American option valuation: implied calibration of GARCH pricing models

This study analyzes the issue of American option valuation when the underlying exhibits a GARCH-type volatility process. We propose the usage of Rubinstein's Edgeworth binomial tree (EBT) in contrast to simulation-based methods being considered in previous studies. The EBT-based valuation approach makes an implied calibration of the pricing model feasible. By empirically analyzing the pricing performance of American index and equity options, we illustrate the superiority of the proposed approach.

Asymmetric output gap effects in Phillips Curve and mark-up pricing models: evidence for the US and the UK

A number of studies have found an asymmetric response of consumer price index inflation to the output gap in the US in simple Phillips curve models. We consider whether there are similar asymmetries in mark-up pricing models, that is, whether the mark-up over producers' costs also depends upon the sign of the (adjusted) output gap. The robustness of our findings to the price series is assessed, and also whether price-output responses in the UK are asymmetric.

The value premium and time-varying volatility

Numerous studies have documented the failure of the static and conditional capital asset pricing models to explain the difference in returns between value and growth stocks. This paper examines the post-1963 value premium by employing a model that captures the time-varying total risk of the value-minus-growth portfolios. Our results show that the time-series of value premia is strongly and positively correlated with its volatility. This conclusion is robust to the criterion used to sort stocks into value and growth portfolios and to the country under review (the US and the UK). Our paper is consistent with evidence on the possible role of idiosyncratic risk in explaining equity returns, and also with a separate strand of literature concerning the relative lack of reversibility of value firms' investment decisions.

Depreciation and its impact on the total return of UK commercial real estate, 1994-2003

Depreciation is a key element of understanding the returns from and price of commercial real estate. Understanding its impact is important for asset allocation models and asset management decisions. It is a key input into well-constructed pricing models and its impact on indices of commercial real estate prices needs to be recognised. There have been a number of previous studies of the impact of depreciation on real estate, particularly in the UK. Law (2004) analysed all of these studies and found that the seemingly consistent results were an illusion as they all used a variety of measurement methods and data. In addition, none of these studies examined impact on total returns; they examined either rental value depreciation alone or rental and capital value depreciation. This study seeks to rectify this omission, adopting the best practice measurement framework set out by Law (2004). Using individual property data from the UK Investment Property Databank for the 10-year period between 1994 and 2003, rental and capital depreciation, capital expenditure rates, and total return series for the data sample and for a benchmark are calculated for 10 market segments. The results are complicated by the period of analysis which started in the aftermath of the major UK real estate recession of the early 1990s, but they give important insights into the impact of depreciation in different segments of the UK real estate investment market.

Real option pricing in mixed-use development projects

The application of real options theory to commercial real estate has developed rapidly during the last 15 Years. In particular, several pricing models have been applied to value real options embedded in development projects. In this study we use a case study of a mixed use development scheme and identify the major implied and explicit real options available to the developer. We offer the perspective of a real market application by exploring different binomial models and the associated methods of estimating the crucial parameter of volatility. We include simple binomial lattices, quadranomial lattices and demonstrate the sensitivity of the results to the choice of inputs and method.

Pricing short leases and break clauses using simulation methodology

This paper examines the changes in the length of commercial property leases over the last decade and presents an analysis of the consequent investment and occupational pricing implications for commercial property investmentsIt is argued that the pricing implications of a short lease to an investor are contingent upon the expected costs of the letting termination to the investor, the probability that the letting will be terminated and the volatility of rental values.The paper examines the key factors influencing these variables and presents a framework for incorporating their effects into pricing models.Approaches to their valuation derived from option pricing are critically assessed. It is argued that such models also tend to neglect the price effects of specific risk factors such as tenant circumstances and the terms of break clause. Specific risk factors have a significant bearing on the probability of letting termination and on the level of the resultant financial losses. The merits of a simulation methododology are examined for rental and capital valuations of short leases and properties with break clauses.It is concluded that in addition to the rigour of its internal logic, the success of any methodology is predicated upon the accuracy of the inputs.The lack of reliable data on patterns in, and incidence of, lease termination and the lack of reliable time series of historic property performance limit the efficacy of financial models.

