance periods, and volatility. When the longer period of insurance taken causes the premium value to be higher, and for different ages, with increasing age, the value of premiums paid will also increase.

Solar Energy Investment Valuation With Intuitionistic Fuzzy Trinomial Lattice Real Option Model

Under the uncertain and the flexibility required conditions, the conventional capital budgeting techniques are insufficient to decide the most feasible investment due to their static nature. Classical real option valuation techniques have been used for various investment options such as deferment and abandonment. Although these techniques help to evaluate the projects in uncertain environments, they still follow the static, certain Boolean logic assumptions. Therefore, further improvement in the real option valuation has been introduced with the usage of fuzzy logic. Fuzzy logic is applied by binomial and Black–Scholes real option valuation methods up to date, but not with the trinomial lattice. Moreover, Types-1 and 2 fuzzy numbers are used; however, the intuitionistic fuzzy numbers are not analyzed in detail in the real option valuation. In this article, we propose an intuitionistic fuzzy trinomial lattice real option valuation model for a solar energy investment project. While valuing the deferment option, expert opinions, two different volatility methods, and a tailor-made electricity price-forecasting model are used. According to our results, the deferment option is valuable and delaying the start of the project provides a much higher expanded net present value than an immediate start. The contribution of this article is that the uncertainty in the real option valuation is modeled from a broader perspective with intuitionistic fuzzy numbers by taking the hesitancy of the decision-maker and the market into account. Consequently, the proposed method would increase the accuracy of the real option valuation in uncertain environments such as renewable energy sector.

Fast Filtering with Large Option Panels: Implications for Asset Pricing

Abstract The cross section of options holds great promise for identifying return distributions and risk premia, but estimating dynamic option valuation models with latent state variables is challenging when using large option panels. We propose a particle Markov Chain Monte Carlo framework with a novel filtering approach and illustrate our method by estimating index option pricing models. Estimates of variance risk premiums, variance mean reversion, and higher moments differ from the literature. We show that these differences are due to the composition of the option sample. Restricting the option sample’s maturity dimension has the strongest impact on parameter inference and option fit in these models.

A discussion on mathematical models for option valuation

Options as a type of financial derivatives have become increasingly popular in recent years; therefore, understanding how to value options as a derivative is crucial. To analyse the problem, we can use mathematical stochastic analysis from the perspectives of risk management and return maximisation, and then develop an option valuation model. Using a literature restatement approach, the mathematical model of option valuation is examined in this study. Bachilier introduced the option valuation model in 1900 as a breakthrough in the study of financial mathematics. In the 1860s, the asset pricing model was introduced, followed by the famous B-S formula published by F. Black and M. Scholes, which is also used to research option valuation. The above-mentioned mathematical models have been refined and are now frequently utilised in the options market. They can also be used as a criterion for buyers to determine the value of options, thus it is important to investigate this subject, which will be the subject of this paper.

Valuation of Compensation for Land Use Restriction

The Spatial Planning Act of Taiwan was implemented on May 1, 2016. To protect the legal rights of landholders, the Ministry of the Interior stipulated Measures for Compensating Loss Incurred during The Implementation of Spatial Planning in accordance with Article 32, Paragraph 3 of the Spatial Planning Act. Compensation is available for relocation or for alteration, where alteration refers to compensation for losses incurred when constructible land is made non-constructible by a special municipality or county (city) and the land cannot be built on. It therefore includes compensation for the value of the right to develop the land.
 Real estate is immobile and inflexible, which reduces uncertainty in its use. Studies have generally used net present value to analyze investment in and development of land. The conventional passive net present value method is employed to appraise land value, usually assuming that the investment plan must be developed immediately and is reversible. This is contrary to the characteristics of real estate investment and development, where ignoring the opportunities and flexibility generated by asset value uncertainty can readily lead to misappraisal of the value of an investment plan. The inclusion of future uncertainty in the valuation is the main difference between the option valuation model and the conventional valuation model.
 Because correctly calculating the compensation for alteration is crucial to whether landowners successfully obtain appropriate compensation when applying for compensation, this study proposed a real option valuation model to appraise compensation for the alteration of privately-owned constructible land. In the model, landowners possessed complete ownership of and decision-making power regarding the land before compensation. Subsequently, the study adopted real options theories to assist private landowners in determining real options at the decision-making stage. The study also took the case of constructible land in Taichung City that was made non-constructible in accordance with the spatial planning of Taichung City as an example to apply the model.

