Momentum or contrarian investment strategies: Evidence from Dutch institutional investors

Haan, Leo de; Kakes, Jan

doi:10.1016/j.jbankfin.2011.01.027

Cited by 68 publications

(24 citation statements)

References 14 publications

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“…12 The equity return differential is calculated as the difference between the MSCI index local currency returns of the foreign country and the United States, where returns are calculated using log differences of the end-of-month index values. 13 Positive monthly excess equity returns imply that foreign equities outperform U.S. equities.…”

Section: Datamentioning

confidence: 99%

“…Empirical work has mostly found that capital flows related to equity purchases, rather than bond purchases, are an important determinant of exchange rates (see for example Gyntelberg et al (2015)). 12 The respective tickers are provided in Table 3 in Appendix C. 13 End-of-month is defined as the last day of a month for which data is available. Second, the depreciation of the USD against emerging market currencies during the Asian crisis, the global financial crisis, and the euro area sovereign debt crisis is visible.…”

Section: Datamentioning

confidence: 99%

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Portfolio Rebalancing in Times of Stress

Fischer

Greminger

Grisse

et al. 2017

gwp

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This paper investigates time variation in the dynamics of international portfolio equity flows. We extend the empirical model of Hau and Rey (2004) by embedding a two-state Markov regime-switching model into the structural VAR. The model is estimated using monthly data, 1995-2015, on equity returns, exchange rate returns and equity flows between the United States and advanced and emerging economies. We find that the data are consistent with portfolio rebalancing. The estimated states match periods of low and high financial stress. Our main result is that for equity flows between the United States and emerging markets, the rebalancing dynamics differ between episodes of high and low levels of financial stress. A switch from the low to the high-stress regime is associated with capital outflows from emerging markets. Once in the high stress regime, the response of capital flows to exchange rate shocks is smaller than in normal (low stress) periods.

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Section: Datamentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Portfolio Rebalancing in Times of Stress

Fischer

Greminger

Grisse

et al. 2017

gwp

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“…Then, the results show how an opposite strategy may lead to improved results. There is a large body of literature on contrarian investment strategies (see, for instance, De Bondt and Thaler, 2012;Chan, 1988;De Haan and Kakes, 2011;Yao, 2012, among others), showing the performance of contrarian investors, defined as those that buy past losers and sell past winners. Our results support the evidence of a contrarian effect in the mutual funds for the sample period analyzed.…”

Section: On the Links Between Partial Frontiers And Persistence Analymentioning

confidence: 99%

On the informativeness of persistence for evaluating mutual fund performance using partial frontiers

Matallín‐Sáez

Soler‐Domínguez

Tortosa‐Ausina

2014

Omega

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The last few years have witnessed a rapid evolution in the literature evaluating mutual fund performance using frontier techniques. The instruments applied, mostly DEA (Data Envelopment Analysis) and, to a lesser extent, FDH (Free Disposal Hull), are able to encompass several dimensions of performance, but they also have some disadvantages that might be preventing a wider acceptance. The recently developed order-m and order-α partial frontiers overcome some of the disadvantages (they are robust with respect to extreme values and noise, and do not suffer from the well-known curse of dimensionality) while keeping the main virtues of DEA and FDH (they are fully-nonparametric). In this article we apply not only the non-convex counterpart of DEA (FDH) but also order-m and order-α partial frontiers to a sample of US mutual funds. The results obtained for both order-m and order-α are useful, since a full ranking of the mutual funds' performance can be obtained. We merge these methods with the literature on mutual fund performance persistence. By combining the two literatures we derive an algorithm which establishes how the choice of m and α parameters intrinsic to order-m and order-α (respectively) relate to the existence of performance persistence and the contrarian effect.

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“…While such positive-feedback trading is understandable from a microprudential perspective, it can lead to procyclicality and to booms and busts in financial markets. Using quarterly data over the period 1999-2005, De Haan and Kakes (2011 find that Dutch pension funds and insurance firms are, on average, negative-feedback traders. Other than De Haan and Kakes (2011), who use survey data that are collected for statistical purposes (balance-of-payments statistics), this study uses regulatory data with an annual frequency.…”

Section: Equity Allocations Over Timementioning

confidence: 99%

“…Using quarterly data over the period 1999-2005, De Haan and Kakes (2011 find that Dutch pension funds and insurance firms are, on average, negative-feedback traders. Other than De Haan and Kakes (2011), who use survey data that are collected for statistical purposes (balance-of-payments statistics), this study uses regulatory data with an annual frequency. Main advantages are better coverage (all regulated investors are included), a longer time-span (1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009), including the recent financial crisis, and a breakdown of traditional life and unit-linked life investments.…”

Section: Equity Allocations Over Timementioning

confidence: 99%