February 2015: Trend Following DOWN -3.39% — YTD: +8.11%
Trend following’s performance accelerated over the last few months, with some markets showing some possible over-extension in their trends. It’s not such a surprise to see some pull-backs finally taking place. This has naturally taken the index down, mostly giving back some of the large open profits.
This is the first negative month in nearly a year, since March last year (if we put aside the two minor -0.02% results in May and October).
Interesting also to note that the best-performing system over the last 12 months (Bollinger Band Breakout – Medium timeframe) is quite clearly the worst performer this month.
Below is the full State of Trend Following report as of last month.
Performance is hypothetical. Chart for February:
And the 12-month chart:
Below are the summary stats:
|Year To Date||8.11%||17.78%|
|Last 12 months||55.24%||13.53%|
|Last calendar year (2014)||41.5%||12.5%|
|Since Index Launch (08-13)||44.52%||12.55%|
|MaxDD (since 2000)||-34.2%|
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 we can give you access to at Wisdom Trading. 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.
The test is set-up with an arbitrary starting capital of 1B, starting in 2000. As the test is intended to represent an hypothetical index, no liquidity/volume constraints are enforced, making the results less dependent on actual simulation capital.
Profits are compounded (assumed to be reinvested).
The purchase or sale price for each trade that generated the hypothetical results is based either on 1) open price, the day after the Buy or Sell signal for the Moving Average-based systems or 2) stop level set by the relevant indicator for the Bollinger or Donchian systems. The actual simulated fill price is obtained by calculating a slippage factor, which is added to (or subtracted from) the theoretical entry price. For a long entry, the slippage factor is calculated by measuring the range from the theoretical entry price to the day’s highest price, and multiplying that amount by the Slippage Percent. (For short
entries, the slippage factor is calculated by measuring the range from the theoretical entry price to the low). The slippage factor is then added to, or subtracted from the theoretical entry price, to obtain the simulated fill price.
Commodity Trading involves substantial risk of loss and is not suitable for all 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.