Economic Feasibility Study of a Chemical Enhanced Oil Recovery Project in Indonesia Based on Conventional Discounted Cash Flow (DCF) And Real Option Valuation Model: Case Study at PT ABC

Indonesia had become an oil exporter that is recognized by the world for many years and joined The Organization of Petroleum Export Community (OPEC) – an organization that controls petroleum production, supplies, and prices in the global market – in 1962. However, oil production in Indonesia has been decreasing from year to year, one of which is due to the lack of investment in the exploration of new oil wells in Indonesia so the majority of upstream oil and gas work in Indonesia is exploiting old wells which will naturally decline steadily. This resulted in Indonesia becoming a net import oil country in 2003. Therefore, additional operations are needed to maximize oil production from these existing wells, one of which is by conducting Chemical Enhanced Oil Recovery (CEOR). The main objective of EOR itself is to mobilize the remaining oil by enhancing the oil displacement and volumetric sweep efficiency. PT. ABC, a subsidiary of PT. XYZ (a state-owned company under SKK Migas and PT Pertamina supervision) which is engaged in the upstream sector in Indonesia, is assigned by the government to carry out one of the CEOR projects that have been determined by the Government. This research covers the economic feasibility of the CEOR Project based on the conventional Discounted Cash Flow (DCF) and Real Option Valuation (ROV) Model. The revenue-sharing policy used for the project economic calculation is the gross split method. The result of the economic analysis using the DCF method is the project is not economically feasible to run as the net present value (NPV) shows negative which is -2,911 MUSD. However, the real option valuation model helped increase the value to 11,416 MUSD by adopting a strategic option which is an option to delay and time flexibility into the project. As a result, the project could be economically feasible if the operation is deferred to the following year and the oil price is over 85.2 USD/BBL.

Economic Feasibility Study of a Chemical Enhanced Oil Recovery Project in Indonesia Based on Conventional Discounted Cash Flow (DCF) And Real Option Valuation Model: Case Study at PT ABC

Economic Feasibility Study of a Chemical Enhanced Oil Recovery Project in Indonesia Based on Conventional Discounted Cash Flow (DCF) And Real Option Valuation Model: Case Study at PT ABC

Retirement Choices in Italy: What an Option Value Model Tells Us

Using Italian data this study estimates the option value model in order to quantify the effect of financial incentives on retirement choices. As far as we know, this is the first empirical study which estimates the conditional multiple-years (CMY) model put forward by Stock and Wise (1990). This implies that we have accounted for dynamic self-selection bias. For the subsample of females the CMY model yields plausible estimates of the preference parameters such as the marginal utility of leisure. This last parameter is typically underestimated if one does not take into account the self-selection problem. From our results it becomes clear that dynamic self-selection results in a considerable downward-bias in the estimate of the marginal utility of leisure. We also performed a simulation study to gauge the effects of a dramatic pension reform. It turns out that the underestimation of the marginal utility of leisure translates into a sizable overprediction of the impact of the reform. For males we also obtain plausible estimates. The results for males should be interpreted with caution because we are not able to fully correct for dynamic self-selection bias.

The evolution of option valuation theory and its application in practice

Options are an important tool in financial markets for managing and transmitting risk, while also providing investors with the opportunity to earn returns. This paper first introduces the basic concepts and characteristics of options, including the definition of an option, buyer and seller, strike price, and expiration date. Next, the differences between European and American options, and the characteristics of Asian and Brazilian options are discussed. Then, the development and extension of option valuation models, as well as their applicability and limitations, are discussed. In addition, the application and role of options in the financial markets are analyzed, as well as option trading strategies and practical examples. The risks and challenges of options trading are further discussed, as well as the concepts of speculation and arbitrage. Finally, suggestions and outlooks for options trading and risk management are presented, as well as an analysis of the current state of research and future trends in options valuation theory and applications.

An empirical test of auction methods in the primary market of sovereign debt

ABSTRACT There has been a long debate as to which of the most extended systems, the uniform system or the discriminatory price system, is the most appropriate for central banks and debt management offices issuing sovereign bonds. The purpose of this paper is to shed light on this question. The main variables to explore the auction mechanisms are the price difference between the primary and secondary markets (price spread) and the coverage ratio. Subsequently, to determine patterns for clarifying which auction system is optimal, we propose a new model based on the price spread and a valuation model for financial options that covers both negative and positive spreads. We conclude that the auction method and the number of primary dealers are relevant parameters in the auction outcome. Finally, the results of the new model are the cornerstone for identifying detailed patterns followed by top-performing countries.

