768 resultados para Monotone likelihood ration property
Resumo:
This paper considers the effect of short- and long-term interest rates, and interest rate spreads upon real estate index returns in the UK. Using Johansen's vector autoregressive framework, it is found that the real estate index cointegrates with the term spread, but not with the short or long rates themselves. Granger causality tests indicate that movements in short term interest rates and the spread cause movements in the returns series. However, decomposition of the forecast error variances from VAR models indicate that changes in these variables can only explain a small proportion of the overall variability of the returns, and that the effect has fully worked through after two months. The results suggest that these financial variables could potentially be used as leading indicators for real estate markets, with corresponding implications for return predictability.
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This paper examines the cyclical regularities of macroeconomic, financial and property market aggregates in relation to the property stock price cycle in the UK. The Hodrick Prescott filter is employed to fit a long-term trend to the raw data, and to derive the short-term cycles of each series. It is found that the cycles of consumer expenditure, total consumption per capita, the dividend yield and the long-term bond yield are moderately correlated, and mainly coincident, with the property price cycle. There is also evidence that the nominal and real Treasury Bill rates and the interest rate spread lead this cycle by one or two quarters, and therefore that these series can be considered leading indicators of property stock prices. This study recommends that macroeconomic and financial variables can provide useful information to explain and potentially to forecast movements of property-backed stock returns in the UK.
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This paper uses a recently developed nonlinear Granger causality test to determine whether linear orthogonalization really does remove general stock market influences on real estate returns to leave pure industry effects in the latter. The results suggest that there is no nonlinear relationship between the US equity-based property index returns and returns on a general stock market index, although there is evidence of nonlinear causality for the corresponding UK series.
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This paper employs a vector autoregressive model to investigate the impact of macroeconomic and financial variables on a UK real estate return series. The results indicate that unexpected inflation, and the interest rate term spread have explanatory powers for the property market. However, the most significant influence on the real estate series are the lagged values of the real estate series themselves. We conclude that identifying the factors that have determined UK property returns over the past twelve years remains a difficult task.
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In vitro studies found that inclusion of dried stinging nettle (Urtica dioica) at 100 mg/g dry matter (DM) increased the pH of a rumen fluid inoculated fermentation buffer by 30% and the effect was persistent for 7 days. Our objective was to evaluate the effects of adding stinging nettle haylage to a total mixed ration on feed intake, eating and rumination activity, rumen pH, milk yield, and milk composition of lactating dairy cows. Six lactating Holstein-Friesian cows were used in a replicated 3 × 3 Latin Square design experiment with 3 treatments and 3 week periods. Treatments were a control (C) high-starch (311 g/kg DM) total mixed ration diet and two treatment diets containing 50 (N5) and 100 (N10) g nettle haylage (DM/kg) as a replacement for ryegrass silage (Lolium perenne). There was an increase (linear, P < 0.010) in the proportion of large particles and a reduction in medium (linear, P = 0.045) and fine particles (linear, P = 0.026) in the diet offered with increasing nettle inclusion. A numerical decrease (linear, P = 0.106) in DM intake (DMI) was observed as nettle inclusion in the diet increased. Milk yield averaged 20.3 kg/day and was not affected by diet. There was a decrease (quadratic, P = 0.01) in the time animals spent ruminating as nettle inclusion in the diet increased, in spite of an increase in the number of boli produced daily for the N5 diet (quadratic, P = 0.031). Animals fed the N10 diet spent less time with a rumen pH below 5.5 (P < 0.05) than cows fed the N5 diet. Averaged over an 8.5 h sampling period, there were no changes in the concentration or proportions of acetate or propionate in the rumen, but feeding nettle haylage reduced the concentrations of n-butyrate (quadratic, P < 0.001), i-butyrate (linear, P < 0.009) and n-caproate (linear, P < 0.003). Milk and fat and protein corrected milk yield were not affected when nettles replaced ryegrass silage in the diet of lactating dairy cows, despite a numerical reduction in feed intake. Rumination activity was reduced by the addition of nettle haylage to the diet, which may reflect differences in fibre structure between the nettle haylage and ryegrass silage fed. Changes observed in rumen pH suggest potential benefits of feeding nettle haylage for reducing rumen acidosis. However, the extent to which these effects were due to the fermentability and structure of the nettle haylage compared to the ryegrass silage fed, or a bioactive component of the nettles, is not certain
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Businesses need property in order to generate turnover and profits. If real estate owners are to be able to provide properties and related services that are desirable, it is crucial that they understand tenants’ requirements and preferences. Changes in the way businesses operate might well lead to an overall reduction in space requirements in all sectors. Faced with reductions in demand, landlords will find themselves in an increasingly competitive marketplace for tenants. Of the array of strategies available to landlords, what strategies should they employ for maximum effect? This paper examines what United Kingdom tenants want from commercial property (retail, industrial and office). The first part provides an analysis of data from several hundred interviews with occupiers of commercial properties owned by some of the largest UK real estate investment companies. Results are presented for each of the asset classes separately. The second part compares the findings with previous research and discusses the strategic implications for landlords.
