relaxations of approximate linear programs for the real option management of commodity storage the real option management of commodity conversion assets gives rise to intractable markov decision processes mdps in part because of the use of high dimensional models of commodity forward curve evolution as commonly done in practice focusing on commodity storage we identify a deficiency of approximate linear programming alp which we address by developing a novel approach to derive relaxations of approximate linear programs we apply our approach to obtain a class of tractable alp relaxations also subsuming an existing method we provide theoretical support for the use of these alp relaxations rather than their associated approximate linear programs applied to existing natural gas storage instances our alp relaxations significantly outperform their corresponding approximate linear programs our best alp relaxation is both near optimal and competitive with albeit slower than state of the art methods for computing heuristic policies and lower bounds on the value of commodity storage but is m

50th anniversary article option pricing valuation models and applications this paper surveys the literature on option pricing from its origins to the present an extensive review of valuation methods for european and american style claims is provided applications to complex securities and numerical methods are surveyed emphasis is placed on recent trends and developments in methodology and modeling

effective sub simulation free upper bounds for the monte carlo pricing of callable derivatives and various improvements to existing methodologies abstract we present a new non nested approach for computing additive upper bounds for callable derivatives using monte carlo simulation it relies on the regression of greeks computed using adjoint methods we also show that it is possible to early terminate paths once points of optimal exercise have been reached a natural control variate for the multiplicative upper bound is introduced which renders it competitive to the additive one in addition a new bi iterative family of upper bounds is introduced which takes a stopping time an upper bound and a martingale as inputs

a study of the relationship between competitiveness and technological innovation capability based on dea models researchers and managers have been searching for appropriate methods to explore the relationship between technological innovation capability and competitiveness in recent years this study attempts to find a systematic quantitative methodology to tackle this problem in a recent survey covering 182 industrial innovative firms in china the traditional data envelopment analysis dea model was employed to analyze the data collected the research results show that only 16 of the enterprises operate on the best practice frontier and there are some inconsistencies between organizational innovation capability and competitiveness in many enterprises decreasing returns to scale were found among about 70 of the inefficient enterprises and increasing returns to scale were found among the remaining 30 of the inefficient enterprises thus the internal innovation harmonizing process in these enterprises is considerably inefficient based on the restricted ranges of the input output factors a multi objective dea projection model has also been developed in this study to provide a benchmark for auditing competitiveness research results further indicate that there is still much room for enterprises to improve competitiveness in situations of confining score ranges of technological innovation capability and competitiveness

the impact of education experience and inner circle advisors on sme performance insights from a study of public development centers in this study we investigate the effects of entrepreneurial human capital on sme performance using data on 2 713 smes within the european union performance was measured in two ways profitability as roa and productivity as revenue per employee results indicate that both profitability and productivity are positively related to industry specific knowledge possessed by the ceo owner prior to starting up the firm and the general business knowledge acquired once the firm is up and running experience as a result of having previously worked in a firm in the same industry before starting a business was related to productivity but there is no relation with profitability there is a link between performance and inclusion of other ceo owners in the founder s inner circle of advisors this relationship is positive when the advisor s venture has experienced failure and negative when the advisor s venture has been successful we discuss the significance of these findings for research and practice

pricing american style securities using simulation abstract we develop a simulation algorithm for estimating the prices of american style securities i e securities with opportunities for early exercise our algorithm provides both point estimates and error bounds for the true security price it generates two estimates one biased high and one biased low both asymptotically unbiased and converging to the true price combining the two estimators yields a confidence interval for the true price the proposed algorithm is especially attractive compared with lattice and finite difference methods when there are multiple state variables and a small number of exercise opportunities preliminary computational evidence is given

convergence from discrete to continuous time contingent claims prices this article generalizes the cox ross and rubinstein 1979 binomial option pricing model and establishes a convergence from discrete time multivariate multinomial models to continuous time multidimensional diffusion models for contigent claims prices the key to the approach is to approximate the n dimensional diffusion price process by a sequence of n variate n 1 nomial processes it is shown that contingent claims prices and dynamic replicating portfolio strategies derived from the discrete time models converge to their corresponding continuous time limits article published by oxford university press on behalf of the society for financial studies in its journal the review of financial studies

