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.

Is there a “case for property” all the time?

The “case for property” in the mixed-asset portfolio is a topic of continuing interest to practitioners and academics. Such an analysis typically is performed over a fixed period of time and the optimum allocation to property inferred from the weight assigned to property through the use of mean-variance analysis. It is well known, however, that the parameters used in the portfolio analysis problem are unstable through time. Thus, the weight proposed for property in one period is unlikely to be that found in another. Consequently, in order to assess the case for property more thoroughly, the impact of property in the mixed-asset portfolio is evaluated on a rolling basis over a long period of time. In this way we test whether the inclusion of property significantly improves the performance of an existing equity/bond portfolio all of the time. The main findings are that the inclusion of direct property into an existing equity/bond portfolio leads to increase or decreases in return, depending on the relative performance of property compared with the other asset classes. However, including property in the mixed-asset portfolio always leads to reductions in portfolio risk. Consequently, adding property into an equity/bond portfolio can lead to significant increases in risk-adjusted performance. Thus, if the decision to include direct property in the mixed-asset portfolio is based upon its diversification benefits the answer is yes, there is a “case for property” all the time!

A note on the use of spreadsheet optimisers in real estate analysis

Modern Portfolio Theory (MPT) has been advocated as a more rational approach to the construction of real estate portfolios. The application of MPT can now be achieved with relative ease using the powerful facilities of modern spreadsheet, and does not necessarily need specialist software. This capability is to be found in the use of an add-in Tool now found in several spreadsheets, called an Optimiser or Solver. The value in using this kind of more sophisticated analysis feature of spreadsheets is increasingly difficult to ignore. This paper examines the use of the spreadsheet Optimiser in handling asset allocation problems. Using the Markowitz Mean-Variance approach, the paper introduces the necessary calculations, and shows, by means of an elementary example implemented in Microsoft's Excel, how the Optimiser may be used. Emphasis is placed on understanding the inputs and outputs from the portfolio optimisation process, and the danger of treating the Optimiser as a Black Box is discussed.

The mean evolution and variability of the Asian summer monsoon: Comparison of ECMWF and NCEP-NCAR reanalyses

The behavior of the Asian summer monsoon is documented and compared using the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis (ERA) and the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) Reanalysis. In terms of seasonal mean climatologies the results suggest that, in several respects, the ERA is superior to the NCEP-NCAR Reanalysis. The overall better simulation of the precipitation and hence the diabatic heating field over the monsoon domain in ERA means that the analyzed circulation is probably nearer reality. In terms of interannual variability, inconsistencies in the definition of weak and strong monsoon years based on typical monsoon indices such as All-India Rainfall (AIR) anomalies and the large-scale wind shear based dynamical monsoon index (DMI) still exist. Two dominant modes of interannual variability have been identified that together explain nearly 50% of the variance. Individually, they have many features in common with the composite flow patterns associated with weak and strong monsoons, when defined in terms of regional AIR anomalies and the large-scale DMI. The reanalyses also show a common dominant mode of intraseasonal variability that describes the latitudinal displacement of the tropical convergence zone from its oceanic-to-continental regime and essentially captures the low-frequency active/break cycles of the monsoon. The relationship between interannual and intraseasonal variability has been investigated by considering the probability density function (PDF) of the principal component of the dominant intraseasonal mode. Based on the DMI, there is an indication that in years with a weaker monsoon circulation, the PDF is skewed toward negative values (i,e., break conditions). Similarly, the PDFs for El Nino and La Nina years suggest that El Nino predisposes the system to more break spells, although the sample size may limit the statistical significance of the results.

Mean climate and transience in the tropics of the UGAMP GCM - sensitivity to convective parametrization

The sensitivity of the UK Universities Global Atmospheric Modelling Programme (UGAMP) General Circulation Model (UGCM) to two very different approaches to convective parametrization is described. Comparison is made between a Kuo scheme, which is constrained by large-scale moisture convergence, and a convective-adjustment scheme, which relaxes to observed thermodynamic states. Results from 360-day integrations with perpetual January conditions are used to describe the model's tropical time-mean climate and its variability. Both convection schemes give reasonable simulations of the time-mean climate, but the representation of the main modes of tropical variability is markedly different. The Kuo scheme has much weaker variance, confined to synoptic frequencies near 4 days, and a poor simulation of intraseasonal variability. In contrast, the convective-adjustment scheme has much more transient activity at all time-scales. The various aspects of the two schemes which might explain this difference are discussed. The particular closure on moisture convergence used in this version of the Kuo scheme is identified as being inappropriate.

