Hedging effectiveness of total returns swaps: application to the Japanese market

The development of the real estate swap market offers many opportunities for investors to adjust the exposure of their portfolios to real estate. A number of OTC transactions have been observed in markets around the world. In this paper we examine the Japanese commercial real estate market from the point of view of an investor holding a portfolio of properties seeking to reduce the portfolio exposure to the real estate market by swapping an index of real estate for LIBOR. This paper explores the practicalities of hedging portfolios comprising small numbers of individual properties against an appropriate index. We use the returns from 74 properties owned by Japanese Real Estate Investment Trusts over the period up to September 2007. The paper also discusses and applies the appropriate stochastic processes required to model real estate returns in this application and presents alternative ways of reporting hedging effectiveness. We find that the development of the derivative does provide the capacity for hedging market risk but that the effectiveness of the hedge varies considerably over time. We explore the factors that cause this variability.

Unlisted property funds and the emerging property markets

This paper sets out to describe the changing nature of global property investment, to provide background information regarding the nature of unlisted property funds and their managers and investors, and especially the role played by unlisted property funds in facilitating cross-border investing. In particular, it focuses on the development of unlisted funds as intermediary structures carrying institutional capital from developed to developing markets. It presents the results of new research by UK research firm Property Funds Research (PFR) and the University of Reading which explores the extent to which this new vehicle has been effective in delivering capital to emerging markets. The research relates the number of funds targetting particular countries and to population and GDP per capita. It finds that there is a very strong relationship between the popularity of a country for investment through this vehicle format and these independent variables. More interesting, perhaps, is the identification of outlier countries where the amount of investment is significantly less - or greater - than that predicted by population and GDP per capita.

The risks of investing in the real estate markets of the asian region

The Asian region has become a focus of attention for investors in recent years. Due to the strong economic performance of the region, the higher expected returns in the area compared with Europe and the USA and the additional diversification benefits investment in the region would offer. Nonetheless many investors have doubts about the prudence of investing in such areas. In particular it may be felt that the expected returns offered in the countries of the Asian region are not sufficient to compensate investors for the increased risks of investing in such markets. These risks can be categorised into under four headings: investment risk, currency risk, political risk, and institutional risk. This paper analyses each of these risks in turn to see if they are sufficiently large to deter real estate investment in the region in general or in a particular country.

Stochastic perturbations to dynamical systems: a response theory approach

Using the formalism of the Ruelle response theory, we study how the invariant measure of an Axiom A dynamical system changes as a result of adding noise, and describe how the stochastic perturbation can be used to explore the properties of the underlying deterministic dynamics. We first find the expression for the change in the expectation value of a general observable when a white noise forcing is introduced in the system, both in the additive and in the multiplicative case. We also show that the difference between the expectation value of the power spectrum of an observable in the stochastically perturbed case and of the same observable in the unperturbed case is equal to the variance of the noise times the square of the modulus of the linear susceptibility describing the frequency-dependent response of the system to perturbations with the same spatial patterns as the considered stochastic forcing. This provides a conceptual bridge between the change in the fluctuation properties of the system due to the presence of noise and the response of the unperturbed system to deterministic forcings. Using Kramers-Kronig theory, it is then possible to derive the real and imaginary part of the susceptibility and thus deduce the Green function of the system for any desired observable. We then extend our results to rather general patterns of random forcing, from the case of several white noise forcings, to noise terms with memory, up to the case of a space-time random field. Explicit formulas are provided for each relevant case analysed. As a general result, we find, using an argument of positive-definiteness, that the power spectrum of the stochastically perturbed system is larger at all frequencies than the power spectrum of the unperturbed system. We provide an example of application of our results by considering the spatially extended chaotic Lorenz 96 model. These results clarify the property of stochastic stability of SRB measures in Axiom A flows, provide tools for analysing stochastic parameterisations and related closure ansatz to be implemented in modelling studies, and introduce new ways to study the response of a system to external perturbations. Taking into account the chaotic hypothesis, we expect that our results have practical relevance for a more general class of system than those belonging to Axiom A.

Bistable systems with stochastic noise: virtues and limits of effective one-dimensional Langevin equations

The understanding of the statistical properties and of the dynamics of multistable systems is gaining more and more importance in a vast variety of scientific fields. This is especially relevant for the investigation of the tipping points of complex systems. Sometimes, in order to understand the time series of given observables exhibiting bimodal distributions, simple one-dimensional Langevin models are fitted to reproduce the observed statistical properties, and used to investing-ate the projected dynamics of the observable. This is of great relevance for studying potential catastrophic changes in the properties of the underlying system or resonant behaviours like those related to stochastic resonance-like mechanisms. In this paper, we propose a framework for encasing this kind of studies, using simple box models of the oceanic circulation and choosing as observable the strength of the thermohaline circulation. We study the statistical properties of the transitions between the two modes of operation of the thermohaline circulation under symmetric boundary forcings and test their agreement with simplified one-dimensional phenomenological theories. We extend our analysis to include stochastic resonance-like amplification processes. We conclude that fitted one-dimensional Langevin models, when closely scrutinised, may result to be more ad-hoc than they seem, lacking robustness and/or well-posedness. They should be treated with care, more as an empiric descriptive tool than as methodology with predictive power.

Attention through self-synchronisation in the spiking neuron stochastic diffusion network

The paper discusses ensemble behaviour in the Spiking Neuron Stochastic Diffusion Network, SNSDN, a novel network exploring biologically plausible information processing based on higher order temporal coding. SNSDN was proposed as an alternative solution to the binding problem [1]. SNSDN operation resembles Stochastic Diffusin on Search, SDS, a non-deterministic search algorithm able to rapidly locate the best instantiation of a target pattern within a noisy search space ([3], [5]). In SNSDN, relevant information is encoded in the length of interspike intervals. Although every neuron operates in its own time, ‘attention’ to a pattern in the search space results in self-synchronised activity of a large population of neurons. When multiple patterns are present in the search space, ‘switching of at- tention’ results in a change of the synchronous activity. The qualitative effect of attention on the synchronicity of spiking behaviour in both time and frequency domain will be discussed.

Time complexity analysis of the stochastic diffusion search

The Stochastic Diffusion Search algorithm -an integral part of Stochastic Search Networks is investigated. Stochastic Diffusion Search is an alternative solution for invariant pattern recognition and focus of attention. It has been shown that the algorithm can be modelled as an ergodic, finite state Markov Chain under some non-restrictive assumptions. Sub-linear time complexity for some settings of parameters has been formulated and proved. Some properties of the algorithm are then characterised and numerical examples illustrating some features of the algorithm are presented.