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In this paper, we investigate what are the drivers of cross-border equity acquisitions made by Sovereign Wealth Funds (SWFs) of the Gulf Cooperation Council (GCC) countries. GCC SWFs are considered as relatively opaque investors and strongly politicized, raising some concerns for perceived political and security risks. Using both Logit and ordered Logit models, we test if the usual determinants of SWFs investments still stand when we look at large or majority acquisitions made by GCC SWFs. Unlike results found in the literature investigating the determinants of SWFs cross-border investments, we find that GCC SWFs do not take into account the financial characteristics of the target firm by taking majority stakes, apart from its financial wealth. The economic, institutional and financial factors of the target country as well as the existence of trade agreements between both countries do not matter in their acquisition/control decision. We also find that firms operating in strategic sectors are targeted by GCC SWFs for diversification purposes but not for the purpose of acquisition or control. Overall, our results lend support to the hypothesis that GCC SWFs differ from other institutional investors in terms of acquisition decision strategy and that financial and commercial motives are not the exclusive target of their acquisition strategy.
Beta coefficients are the cornerstone of asset pricing theory in the CAPM and multiple factor models. This chapter proposes a review of different time series models used to estimate static and time-varying betas, and a comparison on real data. The analysis is performed on the USA and developed Europe REIT markets over the period 2009–2019 via a two-factor model. We evaluate the performance of the different techniques in terms of in-sample estimates as well as through an out-of-sample tracking exercise. Results show that dynamic models clearly outperform static models and that both the state space and autoregressive conditional beta models outperform the other methods.
We examine in this paper the complex decision-making processes that lead to investment location choice of Sovereign Wealth Funds (SWFs). Using a two-tiered dynamic Tobit panel model, we find that country-level factors do not have the same impact on the investment decision and the amount to invest and that SWFs tend to invest more frequently and with higher amounts in countries in which they already have invested. More specifically, we find that SWFs prefer to invest in countries with higher political stability, whereas they are more prone to investing for large amounts in countries that are less democratic and more financially opened. Our results also lend support to the idea that SWFs are prudent in the choice of target country concerning their investment decision but behave as more opportunistic investors concerning the amounts to be invested.
The paper deals with the important financial policy issue of the decision for a country to establish a sovereign wealth fund (SWF). Using a large-scale database, we analyze the economic, political and institutional factors that should be considered in such a decision. In particular, we test if the emergence of SWFs and more specifically of a specific type of SWFs can be explained by the following factors: the excess foreign exchange reserves due to natural resources rents or persistent current account surpluses; the volatility of commodity prices; the appreciation of the real exchange rate leading to the “Dutch Disease” effect and the governance of the country. The results suggest that countries with excess foreign exchange reserves, which are dependent on a commodity and which suffer from an appreciation of the real exchange rate are more likely to create a fund. We also find that commodity-based funds tend to be established in low democratic countries. Finally, our results suggest that the factors driving SWFs creation are different depending on the origin of the funding (commodity or non-commodity) and the macroeconomic objective(s) assigned to the fund. Our results may be of interest for policymakers debating whether or not it can be optimal for the country to establish a SWF.
Sovereign wealth funds (SWFs) have been increasingly active over the past decade, with governments raising concern regarding their actual motives and the potential for cross-border interest in national strategic sectors. The aim of this paper is to contribute to the existing literature by improving our understanding of the decisions being taken by this new class of investors. The decision-making process informing such investments is complex in the sense that it involves several levels of decision that may potentially interact. In this study, we investigate the determinants of SWFs' foreign investments, while considering in a single model the sequence of choices involved in their decisions, specifically (i) the decision to invest abroad or not, (ii) the decision to invest in a listed versus unlisted firm, and (iii) the decision to take large versus small stakes. Using a nested logit approach on one of the largest SWFs, the Singaporean fund Temasek, over the period 1990–2010, we provide clear evidence of dependence in the three levels of decision making considered. In addition, we show that the probability of Temasek's cross-border investment increases with the excess of foreign exchange (FX) reserves, that the SWF tends to target unlisted firms when asymmetry of information is low between the target company and its home country, and that its involvement in large stakes depends on a firm's financial characteristics.
Financial asset prices occasionally exhibit large changes. To deal with their occurrence, observed return series are assumed to consist of a conditionally Gaussian ARMA-GARCH type model contaminated by an additive jump component. In this framework, a new test for additive jumps is proposed. The test is based on standardized returns, where the first two conditional moments of the non-contaminated observations are estimated in a robust way. Simulation results indicate that the test has very good finite sample properties, i.e. correct size and high proportion of correct jump detection. The test is applied to daily returns and detects less than 1% of jumps for three exchange rates and between 1% and 3% of jumps for about 50 large capitalization stock returns from the NYSE. Once jumps have been filtered out, all series are found to be conditionally Gaussian. It is also found that simple GARCH-type models estimated using filtered returns deliver more accurate out-of sample forecasts of the conditional variance than GARCH and Generalized Autoregressive Score (GAS) models estimated from raw data.
In this paper, we examine the intra-day effects of verbal statements and comments on the FX market uncertainty using two measures: continuous volatility and discontinuous jumps . Focusing on the euro-dollar exchange rate, we provide empirical evidence of how these two sources of uncertainty matter in measuring the short-term reaction of exchange rates to communication events. Talks significantly trigger large jumps or extreme events for approximately an hour after the news release. Continuous volatility starts reacting prior to the news, intensifies around the release time and stays at high levels for several hours. Our results suggest that monetary authorities generally tend to communicate with markets on days when uncertainty is relatively severe, and higher than normal. Disentangling the US and Euro area statements, we also find that abnormal levels of volatility are mostly driven by the communication of the Euro area officials rather than US authorities.
This paper investigates the link between jumps in the exchange rate process and rumours of central bank interventions. Using the case of Japan, we analyse specifically whether jumps trigger false reports of intervention (i.e. an intervention is reported when it did not occur). Intraday jumps are extracted using a non-parametric technique recently proposed by Lee and Mykland in 2008 and by Andersen et al . in 2007, and later modified by Boudt et al . in 2011. Rumours are identified by using a unique database of Reuters and Dow Jones newswires. Our results suggest that a significant number of jumps on the YEN/USD have been falsely interpreted by the market as being the result of a central bank intervention. The paper has policy implications in terms of central bank interventions. We show that in times where the central bank is known to intervene, some investors may attach a lot of weight to central bank interventions as a source of exchange rate movement, leading to a false ‘intervention explanation’ for observed jumps.
This paper empirically investigates the induced effect of a more and less transparent central bank intervention (CBI) policy on rumors that can emerge. Using the case of Japan, we estimate a dynamic-probit model that explains the main determinants of false reports (i.e. falsely reported interventions) and anticipative rumors (i.e. rumors about future interventions) with reference to the intervention strategy adopted by the central bank for actual and oral interventions, and the uncertainty climate of the market captured by two volatility measures. Our results suggest that the induced effect of a transparent CBI policy on market rumors critically depends on the type of speeches made by officials.