The inflation hedging characteristics of US and UK investments: a multi-factor error correction approach

Historic analysis of the inflation hedging properties of stocks produced anomalous results, with equities often appearing to offer a perverse hedge against inflation. This has been attributed to the impact of real and monetary shocks to the economy, which influence both inflation and asset returns. It has been argued that real estate should provide a better hedge: however, empirical results have been mixed. This paper explores the relationship between commercial real estate returns (from both private and public markets) and economic, fiscal and monetary factors and inflation for US and UK markets. Comparative analysis of general equity and small capitalisation stock returns in both markets is carried out. Inflation is subdivided into expected and unexpected components using different estimation techniques. The analyses are undertaken using long-run error correction techniques. In the long-run, once real and monetary variables are included, asset returns are positively linked to anticipated inflation but not to inflation shocks. Adjustment processes are, however, gradual and not within period. Real estate returns, particularly direct market returns, exhibit characteristics that differ from equities.

Hedging private international real estate

The performance of an international real estate investment can be critically affected by currency fluctuations. While survey work suggests large international investors with multi-asset portfolios tend to hedge their overall currency exposure at portfolio level, smaller and specialist investors are more likely to hedge individual investments and face considerable specific risk. This presents particular problems in direct real estate investment due to the lengthy holding period. Prior research investigating the issue relies on ex post portfolio measure, understating the risk faced. This paper examines individual risk using a forward-looking simulation approach to model uncertain cashflow. The results suggest that a US investor can greatly reduce the downside currency risk inherent in UK real estate by using a swap structure – but at the expense of dampening upside potential.

Better cross hedges with composite hedging? Hedging equity portfolios using financial and commodity futures

Unless a direct hedge is available, cross hedging must be used. In such circumstances portfolio theory implies that a composite hedge (the use of two or more hedging instruments to hedge a single spot position) will be beneficial. The study and use of composite hedging has been neglected; possibly because it requires the estimation of two or more hedge ratios. This paper demonstrates a statistically significant increase in out-of-sample effectiveness from the composite hedging of the Amex Oil Index using S&P500 and New York Mercantile Exchange crude oil futures. This conclusion is robust to the technique used to estimate the hedge ratios, and to allowance for transactions costs, dividends and the maturity of the futures contracts.

Optimal hedging with higher moments

This study proposes a utility-based framework for the determination of optimal hedge ratios (OHRs) that can allow for the impact of higher moments on hedging decisions. We examine the entire hyperbolic absolute risk aversion family of utilities which include quadratic, logarithmic, power, and exponential utility functions. We find that for both moderate and large spot (commodity) exposures, the performance of out-of-sample hedges constructed allowing for nonzero higher moments is better than the performance of the simpler OLS hedge ratio. The picture is, however, not uniform throughout our seven spot commodities as there is one instance (cotton) for which the modeling of higher moments decreases welfare out-of-sample relative to the simpler OLS. We support our empirical findings by a theoretical analysis of optimal hedging decisions and we uncover a novel link between OHRs and the minimax hedge ratio, that is the ratio which minimizes the largest loss of the hedged position. © 2011 Wiley Periodicals, Inc. Jrl Fut Mark

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.

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.

The (de)merits of minimum-variance hedging: application to the crack spread

We study the empirical performance of the classical minimum-variance hedging strategy, comparing several econometric models for estimating hedge ratios of crude oil, gasoline and heating oil crack spreads. Given the great variability and large jumps in both spot and futures prices, considerable care is required when processing the relevant data and accounting for the costs of maintaining and re-balancing the hedge position. We find that the variance reduction produced by all models is statistically and economically indistinguishable from the one-for-one “naïve” hedge. However, minimum-variance hedging models, especially those based on GARCH, generate much greater margin and transaction costs than the naïve hedge. Therefore we encourage hedgers to use a naïve hedging strategy on the crack spread bundles now offered by the exchange; this strategy is the cheapest and easiest to implement. Our conclusion contradicts the majority of the existing literature, which favours the implementation of GARCH-based hedging strategies.

The cross-currency hedging performance of implied versus statistical forecasting models

This article examines the ability of several models to generate optimal hedge ratios. Statistical models employed include univariate and multivariate generalized autoregressive conditionally heteroscedastic (GARCH) models, and exponentially weighted and simple moving averages. The variances of the hedged portfolios derived using these hedge ratios are compared with those based on market expectations implied by the prices of traded options. One-month and three-month hedging horizons are considered for four currency pairs. Overall, it has been found that an exponentially weighted moving-average model leads to lower portfolio variances than any of the GARCH-based, implied or time-invariant approaches.

