Search results

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 examines the impact of real exchange rates and asymmetric real exchange rates on real stock prices in Malaysia, the Philippines, Singapore, Korea, Japan, the United Kingdom (UK), Germany, Hong Kong and Indonesia.

This study uses the asymmetric autoregressive distributed lag (ARDL) approach and non-linear autoregressive distributed lag (NARDL) approach.

The asymmetric ARDL approach shows more economic variables are found to be statistically significant than the ARDL approach. The asymmetric real exchange rate is mostly found to have a significant impact on the real stock price. Moreover, real output and real interest rates are found to have a significant impact on the real stock price. The Asian financial crisis (1997–1998) and the global financial crisis (2008–2009) are found to have a significant impact on the real stock price in some economies.

Economic variables are important in the determination of stock prices.

It is important to examine the impact of asymmetric real exchange rate on the real stock price as the depreciation of real exchange rate could have different impacts than the appreciation of real exchange rate on the real stock price. The previous studies in the literature mostly found the significant impact of nominal exchange rate on the nominal stock price.

The purpose of this study was to investigate the dynamic interactive link between housing prices, stock market price and effective exchange rate in the Iranian economy for a monthly period from April, 2004, to March, 2019. In addition, for a more accurate analysis, three control and determinates variables including real interest rate, real GDP and FDI have been added to the base model.

For this purpose, we will consider this issue by developing the study of Lean & Smyth (2014), Ali & Zaman (2017) and Coskun et al (2017) in the framework of ADRL and NARDL models. Also, this study analyzed the asymmetric/non-linear impact of stock market indexes and effective exchange rate on Iran’s housing inflation. Asymmetries imply to both positive and negative changes in the variables.

The results obtained from the ADRL and NARDL models suggest that the existence of cointegration relationship between housing market price and its determinants. From linear model, we found that the exchange rate and stock market price have a positive effect on the real estate inflation in the short run; this relationship is also confirmed in the long run. Other empirical results indicate that the GDP stimulates housing price in both long and short run cases, while FDI and real interest rate have an opposite effect. In addition, the results provided by the asymmetric model lead to the rejection of the null hypothesis of no co-integration between the variables. In addition, we found that the effect of stock price in the short and long term are asymmetric and there also is an asymmetric long-run effect of real exchange rate on the real estate price.

Finally, to analyze the sensitivity, we entered two explanatory variables of inflation and money supply to the baseline equation. The finding represented that in both linear and nonlinear framework, a positive correlation between these two variables with housing prices have been proved.

This paper aims to examine the effect of both inflation rate and interest rate on stock prices using quarterly data on non-financial firms listed in DJIA30 and NASDAQ100 for the period 1999-2016. The stock duration model is used to measure the sensitivity in variations in inflation rates and interest rates on stock prices.

The authors use standard statistical tools that include Johansen cointegration test, linearity, normality tests, cointegration regression, Granger causality and vector error correction model.

The results of panel Johansen cointegration analysis show that cointegration exists between the stock prices, the changes in stock prices due to inflation rates and the changes in stock prices due to real interest rates. The results of cointegration regression show that inflation rates are negatively associated with stock prices, the real interest rates and stock prices are positively associated, changes in real interest rates and inflation rates Granger cause significant changes in stock prices, significant speed of adjustment to long run equilibrium between observed stock prices and real interest rates and significant speed of adjustment to long run equilibrium between changes in stock prices due to real interest rates and changes in inflation rates.

This paper contributes to the empirical literature in three ways. The paper examines the effects of inflation and interest rates on stock prices differently from other related studies by separating inflation from real interest rates. The paper examines the causality between stock prices, interest and inflation rates. This paper offers significant updated validity to extended literature that a negative association exists between stock prices and inflation rates. This validity can be considered as an existence a theory of stock prices, inflation rates and interest rates.

Understanding the pricing of real estate equities is a central objective of real estate research. This paper aims to investigate the impact of liquidity on European real estate equity returns, after accounting for well-documented systematic risk factors.

Based on risk factors derived from general equity data, the authors extend the Fama-French time-series regression approach by a liquidity factor, using a pan-European sample of 272 real estate equities.

