Underlying Asset (underlying + asset)

Distribution by Scientific Domains

Terms modified by Underlying Asset

  • underlying asset price

  • Selected Abstracts


    Implied trees in illiquid markets: A Choquet pricing approach

    INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 6 2002
    Silvia Muzzioli
    Implied trees are necessary to implement the risk neutral valuation approach, and standard methodologies for their derivation are based on the validity of the put call parity. However, in illiquid markets the put call parity fails to hold, and the uniqueness of the artificial probabilities leaves room for an interval. The contribution of this article is twofold. First we propose a methodology for the derivation of implied trees in illiquid markets. Such a methodology, by contrast with standard ones, takes into account the information stemming both from call and put prices. Second, we set up a framework for pricing derivatives written on an underlying asset traded on an illiquid market. To this end we have extended the Choquet integral definition to account for interval payoffs of the underlying asset. The price interval we obtain may be interpreted as a bid-ask price quoted by the intermediary issuing the derivative security. 2002 Wiley Periodicals, Inc. [source]


    Real Options: Meeting the Georgetown Challange

    JOURNAL OF APPLIED CORPORATE FINANCE, Issue 2 2005
    Thomas E. Copeland
    In response to the demand for a single, generally accepted real options methodology, this article proposes a four-step process leading to a practical solution to most applications of real option analysis. The first step is familiar: calculate the standard net present value of the project assuming no managerial flexibility, which results in a value estimate (and a "branch" of a decision tree) for each year of the project's life. The second step estimates the volatility of the value of the project and produces a value tree designed to capture the main sources of uncertainty. Note that the authors focus on the uncertainty about overall project value, which is driven by uncertainty in revenue growth, operating margins, operating leverage, input costs, and technology. The key point here is that, in contrast to many real options approaches, none of these variables taken alone is assumed to be a reliable surrogate for the uncertainty of the project itself. For example, in assessing the option value of a proven oil reserve, the relevant measure of volatility is the volatility not of oil prices, but of the value of the operating entity,that is, the project value without leverage. The third step attempts to capture managerial flexibility using a decision "tree" that illustrates the decisions to be made, their possible outcomes, and their corresponding probabilities. The article illustrate various kinds of applications, including a phased investment in a chemical plant (which is treated as a compound option) and an investment in a peak-load power plant (a switching option with changing variance, which precludes the use of constant risk-neutral probabilities as in standard decision tree analysis). The fourth and final step uses a "no-arbitrage" approach to form a replicating portfolio with the same payouts as the real option. For most corporate investment projects, it is impossible to locate a "twin security" that trades in the market. In the absence of such a security, the conventional NPV of a project (again, without flexibility) is the best candidate for a perfectly correlated underlying asset because it represents management's best estimate of value based on the expected cash flows of the project. [source]


    A neural network versus Black,Scholes: a comparison of pricing and hedging performances

    JOURNAL OF FORECASTING, Issue 4 2003
    Henrik Amilon
    Abstract An Erratum has been published for this article in Journal of Forecasting 22(6-7) 2003, 551 The Black,Scholes formula is a well-known model for pricing and hedging derivative securities. It relies, however, on several highly questionable assumptions. This paper examines whether a neural network (MLP) can be used to find a call option pricing formula better corresponding to market prices and the properties of the underlying asset than the Black,Scholes formula. The neural network method is applied to the out-of-sample pricing and delta-hedging of daily Swedish stock index call options from 1997 to 1999. The relevance of a hedge-analysis is stressed further in this paper. As benchmarks, the Black,Scholes model with historical and implied volatility estimates are used. Comparisons reveal that the neural network models outperform the benchmarks both in pricing and hedging performances. A moving block bootstrap is used to test the statistical significance of the results. Although the neural networks are superior, the results are sometimes insignificant at the 5% level.,Copyright 2003 John Wiley & Sons, Ltd. [source]


