May 2014: Trend Following NEUTRAL -0.02% — YTD: -2.81%
A near-zero result for the index in May, which continues its multi-months stagnating (consolidating?) phase. Interesting to note that the performance is improving on the 12-month rolling basis as the strong negative months from last year are dropped off. Indeed, one of the systems is showing positive performance over the last 12 months for the first time since the index launch. We’re hoping it might be a further sign of a turn-around.
The 12-month chart again showing a fairly flat performance since October:
|Year To Date||-2.81%||10.27%|
|Last 12 months||-12.8%||11.82%|
|Last calendar year (2013)||-13.29%||12.66%|
|Since Index Launch (08-13)||-8.17%||10.2%|
|MaxDD (since 2000)||-34.31%|
Individual System Contribution
The index is composed of several systems, each traded over different time horizons (short, medium and long) with a diversified portfolio of futures (details of the index components and construction can be found further below, in the next section).
The contribution of each individual system to the overall index performance is measured on a daily basis. The following chart shows the evolution of each system’s respective performance attribution over the last month:
And further below, the performance attribution of each system over the last 12 months, sorted by ranking:
Please note the colour-coding to assist reading the charts:
- one “color hue” per system (e.g. blue for “BBB” system)
- one “shade” per time horizon (e.g. dark for “L” – Long-term system)
The index performance is simulated using Trading Blox and CSI data (back-adjusted contracts rolling on Open Interest). The performance of the index is directly derived from the performance of a Trading Blox simulation suite composed of each system component as a system part of that suite.
The simulation uses realistic trading friction parameters (slippage, commissions, interest as detailed aside).
The individual system performance attributions are directly extracted from the same simulation run.
Trade Friction parameters
|Slippage||5% of ATR|
|Commisions||$20 per contract|
|Slippage on rolls||Yes|
|Roll slippage||5% of ATR|
The portfolio selected for the index represents a diversified mix of global futures balanced across all sectors:
|Euro / Japanese Yen||CME|
|Korean Won||KRX (Kofex)|
|New Zealand Dollar||CME|
|US Dollar Index||ICE US|
|Brent Crude Oil||ICE EUR (IPE)|
|Light Sweet Crude Oil (WTI) E-mini||NYMEX|
|Natural Gas (Henry Hub) E-mini||NYMEX|
|Crude Palm Oil||BMD (MDEX)|
|Milling Wheat||EURONEXT (MATIF)|
|Rice Rough||CME (CBOT)|
|Copper E-mini||CME (NYMEX)|
|FTSE Xinhua China A50 index||SGX|
|Hang Seng index mini||HKEx|
|Mini Russell 1000 index||ICE US (NYFE)|
|MSCI Singapore Stock index||SGX|
|Canadian 10-Year Govt Bond||MX|
|Euro German Bund||EUREX|
|Japanese 10-Year Govt Bond||SGX|
|Swiss 10-Year Govt Bond||EUREX|
|US T-Notes 5-Year||CME (CBOT)|
|90-Day NZ Bank Bills||ASX (SFE-NZFE)|
|Euribor 3-month||EURONEXT (LIFFE)|
|Cocoa||ICE US (NYBOT-CSCE)|
|Coffee||ICE US (NYBOT-CSCE)|
|Milk (Class III)||CME|
|Sugar (#11)||ICE US (NYBOT-CSCE)|
The above is a representation of the global futures markets that Wisdom Trading can give you access to.
For the full list of products and markets, please check our global products page. We cover over 300 markets in more than 30 exchanges globally.
One of the main goals of the index is to mirror the performance of trend following in general. As such, the trading strategy is based on simple, public trading systems that use trend following principles. Each system is declined in three different timeframes (long, medium and short) to cover a wide spectrum of trend duration and increase overall diversification.
|Color||Component||System used||Trading Horizon||Parameters||Pos. Size|
|BBB-S||Bollinger Band Breakout||Short-term||20,2||0.483|
|BBB-M||Bollinger Band Breakout||Medium-term||50,2||0.63|
|BBB-L||Bollinger Band Breakout||Long-term||200,2||1|
|DMA-S||Dual Moving Average||Short-term||20,10||0.17|
|DMA-M||Dual Moving Average||Medium-term||50,20||0.17|
|DMA-L||Dual Moving Average||Long-term||200,50||0.19|
|TMA-S||Triple Moving Average||Short-term||50,20,10||0.41|
|TMA-M||Triple Moving Average||Medium-term||200,50,20||0.59|
|TMA-L||Triple Moving Average||Long-term||800,200,50||0.93|
The money management aspect of the overall system simply allocates a fixed percentage of equity to each new position’s calculated risk (based on volatility). Each system is set up with a different percent of equity in order to calibrate (or normalize) the volatility of each system. The calibration was performed by assigning a position sizing percent to normalize the standard deviation of each system’s result stream on the period 2000-2010 (normalization period). The period from 2010-2013 was used for validation.
Commodity Trading involves high risks and you can lose a significant amount of money. Commodity trading is not suitable for many investors. Any performance results listed in all marketing materials represents simulated computer results over past historical data, and not the results of an actual account. All opinions expressed anywhere on this website are only opinions of the author. The information contained here was gathered from sources deemed reliable, however, no claim is made as to its accuracy or content. Different testing platforms can produce slightly different results. Our systems are only recommended for well capitalized and experienced futures traders.
CFTC-required risk disclosure for hypothetical results
Hypothetical performance results have many inherent limitations, some of which are described below. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown. in fact, there are frequently sharp differences between hypothetical performance results and the actual results subsequently achieved by any particular trading program.
One of the limitations of hypothetical performance results is that they are generally prepared with the benefit of hindsight. In addition, hypothetical trading does not involve financial risk, and no hypothetical trading record can completely account for the impact of financial risk in actual trading. For example, the ability to withstand losses or to adhere to a particular trading program in spite of trading losses are material points which can also adversely affect actual trading results. There are numerous other factors related to the markets in general or to the implementation of any specific trading program which cannot be fully accounted for in the preparation of hypothetical performance results and all of which can adversely affect actual trading results.