The empirical results indicate that liquidity is a significant pricing factor in real estate stock returns, even after controlling for market, size and book-to-market factors. In addition, the authors detect that real estate stock returns load predominantly positively on the liquidity risk factor, suggesting that real estate equities tend to behave like illiquid common equities. These findings are underpinned by a series of robustness checks. Running a comparative analysis with alternative factor models, the authors further demonstrate that the liquidity-augmented asset-pricing model is most appropriate for explaining European real estate stock returns.

The inclusion of sentiment and downside risk factors could provide further insights into real estate asset pricing in European capital markets.

This is the first study to examine the role of liquidity as a systematic risk factor in a pan-European setting.

The purpose of this paper is to re‐examine the relationship between real investment and stock prices for the USA for 1960‐2005 in view of distinct economic regimes during the 40‐year period.

The paper employs simple models of investment, checks for cointegration, and applies the value at risk (VAR) methodology.

First, it was found that during the 1960‐1990 period investment and the stock market exhibited a good relationship and shared a common stochastic trend. Second, during the 1990‐2005 period this relationship broke down. Finally, extending the model to include the long‐term interest rate did not produce significant impacts on or feedbacks from and to either variable. It is concluded that the 1990‐2005 period has been distinct from the previous periods in that the stock market did not always abide by the fundamentals such as interest rates and/or investment expenditures. It is thus concluded that the high stock market growth rates of the 1990s have adversely impacted real investment expenditures.

Lack of influence of the real long‐term interest rate on either the investment of the stock price equations for the 1990‐2005 period. This implies that both investment and the stock market did not “take into account” a fundamental variable, the discount rate, instead they had a run on their own (especially the stock market).

The value of the paper is in showing that interest rates and investment expenditures do not always move as economic theory predicts or that economic fundamentals do not always rule.

I survey applications of Markov switching models to the asset pricing and portfolio choice literatures. In particular, I discuss the potential that Markov switching models have to fit financial time series and at the same time provide powerful tools to test hypotheses formulated in the light of financial theories, and to generate positive economic value, as measured by risk-adjusted performances, in dynamic asset allocation applications. The chapter also reviews the role of Markov switching dynamics in modern asset pricing models in which the no-arbitrage principle is used to characterize the properties of the fundamental pricing measure in the presence of regimes.

Are share markets too volatile? While it is difficult to ignore share market volatility it is important to determine whether volatility is excessive. This paper replicates the Shiller (1981) test as well as applying standard time series analysis to annual Australian stock market data for the period 1883 to 1999. While Shiller’s test suggests the possibility of excess volatility, time series analysis identifies a long‐run relationship between share market value and dividends, consistent with the share market reverting to its fundamental discounted cash flow value over time.

The purpose of this study is to investigate the interactive relationships between oil price shocks and the Nigeria stock market.

The paper applied the multivariate vector auto‐regression that employed the generalized impulse response function and the forecast variance decomposition error.

Empirical evidence reveals that stock market returns exhibit insignificant positive response to oil price shocks but reverts to negative effects after a period of time depending on the nature of the oil price shocks. The results are similar even with the inclusion of other variables. Also, the asymmetric effect of oil price shocks on the Nigerian stock returns indices is not supported by statistical evidences.

This is the first study to examine the dynamic linkages between stock market behaviour and oil price shocks in Nigeria.

In this paper, we examine dynamic relationships among three housing market variables and a stock market index in a multivariate vector autoregressive error correction (VAREC) model. It is first found that, in the USA, sales and the median sales price of the existing single‐family homes and the 30‐year mortgage rate have unit roots, while the New York Stock Exchange (NYSE) value‐weighted portfolio returns appear random. Moreover, it is found that not only are three real estate variables cointegrated with one another but that they are also cointegrated with the stock index returns. After controlling for the unit root problem and cointegration, a multivariate VAREC model is further developed to examine dynamic relationships among the four variables using Johansen’s approach. It is found that the price, mortgage rate, and stock returns affect sales. It is found that the mortgage rate and stock returns affect the price. The 30‐year mortgage rate is affected by sales and the stock returns. Except for the mortgage rate which is negatively correlated with the stock returns, significant evidence is not found that sales and the median sales price affect the stock returns directly.