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Real estate is the last major asset class without liquid derivatives markets. The reasons for that are not fully known or understood. Therefore, the purpose of this paper is to better understand the main factors that influence the propensity of commercial real estate investors in the UK to employ property derivatives.

The research methodology that was chosen for this research is grounded theory which, in its original form, goes back to Glaser and Strauss (1967). A total of 43 interviews were conducted with 46 real estate professionals in the UK from property investment management firms (investing directly or indirectly in real estate), multi-asset management firms, real estate investment trusts, banks, and brokerage and advisory firms, among others.

The research results show 29 factors that influence the propensity of direct and indirect real estate investors in the UK to employ property derivatives. Out of the 29 factors, the current research identified 12 factors with high-explanatory power, 6 with a contributing role and 11 with low explanatory power. Moreover, factors previously discussed in the literature are tested and assessed as to their explanatory power. The focus of this paper is on those factors with high-explanatory power. From the research data, three main reasons have been identified as the sources of investor reluctance to trade in property derivatives. The first and main reason is related to a mismatch between motivations of property investment managers and what can be achieved with the instruments. The second reason, which ties in with the first one, is a general misunderstanding as to the right pricing technique of property derivatives. Finally, the third reason is a general lack of hedging demand from the investor base owing to the long investment horizons through market cycles.

The research contributes to the literature on property derivatives in various ways. First, it extends the literature on market hurdles in property derivatives markets by testing and extending the hurdles that were proposed previously. Second, the research shows that the existing pricing models need to be extended in order to account for the risk perception of practitioners and their concerns with regard to liquidity levels.

For both theory and practice, the research has shown some limitations in using property derivatives for purposes such as creating index exposure or hedging. Another contribution, in this case to practice, is that this study provides a clearer picture as to the reasons that keep property investment managers away from using property derivatives.

The research results indicate that liquidity per se is not a universal remedy for the problems in the market. In addition to the need for improving the understanding of the pricing mechanism, practitioners should give more thought to the notion of real estate market risk and the commensurate returns that can reasonably be expected when they take or reduce it. This implies that property index futures currently do not price like those on any other investable asset class.

The purpose of this paper is to provide a framework of replication pricing of derivatives and identify funding valuation adjustment (FVA) and credit valuation adjustments (CVA) as price components.

The authors propose the notion of bilateral replication pricing. In the absence of funding cost, it reduces to unilateral replication pricing. The absence of funding costs, it introduces bid–ask spreads.

The valuation of CVA can be separated from that of FVA, so-called split up. There may be interdependence between FVA and the derivatives value, which then requires a recursive procedure for their numerical solution.

The authors have assume deterministic interest rates, constant CDS rates and loss rates for the CDS. The authors have also not dealt with re-hypothecation risks.

The results of this paper allow user to identify CVA and FVA, and mark to market their derivatives trades according to the recent market standards.

For the first time, a line between the risk-neutral pricing measure and the funding risk premiums is drawn. Also, the notion of bilateral replication pricing extends the unilateral replication pricing.

To propose a new methodology to infer the risk‐neutral default probability curve of a generic firm XYZ from equity options prices.

It is assumed that the market is arbitrage‐free and the “market” probability measure implied in the equity options prices to the pricing of credit risky assets is applied. First, the equity probability density function of XYZ is inferred from a set of quoted equity options with different strikes and maturities. This function is then transformed into the probability density function of the XYZ assets and the term structure of the “option implied” XYZ default probabilities is calculated. These default probabilities can be used to price corporate bonds and, more generally, single‐name credit derivatives as “exotic” equity derivatives.

Equity derivatives and credit derivatives have ultimately the same (unobservable) underlying, the XYZ assets value. A model that considers any security issued by XYZ as derivatives on the firm's assets can be used to price these securities in a consistent way to each other and/or detect relative/value opportunities.

The paper offers both a pricing tool for traded single‐name credit risky assets or a relative value tool in liquid markets.

In terms of notional value outstanding, derivatives markets declined in both over-the-counter and exchange-traded transactions during the 2007–2009 global financial crisis (GFC) period, as counterparty and credit concerns became pre-eminent. However, during the 2010–2011 second stage of the GFC, markets rebounded and by June 2011 outstandings reached new levels which highlight the importance these contracts continue to play in the day-to-day risk management and trading activities of corporations and financial intermediaries. The bulk of the contracts traded are interest rate-related instruments and are denominated in either US dollars or Euro. Credit-related instruments remain an important market segment, although outstandings remain at pre-crisis period levels. Of particular concern for regulators is the role of non-bank financial intermediaries, which are the main counterparty to derivatives transactions. While their share of the market remains unchanged over the last decade, outstandings overall have increased more than fourfold. The present volume considers the issues that participants face in today's derivatives markets including the potential impact of derivatives on economic stability, pricing issues, modelling as well as model performance and the application of derivatives for risk management and corporate control.

The goal of the paper is to analyse the various issues attached to the valuation of weather derivatives. We focus our study on temperature‐related contracts since they are the most widely traded at this point and try to address the following questions: (i) should the quantity underlying the swaps or options contracts be defined as the temperature, degree‐days or cumulative degree‐days? This discussion is conducted both in terms of the robustness of the statistical modelling of the state variable and the mathematical valuation of the option (European versus Asian). (ii) What pricing approaches can tackle the market incompleteness generated by a non‐tradable underlying when furthermore the market price of risk is hard to identify in other traded instruments and unlikely to be zero? We illustrate our study on a database of temperatures registered at Paris Le Bourget and compare the calls and puts prices obtained using the different methods most widely used in weather markets.