An analytical GARCH valuation model for spread options with default risk

In this paper, an analytical pricing formula for spread options with credit default risk is derived. Assets are set within discrete-time CAPM markets and Heston–Nandi GARCH processes are adopted for capturing the variance dynamics of asset returns. The proposed model decomposes the risk of all assets into idiosyncratic and systematic parts, and considers the impacts on the default intensity of market fluctuations. A corresponding theoretical framework of discrete-time credit risk modeling in reduced-form is also provided. We incorporate the credit risk and systematic factor into an affine-GARCH valuation model and utilize Fourier transform techniques to obtain the analytic spread option prices. Finally, the empirical results and numerical analysis for different model parameters are displayed.

Option hedging using LSTM-RNN: an empirical analysis

This paper proposes an optimal hedging strategy in the presence of market frictions using the Long Short Term Memory Recurrent Neural Network (LSTM-RNN) method, which is a modification of the method proposed in Buehler et al. (Deep hedging. Quant. Finance, 2019, 19(8), 1271–1291). The market frictions are transaction costs, liquidity constraints, trading limits and cost of funds. The loss function is a spectral risk measure. We first make an empirical analysis of the LSTM-RNN model of real option markets, which are the Asian market (domestic market 50 ETF option, Hong Kong Hang Seng Index Option, Nikkei Index Option), the North American market (S&P 500 Index Option) and the European market (FTSE 100 Index Option). The benchmark models are from Leland (Option pricing and replication with transaction costs. J. Finance., 1985, 40(5), 1283–1301), Boyle and Vorst (Option replication in discrete time with transaction costs. J. Finance, 1992, 47(1), 271–293) and Whalley and Wilmott (A hedging strategy and option valuation model with transaction costs. OCIAM Working Paper, Mathematical Institute, Oxford, 1993). Finally, we compare the results from the LSTM-RNN model with benchmark models involving transaction costs for both simulated market data generated by Geometric Brownian Motion (GBM) and the Heston model and real market data. The results show that the LSTM-RNN model outperforms benchmark models for low or medium volatility (<0.8), OTM moneyness and under a certain risk level (<80%) in the GBM market setting. For the 50ETF option market, the LSTM-RNN model outperforms benchmark models for ATM and under a certain risk level (<15%). For the HSI option market, the LSTM-RNN model outperforms benchmark models when transaction costs are smaller than 1.5%. For the Nikkei and S&P 500 option markets, the LSTM-RNN model always outperforms benchmark models. For the FTSE option market, the LSTM-RNN model outperforms benchmark models when moneyness is not too deeply ITM.

Valuation of bitcoin options

AbstractWe propose an equilibrium valuation model for bitcoin options by extending Cao. Bitcoin is interpreted as a foreign currency in a small open economy where money supply and aggregate dividend are exogenous. The equilibrium bitcoin prices increase with diffusive and jump risks of these two exogenous factors. Analytical option pricing formulas are obtained with Merton's model as a special case. Static analysis reveals that a bitcoin call (put) option value increases (decreases) with the money supply growth rate. Numerical analysis shows that all risks lead to a positive premium in option prices relative to the Black–Scholes model.

Modeling Price Dynamics, Optimal Portfolios, and Option Valuation for Cryptoassets

The authors demonstrate the construction of an optimal dynamic portfolio of cryptoassets that minimizes either return variance or conditional value at risk. One can view such a portfolio as a minimum-risk index for this asset class. They carefully backtested the dynamic portfolio model and developed a fair valuation model for options based on a dynamic pricing model for the underlying cryptoasset index. They obtain the valuation by passing from the natural world to the equivalent martingale measure via the Esscher transform. The work underscores the need for a cryptoasset index–based exchange-traded fund, the development of derivatives, particularly for cryptoportfolio insurance purposes, and the development of (nearly) riskless rates for this asset class. <b>TOPICS:</b>Currency, options, statistical methods, VAR and use of alternative risk measures of trading risk <b>Key Findings</b> ▪ This article provides a methodology for constructing an optimal dynamic portfolio of major cryptoassets that minimizes either return variance or conditional value at risk. ▪ The authors develop a fair valuation model for options based on a dynamic pricing model for the underlying cryptoindex. ▪ The work emphasizes the need for a cryptoasset index–based exchange-traded fund and the development of derivatives, in particular for cryptoportfolio insurance purposes.

Gene Editing Versus Genetic Modification in the Research and Development of New Crop Traits: An Economic Comparison

Gene editing is a relatively new plant‐breeding tool that, unlike earlier methods such as genetic modification, is more precise in targeting its manipulations to site‐specific locations within the genome. This precision with gene editing offers considerable research and development cost economies and a higher probability of success, particularly for the initial discovery phase of research and development. This study quantifies the advantages of gene editing versus genetic modification by examining the minimum required planted area for a proposed trait where a typical crop technology company can expect to break even on its research and development investment using a real option valuation model. A novel feature of the model is the combination of a decision tree with a binomial lattice for project valuation with an embedded abandonment real option. A primary numerical result from the model was the observation that gene editing required a much smaller potential market area (96% smaller) to break even on the financial investment when compared to genetic modification for the same trait value per acre. This result held across a wide range of potential trait values. Sensitivity analysis on the results indicated that the much higher probability of success for gene editing in the discovery phase of research and development was the primary driver of the difference in break‐even acreage.