a stochastic control approach to manage operational risk in power systems in this paper the novel method operational risk managing optimal power flow ormopf for minimizing the expected cost of power system operation is proposed in contrast to previous research in the area the proposed method does not use a security criterion instead the expected cost of operation includes expected costs of system failures this will lead to more flexible operating limits giving a more adequate balance between risk and economic benefit of transmission the method assumes a set of observable system variables such as transfers through specific transmission corridors system frequency or distance to a bifurcation surface then impulse control is applied to find an optimal strategy for activation of tertiary reserves based on the values of the observables

practical policy iteration generic methods for obtaining rapid and tight bounds for bermudan exotic derivatives using monte carlo simulation abstract we introduce a set of improvements which allow the calculation of very tight lower bounds for bermudan derivatives using monte carlo simulation these tight lower bounds can be computed quickly and with minimal hand crafting our focus is on accelerating policy iteration to the point where it can be used in similar computation times to the basic least squares approach but in doing so introduce a number of improvements which can be applied to both the least squares approach and the calculation of upper bounds using the andersen broadie method the enhancements to the least squares method improve both accuracy and efficiency results are provided for the displaced diffusion libor market model demonstrating that our practical policy iteration algorithm can be used to obtain tight lower bounds for cancellable cms steepener snowball and vanilla swaps in similar times to the basic least squares method

pricing and exercising american options an asymptotic expansion approach abstract this paper proposes and implements a novel asymptotic expansion approach for pricing discretely monitored american options and approximating their optimal early exercise boundaries under a generic class of multivariate derivative pricing models incorporating both stochastic volatility and levy driven jumps in asset return the price and the critical value can be expanded up to any arbitrary order around those under a simple constant volatility jump diffusion model the expansion terms are then efficiently implemented by exactly solving some backward inductions via closed form fourier transforms where a substantial extension of the hilbert transform method of feng and linetsky 2008a 2009 plays an important role the efficiency of our method is illustrated through some representative examples as applications we analyze the impacts of various model parameters on the optimal early exercise boundary compare the optimal early exercise boundaries under different models and propose a derivative proxy based method for practically exercising american options under models with stochastic volatility and jumps

extending quadrature methods to value multi asset and complex path dependent options abstract the exposition of the quadrature quad method andricopoulos widdicks duck and newton 2003 universal option valuation using quadrature methods journal of financial economics 67 447 471 see also corrigendum journal of financial economics 73 603 2004 is significantly extended to cover notably more complex and difficult problems in option valuations involving one or more underlyings trials comparing several techniques in the literature adapted from standard lattice grid and monte carlo methods to tackle particular types of problem show that quad offers far greater flexibility superior convergence and hence increased accuracy and considerably reduced computational times the speed advantage of quad means that even under the curse of dimensionality it is not necessary to resort to monte carlo methods certainly for options involving up to five underlying assets given the universality and flexibility of the method it should be the method of choice for pricing options involving multiple underlying assets in the presence of many features such as early exercise or path dependency

convergence and biases of monte carlo estimates of american option prices using a parametric exercise rule abstract this paper presents an algorithm for pricing american options using monte carlo simulation the method is based on using a parametric representation of the early exercise decision it is shown that as long as this parametric representation subsumes all relevant stopping times error bounds can be constructed using two different estimates one which is biased low and one which is biased high both are consistent and asymptotically unbiased estimators of the true option value results for high dimensional american options confirm the viability of the numerical procedure the convergence results of the paper shed light into the biases present in other algorithms proposed in the literature

productivity and intermediate products a frontier approach abstract in recent years it has become popular to measure productivity using non parametric approaches however this has been done while ignoring intermediate products here we develop a non parametric productivity measure that explicitly incorporates such products

american options under stochastic volatility the problem of pricing an american option written on an underlying asset with constant price volatility has been studied extensively in literature real world data however demonstrate that volatility is not constant and stochastic volatility models are used to account for dynamic volatility changes option pricing methods that have been developed in literature for pricing under stochastic volatility focus mostly on european options we consider the problem of pricing american options under stochastic volatility which has had relatively much less attention from literature first we develop a transformation procedure to compute the optimal exercise policy and option price and provide theoretical guarantees for convergence second using this computational tool we explore a variety of questions that seek insights into the dependence of option prices exercise policies and implied volatilities on the market price of volatility risk and correlation between the asset and stochastic volatility the speed and accuracy of the procedure are compared against existing methods as well

