August fall for Trend Following

August fall for Trend Following

Wisdom State of Trend Following

August 2016 Trend Following: DOWN  -7.32%  /  YTD: -7.95%

August was mostly one-sided, sliding down to a strong negative performance, and taking with it the Year-To-Date performance to a similar level. Interesting to note the shorter timeframes weighing on the index while the longer timeframes are still positive/neutral on a 12-month horizon (we do offer trading systems with long-term timeframes).

Note the drawdown level as well, getting a little bit closer to the Max Drawdown (since the start date of the index in Jan-2000). These occasions have historically proven a good time to start investing in a trend following strategy. It will be interesting to monitor the evolution of the index over the last few months.

Despite this recent performance, the index is still well positive (+35%) since launch in live monitoring, in 2013, which interestingly was at similar levels of drawdown. The performance since the start of the backtest in 2000 is at +1,279% compounded.

Below is the full State of Trend Following report as of last month.

Performance is hypothetical.

Chart for August:

Wisdom State of Trend Following - August 2016


And the 12-month chart:

Wisdom State of Trend Following 12 months - August 2016

Below are the summary stats:

HorizonReturnAnn. Vol.
Last month-7.32%10.31%
Year To Date-7.95%15.74%
Last 12 months-8.47%16.23%
Last calendar year (2015)7.57%16.88%
Since Index Launch (08-13)34.47%14.58%
Current DD-20.55%
MaxDD (since 2000)-31.94%

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: 

System Attribution August 2016


And further below, the performance attribution of each system over the last 12 months, sorted by ranking:

System Attribution-12 months August 2016

System12-monthlast month

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)

Index Methodology

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

Slippage5% of ATR
Min. slippage$15.00
Commisions$20 per contract
Slippage on rollsYes
Roll slippage5% of ATR
Earn interestYes


The portfolio selected for the index represents a diversified mix of global futures balanced across all sectors:


Brazilian RealCME
Canadian DollarCME
Euro / Japanese YenCME
Korean WonKRX (Kofex)
New Zealand DollarCME
US Dollar IndexICE US


Brent Crude OilICE EUR (IPE)
Gasoline (RBOB)NYMEX
Light Sweet Crude Oil (WTI) E-miniNYMEX
Natural Gas (Henry Hub) E-miniNYMEX


Crude Palm OilBMD (MDEX)
Rice RoughCME (CBOT)
SoybeansCME (CBOT)
Yellow MaizeSAFEX


PlatinumCME (NYMEX)


Cattle FeederCME
Live CattleCME

Equity Indices

Dax indexEUREX
FTSE Xinhua China A50 indexSGX
Hang Seng index miniHKEx
Mini Russell 1000 indexICE US (NYFE)
MSCI Singapore Stock indexSGX


Canadian 10-Year Govt BondMX
Euro German BundEUREX
Japanese 10-Year Govt BondSGX
Swiss 10-Year Govt BondEUREX
US T-Notes 5-YearCME (CBOT)


90-Day NZ Bank BillsASX (SFE-NZFE)
Euribor 3-monthEURONEXT (LIFFE)


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.

ColorComponentSystem usedTrading HorizonParametersPos. Size
BBB-SBollinger Band BreakoutShort-term20,20.483
BBB-MBollinger Band BreakoutMedium-term50,20.63
BBB-LBollinger Band BreakoutLong-term200,21
DMA-SDual Moving AverageShort-term20,100.17
DMA-MDual Moving AverageMedium-term50,200.17
DMA-LDual Moving AverageLong-term200,500.19
DON-SDonchian BreakoutShort-term200.44
DON-MDonchian BreakoutMedium-term500.58
DON-LDonchian BreakoutLong-term2000.85
TMA-STriple Moving AverageShort-term50,20,100.41
TMA-MTriple Moving AverageMedium-term200,50,200.59
TMA-LTriple Moving AverageLong-term800,200,500.93

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.

Material Assumptions

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.


Risk Disclosures

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.


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