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Purpose – Price indices for commercial real estate markets are difficult to construct because assets are heterogeneous, they are spatially dispersed and they are infrequently traded. Appraisal-based indices are one response to these problems, but may understate volatility or fail to capture turning points in a timely manner. This paper estimates “transaction linked indices” for major European markets to see whether these offer a different perspective on market performance. The paper aims to discuss these issues. Design/methodology/approach – The assessed value method is used to construct the indices. This has been recently applied to commercial real estate datasets in the USA and UK. The underlying data comprise appraisals and sale prices for assets monitored by Investment Property Databank (IPD). The indices are compared to appraisal-based series for the countries concerned for Q4 2001 to Q4 2012. Findings – Transaction linked indices show stronger growth and sharper declines over the course of the cycle, but they do not notably lead their appraisal-based counterparts. They are typically two to four times more volatile. Research limitations/implications – Only country-level indicators can be constructed in many cases owing to low trading volumes in the period studied, and this same issue prevented sample selection bias from being analysed in depth. Originality/value – Discussion of the utility of transaction-based price indicators is extended to European commercial real estate markets. The indicators offer alternative estimates of real estate market volatility that may be useful in asset allocation and risk modelling, including in a regulatory context.
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A class identification algorithms is introduced for Gaussian process(GP)models.The fundamental approach is to propose a new kernel function which leads to a covariance matrix with low rank,a property that is consequently exploited for computational efficiency for both model parameter estimation and model predictions.The objective of either maximizing the marginal likelihood or the Kullback–Leibler (K–L) divergence between the estimated output probability density function(pdf)and the true pdf has been used as respective cost functions.For each cost function,an efficient coordinate descent algorithm is proposed to estimate the kernel parameters using a one dimensional derivative free search, and noise variance using a fast gradient descent algorithm. Numerical examples are included to demonstrate the effectiveness of the new identification approaches.
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Understanding the performance of banks is of the utmost importance due to the impact the sector may have on economic growth and financial stability. Residential mortgage loans constitute a large proportion of the portfolio of many banks and are one of the key assets in the determination of their performance. Using a dynamic panel model, we analyse the impact of residential mortgage loans on bank profitability and risk, based on a sample of 555 banks in the European Union (EU-15), over the period from 1995 to 2008. We find that an increase in residential mortgage loans seems to improve bank’s performance in terms of both profitability and credit risk in good market, pre-financial crisis, conditions. These findings may aid in explaining why banks rush to lend to property during booms because of the positive effect it has on performance. The results also show that credit risk and profitability are lower during the upturn in the residential property cycle.
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Flash floods pose a significant danger for life and property. Unfortunately, in arid and semiarid environment the runoff generation shows a complex non-linear behavior with a strong spatial and temporal non-uniformity. As a result, the predictions made by physically-based simulations in semiarid areas are subject to great uncertainty, and a failure in the predictive behavior of existing models is common. Thus better descriptions of physical processes at the watershed scale need to be incorporated into the hydrological model structures. For example, terrain relief has been systematically considered static in flood modelling at the watershed scale. Here, we show that the integrated effect of small distributed relief variations originated through concurrent hydrological processes within a storm event was significant on the watershed scale hydrograph. We model these observations by introducing dynamic formulations of two relief-related parameters at diverse scales: maximum depression storage, and roughness coefficient in channels. In the final (a posteriori) model structure these parameters are allowed to be both time-constant or time-varying. The case under study is a convective storm in a semiarid Mediterranean watershed with ephemeral channels and high agricultural pressures (the Rambla del Albujón watershed; 556 km 2 ), which showed a complex multi-peak response. First, to obtain quasi-sensible simulations in the (a priori) model with time-constant relief-related parameters, a spatially distributed parameterization was strictly required. Second, a generalized likelihood uncertainty estimation (GLUE) inference applied to the improved model structure, and conditioned to observed nested hydrographs, showed that accounting for dynamic relief-related parameters led to improved simulations. The discussion is finally broadened by considering the use of the calibrated model both to analyze the sensitivity of the watershed to storm motion and to attempt the flood forecasting of a stratiform event with highly different behavior.
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The influence of the size distribution of particles on the viscous property of an electrorheological fluid has been investigated by the molecular dynamic simulation method. The shear stress of the fluid is found to decrease with the increase of the variance sigma(2) of the Gaussian distribution of the particle size, and then reach a steady value when sigma is larger than 0.5. This phenomenon is attributed to the influence of the particle size distribution on the dynamic structural evolution in the fluid as well as the strength of the different chain-like structures formed by the particles.