dynamic portfolio optimization with transaction costs heuristics and dual bounds we consider the problem of dynamic portfolio optimization in a discrete time finite horizon setting our general model considers risk aversion portfolio constraints e g no short positions return predictability and transaction costs this problem is naturally formulated as a stochastic dynamic program unfortunately with nonzero transaction costs the dimension of the state space is at least as large as the number of assets and the problem is very difficult to solve with more than one or two assets in this paper we consider several easy to compute heuristic trading strategies that are based on optimizing simpler models we complement these heuristics with upper bounds on the performance with an optimal trading strategy these bounds are based on the dual approach developed in brown et al brown d b j e smith p sun 2009 information relaxations and duality in stochastic dynamic programs oper res 58 4 785 801 in this context these bounds are given by considering an investor who has access to perfect information about future returns but is penalized for using this advance information these heuristic strategies and bounds can be evaluated using monte carlo simulation we evaluate these heuristics and bounds in numerical experiments with a risk free asset and 3 or 10 risky assets in many cases the performance of the heuristic strategy is very close to the upper bound indicating that the heuristic strategies are very nearly optimal this paper was accepted by dimitris bertsimas optimization

american option sensitivities estimation via a generalized infinitesimal perturbation analysis approach in this paper we develop efficient monte carlo methods for estimating american option sensitivities the problem can be reformulated as how to perform sensitivity analysis for a stochastic optimization problem with model uncertainty we introduce a generalized infinitesimal perturbation analysis ipa approach to resolve the difficulty caused by discontinuity of the optimal decision with respect to the underlying parameter the ipa estimators are unbiased if the optimal decisions are explicitly known to quantify the estimation bias caused by intractable exercising policies in the case of pricing american options we also provide an approximation guarantee that relates the sensitivity under the optimal exercise policy to that computed under a suboptimal policy the price sensitivity estimators yielded from this approach demonstrate significant advantages numerically in both high dimensional environments and various process settings we can easily embed them into many of the most popular pricing algorithm

primal dual simulation algorithm for pricing multidimensional american options this paper describes a practical algorithm based on monte carlo simulation for the pricing of multidimensional american i e continuously exercisable and bermudan i e discretely exercisable

closed form solutions for term structure derivatives with log normal interest rates we derive a unified model that gives closed form solutions for caps and floors written on interest rates as well as puts and calls written on zero coupon bonds the crucial assumption is that simple interest rates over a fixed finite period that matches the contract which we want to price are log normally distributed moreover this assumption is shown to be consistent with the heath jarrow morton model for a specific choice of volatility closed form solutions for interest rate derivatives in particular caps floors and bond options have been obtained by a number of authors for markovian term structure models with normally distributed interest rates or alternatively log normally distributed bond prices see for example jamshidian 1989 1991a heath jarrow and morton 1992 brace and musiela 1994 geman el karoui and rochet 1995 these models support black scholes type formulas most frequently used by practitioners for pricing bond options and swaptions unfortunately these models imply negative interest rates with positive probabilities and hence they are not arbitrage free in an economy with opportunities for riskless and costless storage of money briys crouhy and schobel 1991 apply the gaussian framework to derive closed form solutions for caps floors and european zero coupon bond options to exclude the influence of negative forward rates on the pricing of zero coupon bond options they introduce an additional boundary condition as shown by rady and sandmann 1994 these pricing formulas are only supported by a term structure model with an absorbing boundary for the forward rate at zero where the absorbing probability is not negligible which for a term structure model is a quite problematic assumption

relative sources of european regional productivity convergence a bootstrap frontier approach enflo k and hjertstrand p relative sources of european regional productivity convergence a bootstrap frontier approach regional studies this paper addresses the issue of western european regional productivity growth and convergence by means of data envelopment analysis dea decomposing labour productivity into efficiency change technical change and capital accumulation the decomposition shows that most regions have fallen behind the production frontier in efficiency and that capital accumulation has had a diverging effect on the labour productivity distribution using bootstrapping methods the paper also accounts for the inherent bias and the stochastic elements in the efficiency estimation it is found that the relative ranking of the efficiency scores remains stable after the bias correction even after controlling for spatially correlated measurement errors and that the dea successfully identifies the regions on the production frontier as significantly more efficient than other regions enfl

