Carry trade portfolio optimization using particle swarm optimization

Portfolio optimization has as its objective to find optimal portfolios, which apportion capital between their constituent assets such that the portfolio's risk adjusted return is maximized. Portfolio optimization becomes more complex as constraints are imposed, multiple sources of return are included, and alternative measures of risk are used. Meta-heuristic portfolio optimization can be used as an alternative to deterministic approaches under increased complexity conditions. This paper uses a particle swarm optimization (PSO) algorithm to optimize a diversified portfolio of carry trades. In a carry trade, investors profit by borrowing low interest rate currencies and lending high interest rate currencies, thereby generating return through the interest rate differential. However, carry trades are risky because of their exposure to foreign exchange losses. Previous studies showed that diversification does significantly mitigate this risk. This paper goes one step further and shows that meta-heuristic portfolio optimization can further improve the risk adjusted returns of diversified carry trade portfolios.

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