Racionalidade comunicativa e educação : um estudo sobre o pensamento de Jürgen Habermas enfatizando a formação da competência interativa como aprendizado da razão comunicacional

A presente dissertação tem como propósito, a partir do estudo e apropriação reflexiva da Teoria do Agir Comunicativo de Jürgen Habermas, identificar espaços alternativos no ambiente escolar através dos quais possamos implementar ações didático-pedagógicas e administrativas que oportunizem o aprendizado da razão comunicativa, bem como favoreçam o desenvolvimento de competências alicerçadas na interatividade. Para tanto, partimos de uma abordagem sobre a modernidade, enquanto contextualização geral, enfatizando os movimentos filosóficos através dos quais se criaram as condições que permitiram a formulação do paradigma da subjetividade. Visando desocultar a gênese da alienação nossa reflexão esteve atenta aos elementos que oportunizaram a transformação da razão emancipatória em razão instrumental, ou seja, os motivos circunstanciais que tornaram possível a geração de patologias e a obstrução dos canais da comunicação na sociedade capitalista ocidental. A racionalidade comunicativa, como resultado da reviravolta lingüística, representa uma formulação reflexiva e crítica da razão capaz de oferecer alternativas de ação que possibilitem o resgate, a renovação e a promoção da racionalidade na sua multiplicidade de formas e vozes. Constitui-se num novo paradigma através do qual torna-se viável a análise crítica das patologias sociais e escolares oriundas do processo de racionalização das relações sociais e produtivas, assim como das imagens religiosas e metafísicas do mundo. A racionalidade comunicativa, pelo fato de privilegiar a dialogicidade intersubjetivo-argumentativa, fecunda o mundo escolar com múltiplas possibilidades de ação calcadas no desenvolvimento de competências interativas via aprendizado da racionalidade.

Estudo comparativo da transformada Karhunen-Loève na compressão de imagens

A representação de funções através da utilização de bases (KERNEL) de representação tem sido fundamental no processamento digital de sinais. A Transformada KARHUNEN-LOÈVE (KLT), também conhecida como Transformada HOTELLING, permite a representação de funções utilizando funções-base formadas pelos autovetores da matriz de correlação do sinal considerado. Nesse aspecto essa transformada fornece uma base ótima, isto é, aquela que proporciona o menor valor de Erro Quadrático Médio entre o sinal reconstruído e o original, para um determinado número de coeficientes. A dificuldade na utilização da KLT está no tempo adicional para calcular os autovetores (base) da matriz de correlação, o que muitas vezes inviabiliza a sua utilização nas aplicações em tempo real. Em muitas aplicações a KLT é utilizada em conjunto com outras transformadas melhorando os resultados destas aplicações. Sendo considerada a transformada ótima no sentido do Erro Quadrático Médio, este trabalho apresenta um estudo da Transformada KARHUNEN-LOÈVE nas aplicações de compressão de imagens bidimensionais estáticas e em tons de cinza, realizando também a comparação desta técnica com outras técnicas (DCT e WAVELET) buscando avaliar os pontos fortes e fracos da utilização da KLT para este tipo de aplicação. Duas técnicas importantes para solucionar o problema de cálculo dos autovalores e autovetores da matriz de correlação (Método de JACOBI e Método QL) são também apresentadas neste trabalho. Os resultados são comparados utilizando a Razão Sinal/Ruído de Pico (PSNR), a Razão de Compressão (CR) e os tempos de processamento (em segundos) para geração dos arquivos compactados.

Regulação ótima sob agência comum e risco de corrupção

Mostramos que separar reguladores não benevolentes é a resposta institucional ótima quando os projetos regulados são grandes , i.e., apresentam benefício mar- ginal alto. Como separação impede que os reguladores se coordenem para se apro- priar de toda a renda informacional do agente quando sabem o tipo desse último, há um trade-o¤ entre poupança de renda informacional e e ciência alocativa, pois o jogo entre os reguladores induzido pela separação gera distorção em relação à alocação sob um único regulador. Quando a renda informacional em questão é grande, vale a pena a divisão de reguladores.