Pricing inefficiencies in private real estate markets using total return swaps

Efficient markets should guarantee the existence of zero spreads for total return swaps. However, real estate markets have recorded values that are significantly different from zero in both directions. Possible explanations might suggest non-rational behaviour by inexperienced market players or unusual features of the underlying asset market. We find that institutional characteristics in the underlying market lead to market inefficiencies and, hence, to the creation of a rational trading window with upper and lower bounds within which transactions do not offer arbitrage opportunities. Given the existence of this rational trading window, we also argue that the observed spreads can substantially be explained by trading imbalances due to the limited liquidity of a newly formed market and/or to the effect of market sentiment, complementing explanations based on the lag between underlying market returns and index returns.

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 elasticity of demand is about occupancy, not prices: building European demand curves based on occupancy elasticity

The peak congestion of the European grid may create significant impacts on system costs because of the need for higher marginal cost generation, higher cost system balancing and increasing grid reinforcement investment. The use of time of use rates, incentives, real time pricing and other programmes, usually defined as Demand Side Management (DSM), could bring about significant reductions in prices, limit carbon emissions from dirty power plants, and improve the integration of renewable sources of energy. Unlike previous studies on elasticity of residential electricity demand under flat tariffs, the aim of this study is not to investigate the known relatively inelastic relationship between demand and prices. Rather, the aim is to assess how occupancy levels vary in different European countries. This reflects the reality of demand loads, which are predominantly determined by the timing of human activities (e.g. travelling to work, taking children to school) rather than prices. To this end, two types of occupancy elasticity are estimated: baseline occupancy elasticity and peak occupancy elasticity. These represent the intrinsic elasticity associated with human activities of single residential end-users in 15 European countries. This study makes use of occupancy time-series data from the Harmonised European Time Use Survey database to build European occupancy curves; identify peak occupancy periods; draw time use demand curves for video and TV watching activity; and estimate national occupancy elasticity levels of single-occupant households. Findings on occupancy elasticities provide an indication of possible DSM strategies based on occupancy levels and not prices.

The effect of the molecular weight on the electro-optic properties of methacrylate-based side-chain liquid crystal polymers

A series of methacrylate-based side-chain liquid crystal polymers has been prepared with a range of molecular weights. For the high molecular weight polymers a smectic phase is observed with a very narrow nematic range; however, for low molecular weight polymers only the nematic phase is observed. A marked reduction in the glass transition temperature, TSN and TNI is observed with a reduction in the molecular weight. The orientational order parameters for these polymers in the liquid crystal phase have been determined using infra-red dichroism. It is found that the higher the molecular weight of the polymer, the greater is the threshold voltage of the electro-optic response and the lower the order parameter. The increase in the threshold voltage with increasing molecular weight may be related to the intrinsic curvature elasticity and hence to the coupling between the mesogenic units and the polymer backbone.

Synthesis, crystal structures and magnetic properties of a phenoxo-bridged dinuclear Cu(II) complex and a dicyanamide bridged novel molecular rectangle based on it

The phenoxo-bridged dinuclear Cu-II complex [Cu2L2-(NCNCN)(2)] (1) and the dicyanamide-bridged molecular rectangle [Cu4L4{mu(1,5)-(NCNCN)(2)}]center dot(ClO4)(2)(H2O)(2) (2) were synthesized using the tridentate reduced Schiff-base ligand HL {2-[(2-dimethylamino-ethylamino) methyl] phenol}. The complexes were characterized by X-ray structural analyses and variable-temperature magnetic susceptibility measurements. Complex 2 was formed through the joining of the phenoxo-bridged dinuclear Cu2O2 cores of 1 via the mu(1,5)-bridging mode of dicyanamide. The structural properties of the Cu2O2 cores in two complexes are significantly different. The geometry of the copper ions is distorted trigonal bipyramid in 1 but is nearly square-pyramidal in 2. These differences have a marked effect on the magnetic properties of two compounds. Although both are antiferromagnetically coupled, the coupling constants (J = -185.2 and -500.9 cm(-1) for 1 and 2, respectively) differ considerably.

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.

Is intrinsic energy efficiency reflected in the pricing of office leases?

This paper investigates whether the intrinsic energy efficiency rating of an office building has a significant impact on its rental value. A sample of 817 transactions for offices with Energy Performance Certificates (EPCs) in the UK is used to assess whether a pricing differential can be identified, depending on the energy rating. While previous analyses of this topic have typically relied on appraisal-based and/or asking rent data, the dataset used in this research contains actual contract rents as well as information on lease terms. The results indicate a significant rental premium for energy-efficient buildings. However, it is found that this premium appears to be mainly driven by the youngest cohort of state-of-the-art energy-efficient buildings. The results also show that tenants of more energy-efficient buildings tend to pay a lower service charge, but this link appears to be rather weak and limited to newer buildings. Hence, it is argued that the information contained in the EPC is still not fully taken into account in the UK commercial property market with the possible exception of both the highest and the lowest EPC ratings.

Idiosyncratic volatility and the pricing of poorly-diversified portfolios

This article examines the role of idiosyncratic volatility in explaining the cross-sectional variation of size- and value-sorted portfolio returns. We show that the premium for bearing idiosyncratic volatility varies inversely with the number of stocks included in the portfolios. This conclusion is robust within various multifactor models based on size, value, past performance, liquidity and total volatility and also holds within an ICAPM specification of the risk–return relationship. Our findings thus indicate that investors demand an additional return for bearing the idiosyncratic volatility of poorly-diversified portfolios.

Knowledge-based design cost estimation through extending industry foundation classes

In order to overcome divergence of estimation with the same data, the proposed digital costing process adopts an integrated design of information system to design the process knowledge and costing system together. By employing and extending a widely used international standard, industry foundation classes, the system can provide an integrated process which can harvest information and knowledge of current quantity surveying practice of costing method and data. Knowledge of quantification is encoded from literatures, motivation case and standards. It can reduce the time consumption of current manual practice. The further development will represent the pricing process in a Bayesian Network based knowledge representation approach. The hybrid types of knowledge representation can produce a reliable estimation for construction project. In a practical term, the knowledge management of quantity surveying can improve the system of construction estimation. The theoretical significance of this study lies in the fact that its content and conclusion make it possible to develop an automatic estimation system based on hybrid knowledge representation approach.

Electricity derivatives pricing with forward-looking information

In order to increase overall transparency on key operational information, power transmission system operators publish an increasing amount of fundamental data, including forecasts of electricity demand and available capacity. We employ a fundamental model for electricity prices which lends itself well to integrating such forecasts, while retaining ease of implementation and tractability to allow for analytic derivatives pricing formulae. In an extensive futures pricing study, the pricing performance of our model is shown to further improve based on the inclusion of electricity demand and capacity forecasts, thus confirming the general importance of forward-looking information for electricity derivatives pricing. However, we also find that the usefulness of integrating forecast data into the pricing approach is primarily limited to those periods during which electricity prices are highly sensitive to demand or available capacity, whereas the impact is less visible when fuel prices are the primary underlying driver to prices instead.