Multidecadal modulation of El Nino-Southern Oscillation (ENSO) variance by Atlantic Ocean sea surface temperatures

Observations suggest a possible link between the Atlantic Multidecadal Oscillation (AMO) and El Nino Southern Oscillation (ENSO) variability, with the warm AMO phase being related to weaker ENSO variability. A coupled ocean-atmosphere model is used to investigate this relationship and to elucidate mechanisms responsible for it. Anomalous sea surface temperatures (SSTs) associated with the positive AMO lead to change in the basic state in the tropical Pacific Ocean. This basic state change is associated with a deepened thermocline and reduced vertical stratification of the equatorial Pacific ocean, which in turn leads to weakened ENSO variability. We suggest a role for an atmospheric bridge that rapidly conveys the influence of the Atlantic Ocean to the tropical Pacific. The results suggest a non-local mechanism for changes in ENSO statistics and imply that anomalous Atlantic ocean SSTs can modulate both mean climate and climate variability over the Pacific.

Forecasting exchange rate volatility using conditional variance models selected by information criteria

This paper uses appropriately modified information criteria to select models from the GARCH family, which are subsequently used for predicting US dollar exchange rate return volatility. The out of sample forecast accuracy of models chosen in this manner compares favourably on mean absolute error grounds, although less favourably on mean squared error grounds, with those generated by the commonly used GARCH(1, 1) model. An examination of the orders of models selected by the criteria reveals that (1, 1) models are typically selected less than 20% of the time.

New perspectives on the Northern Hemisphere winter storm tracks

The aim of this paper is to explore the use of both an Eulerian and system-centered method of storm track diagnosis applied to a wide range of meteorological fields at multiple levels to provide a range of perspectives on the Northern Hemisphere winter transient motions and to give new insight into the storm track organization and behavior. The data used are primarily from the European Centre for Medium-Range Weather Forecasts reanalyses project extended with operational analyses to the period 1979-2000. This is supplemented by data from the National Centers for Environmental Prediction and Goddard Earth Observing System 1 reanalyses. The range of fields explored include the usual mean sea level pressure and the lower- and upper-tropospheric height, meridional wind, vorticity, and temperature, as well as the potential vorticity (PV) on a 330-K isentropic surface (PV330) and potential temperature on a PV = 2 PVU surface (theta(PV2)). As well as reporting the primary analysis based on feature tracking, the standard Eulerian 2-6-day bandpass filtered variance analysis is also reported and contrasted with the tracking diagnostics. To enable the feature points to be identified as extrema for all the chosen fields, a planetary wave background structure is removed at each data time. The bandpass filtered variance derived from the different fields yield a rich picture of the nature and comparative magnitudes of the North Pacific and Atlantic storm tracks, and of the Siberian and Mediterranean candidates for storm tracks. The feature tracking allows the cyclonic and anticyclonic activities to be considered seperately. The analysis indicates that anticyclonic features are generally much weaker with less coherence than the cyclonic systems. Cyclones and features associated with them are shown to have much greater coherence and give tracking diagnostics that create a vivid storm track picture that includes the aspects highlighted by the variances as well as highlighting aspects that are not readily available from Eulerian studies. In particular, the upper-tropospheric features as shown by negative theta(PV2), for example, occur in a band spiraling around the hemisphere from the subtropical North Atlantic eastward to the high latitudes of the same ocean basin. Lower-troposphere storm tracks occupy more limited longitudinal sectors, with many of the individual storms possibly triggered from the upper-tropospheric disturbances in the spiral band of activity.

The effect of doubled CO2 and model basic state biases on the monsoon-ENSO system. I: Mean response and interannual variability

The impact of doubled CO2 concentration on the Asian summer monsoon is studied using a coupled ocean-atmosphere model. Both the mean seasonal precipitation and interannual monsoon variability are found to increase in the future climate scenario presented. Systematic biases in current climate simulations of the coupled system prevent accurate representation of the monsoon-ENSO teleconnection, of prime importance for seasonal prediction and for determining monsoon interannual variability. By applying seasonally varying heat flux adjustments to the tropical Pacific and Indian Ocean surface in the future climate simulation, some assessment can be made of the impact of systematic model biases on future climate predictions. In simulations where the flux adjustments are implemented, the response to climate change is magnified, with the suggestion that systematic biases may be masking the true impact of increased greenhouse gas forcing. The teleconnection between ENSO and the Asian summer monsoon remains robust in the future climate, although the Indo-Pacific takes on more of a biennial character for long periods of the flux-adjusted simulation. Assessing the teleconnection across interdecadal timescales shows wide variations in its amplitude, despite the absence of external forcing. This suggests that recent changes in the observed record cannot be distinguished from internal variations and as such are not necessarily related to climate change.

Vertical structure of anthropogenic zonal-mean atmospheric circulation change

The atmospheric circulation changes predicted by climate models are often described using sea level pressure, which generally shows a strengthening of the mid-latitude westerlies. Recent observed variability is dominated by the Northern Annular Mode (NAM) which is equivalent barotropic, so that wind variations of the same sign are seen at all levels. However, in model predictions of the response to anthropogenic forcing, there is a well-known enhanced warming at low levels over the northern polar cap in winter. This means that there is a strong baroclinic component to the response. The projection of the response onto a NAM-like zonal index varies with height. While at the surface most models project positively onto the zonal index, throughout most of the depth of the troposphere many of the models give negative projections. The response to anthropogenic forcing therefore has a distinctive baroclinic signature which is very different to the NAM