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The risk/return trade‐off is a perennial problem of portfolio managers. Portfolio diversification strategies should be such that investments are held in markets that are well‐insulated from each other so that the effects of market fluctuations in one market are not transferred to the other. Conventional wisdom suggests that a well‐diversified portfolio should contain assets spread across different markets, such as holdings of equities, bonds and property, while an increasingly accepted notion is that portfolios should also be diversified internationally. Research over the last few years has, if not questioned this conventional wisdom, at least sought confirmation. The current paper continues this inquiry. Looks, in particular, at the twin issues of whether property should form part of a well‐diversified domestic portfolio, and whether property should form part of a portfolio that is diversified internationally. Using the relatively new technique of cointegration analysis, provides evidence from the USA, the UK and Australia that domestic real estate and equity markets are segmented, and also provides evidence that securitized property markets are segmented internationally ‐ implying that there are risk‐reduction benefits to be gained through diversification in both instances.

Over the last decade or so there has been an increased interest in combining the forecasts from different models. Pooling the forecast outcomes from different models has been shown to improve out‐of‐sample forecast test statistics beyond any of the individual component techniques. The discussion and practice of forecast combination has revolved around the pooling of results from individual forecasting methodologies. A different approach to forecast combination is followed in this paper. A method is used in which negatively correlated forecasts are combined to see if this offers improved out‐of‐sample forecasting performance in property markets. This is compared with the outcome from both the original model and with benchmark naïve forecasts over three 12‐month out‐of‐sample periods. The study will look at securitised property in three international property markets – the USA, the UK and Australia.

Understanding cyclical activity is an important component of efficient portfolio management. Property appraisal models that do not explicitly take into account cyclical fluctuations may produce unrealistic valuation estimates resulting in property assets being incorrectly added to or removed from the general investment portfolio. In this paper we use conventional spectral analysis techniques to examine property and financial assets for evidence of cycles and co‐cycles. One finding is that the very pronounced cyclical patterns that appear in direct real estate markets and the economy as a whole are very much less obvious once they have filtered through to securitised property markets and financial assets markets.

Conventionally, between 5 and 20 per cent of a portfolio is invested in real estate. Whether this is prudent diversification or not depends on whether property and other financial assets markets are integrated. The notion of market integration/segmentation across the economy is of central importance. Disturbances in market fundamentals in a given market generate movements of capital into and out of the affected market. If various markets are well integrated, then it is expected that a high degree of asset substitution will take place, such substitution having a significant impact on price fluctuations in the relevant market. On the other hand, if markets are not integrated, then this has significant implications for portfolio investment where managers seek to develop well‐diversified portfolios as a means of risk reduction. Recent literature has recognized the need to understand and measure the degree of market integration, and research has focused on techniques to do this. Studies have attempted to measure the degree of integration in money and bond markets, real assets markets and among international real estate investment trusts. Uses cointegration techniques to examine the extent to which physical real estate markets and financial assets markets are integrated. Tends to support the notion of market segmentation and, by default, supports the conventional wisdom of diversification between real estate and other financial assets.

Evidence of mean reversion in U.S. stock prices during the post‐World War II era is mixed. I find that using the standard portfolio formation method to construct size‐sorted portfolios is inadequate for detecting mean reversion. Using alternative portfolio formation methods and additional cross‐sectional power gained from size‐sorted portfolios during the period 1963 to 1998, I find strong evidence of mean reversion in portfolio prices. My findings imply a significantly positive speed of reversion with a half‐life of approximately three and a half years. Parametric contrarian investment strategies that exploit mean reversion outperform buy‐and‐hold and standard contrarian strategies.

House price-to-rent (P-t-R) ratios are among the most widely used measures of housing market conditions. Given the theoretical and apparent bidirectional, causal relationships and imbalances between the housing market, broader economy and financial market determinants, it is important to understand the relationship between macro- and micro-economic characteristics in relation to the P-t-R ratio to enhance the understanding of housing market dynamics. This paper studies the joint dynamics and persistence of house prices and rents and examines the temporal interactions of the P-t-R ratio and economic and financial determinants.

The authors examine the lead–lag relationships between the P-t-R ratios and a spectrum of macroeconomic variables using cointegration and causality methods, initially at the aggregate position and also across housing types within the Northern Ireland housing market to establish whether there are subtle differences in how various housing segments react to changes in economic activity and market fundamentals.

The findings reveal price switching dynamics and some very distinct long- and short-run relationships between macroeconomic and financial indicators and the P-t-R ratios across the various housing segments. The results exhibit monetary supply, foreign exchange markets and the stock market to be important drivers of the P-t-R ratio, with P-t-R movements seemingly tied, or are in tandem, with the overall economy, particularly with the construction sector.

The study shows that the P-t-R ratio can be used as an early measure for establishing the effects of macroprudential policy changes and how these may manifest across housing tiers and quality, which can further act as a signal for preventing or at least mitigating future irrational price cyclicity. These insights serve to inform housing and economic policy and macroprudential policy design, principally within lending policy and the effect of regulatory interventions and further enhance the understanding of the P-t-R ratio on housing market structure and dynamics.