The application of weather derivatives in hedging crop yield risk is gaining more interest. However, the further development of weather derivatives – particularly exchange-traded – in the agricultural sector has been impeded by concerns over their hedging performance. The purpose of this paper is to develop a new framework to derive the optimal hedging strategy and evaluate hedging effectiveness.

This framework incorporates a stochastic temperature model, a crop yield model, a risk-neutral pricing method and a profit optimization procedure. Based on a large number of simulated scenarios, the authors study crop yield hedge for a future year. The authors allow the hedger to choose from different types of exchange-traded weather derivatives, and examine the impact of various factors on the optimal hedging strategy.

The analysis shows that hedging objective, pricing method and geographical location of the hedged exposure all play important roles in choosing the best hedging strategy and assessing hedging effectiveness.

This framework is forward-looking, because it focusses on the crop yield hedge for a future year rather than on the historical hedging effectiveness often studied in literature. It utilizes the most up-to-date information related to temperature and crop yield, and hence produces a hedging strategy which is more relevant to the year under consideration.

This paper examines the pricing of interest rates derivatives such as caps and swaptions in the pricing kernel framework. The underlying state variable is extended to the general infinitely divisible Levy process. For computational purposes, a simple pricing kernel as in Flesaker and Hughston (1996) and Jin and Glasserman (2001) is used. The main contribution or purpose of this paper is to find several proper positive martingales, which is key role of practical applications of the pricing kernel approach with interest rates guarantee to be positive. Particularly, this paper first finds and applies a quite general type of a positive martingale process to pricing interest rate derivatives such as swaptions and range notes in the incomplete market setting. Such interest rate derivatives are hard to find analytic solutions. Consequently, this paper shows that such a choice of the positive martingale in the kernel framework is a promising approach to price interest rate derivatives

This paper gives a selective review on some recent developments of nonparametric methods in both continuous and discrete time finance, particularly in the areas of nonparametric estimation and testing of diffusion processes, nonparametric testing of parametric diffusion models, nonparametric pricing of derivatives, nonparametric estimation and hypothesis testing for nonlinear pricing kernel, and nonparametric predictability of asset returns. For each financial context, the paper discusses the suitable statistical concepts, models, and modeling procedures, as well as some of their applications to financial data. Their relative strengths and weaknesses are discussed. Much theoretical and empirical research is needed in this area, and more importantly, the paper points to several aspects that deserve further investigation.

This paper aims to test three parametric models in pricing and hedging higher-order moment swaps. Using vanilla option prices from the volatility surface of the Euro Stoxx 50 Index, the paper shows that the pricing accuracy of these models is very satisfactory under four different pricing error functions. The result is that taking a position in a third moment swap considerably improves the performance of the standard hedge of a variance swap based on a static position in the log-contract and a dynamic trading strategy. The position in the third moment swap is taken by running a Monte Carlo simulation.

This paper undertook empirical tests of three parametric models. The aim of the paper is twofold: assess the pricing accuracy of these models and show how the classical hedge of the variance swap in terms of a position in a log-contract and a dynamic trading strategy can be significantly enhanced by using third-order moment swaps. The pricing accuracy was measured under four different pricing error functions. A Monte Carlo simulation was run to take a position in the third moment swap.

The results of the paper are twofold: the pricing accuracy of the Heston (1993) model and that of two Levy models with stochastic time and stochastic volatility are satisfactory; taking a position in third-order moment swaps can significantly improve the performance of the standard hedge of a variance swap.

The limitation is that these empirical tests are conducted on existing three parametric models. Maybe more critical insights could have been revealed had these tests been conducted in a brand new derivatives pricing model.

This work is 100 per cent original, and it undertook empirical tests of the pricing and hedging accuracy of existing three parametric models.

The purpose of this paper is to introduce a continuous time version of the speculative storage model of Deaton and Laroque (1992) and to use for pricing derivatives, in particular insurances on agricultural prices.

The methodology of financial engineering is used in order to find the partial differential equations that the dynamics of derivative prices have to satisfy. Furthermore, by using the Monte-Carlo method (and Feynman-Kac theorem) the insurance prices is computed.

Results of this paper show that insurance prices (and derivative prices in general) are heavily influenced by market structure, in particular, the demand function specifications. Furthermore, through an empirical analysis, the performance of the continuous time speculative storage model is compared with the geometric Brownian motion model. It is shown that the speculative storage model outperforms the actual data.

Since the agricultural insurances in many countries are subsidised by government, the results of this paper can be used by policy makers to measure changes in agricultural insurance premiums in scenarios that market experiences changes in demand. In the same manner, insurance companies and investors can use the results of this paper to better price agricultural derivatives.

The issue of agricultural insurance pricing (in general derivative pricing) is of great concern to policy makers, investors and insurance companies. To the author’s knowledge, an approach which uses the methodology of financial engineering to compute the insurance prices (in general derivatives) is new within the literature.