Alain Coën

International portfolio choice in an overlapping generations model with transaction costs

This paper studies the implications for international portfolio diversification of a simple OLG model of the world economy with transaction costs. Our main result shows that the introduction of very small transaction costs is sufficient to reproduce the large home bias observed in the composition of portfolios.

Another Look at Asian REITs Performance after the Global Financial Crisis

The aim of this chapter is to revisit the performance of Asian REITs before and after the sub-prime crisis using risk-adjusted performance measures based on multifactor models. First, we use performance measures (including the Generalized Treynor Ratio) able to capture the variety of systematic risk sources related to real estate in Asia. Second, we implement unbiased estimators to correct for the econometric bias induced by errors-in-variables (EIV) in asset pricing models. With these different adjustments, we analyze the persistence and stability of performance measures before and after the crisis for a database of 206 Asian REITs covering nine countries across Asia-Pacific. Our results shed a new light on risk-adjusted performance measures of Asian REITs during a key period since the regime was introduced in the Asia-Pacific region.

The Evolution of Financial Analysts’ Forecasts for Asian REITs and Real Estate Companies

In this chapter, our aim is to analyze the accuracy and the quality of financial analysts’ forecast for Asian Pacific REITs and Asian Pacific real estate companies from 2001 to 2012. We consider the financial crisis of 2008 as a breakdown in the performance of financial analysts. Using IBES database for a very large sample of 12 Asian countries, we compare the accuracy of earnings forecasts at country level and sector level to shed a new light on Asian REITs and Asian real estate. Our results report a relevant evolution of financial analysts’ forecast for Asian Pacific REITs and real estate companies after the crisis.

International Listed Real Estate Returns and Errors-in-Variables: Evidence from the Global Financial Crisis

Using the Global Financial Crisis (GFC) as a breakdown, we revisit the risk and return characteristics of publicly traded real estate companies from 14 countries proxied by FTSE EPRA indices over the period 2000 to 2015 in presence of errors-in-variables. We extend the seminal work of Bond, Karolyi and Saunders (2003), and shed a new light on the relative performance of listed real estate before and after the GFC. First, we suggest the use of various asset pricing models including the Fama-French (2015) five-factor asset pricing model with global and country-level factors. Second, we implement unbiased estimators to correct for the econometric bias induced by errors-in-variables (EIV) in asset pricing models. Third, we deal with the impact of illiquidity (measured by serial correlation) on the risk properties of international securitized real estate returns. Our findings show that international listed real estate risk factors changed radically after the GFC, which has resulted in more homogeneous markets internationally and less diversification opportunities for US-based investors.

Financial Analysts’ Forecasts, Uncertainty and Abnormal Returns: Evidence from «Green» REITs

The aim of this study is to analyze and compare the abnormal earnings announcement returns of «green» and «non-green» U.S. REITs from 2010 to 2017. We focus on the impact of financial analysts’ forecast accuracy, market-level uncertainty, REIT-level uncertainty and synchronicity. First, we document the coverage, the accuracy and the bias of financial analysts’ earnings forecasts (ffo) on «green» and «non-green» REITs. Our results report that the level of accuracy and the level of optimism are statistically different for these two categories. Second, we observe that abnormal stock returns, abnormal trading volume and abnormal volatility may be related to «greenness» and synchronicity. Our results shed a new light on the link between the concept of «greenness» and the level of information on stock markets.

Did Security Analysts Overreact During the Global Financial Crisis? Canadian Evidence

Abstract Our main objective in this study is to revisit the seminal work of De Bondt and Thaler (1990), a quarter century later. Focusing on the global financial crisis in 2008, we analyze the evolution of financial analysts’ performance on Canadian stock markets from 2005 to 2014. We consider the quality and the accuracy of earnings forecasts to “investigate one possible source of rationality” during a major crisis on financial markets. Our results report contrasted results among industrial sectors and highlight the evolution of financial analysts’ forecasts before and after the crisis. Finally, we shed a new light on the identification of the “presumed smart money segment.”

Real Estate and Consumption Growth as Common Risk Factors in Asset Pricing Models

Using a linear multifactor pricing model, we study the influence of equity market, the consumption growth and the return on real estate wealth on asset returns. The real estate risk factor is proxied alternatively by the National Association of Real Estate Investment Trusts (NAREIT) index, unlevered NAREIT index and National Council of Real Estate Investment Fiduciaries property index. Estimates are based on CRSPs monthly decile portfolio returns from January 1972 to December 2013 (including the Vintage REIT era and the New REIT era). Generalized method of moment results show that the real estate factor is particularly useful to explain the cross‐sectional variation of returns in the last two decades generally associated with the so‐called real estate bubble.

Normalized Risk-Adjusted Performance Measures Revisited: The Performance of Funds of Hedge Funds Before and After the Crisis

This chapter revisits the performance of funds of hedge funds (FoHFs) after the global financial crisis using normalized risk-adjusted performance measures based on multifactor models. (i) We develop performance measures able to capture the variety of systematic risk sources. (ii) We deal with the impact of smoothing on the risk return properties of FoHFs using an adjustment technique for illiquidity. (iii) We implement unbiased estimators to correct for the econometric bias induced by errors-in-variables (EIVs) in asset pricing models. With these different adjustments, we analyze the persistence and stability of performance measures before and after the crisis for a database of funds of hedge funds. Our results clearly show that the normalized risk-adjusted performance measures corrected for smoothing effect and EIVs outperform the alternatives measures before and after the crisis.

The Impact of Cross-Border Mergers and Acquisitions on Financial Analysts’ Forecasts: Evidence from the Canadian Stock Market

The main objective of this chapter is to analyze the performance of financial analysts before and after cross-border mergers and acquisitions. We propose to focus on the evolution of financial analysts’ forecast (hereafter FAF) accuracy and FAF bias. We compare the pre-merger and post-merger forecast accuracy of consensus analysts’ forecasts two years after the merger on the Canadian stock market for the 1990–2004 period.

Integrated Volatility and UHF-GARCH Models: A Comparison Using High Frequency Financial Data

A very promising literature has been recently devoted to the modeling of ultra-high-frequency (UHF) data. The main problem encountered to measure volatility dynamics of high-frequency intra-daily data lies in the irregularity at which observations arrive. Engle and Russell (1998) have proposed a new class of point processes with dependent arrival rates: autoregressive conditional duration (ACD) point processes. Engle (2000) has generalized this approach and developed a Ultra-High-Frequency GARCH model. At the same time, Andersen and Bollerslev (1998) and Bollerslev and Wright (2001) have studied the volatility of UHF financial data by introducing the concept of integrated volatility. This integrated volatility is measured by the squared value of intra-daily returns. Our first aim in this paper is to develop an empirical application of ACD GARCH models in forecasting future volatilities. Then we propose another contribution in comparing the performances of ACD GARCH models with the integrated volatility. Therefore we propose a procedure to take into account the calendar effect or the time of day effect. We introduce an adjusted duration to calculate volatilities before comparing volatility forecasts. We show that the models induced by the two approaches lead to poor performances. Nevertheless, our results show that the integrated volatility method tends to outperform UHF-GARCH models.