This study is the first in the housing literature that examines the causal relationships between the P-t-R ratio and macroeconomic activity at the sub-market level. It investigates whether and how money supply, inflation, foreign exchange markets, general economic productivity and other important macroeconomic factors interact with the pricing of different property types over time.

This paper aims to explore principal drivers affecting prices in the Australian housing market, aiming to detect the presence of housing bubbles within it. The data set analyzed covers the past two decades, thereby including the period of the most recent housing boom between 2012 and 2015.

The paper describes the application of combined enhanced rigorous econometric frameworks, such as ordinary least square (OLS), Granger causality and the Vector Error Correction Model (VECM) framework, to provide an in-depth understanding of house price dynamics and bubbles in Australia.

The empirical results presented reveal that Australian house prices are driven primarily by four key factors: mortgage interest rates, consumer sentiment, the Australian S&P/ASX 200 stock market index and unemployment rates. It finds that these four key drivers have long-term equilibrium in relation to house prices, and any short-term disequilibrium always self-corrects over the long term because of economic forces. The existence of long-term equilibrium in the housing market suggests it is unlikely to be in a bubble (Diba and Grossman, 1988; Flood and Hodrick, 1986).

The foremost contribution of this paper is that it is the first rigorous study of housing bubbles in Australia at the national level. Additionally, the data set renders the study of particular interest because it incorporates an analysis of the most recent housing boom (2012-2015). The policy implications from the study arise from the discussion of how best to balance monetary policy, fiscal policy and macroeconomic policy to optimize the steady and stable growth of the Australian housing market, and from its reconsideration of affordability schemes and related policies designed to incentivize construction and the involvement of complementary industries associated with property.

The purpose of this paper is to assess the duration of the UK commercial property cycles, their volatility and persistence to gauge future market direction.

The study employs a novel approach to dissect cycles in a form of a three-step algorithm. First, the Hodrick-Prescott de-trends the selected variables. Second, volatility (measured by the variance) screens periods of atypical fluctuations in the series. Finally, the series is regressed against its past values to assess the level of persistence. The sequential steps screen the length of the cycles in UK commercial property market to facilitate interpretation.

The estimates suggest that UK commercial property market follows an eight-year cycle. Combined modelling results indicate that the current market trend is likely to change over the coming year. The modelling suggests increasing probability of a market correction in late 2016/early 2017.

This updated appreciation of the UK commercial property cycle duration allows for better market timing and investment decision making.

The paper adds additional evidence on the contested issue of UK commercial property cycle duration.

Real estate and stocks are two major asset types in an investor’s portfolio. Therefore, this paper aims to investigate the relationship between these two markets to provide a valuable insight into the process of portfolio optimization and security selection.

This study examines the long-run relationship between residential real estate prices and stock market index in the case of Germany for the period of 2005-2017 by applying time series econometrics techniques. To this aim, this study uses Hedonic House Price Index as a proxy for real estate prices and DAX30 as a proxy for stock prices. Moreover, three additional variables, namely, consumer confidence, credit availability and supply of mortgage loans, are incorporated as control variables to assess the robustness of the results.

Obtained empirical results indicate a long-run relationship between stock prices and real estate prices which suggests that in long-run, there is no diversification benefit from allocating stock and real estate assets in a portfolio. This finding is especially important for long-term investors such as pension funds.

To the authors’ best knowledge, this is the first study that empirically investigates the relationship between the real estate market and stock prices using the Hedonic Price Index for the case of Germany.

The study seeks to find the effect of financial leverage on the firm performance of non-financial companies listed in the Tokyo stock market.

The study collected data from 263 companies in the automobile and industrial producer sectors listed on the Tokyo stock exchange between 2001 and 2021. The generalized method of moments was used to estimate the effect of leverage on financial performance due to its ability to overcome the problems of endogeneity and autocorrelation.

The study found that the equity multiplier has a positive and statistically significant effect on return on assets (ROA), return on equity (ROE) and earning per share (EPS). The study discovered that the interest coverage ratio has a positive and statistically significant effect on ROA, ROE, EPS and Tobin’s Q. The results revealed that the degree of financial leverage and debt to earnings before interest, taxes, depreciation and amortization (EBITDA) have a negative and statistically significant effect on ROE, EPS and Tobin’s Q. The study also found that the capitalization ratios of the firms have a negative and statistically significant effect on ROA, ROE, EPS and Tobin’s Q.

The use of debt financing, which presents financial leverage, indicates that the companies can make enough earnings to pay off the interest and principal (debt service obligations), which were shown by the interest coverage ratio, as well as to pay all the long-term fixed expenses, which were shown by the fixed charge coverage ratio. Interest and fixed charge coverage have a positive statistically significant effect on the financial performance of automobile and industrial producer companies.

The study focused on the effect of financial leverage on financial performance by relying on pecking and trade-off theories to contribute to the existing body of literature in finance.