    HEDGING STRATEGIES AND MINIMAL VARIANCE PORTFOLIOS FOR EUROPEAN AND EXOTIC OPTIONS IN A LVY MARKET

    MATHEMATICAL FINANCE, Issue 4 2010
    Wing Yan Yip
    This paper presents hedging strategies for European and exotic options in a Lvy market. By applying Taylor's theorem, dynamic hedging portfolios are constructed under different market assumptions, such as the existence of power jump assets or moment swaps. In the case of European options or baskets of European options, static hedging is implemented. It is shown that perfect hedging can be achieved. Delta and gamma hedging strategies are extended to higher moment hedging by investing in other traded derivatives depending on the same underlying asset. This development is of practical importance as such other derivatives might be readily available. Moment swaps or power jump assets are not typically liquidly traded. It is shown how minimal variance portfolios can be used to hedge the higher order terms in a Taylor expansion of the pricing function, investing only in a risk-free bank account, the underlying asset, and potentially variance swaps. The numerical algorithms and performance of the hedging strategies are presented, showing the practical utility of the derived results. [source]


    Nonconvergence in the Variation of the Hedging Strategy of a European Call Option

    MATHEMATICAL FINANCE, Issue 4 2003
    R. Th.
    In this paper we consider the variation of the hedging strategy of a European call option when the underlying asset follows a binomial tree. In a binomial tree model the hedging strategy of a European call option converges to a continuous process when the number of time points increases so that the price process of the underlying asset converges to a Brownian motion, the Bachelier model. However, the variation of the hedging strategy need not converge to the variation of the limit process. In fact, it is shown that the asymptotic variation of the hedging strategy may be of any order. [source]


    Robust Hedging of Barrier Options

    MATHEMATICAL FINANCE, Issue 3 2001
    Haydyn Brown
    This article considers the pricing and hedging of barrier options in a market in which call options are liquidly traded and can be used as hedging instruments. This use of call options means that market preferences and beliefs about the future behavior of the underlying assets are in some sense incorporated into the hedge and do not need to be specified exogenously. Thus we are able to find prices for exotic derivatives which are independent of any model for the underlying asset. For example we do not need to assume that the underlying assets follow an exponential Brownian motion. We find model-independent upper and lower bounds on the prices of knock-in and knock-out puts and calls. If the market prices the barrier options outside these limits then we give simple strategies for generating profits at zero risk. Examples illustrate that the bounds we give can be fairly tight. [source]


    MSM Estimators of European Options on Assets with Jumps

    MATHEMATICAL FINANCE, Issue 2 2001
    Joo Amaro de Matos
    This paper shows that, under some regularity conditions, the method of simulated moments estimator of European option pricing models developed by Bossaerts and Hillion (1993) can be extended to the case where the prices of the underlying asset follow Lvy processes, which allow for jumps, with no losses on their asymptotic properties, still allowing for the joint test of the model. [source]


    Analytical Valuation of American Options on Jump-Diffusion Processes

    MATHEMATICAL FINANCE, Issue 1 2001
    Chandrasekhar Reddy Gukhal
    We derive analytic formulas for the value of American options when the underlying asset follows a jump-diffusion process and pays continuous dividends. They early exercise premium has a form very different form from that for diffusion processes, and this can be attributed to the discontinuous nature of the price paths. Analytical formulas are derived for several distributions of the jump amplitude. [source]


    Numerical valuation of options under Kou's model

    PROCEEDINGS IN APPLIED MATHEMATICS & MECHANICS, Issue 1 2007
    Jari ToivanenArticle first published online: 6 AUG 200
    Numerical methods are developed for pricing European and American options under Kou's jump-diffusion model which assumes the price of the underlying asset to behave like a geometrical Brownian motion with a drift and jumps whose size is log-double-exponentially distributed. The price of a European option is given by a partial integro-differential equation (PIDE) while American options lead to a linear complementarity problem (LCP) with the same operator. Spatial differential operators are discretized using finite differences on nonuniform grids and time stepping is performed using the implicit Rannacher scheme. For the evaluation of the integral term easy to implement recursion formulas are derived which have optimal computational cost. When pricing European options the resulting dense linear systems are solved using a stationary iteration. Also for pricing American options similar iterations can be employed. A numerical experiment demonstrates that the described method is very efficient as accurate option prices can be computed in a few milliseconds on a PC. ( 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source]


