Abstract
This paper investigates the concept of risk appetite. A number of methodologies for building a risk appetite index are proposed. It is shown how this index can be utilised to improve portfolio construction in currency markets. Portfolios are constructed using quadratic optimisation. Different strategies, in particular Carry, Value and Momentum, are combined via our optimisation procedure, leading to return outcomes that possess certain desirable properties relative to an equally weighted benchmark.
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Notes
This is a consequence of the Perron--Frobenius theorem.
The non-parametric estimate is computed using an Epanechnikov kernel with a bandwidth of 0.15 (Wand and Jones (1994))
Note: In reporting GQRI and DGQRI parameters, values have been pre-multiplied by 10,000.
Although for the purposes of this paper we only report results relating to AUD/USD and JPYNZD, results highlighting the potential explanatory power of GQRI on the conditional volatility of numerous other developed market currencies are available upon request.
These results on VIX are available on request from the authors.
More specifically, while just 1.4 per cent of respondents believe that exchange rate movements reflect changes in the fundamental value of a currency on an intra-day basis, this figure grew to 88 per cent when considering exchange rate movements over horizons greater than 6 months. This links in well to the emerging consensus that the out-of-sample performance of fundamental-based exchange rate models improves as the forecast horizon under examination increases (see, for instance, Flood and Taylor, 1996; Cheung et al., 2005).
Given the fact that the mean return of an asset is typically several orders of magnitude lower than its standard deviation, it is usually assumed that the mean return of an asset over the short-term horizon is equal to zero (see for instance Figlewski, 1997).
The results reported in Table 5 have been replicated for a variety of decay factor values and are available from the authors upon request.
See for instance JP Morgan RiskMetrics (1996).
It may also be worthwhile noting that while we have also calculated the minimum variance portfolio, the subsequent results are extremely similar to those given by the equally weighted approach to portfolio construction and are not reported here. All results are, of course, available from the authors upon request.
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The authors would like to thank James Tyrrell for his helpful comments and assistance in completing this research work.
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2received the PhD degree in Computational Finance from University of Essex (2008). His PhD degree focused on Evolutionary Computation in Financial Decision Making, with applications in statistical arbitrage and foreign exchange trading. He is currently employed as quantitative trader at Liquid Capital Management. Before this he worked in proprietary quantitative trading at Lehman Brothers, and before that as a quantitative research analyst at Old Mutual Asset Managers.
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Luo, J., Saks, P. & Satchell, S. Implementing risk appetite in the management of currency portfolios. J Asset Manag 9, 380–397 (2009). https://doi.org/10.1057/jam.2008.40
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DOI: https://doi.org/10.1057/jam.2008.40