**5. Conclusions**

This paper focuses on three "safe haven" assets which have received wide attention in the recent applied literature (gold, Swiss Franc, and oil), and explores some statistical properties of these assets with a particular focus on their time-varying correlation patterns.

The influence of financial crises and macroeconomic variables on dynamic correlations between "safe haven" assets have seldom been explored. This represents one major drawback in the literature, since the last two decades witnessed many financial crises with important international spillover effects. Moreover, the impact of macroeconomic and financial variables on co-movements between "safe haven" asset returns is likely to be substantial, particularly if these variables reflect the degree of risk aversion, economic uncertainty, or the degree of confidence of economic agents.

In this perspective, this paper fills one relevant gap in the applied literature on "safe haven" assets, providing a thorough analysis about the determinants of their return co-movements during the last two decades.

The main empirical findings may be summarized as follows.

Financial crises produced a significant increase in all pair-wise correlations between "safe haven" assets. This influence is not limited to major financial turbulences (global financial crisis, Eurozone debt crisis), but involves all subsequent crises episodes (Russian financial crisis, Chinese stock market

crisis, Turkish financial crisis). This pervasive e ffect of financial crises implies that gold, oil, and the Swiss Franc retained their "safe haven" status during the last two decades.

A latter important result refers to the e ffects of some outstanding macroeconomic variables. The world equity risk premium stands out as the most relevant variable a ffecting return co-movements. The impact of this risk aversion indicator on "safe haven" assets return co-movements is always large, and explains a consistent fraction of correlation patterns. Another noticeable influence stems from various economic policy uncertainty indicators, which played a further relevant role in shaping global investors asset allocation choices towards "safe haven" financial assets. The e ffects of other macroeconomic variables, such as consumer confidence or systemic stress indicators, are instead more limited. Overall, the empirical evidence for macroeconomic variables reiterates the features of gold, oil, and the Swiss Franc as important "safe haven" assets during the period examined.

This paper can be profitably extended along many research directions.

The robustness of results may be assessed using data sampled at higher frequencies (weekly, daily, intra-daily). Moreover, this analysis can be extended to other financial assets typically included in the "safe haven" category (US long-term governmen<sup>t</sup> bonds, the Yen exchange rate, and other precious metals).

A further interesting research area is represented by the use of more sophisticated models to compute dynamic conditional correlations. Profitable research directions are represented by some extension of Engle (2002) seminal model, allowing for asymmetric responses in conditional variance and conditional correlations to negative returns, or allowing correlation dynamics to depend on asset variances through a threshold structure.

In a more general perspective, the development of powerful econometric techniques for the analysis of conditional correlation structures of a large number of assets remains on the top of the research agenda. Although plagued by the curse of dimensionality problem, this represents a crucial condition for a more accurate assessment of the hedging properties of "safe haven" assets against traditional financial instruments and the development of e fficient dynamic asset allocation strategies.

**Funding:** This research received no external funding.

**Acknowledgments:** The author is thankful to the anonymous referees for very useful comments.

**Conflicts of Interest:** The author declares no conflict of interest.