Option valuations and asset demands and supplies

If stock demand and supply determine stock prices, it should be possible for them to change option premiums. We propose a new valuation formula for pricing European options on the underlying stock, the price of which is determined by its demand and supply in a given transaction. Our mathematical model and numerical evidence demonstrate that the premiums of call options are increased with the stock demand and decreased with stock supply, and that the premiums of put options move downward with the stock demand and move upward with stock supply. Rather than by a given exogenous process that describes stock prices in option pricing models, we generate the stock price process by looking at the asset’s supply and demand. This notion regarding an underlying asset’s price determination can be further applied to develop other option valuation models.

Financial instruments and investment strategies based on volatility – proprietary strategies and market-neutral financial products

The paper presents a comprehensive introduction to volatility trading, from explaining the definition of volatility, through simple strategies for getting exposure to volatility, to advanced ETN products constructed from derivatives on the VIX index. The theoretical part discusses the idea of volatility trading derived from the assumptions of the Black-Scholes option valuation model. The remainder of this paper presents derivatives that provide exposure to volatility along with the opportunities and pitfalls faced by investors in this market. The practical part presents the proprietary approach to creating investment strategies based on the anomalies of implied volatility of the S &amp; P500 and model portfolios built of products from the Volatility ETP segment and the ETF for the S &amp; P500 index, dedicated to cautious investors, which can be an alternative to mixed equity and bond portfolios.

The Bitcoin options market: A first look at pricing and risk

ABSTRACT This paper offers the first-ever look at Bitcoin options by investigating the wedge between optimum Bitcoin option prices based on classical option valuation models (Black-Scholes-Merton and the Heston-Nandi GARCH (1,1)) and actual premiums at which these options are trading. For this purpose, we use near-the-money call and put options traded on Deribit platform as on 27.01.2020, with the maturities ranging from January 31 to 25 September 2020. In addition, we analyse the risk inherent in Bitcoin options by calculating their Greeks and comparing them to those of traditional commodity options. Pricing results suggest slight overpricing and underpricing for Bitcoin call options with the strike $8,000 maturing on 30.01.2020 and 28.02.2020, respectively. We also find that the Bitcoin options provide much stable deltas over time compared to the other commodity options. This result implies higher insulation from undue price rises with the passage of time for investors in Bitcoin options. Our results are useful to regulators, investors and market managers in better understanding the nuances of the Bitcoin options market in addition to making more informed investment choices.

Option valuation under no-arbitrage constraints with neural networks

In this paper, we start from the no-arbitrage constraints in option pricing and develop a novel hybrid gated neural network (hGNN) based option valuation model. We adopt a multiplicative structure of hidden layers to ensure model differentiability. We also select the slope and weights of input layers to satisfy the no-arbitrage constraints. Meanwhile, a separate neural network is constructed for predicting option-implied volatilities. Using S&P 500 options, our empirical analyses show that the hGNN model substantially outperforms well-established alternative models in the out-of-sample forecasting and hedging exercises. The superior prediction performance stems from our model’s ability in describing options on the boundary, and in offering analytical expressions for option Greeks which generate better hedging results.

Funciones isoelásticas de utilidad, rejillas trinomiales, volatilidad y aversión al riesgo cambiante: Un modelo de valuación con opciones reales de empresas de base tecnológica

La valoración de inversiones en I&amp;D, intangibles y empresas de base tecnológica (ebt) requiere de modelos que valoren: flexibilidad estratégica, volatilidad cambiante según ciclo de vida y riesgos sin activos financieros gemelos. En mercados incompletos e imperfectos, los riesgos deben valorarse con funciones de utilidad del inversor. Por lo expuesto, se propone un modelo de valuación de opciones reales con rejillas trinomiales, volatilidad cambiante, funciones isoelásticas de utilidad y aversión al riesgo variable. Mediante un análisis de caso y estudio de sensibilidad sobre valuación de ebt, es ilustrado su funcionamiento. Los resultados obtenidos demuestran su versatilidad. El modelo captura riesgos “privados” y flexibilidad estratégica, como herramienta de valuación para este tipo de inversiones dentro de mercados ambiguos, imperfectos e incompletos.