Purpose -The purpose of this paper is to dissect the dynamic linkages between foreign equity flows, exchange rates and equity returns in the Philippines. Design/methodology/approach -Using a parsimonious SVARX-GARCH model and unique daily equity flow data, this research models the relationship between net equity flows, conditional variance of stock returns and conditional variance of exchange rates. Findings -The authors find several noteworthy results, which are unique to this study and several results that confirm existing literature. Much of existing literature on foreign equity flows into emerging economies find that foreign equity investors are trend chasers and equity flows are auto correlated. The authors confirm these finding in the Philippines and document two new and important findings. First, it was found that unexpected increases in foreign equity flows to the Philippines increases the conditional volatility of the Filipino stock market significantly over the next two weeks of trading. The second major finding is that unexpected shocks to foreign equity flows sharply increases the conditional variance of the USD/PHP exchange rate over the next two to three weeks of trading. Practical implications -Taken together, the results indicate that foreign equity investment, while providing many benefits for small open economies such as the Philippines, does in the short run increase the conditional variance of both the equity market and exchange rates. Policy makers must weigh the benefits of increased risk sharing and the potential for lower costs of capital with the short-run potential for increase swings in asset prices. Originality/value -This paper is one of the only studies of its kind to test the impact of foreign equity flows on the conditional volatility of returns and exchange rates.

The study finds evidence in favor of Evans (1991) definition of periodically collapsing speculative bubbles in the Indian real estate market when the market is tested for a bubble by examining data from May 1, 2009, to May 30, 2012. Using consistent momentum threshold auto regressive (MTAR) model developed by Enders and Siklos (2001) with Chans (1993) methodology, this study finds evidence of co-integration as well as asymmetric adjustment toward long-run equilibrium, which is evidence of a periodically collapsing positive speculative bubble. However, except for the residuals-augmented DickeyFuller (RADF) test, none of the conventional tests such as the augmented DickeyFuller and the PhillipsPerron tests find evidence of a bubble.

Purpose – This paper aims to examine the risk premium for investors in a changing information environment in the Taiwan, New York and London real estate markets from March 2006 to November 2014. This study attempts to quantify behavioral expectations regarding (or motivation for) investment in the Taiwanese real estate in a changing information environment. Design/methodology/approach – This paper uses the rolling generalised autoregressive conditionally heteroskedastic in mean (GARCH-M) methodology which fixes the problem of conventional GARCH-M methodology. Findings – Empirical evidence suggests that the time-varying risk premium changed for the Taiwan real estate market with a new information set. The risk premium changed from 1.305 per cent per month to −7.232 per cent per month. The study also found persistent volatility shocks from March 2006 to November 2014. No such evidence was found for the New York and London real estate markets. Overall, this study finds evidence of a time-varying risk premium, partly explainable by governmental policies and partly unexplainable. Research limitations/implications – The use of the index of Standard and Poor’s Taiwan Real Estate Investment Trusts to study the Taiwan real estate industry may have aggregation effects in result. Practical implications – The present study will provide guidance to investors as well as policymakers regarding the Taiwan real estate market. Originality/value – This study uses the rolling GARCH-M model, which is a first for the Taiwan real estate market.

Purpose This paper aims to examine the integration of housing markets in Canada by examining housing price data (1999–2016) of six metropolitan areas in different provinces, namely, Calgary, Vancouver, Winnipeg, Toronto, Montreal and Halifax. The authors test for cointegration, driver cities of long-run relationships, long-run Granger causality and instantaneous causality in light of the global financial crisis (GFC) (2007–2008). Design/methodology/approach The authors use Johansen’s system cointegration approach with structural breaks. Moving average representation is used for common stochastic trend(s) analysis. Finally, the authors apply vector error correction model-based Granger causality and instantaneous causality. Findings Cities’ housing prices are in long-run equilibrium. Post-crisis Canadian housing markets became more integrated. The Calgary, Vancouver, Toronto and Montreal markets drive the Canadian housing market, leading all cities toward long-run equilibrium. Strong long-run Granger causality exists, but the authors observe no instantaneous causality. Price information takes time to disseminate, and long-run price adjustments play a significant role in causation. Practical implications The findings of cointegration increasing after the GFC and strong lead–lag can be used by investors to arbitrage and optimize portfolios. This can also help national and local policymakers in mitigating risk. Incorporating these findings can lead to better price forecasting. Originality/value This study presents many novelties for the Canadian housing market: it is the first to use repeat-sales regional pricing indices to test long-run behaviors, conduct common stochastic trend analyzes and present causality relations.

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