Emerging Markets Currencies Strategy (EMCS)

Transcription

1 Emerging Markets Currencies Strategy (EMCS) In the late 1980s we postulated the concept of baby markets and that such infant markets lend themselves better to systematic trading than mature markets. In effect, our Magnum Currency Program, which ran from 1979 to 1984, had a good chance since currencies in those years were indeed baby markets. The Magnum trading rules which worked fine for currencies would not have worked with wheat or corn futures, or the stock market, the most mature markets of all. We use statistical research in determining which markets are most suitable for a systematic trading approach. In 1988 we were first in performing Rescaled Range Analysis and plotting the Hurst Exponent of five IMM currencies, relying primarily on Jens Feder s just published textbook FRACTALS. An ominous quirk of fate would have it that 23 years later Hans Feder, the author s son, was leading the FX Select team at Deutsche Bank. We demonstrated the memory effect in currencies had been declining since 1979 and thus decreased the efficiency of trading systems, leading to our concept of baby markets. Baby markets are more useful for trading systems than mature markets. Indeed, emerging markets currencies are today s baby markets. Our Emerging Markets Currency Strategy EMCS offers a systematic approach to highly trending emerging market currencies, holding long term positions on a multi-month time horizon. Emerging currency markets are still in an infant stage. Conditioned by their inherently lower volume, they display much higher trending qualities than mature G7 currency markets, which have become more random over time. Universe of EM currencies monitored daily (currencies in bold are in the current portfolio) ASIA SOUTH AMERICA EUROPE REST Russian Ruble Chinese Yuan Indian Rupee Thai Baht Indonesian Rupiah Korean Won Malaysian Ringit Singapore Dollar Taiwan Dollar Brazilian Real Chilean Peso Mexican Peso Colombian Peso Hungarian Forint Turkish Lira Polish Zloty Romanian Leu Czech Koruna Israeli Shekel South African Rand The Emerging Markets Currencies Strategy monitors the serial dependence of 21 EM currencies in Asia, Eastern Europe, South America, the Middle East and the rest of the world. On these criteria, the top 7 currencies in the EM portfolio are currently the Russian ruble, the Chinese yuan, the Indian rupee, the Thai baht, the Brazilian real, the Chilean peso and the Mexican peso. The Hurst Exponent for a complete (e.g. Brownian motion) randomness is 0.50 Currency Brazilian Real Chilean Peso Mexican Peso Thai Baht Indian Rupee Russian Ruble Chinese Yuan SYMBOL BRL CPL MXN THB INR RUB CNY Hurst Exp Avg Return 11.1% 5.7% 2.4% 6.1% 9.7% 10.7% 27.6% 1