Pricing and hedging short sterling options using artificial neural networks

This paper compares the performance of artificial neural networks (ANNs) with that of the modified Black model in both pricing and hedging Short Sterling options. Using high frequency data, standard and hybrid ANNs are trained to generate option prices. The hybrid ANN is significantly superior to both the modified Black model and the standard ANN in pricing call and put options. Hedge ratios for hedging Short Sterling options positions using Short Sterling futures are produced using the standard and hybrid ANN pricing models, the modified Black model, and also standard and hybrid ANNs trained directly on the hedge ratios. The performance of hedge ratios from ANNs directly trained on actual hedge ratios is significantly superior to those based on a pricing model, and to the modified Black model.

How contractors price risk in bids: theory and practice

Formal and analytical models that contractors can use to assess and price project risk at the tender stage have proliferated in recent years. However, they are rarely used in practice. Introducing more models would, therefore, not necessarily help. A better understanding is needed of how contractors arrive at a bid price in practice, and how, and in what circumstances, risk apportionment actually influences pricing levels. More than 60 proposed risk models for contractors that are published in journals were examined and classified. Then exploratory interviews with five UK contractors and documentary analyses on how contractors price work generally and risk specifically were carried out to help in comparing the propositions from the literature to what contractors actually do. No comprehensive literature on the real bidding processes used in practice was found, and there is no evidence that pricing is systematic. Hence, systematic risk and pricing models for contractors may have no justifiable basis. Contractors process their bids through certain tendering gateways. They acknowledge the risk that they should price. However, the final settlement depends on a set of complex, micro-economic factors. Hence, risk accountability may be smaller than its true cost to the contractor. Risk apportionment occurs at three stages of the whole bid-pricing process. However, analytical approaches tend not to incorporate this, although they could.

Systematic property risk: quantifying UK property betas 1983-2005

The increased frequency in reporting UK property performance figures, coupled with the acceptance of the IPD database as the market standard, has enabled property to be analysed on a comparable level with other more frequently traded assets. The most widely utilised theory for pricing financial assets, the Capital Asset Pricing Model (CAPM), gives market (systematic) risk, beta, centre stage. This paper seeks to measure the level of systematic risk (beta) across various property types, market conditions and investment holding periods. This paper extends the authors’ previous work on investment holding periods and how excess returns (alpha) relate to those holding periods. We draw on the uniquely constructed IPD/Gerald Eve transactions database, containing over 20,000 properties over the period 1983-2005. This research allows us to confirm our initial findings that properties held over longer periods perform in line with overall market performance. One implication of this is that over the long-term performance may be no different from an index tracking approach.

Judgments, forecasts and decisions: an analysis of fund managers over time

Decision theory is the study of models of judgement involved in, and leading to, deliberate and (usually) rational choice. In real estate investment there are normative models for the allocation of assets. These asset allocation models suggest an optimum allocation between the respective asset classes based on the investors’ judgements of performance and risk. Real estate is selected, as other assets, on the basis of some criteria, e.g. commonly its marginal contribution to the production of a mean variance efficient multi asset portfolio, subject to the investor’s objectives and capital rationing constraints. However, decisions are made relative to current expectations and current business constraints. Whilst a decision maker may believe in the required optimum exposure levels as dictated by an asset allocation model, the final decision may/will be influenced by factors outside the parameters of the mathematical model. This paper discusses investors' perceptions and attitudes toward real estate and highlights the important difference between theoretical exposure levels and pragmatic business considerations. It develops a model to identify “soft” parameters in decision making which will influence the optimal allocation for that asset class. This “soft” information may relate to behavioural issues such as the tendency to mirror competitors; a desire to meet weight of money objectives; a desire to retain the status quo and many other non-financial considerations. The paper aims to establish the place of property in multi asset portfolios in the UK and examine the asset allocation process in practice, with a view to understanding the decision making process and to look at investors’ perceptions based on an historic analysis of market expectation; a comparison with historic data and an analysis of actual performance.

Commodity price dynamics and derivatives valuation: a review

This paper reviews extant research on commodity price dynamics and commodity derivatives pricing models. In the first half, we provide an overview of stylized facts of commodity price behavior that have been explored and documented in the theoretical and empirical literature. In the second half, we review existing derivatives pricing models and discuss how the peculiarities of commodity markets have been integrated in these models. We conclude the paper with a brief outlook on important research questions that need to be addressed in the future.

