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This study uses parametric hazard models to investigate duration dependence in US stock market cycles over the January 1929 through December 1992 period. Market cycles are determined using the Beveridge‐Nelson (1981) approach to the decomposition of economic time series. The results show that both real and nominal cycles exhibit positive duration dependence. The implication of this finding is that actual prices revert to their permanent or trend level in a non‐random manner as the cyclical component dissipates over time. This process is consistent with mean reversion in price and suggests that predictable periodicity in market cycles may exist. Only limited evidence is obtained that discrete shifts or trends in mean cycle duration exist. The length of market cycles appears not to have changed over the 1929–92 period.

The purpose of this paper is to expand our understanding of processes governing commercial property cycles, and to provide tools, which enable identification of property cycles’ turning points’ location.

This paper is divided into three parts. The first looks at the demand-supply dynamics and the location of two characteristic cyclic points, the market bottom and the cycle commencement. In the second part a property relevant formula for entropy is derived, and its relation to the cycle overheated stage and the market peak is studied. In the third part, we discuss still another characteristic point of the cycle, which relates to the stage when developers elect to undertake new projects. This analysis is done by employing the chaos theory, and its relation to the cyclic evolution.

It is found that some markets cycle, while others fluctuate only. A clear method for distinguishing among these is provided. The bottom of a cycle may overlap or be time separated from the start of a subsequent cycle. Market peaks are characterised by a sharp decrease in financial component to entropy for top quality building grades. A cycling market is characterised by crossing of a distinct vacancy rate during the cycle progression.

The tools developed in the paper allow for clear characterisation of the market types and their cyclic behaviour. This in turn allows for timely characterisation of the market state and for short time-frame forecasting. The depth of a cycle may be calculated and the subsequent correction level estimated.

The paper utilises cross-field approach by taking methods from both physics and mathematics and applying them to property markets. It breaks new ground both in property research and in applied mathematics by showing how the current frontier in pure mathematics may be applied to property.

This study examines the durations of US stock market cycle expansions and contractions for the presence of seasonality. Specifically, it is determined whether the distributional characteristics (i.e., location and dispersion) of the durations of market expansions and contractions are dependent on the time of the year the market phase begins or ends. The duration data are obtained from a stock market chronology of monthly peak and trough dates for the period May 1835 through July 1998 and nonparametric rank‐based tests are used to test for the presence of seasonality. In order to provide some evidence on robustness with respect to the sample data, results are obtained for the entire sample period as well as for various sub‐periods. When the data are aggregated on a quarterly basis, the evidence suggests that seasonal structures are present in stock market cycle durations. These seasonals are related primarily to shifts in location over the course of the year and to when a market expansion or contraction begins. However, when the duration data are aggregated on a bi‐annual basis, support for seasonality is much more limited.

This paper aims to review property cycle theory and the relevance of the larger body of knowledge about cycles with reference to the housing market. It also aims to highlight the lack of research into property cycles in the residential sector on a suburb or smaller region basis, as well as the potential for increased knowledge about cycles to assist to avoid housing stress.

The paper conducts a literature review of previous cycle research and encourages the use of cycle theory. It discusses the established body of knowledge about business cycles and the office market sector, as well as investigating levels of housing affordability and how detailed knowledge about property cycles can assist to decrease housing affordability in residential areas, which will eventually experience a downturn.

It is argued that an increased level of certainty about cycle behaviour in particular suburbs will give households a higher level of confidence when considering whether and when to enter the market. Property cycle research has the potential to assist low‐income homeowners to better understand the characteristics of cycles and associated risks in each residential.

This is a conceptual paper and has conducted a review of cycle research and housing affordability in certain countries. Some areas or countries may be affected to varying degrees by property cycles and levels of housing affordability.

In extended periods of high volatility it is argued that a better understanding of housing cycles will allow more homeowners to avoid negative equity and the stress associated with repossessions. Property cycles are unavoidable although there is typically relatively little information available in the open market about the timing and amplitude of cycles in individual areas.

This paper is unique as it highlights the potential for property cycles to be used to avoid housing stress in the residential market. Traditionally cycle research is used to increase returns and avoid downturns in the office and/or business sectors.

This research aims to investigate whether and to what extent the co-movements of cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles are linked across G7 from February 1990 to June 2014.

The empirical approaches include correlation analysis on Hodrick–Prescott (HP) cycles, HP cycle return spillovers effects using Diebold and Yilmaz’s (2012) spillover index methodology, as well as Croux et al.’s (2001) dynamic correlation and cohesion methodology.