    A Measure of Fundamental Volatility in the Commercial Property Market

    REAL ESTATE ECONOMICS, Issue 4 2003
    Shaun A. Bond
    The low level of volatility observed in appraisal-based commercial property indices relative to other asset classes has been frequently noted and extensively commented on in the real estate finance literature. However, the volatility of such commercial property indices is only one source of information on the second moment of commercial property returns. The volatility of securitized property returns forms another potential source of information, though there is some uncertainty about how closely the volatility of securitized returns may match the volatility of the underlying asset. Each measure of volatility has a potential source of noise associated with it. This paper proposes a fundamental measure of volatility for the commercial property market by using a stochastic volatility model to filter out the signal in the different sources of volatility information. This allows for different measures of volatility to be decomposed into transitory noise and unobserved fundamental volatility. The suitability of such an approach and the properties of the underlying fundamental volatility series are analyzed using data from the U.K. property market. [source]


    A Generalization of the Brennan,Rubinstein Approach for the Pricing of Derivatives

    THE JOURNAL OF FINANCE, Issue 2 2003
    Antnio Cmara
    This paper derives preference-free option pricing equations in a discrete time economy where asset returns have continuous distributions. There is a representative agent who has risk preferences with an exponential representation. Aggregate wealth and the underlying asset price have transformed normal distributions which may or may not belong to the same family of distributions. Those pricing results are particularly valuable (a) to show new sufficient conditions for existing risk-neutral option pricing equations (e.g., the Black,Scholes model), and (b) to obtain new analytical solutions for the price of European-style contingent claims when the underlying asset has a transformed normal distribution (e.g., a negatively skew lognormal distribution). [source]


    Alternative tilts for nonparametric option pricing

    THE JOURNAL OF FUTURES MARKETS, Issue 10 2010
    M. Ryan Haley
    This study generalizes the nonparametric approach to option pricing of Stutzer, M. (1996) by demonstrating that the canonical valuation methodology introduced therein is one member of the Cressie,Read family of divergence measures. Alhough the limiting distribution of the alternative measures is identical to the canonical measure, the finite sample properties are quite different. We assess the ability of the alternative divergence measures to price European call options by approximating the risk-neutral, equivalent martingale measure from an empirical distribution of the underlying asset. A simulation study of the finite sample properties of the alternative measure changes reveals that the optimal divergence measure depends upon how accurately the empirical distribution of the underlying asset is estimated. In a simple Black,Scholes model, the optimal measure change is contingent upon the number of outliers observed, whereas the optimal measure change is a function of time to expiration in the stochastic volatility model of Heston, S. L. (1993). Our extension of Stutzer's technique preserves the clean analytic structure of imposing moment restrictions to price options, yet demonstrates that the nonparametric approach is even more general in pricing options than originally believed. 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:983,1006, 2010 [source]


    Pricing American options by canonical least-squares Monte Carlo

    THE JOURNAL OF FUTURES MARKETS, Issue 2 2010
    Qiang Liu
    Options pricing and hedging under canonical valuation have recently been demonstrated to be quite effective, but unfortunately are only applicable to European options. This study proposes an approach called canonical least-squares Monte Carlo (CLM) to price American options. CLM proceeds in three stages. First, given a set of historical gross returns (or price ratios) of the underlying asset for a chosen time interval, a discrete risk-neutral distribution is obtained via the canonical approach. Second, from this canonical distribution independent random samples of gross returns are taken to simulate future price paths for the underlying. Third, to those paths the least-squares Monte Carlo algorithm is then applied to obtain early exercise strategies for American options. Numerical results from simulation-generated gross returns under geometric Brownian motions show that the proposed method yields reasonably accurate prices for American puts. The CLM method turns out to be quite similar to the nonparametric approach of Alcock and Carmichael and simulations done with CLM provide additional support for their recent findings. CLM can therefore be viewed as an alternative for pricing American options, and perhaps could even be utilized in cases when the nature of the underlying process is not known. 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:175,187, 2010 [source]


    Minimum variance cross hedging under mean-reverting spreads, stochastic convenience yields, and jumps: Application to the airline industry

    THE JOURNAL OF FUTURES MARKETS, Issue 8 2009
    Mark Bertus
    Exchange traded futures contracts often are not written on the specific asset that is a source of risk to a firm. The firm may attempt to manage this risk using futures contracts written on a related asset. This cross hedge exposes the firm to a new risk, the spread between the asset underlying the futures contract and the asset that the firm wants to hedge. Using the specific case of the airline industry as motivation, we derive the minimum variance cross hedge assuming a two-factor diffusion model for the underlying asset and a stochastic, mean-reverting spread. The result is a time-varying hedge ratio that can be applied to any hedging horizon. We also consider the effect of jumps in the underlying asset. We use simulations and empirical tests of crude oil, jet fuel cross hedges to demonstrate the hedging effectiveness of the model. 2009 Wiley Periodicals, Inc. Jrl Fut Mark 29:736,756, 2009 [source]