Speculative bubbles and the cross-sectional variation in stock returns

Evidence suggests that rational, periodically collapsing speculative bubbles may be pervasive in stock markets globally, but there is no research that considers them at the individual stock level. In this study we develop and test an empirical asset pricing model that allows for speculative bubbles to affect stock returns. We show that stocks incorporating larger bubbles yield higher returns. The bubble deviation, at the stock level as opposed to the industry or market level, is a priced source of risk that is separate from the standard market risk, size and value factors. We demonstrate that much of the common variation in stock returns that can be attributable to market risk is due to the co-movement of bubbles rather than being driven by fundamentals.

Analytic approximations for multi-asset option pricing

We derive general analytic approximations for pricing European basket and rainbow options on N assets. The key idea is to express the option’s price as a sum of prices of various compound exchange options, each with different pairs of subordinate multi- or single-asset options. The underlying asset prices are assumed to follow lognormal processes, although our results can be extended to certain other price processes for the underlying. For some multi-asset options a strong condition holds, whereby each compound exchange option is equivalent to a standard single-asset option under a modified measure, and in such cases an almost exact analytic price exists. More generally, approximate analytic prices for multi-asset options are derived using a weak lognormality condition, where the approximation stems from making constant volatility assumptions on the price processes that drive the prices of the subordinate basket options. The analytic formulae for multi-asset option prices, and their Greeks, are defined in a recursive framework. For instance, the option delta is defined in terms of the delta relative to subordinate multi-asset options, and the deltas of these subordinate options with respect to the underlying assets. Simulations test the accuracy of our approximations, given some assumed values for the asset volatilities and correlations. Finally, a calibration algorithm is proposed and illustrated.

The ASSET intercomparison of ozone analyses: method and first results

This paper aims to summarise the current performance of ozone data assimilation (DA) systems, to show where they can be improved, and to quantify their errors. It examines 11 sets of ozone analyses from 7 different DA systems. Two are numerical weather prediction (NWP) systems based on general circulation models (GCMs); the other five use chemistry transport models (CTMs). The systems examined contain either linearised or detailed ozone chemistry, or no chemistry at all. In most analyses, MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) ozone data are assimilated; two assimilate SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Chartography) observations instead. Analyses are compared to independent ozone observations covering the troposphere, stratosphere and lower mesosphere during the period July to November 2003. Biases and standard deviations are largest, and show the largest divergence between systems, in the troposphere, in the upper-troposphere/lower-stratosphere, in the upper-stratosphere and mesosphere, and the Antarctic ozone hole region. However, in any particular area, apart from the troposphere, at least one system can be found that agrees well with independent data. In general, none of the differences can be linked to the assimilation technique (Kalman filter, three or four dimensional variational methods, direct inversion) or the system (CTM or NWP system). Where results diverge, a main explanation is the way ozone is modelled. It is important to correctly model transport at the tropical tropopause, to avoid positive biases and excessive structure in the ozone field. In the southern hemisphere ozone hole, only the analyses which correctly model heterogeneous ozone depletion are able to reproduce the near-complete ozone destruction over the pole. In the upper-stratosphere and mesosphere (above 5 hPa), some ozone photochemistry schemes caused large but easily remedied biases. The diurnal cycle of ozone in the mesosphere is not captured, except by the one system that includes a detailed treatment of mesospheric chemistry. These results indicate that when good observations are available for assimilation, the first priority for improving ozone DA systems is to improve the models. The analyses benefit strongly from the good quality of the MIPAS ozone observations. Using the analyses as a transfer standard, it is seen that MIPAS is similar to 5% higher than HALOE (Halogen Occultation Experiment) in the mid and upper stratosphere and mesosphere (above 30 hPa), and of order 10% higher than ozonesonde and HALOE in the lower stratosphere (100 hPa to 30 hPa). Analyses based on SCIAMACHY total column are almost as good as the MIPAS analyses; analyses based on SCIAMACHY limb profiles are worse in some areas, due to problems in the SCIAMACHY retrievals.