A simplified pricing model for volatility futures

We develop a general model to price VIX futures contracts. The model is adapted to test both the constant elasticity of variance (CEV) and the Cox–Ingersoll–Ross formulations, with and without jumps. Empirical tests on VIX futures prices provide out-of-sample estimates within 2% of the actual futures price for almost all futures maturities. We show that although jumps are present in the data, the models with jumps do not typically outperform the others; in particular, we demonstrate the important benefits of the CEV feature in pricing futures contracts. We conclude by examining errors in the model relative to the VIX characteristics

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.

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.

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.

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.

The impact of livestock assets among indigenous communities: findings from a comparative model in Bolivia

Measuring poverty has occupied a lot of space in the development discourse. Over the years a number of approaches have been offered to capture the experience of what it means to be poor. However, latterly such approaches often ignore core assets. Indeed, the comparative impact of livestock vs. other core assets such as land and education on poverty has not been well explored. Therefore, the authors created an 'asset impact model' to examine changes to both tangible and intangible assets at the household level, with a particular focus on gender and ethnicity among communities residing in the Bolivian Altiplano. The simple model illustrates that for indigenous women, a 20 per cent increase in the livestock herd has the same impact on household income as increasing the education levels by 20 per cent and household land ownership by 5 per cent. The study illustrates the potential role of a productive, tangible asset, i.e. livestock, on poverty reduction in the short term. The policy implications of supporting asset-focused measures of poverty are discussed.

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.

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 risks and the cross-section of equity returns

The article examines whether commodity risk is priced in the cross-section of global equity returns. We employ a long-only equally-weighted portfolio of commodity futures and a term structure portfolio that captures phases of backwardation and contango as mimicking portfolios for commodity risk. We find that equity-sorted portfolios with greater sensitivities to the excess returns of the backwardation and contango portfolio command higher average excess returns, suggesting that when measured appropriately, commodity risk is pervasive in stocks. Our conclusions are robust to the addition to the pricing model of financial, macroeconomic and business cycle-based risk factors.

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 dynamics of asset prices and transaction activity in illiquid markets: the case of private commercial real estate

This paper investigates the relationship between capital flows, turnover and returns for the UK private real estate market. We examine a number of possible implication of capital flows and turnover on capital returns testing for evidence of a price pressure effect, ‘return chasing’ behaviour and information revelation. The main tool of analysis is a panel vector autoregressive (VAR) regression model in which institutional capital flows, turnover and returns are specified as endogenous variables in a two equation system in which we also control for macro-economic variables. Data on flows, turnover and returns are obtained for the 10 market segments covering the main UK commercial real estate sectors. Our results do not support the widely-held belief among practitioners that capital flows have a ‘price pressure’ effect. Although there is some evidence of return chasing behaviour, the short timescales involved suggest this finding may be due to delayed recording of flows relative to returns given the difficulties of market entry. We find a significant positive relationship between lagged turnover and contemporaneous capital returns, suggesting that asset turnover provides pricing information.

The significance of occupancy steadiness in residential consumer response to Time of Use pricing: Evidence from a stochastic adjustment model

The recent roll-out of smart metering technologies in several developed countries has intensified research on the impacts of Time-of-Use (TOU) pricing on consumption. This paper analyses a TOU dataset from the Province of Trento in Northern Italy using a stochastic adjustment model. Findings highlight the non-steadiness of the relationship between consumption and TOU price. Weather and active occupancy can partly explain future consumption in relation to price.