2 Monthly Performance Table * data out of sample as of 1 October 2016 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov FY 2019 (8.53%) +2.79% +0.18% (5.56%) % (0.48%) (0.15%) (2.75%) (3.19%) (2.91%) +0.63% +7.99% (1.86%) +4.52% (1.94%) (0.71%) +2.61% 2017 (0.22%) +0.06% +0.37% (0.16%) (0.71%) +0.72% (0.36%) +2.51% (3.07%) +1.04% +0.27% +5.04% +5.50% % (1.96%) (11.91%) +1.40% +0.82% +7.17% (1.31%) +0.45% +2.33% +1.78% +2.23% +4.73% % % (2.69%) +0.39% (1.51%) +1.67% +0.71% +5.55% +9.63% +2.31% (3.82%) +4.60% +5.99% % % (3.26%) (1.63%) +1.82% (1.56%) (0.90%) (1.33%) +2.48% +1.56% +2.22% +6.56% +5.33% % % (0.95%) +0.55% +2.19% (4.34%) +2.15% +2.21% +4.98% (5.82%) (0.09%) +2.35% +0.84% +5.27% 2012 (9.42%) (3.40%) +0.76% +0.75% (1.60%) (2.67%) (0.14%) (0.94%) (4.09%) +1.32% +1.11% (1.21%) (19.52%) 2011 (2.62%) +1.92% +1.62% +3.63% (0.94%) +0.70% +1.67% (1.85%) +4.29% (7.94%) +5.97% +5.82% % 2010 (2.43%) +0.83% +2.01% +0.13% (2.15%) +1.99% (1.63%) (1.55%) +6.31% +0.75% (1.31%) +4.60% +7.54% % +4.64% (3.47%) (3.47%) +0.65% +1.93% +1.03% (1.27%) +2.26% +2.78% +2.63% (0.68%) % % +3.59% +2.06% (0.09%) +3.52% +3.76% +0.54% (1.28%) (1.72%) % +4.22% +1.03% % % +1.21% +3.51% +1.90% +3.12% +1.32% +4.04% (3.85%) +4.00% +3.75% +0.78% +3.03% % 2006 (1.50%) +1.33% (0.96%) +3.96% (2.35%) +0.45% +0.38% +0.37% (0.08%) +0.55% +1.30% +0.56% +4.02% % +1.51% (2.45%) +0.44% +0.78% +1.82% +3.87% +0.30% +2.63% +0.13% +2.99% (2.20%) % *data shown are gross, before management and performance fees 1,900,000 1,800,000 1,700,000 1,600,000 1,500,000 1,400,000 1,300,000 1,200,000 1,100,000 1,000, , , , , Robustness of model: The average position change (trade frequency) is 1.5 times per currency per year. Therefore slippage and execution cost are entirely negligible. Because of the low trading frequency, the gross performance shown while pro forma is an extremely robust model, in comparison to modeling with regular trading frequency. Salient Statistics: Annual average return Annualised Volatility Information Ratio Best 12 months Worst 12 months 11.4% 11.5% % -19.5% During our research into the memory behaviour of currency markets in the mid-1980s we were also first to point to the odd fact that currencies do not scale logarithmically like commodities or stocks. Think about that for a while: it makes risk-scaling easier. In the following pages we present the monthly charts of the seven Emerging Markets Currencies currently in the EMCS Portfolio. On day-to-day observation, the highly trending data speak and create performance, not the trading. 2

3 Brazilian Real Chilean Peso Mexican Peso 3

4 Chinese Yan Indonesian Rupee Russian Ruble 4

5 Thai Baht Hurst Exponent (Memory Effect) of various Emerging Markets Currencies (light blue currencies in the current EMCS Portfolio) CNY IDR ZAR CPL RUB BRL MYR CZK MXN TRY INR TWD PLN IRL HUF THB RON SGD COP KRW DISCLOSURE: Backtested performance is NOT an indicator of future actual results. The results reflect performance of a strategy not historically offered to investors and do NOT represent returns that any investor actually attained. Backtested results are calculated by the retroactive application of a model constructed on the basis of historical data and based on assumptions integral to the model which may or may not be testable and are subject to losses. General assumptions include: Clients would have been able to participate in EMCS and the markets were sufficiently liquid to permit all trading. Changes in these assumptions may have a material impact on the backtested returns presented. Certain assumptions have been made for modelling purposes and some of these may not be realised. No representations and warranties are made as to the reasonableness of the assumptions. This information is provided for illustrative purposes only. Backtested performance is developed with the benefit of hindsight and has inherent limitations. Specifically, backtested results do not reflect actual trading or the effect of material economic and market factors on the decision-making process. Since trades have not actually been executed, results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity, and may not reflect the impact that certain economic or market factors may have had on the decision-making process. Further, backtesting allows the selection methodology to be adjusted until past returns are maximized. On the other hand, out of sample results of EMCS are since 1 October 2016 and have not been subject to any further optimisation. Actual performance may differ significantly from backtested performance. Backtested results are presented gross-of fees and do not include the effect of backtested transaction costs, management fees, performance fees or expenses, if applicable. Please note all regulatory considerations regarding the presentation of fees must be taken into account. No cash balance or cash flow is included in the calculation. EMCS Emerging Markets Currencies Strategy This Research Paper has been prepared by Peter Panholzer, DynexCorp 15 March