There are fairly strong cycle-return spillover effects between the cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles. The interactions among the cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles in G7 are less positively pronounced or exhibit counter-cyclical behavior at the traditional business cycle (medium-term) frequency band when “pure” stock market cycles are considered.

The research is subject to the usual limitations concerning empirical research.

This study finds that real estate is an important factor in influencing the degree and behavior of the relationship between cross-country business cycles and cross-country stock market cycles in G7. It provides important empirical insights for portfolio investors to understand and forecast the differential benefits and pitfalls of portfolio diversification in the long-, medium- and short-cycle horizons, as well as for research studying the linkages between the real economy and financial sectors.

In adding to the existing body of knowledge concerning economic globalization and financial market interdependence, this study evaluates the linkages between business cycles, stock market cycles and public real estate market cycles cross G7 and adds to the academic real estate literature. Because public real estate market is a subset of stock market, our approach is to use an original stock market index, as well as a “pure” stock market index (with the influence of real estate market removed) to offer additional empirical insights from two key complementary perspectives.

This chapter sheds new light on the linkages between stock market fluctuations and business cycles in Asia. It shows that at cyclical frequencies stock markets lead business cycles by six months on average. China, Korea, and Taiwan constitute exceptions, as their real and stock market cycles are contemporaneously synchronized. The low level of maturity of these markets offers a potential explanation of this outcome. Furthermore, we find that the linkage also holds during phases of cyclical upswing and downturn, with the exception of China, where the financial market lags behind industrial production during expansions. Finally, for most of the countries (except Thailand and Malaysia), the linkage is also robust to the presence of financial crises.

The purpose of this paper is to provide a dating system for the Italian residential real estate market from 1927 to 2019 and investigate its interaction with credit and business cycles.

To detect the local turning point of the Italian residential real estate market, the authors apply the honeycomb cycle developed by Janssen et al. (1994) based on the joint analysis of house prices and the number of transactions. To this end, the authors use a unique historical reconstruction of house price levels by Baffigi and Piselli (2019) in addition to data on transactions.

This study confirms the validity of the honeycomb model for the last four decades of the Italian housing market. In addition, the results show that the severe downsizing of the housing market is largely associated with business and credit contraction, certainly contributing to exacerbating the severity of the recession. Finally, preliminary evidence suggests that whenever a price bubble occurs, it is coincident with the start of phase 2 of the honeycomb cycle.

To the best of the authors’ knowledge, this is the first time that the honeycomb approach has been tested over such a long historical period and compared to the cyclic features of financial and real aggregates. In addition, even if the honeycomb cycle is not a model for detecting booms and busts in the housing market, the preliminary evidence might suggest a role for volume/transactions in detecting housing market bubbles.

This study investigates whether cyclical turning points in the U.S. and U.K. stock markets are unevenly distributed over the year, that is, whether they are more likely to occur during certain months of the year. In examining this form of periodic seasonality, a Markov switching‐model is applied to U.S. and U.K. stock market chronologies of monthly peak and trough dates for the periods May 1835 through March 2000 and May 1836 through September 2000, respectively. In order to provide some evidence on robustness with respect to the sample data, results are obtained for the entire sample periods as well as for various sub‐. For both markets, the evidence indicates that while the probability of moving from an expansion to a contraction does not depend on the month of the year, the probability of switching from a contraction is greater for some months. Additionally, the durations of contractions, but not expansions, are dependent on the month of the year in which they begin.

This paper aims to investigate Chinese bull and bear markets. The Chinese stock market has experienced a long period of bear cycle from early 2000 until 2006, and then it fluctuated greatly until 2010. However, the cyclical behaviour of stock markets during this period is less well established. This paper aims to answer the question why the Chinese stock market experienced a long duration of bear market and what factors would have impacted this cyclical behaviour.

By comparing the intervals of bull and bear markets between stocks and indices based on a Markov switching model, this paper examines whether different industries or A- and B-share markets could lead to different stock market cyclical behaviour and whether firm size can determine the relationship between the firm stock cycles on the market cycles.

This paper finds a high degree of overlapping of bear cycles between stocks and indices and a high level of overlapping between the bear market and a fraction of stock with increasing stock prices. This leads to the conclusion that the stock performance and trading behaviour are widely diversified. Furthermore, the paper finds that the same industry may have different overlapping intervals of bull or bear cycles in the Shanghai and Shenzhen stock markets. Firms with different sizes could have different overlapping intervals with bull or bear cycles.

This paper fills the literature gap by establishing the cyclical behaviour of stock markets.

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.