    The limits to stock index arbitrage: Examining S&P 500 futures and SPDRS

    THE JOURNAL OF FUTURES MARKETS, Issue 12 2008
    Nivine Richie
    This study examines factors affecting stock index spot versus futures pricing and arbitrage opportunities by using the S&P 500 cash index and the S&P 500 Standard and Poor's Depository Receipt (SPDR) Exchange-Traded Fund (ETF) as "underlying cash assets." Potential limits to arbitrage when using the cash index are the staleness of the underlying cash index, trading costs, liquidity (volume) issues of the underlying assets, the existence of sufficient time to execute profitable arbitrage transactions, short sale restrictions, and the extent to which volatility affects mispricing. Alternatively, using the SPDR ETF as the underlying asset mitigates staleness and trading cost problems as well as the effects of volatility associated with the staleness of the cash index. Minute-by-minute prices are compared over different volatility levels to determine how these factors affect the limits of S&P 500 futures arbitrage. Employing the SPDR as the cash asset examines whether a liquid tradable single asset with low trading costs can be used for pricing and arbitrage purposes. The analysis examines how long mispricing lasts, the impact of volatility on mispricing, and whether sufficient volume exists to implement arbitrage. The minute-by-minute liquidity of the futures market is examined using a new transaction volume futures database. The results show that mispricings exist regardless of the choice of the underlying cash asset, with more negative mispricings for the SPDR relative to the S&P 500 cash index. Furthermore, mispricings are more frequent in high- and mid-volatility months than in low-volatility months and are associated with higher volume during high-volatility months. 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:1182,1205, 2008 [source]


    Hedging under the influence of transaction costs: An empirical investigation on FTSE 100 index options

    THE JOURNAL OF FUTURES MARKETS, Issue 5 2007
    Andros Gregoriou
    The Black,Scholes (BS; F. Black & M. Scholes, 1973) option pricing model, and modern parametric option pricing models in general, assume that a single unique price for the underlying instrument exists, and that it is the mid- (the average of the ask and the bid) price. In this article the authors consider the Financial Times and London Stock Exchange (FTSE) 100 Index Options for the time period 1992,1997. They estimate the ask and bid prices for the index, and show that, when substituted for the mid-price in the BS formula, they provide superior option price predictors, for call and put options, respectively. This result is reinforced further when they .t a non-parametric neural network model to market prices of liquid options. The empirical .ndings in this article suggest that the ask and bid prices of the underlying asset provide a superior fit to the mid/closing price because they include market maker's, compensation for providing liquidity in the market for constituent stocks of the FTSE 100 index. 2007 Wiley Periodicals, Inc. Jrl Fut Mark 27:471,494, 2007 [source]


    The Financial Crisis: Causes and Lessons,

    JOURNAL OF APPLIED CORPORATE FINANCE, Issue 3 2010
    Kenneth E. Scott
    The author argues that the root cause of the recent crisis was a housing bubble whose origins can be traced to loose monetary policy and a government housing policy that continually pushed for lower lending standards to increase home ownership. The negative consequences of such policies were amplified when transmitted throughout the financial system by financial institutions through the process of securitization. In attempting to assess culpability for the crisis and identify possible reforms, the author focuses on three categories: 1Defects in Financial Products: Without criticizing derivatives and the process of securitization, the author identifies the sheer complexity of the securities as a major source of the problem,for which the solution is a simpler security design combined with greater disclosure about the underlying assets being securitized. 2Defects in Risk Management: Thanks in large part to agency and other incentive problems, there was universal underestimation of risks by mortgage originators and financial institutions throughout the securitization chain. Changing incentive pay structures is part of the solution, and so are better accounting rules for SPEs. But more effective regulatory oversight and ending "too big to fail" may well be the only way to curb excessive private risk-taking. 3Defects in Government Policy and Regulation: While acknowledging the need for more effective oversight, the author argues that there was ample existing authority for U.S. regulators to have addressed these issues. Lack of power and authority to regulate was not at the heart of the problem,the real problem was lack of foresight and judgment about the unexpected. After expressing doubt that regulators can prevent major financial failures, the author recommends greater attention to devising better methods of resolving such failures when they occur. One of the main goals is to ensure that losses are borne not by taxpayers but by private investors in a way that maintains incentives for market discipline while limiting spillover costs to the entire system. [source]


