This is the same idea as our FX majors allocation with emerging market currencies, where the local carry can be much more attractive, but usually comes with more instability and price volatility.

Symbol Currency Name Issuer Target Allocation (%)
INRUSD Indian Rupee Reserve Bank of India 30.818572
PHPUSD Philippine Peso Bangko Sentral ng Pilipinas 22.532194
PLNUSD Złoty National Bank of Poland 12.723751
TRYUSD Turkish Lira Central Bank of the Republic of Turkey 24.562912
COPUSD Colombian peso Banco de la República 9.362569

» Performance chart of our allocation versus its benchmark:

 

 

                    Note: The benchmark has been scaled to achieve equal volatility over the period, in order to get a pound for pound visual comparison of compounded returns.

 

» Key performance metrics over the last 18 months:

 

Total Return Realized Volatility Relative Volatility / Benchmark Excess Return1 Sharpe Ratio1 Maximum Drawdown2 Calmar Ratio Correlation Beta R-squared3 Annualized Alpha4 Treynor Ratio Up Capture Down Capture Active Return5 Tracking Error5 Information Ratio5
ALLOCATION -7.7% 4.3% 1.15 -15.0% -3.51 -8.0% 0.97 0.46 0.53 21% -7.2% -0.09 41.5% 86.7% -14.8% 4.5% -3.32
BENCHMARK 7.1% 3.7% – -0.2% -0.06 -4.0% 1.78 – – – – – – – – – –
INRUSD -6.1% 4.5% 1.2 -13.5% -3 -6.5% 0.94 0.31 0.37 9% -5.5% -0.11 22.7% 55.4% -13.7% 5.3% -2.59
PHPUSD -2.5% 7.1% 1.91 -9.8% -1.38 -6.0% 0.41 0.42 0.8 18% -4.9% -0.02 77.9% 110.0% -14.6% 7.7% -1.91
PLNUSD 8.3% 12.3% 3.28 1.0% 0.08 -8.7% 0.96 0.37 1.23 14% 0.1% 0.04 140.1% 144.2% -13.9% 13.7% -1.01
TRYUSD -23.2% 5.3% 1.43 -30.5% -5.73 -23.2% 1 0.02 0.03 0% -15.6% -6 -37.5% 61.4% -30.5% 7.5% -4.09
COPUSD -2.6% 14.3% 3.83 -10.0% -0.7 -15.9% 0.17 0.21 0.79 4% -4.5% -0.02 89.1% 121.9% -25.8% 18.0% -1.43
Notes:
1 For the estimation of the Sharpe ratio, we calculated excess return and excess volatility against the daily returns of the Nasdaq US T-Bill V2 Index (“NQCASH2”).
2 Drawdowns are calculated on daily closing prices (i.e. not intraday highs and lows).
3 The R-squared indicates how much the variance of a security can be explained by the variance of the benchmark: if a security has a low R-squared value, the CAPM single-factor linear relationship doesn’t explain much of the variance of the security, and the CAPM metrics (beta, alpha, Treynor ratio) are not useful for this particular security.
4 The annualized alpha is a compounded calculation from CAPM estimations on daily returns.
5 The active performance metrics are calculated relative to the volatilty-adjusted benchmark (i.e. the benchmark multiplied by the relative volatility of the allocation).

» Charting each security in the allocation:

 











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