numerical evaluation of multivariate contingent claims we develop a numerical approximation method for valuing multivariate contingent claims the approach is based on an n dimensional extension of the lattice binomial method closed form solutions for the jump probabilities and the jump amplitudes are obtained the accuracy of the method is illustrated in the case of european options when there are three underlying assets article published by oxford university press on behalf of the society for financial studies in its journal the review of financial studies

a lattice framework for option pricing with two state variables a procedure is developed for the valuation of options when there are two underlying state variables the approach involves an extension of the lattice binomial approach developed by cox ross and rubinstein to value options on a single asset details are given on how the jump probabilities and jump amplitudes may be obtained when there are two state variables this procedure can be used to price any contingent claim whose payoff is a piece wise linear function of two underlying state variables provided these two variables have a bivariate lognormal distribution the accuracy of the method is illustrated by valuing options on the maximum and minimum of two assets and comparing the results for cases in which an exact solution has been obtained for european options one advantage of the lattice approach is that it handles the early exercise feature of american options in addition it should be possible to use this approach to value a number of financial instruments that have been created in recent years

an audit of technological innovation capabilities in chinese firms some empirical findings in beijing china abstract recent studies have advocated different technological innovation capabilities tics and discussed their impact on a firm s competitive performance this paper introduces a study framework of innovation audit and examines the relevance of seven tics to building and sustaining the competitiveness of chinese firms empirical data was acquired through a recent study of 213 chinese firms in beijing china regression analysis was employed to examine the correlation between tics and innovation rate sales growth and product competitiveness among these firms the findings verify that r d and resources allocation capabilities are the two most important tics a strong r d capability could safeguard innovation rate and product competitiveness in large and medium sized firms whereas a resources allocation capability would enhance the sales growth in small firms however the impact of learning and organising capabilities on a firm s innovation performance has yet to be investigated the findings of this paper suggest that chinese firms should consider a more balanced focus on their tics harmonising enhancement in order to maintain their sustainable development effectively plan and implement their innovation strategies as well as enhance their whole innovation capability chinese firms should closely relate their tics to the formulation of technology strategy and harmonisation of innovation and r d activities

numerical valuation of high dimensional multivariate american securities we consider the problem of pricing an american contingent claim whose payoff depends on several sources of uncertainty several efficient numerical lattice based techniques exist for pricing american securities depending on one or few up to three risk sources however these methods cannot be used for high dimensional problems since their memory requirement is exponential in the number of risk sources we present an efficient numerical technique that combines monte carlo simulation with a particular partitioning method of the underlying assets space which we call stratified state aggregation ssa using this technique we can compute accurate approximations of prices of american securities with an arbitrary number of underlying assets our numerical experiments show that the method is practical for pricing american claims depending on up to 400 risk sources

measuring the efficiency of china s regional innovation systems application of network data envelopment analysis dea chen k and guan j measuring the efficiency of china s regional innovation systems application of network data envelopment analysis dea regional studies this study applies a relational network data analysis envelopment to the systematic evaluation of the innovation efficiency of china s regional innovation systems by decomposing the innovation process into the two connecting sub processes technological development and subsequent technological commercialization the results show that only one fifth of china s regional innovation systems are operating on the empirical best practice frontier during the whole process from technological development to commercialization furthermore it is found that substantial inconsistencies exist between technological development capacity and commercialization capacity in most regional innovation systems and that downstream commercialization capacity plays a more important role in the innovation performance of regional innovation systems chen k et guan j evaluer

relative efficiency of r d activities a cross country study accounting for environmental factors in the dea approach abstract this paper applies the production framework associated with the data envelopment analysis dea method to evaluate the relative efficiency of r d activities across countries r d capital stocks and manpower are treated as inputs while patents and academic publications are considered as outputs a three stage approach which involves using dea for evaluating efficiency and using tobit regressions for controlling the external environment is applied to 30 countries in recent years the results show that less than one half of the countries are fully efficient in r d activities and that more than two thirds are at the stage of increasing returns to scale most countries have a more significant advantage in producing sci cum ei publications than in generating patents