    Robust Hedging of Barrier Options

    MATHEMATICAL FINANCE, Issue 3 2001
    Haydyn Brown
    This article considers the pricing and hedging of barrier options in a market in which call options are liquidly traded and can be used as hedging instruments. This use of call options means that market preferences and beliefs about the future behavior of the underlying assets are in some sense incorporated into the hedge and do not need to be specified exogenously. Thus we are able to find prices for exotic derivatives which are independent of any model for the underlying asset. For example we do not need to assume that the underlying assets follow an exponential Brownian motion. We find model-independent upper and lower bounds on the prices of knock-in and knock-out puts and calls. If the market prices the barrier options outside these limits then we give simple strategies for generating profits at zero risk. Examples illustrate that the bounds we give can be fairly tight. [source]


    The Role of the Underlying Real Asset Market in REIT IPOs

    REAL ESTATE ECONOMICS, Issue 1 2005
    Jay C. Hartzell
    A leading explanation for IPO cycles is time-varying supply and demand for the underlying assets of the firms that are considering going public. We test this hypothesis using REIT IPOs, taking advantage of the relative transparency of the underlying real asset markets. We document links between REIT IPO activity and both the conditions of the underlying real estate market and the price of REITs. We find no significant relation between the heat of the IPO market and post-IPO operating performance, implying homogeneous firm quality across IPO cycles. Finally, we show that lagged IPO proceeds are related to future increases in investment and in capacity utilization. [source]


    The limits to stock index arbitrage: Examining S&P 500 futures and SPDRS

    THE JOURNAL OF FUTURES MARKETS, Issue 12 2008
    Nivine Richie
    This study examines factors affecting stock index spot versus futures pricing and arbitrage opportunities by using the S&P 500 cash index and the S&P 500 Standard and Poor's Depository Receipt (SPDR) Exchange-Traded Fund (ETF) as "underlying cash assets." Potential limits to arbitrage when using the cash index are the staleness of the underlying cash index, trading costs, liquidity (volume) issues of the underlying assets, the existence of sufficient time to execute profitable arbitrage transactions, short sale restrictions, and the extent to which volatility affects mispricing. Alternatively, using the SPDR ETF as the underlying asset mitigates staleness and trading cost problems as well as the effects of volatility associated with the staleness of the cash index. Minute-by-minute prices are compared over different volatility levels to determine how these factors affect the limits of S&P 500 futures arbitrage. Employing the SPDR as the cash asset examines whether a liquid tradable single asset with low trading costs can be used for pricing and arbitrage purposes. The analysis examines how long mispricing lasts, the impact of volatility on mispricing, and whether sufficient volume exists to implement arbitrage. The minute-by-minute liquidity of the futures market is examined using a new transaction volume futures database. The results show that mispricings exist regardless of the choice of the underlying cash asset, with more negative mispricings for the SPDR relative to the S&P 500 cash index. Furthermore, mispricings are more frequent in high- and mid-volatility months than in low-volatility months and are associated with higher volume during high-volatility months. 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:1182,1205, 2008 [source]


    Pricing American exchange options in a jump-diffusion model

    THE JOURNAL OF FUTURES MARKETS, Issue 3 2007
    Snorre Lindset
    A way to estimate the value of an American exchange option when the underlying assets follow jump-diffusion processes is presented. The estimate is based on combining a European exchange option and a Bermudan exchange option with two exercise dates by using Richardson extrapolation as proposed by R. Geske and H. Johnson (1984). Closed-form solutions for the values of European and Bermudan exchange options are derived. Several numerical examples are presented, illustrating that the early exercise feature may have a significant economic value. The results presented should have potential for pricing over-the-counter options and in particular for pricing real options. 2007 Wiley Periodicals, Inc. Jrl Fut Mark 27:257,273, 2007 [source]