Historical Performance of Trend Following Post-Drawdown

August marked a local low for our Trend Following index, reaching about two thirds of the max historical drawdown. We were commenting on the fact that, historically, drawdowns have typically proved a good time to invest or start trading a trend following strategy.

This prompted us to run a test to check the historical results on the index. We decided to investigate the historical performance immediately following the first day of a large drawdown (2/3 of MaxDD reached).

The backtest for the index starts on January 2000. We let the backtest run for 5 years, to establish an initial baseline maximum drawdown (MaxDD). We then picked all occurrences thereafter where the drawdown reached

two thirds of the MaxDD at the time (limiting the number of occurrences to one per year to limit overlap). Measuring and plotting the performance of the index past these occurrences gives an indication of the historical post-drawdown average performance.

For context, below is a chart of the equity curve and drawdowns for the full duration of backtest and live test (performance is hypothetical):


Post-Drawdown Performance

From 2005 onwards, there were 5 occurrences/years during which the drawdown reached the MaxDD two-third level. Despite this, the index still returned +435% (or +15.5% annualized), as drawdowns are an integral part of a successful trend following strategy. These are the dates for these drawdowns:

  • April 2005
  • May 2006
  • March 2008
  • January 2010
  • May 2011

Below is the chart showing the equity curve post-drawdowns, for all these instances, plotted for a duration of 3 years each. A composite curve is added to derive an average tendency. Performance is hypothetical.


In some cases the drawdown extends for a period of time but most of the post-drawdown performance is positive (in 80% of cases), as illustrated by the composite curve, nearly doubling in value after 3 years.

Below are the average performances at different time horizons:

Horizon Return
3-month +4.63%
6-month +11.19%
12-month +24.39%
18-month +32.12%
2-years +39.82%
3-years +88.92%

Note also that the index was launched in live monitoring (post-backtest) at high levels of drawdown and has returned over 34% since. It will be interesting to monitor the performance of the index over the next few months.

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).

For more information on the index (systems and portfolio used and other details), please check our latest State of Trend Following report.

Trade Friction parameters

Slippage 5% of ATR
Min. slippage $15.00
Commisions $20 per contract
Slippage on rolls Yes
Roll slippage 5% of ATR
Earn interest Yes

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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