AXIOM Long Term is a mechanical, trend-following system that trades all global commodities using end-of-day data. It employs a unique entry qualifier that requires the confluence and mutual confirmation of a number of trend cycles. The system may be purchased fully revealed, and it may be traded directly by the individual purchaser or through a broker-assist program. AXIOM runs on the TradeStation platform and was officially released on April 27, 2004.
The following elements are keys to AXIOM's success:
- Simple Logic: Both entry and exit logic are straightforward in identifying the trend and trend change.
- Robust Performance: AXIOM is unique in that it is able to trade a wide variety of markets and both intraday and day time-frames. Such versatility is indicative of a system based upon the realities of the market. This increases the likelihood that strong performance will continue.
- Low Risk: Stops may be set from $2000-$4000, with little reduction in performance at the lesser risk levels
- Diversification: Choose from a wide range of markets to create a portfolio with the right risk/reward profile for you.
- Peace of Mind: Early in a move, the protective stop is moved to lock in a small profit, thus reducing the risk window to fewer days and also ensuring that healthy winners aren't allowed to become losers.
- Unique Entries: All entries are on the open of the following day. Most occur after a price breakout, but a unique volatility filter also allows entries after a retracement has occurred.
- Unique Markets: After extensive research, a number of non-US markets were found that are liquid and better trenders than their US relatives. They also provide further diversification, with less dependence upon US market forces. These have been incorporated into the recommended portfolios.
- High Average Trade Profit: The average trade profit is $800-$1000, depending upon the portfolio and risk setting.
- High Winning Percent: Because of careful trend identification and quickly locking-in profits, winners are 50-55% of trades.
- Staying Power: AXIOM winners average 90-95 days because they allow the market breathing room and limit premature exits.
Examples of AXIOM Long Term Trades
The foundation of what would become AXIOM was first formulated in 1995, using a pool of about 30 commodities as the test sample. However, due to capitalization concerns, I did not trade it and instead returned to my interest in the S&P. In August of 2003 I tested the original to see how it would have performed in the intervening years and was pleased to see it had done very well. From August through April, 2004 I worked extensively on improving the basic entry technique. I then tested many, many different types and variations of exit strategies on the original marketsATRs, Bollinger Bands, variable moving averages, days-in-trade, RSI, dollar volatility, etc. In the end, I settled on simple, fixed-dollar stop strategies: an initial relatively close stop, one or two profit-lock stops, and a profit objective. These did the best job of minimizing risk, letting trades run their course, and protecting profit. With the initial development phase completed, I tested an additional 30 markets, and found results to be excellent. Entries and exits were refined again, and an additional dozen markets were added to the test pool. Using this 72 commodity portfolio, final exits values were set.
AXIOM Long Term versus AXIOM Index
Both versions of AXIOM rely on the observation that markets consist of a variety of cycles and that successful trading requires the mutual confirmation of these trends. The original version of AXIOM used four cycles, and this became AXIOM Index. Adding additional cycles proved a better platform for trading non-index markets using daily bars, and this version became AXIOM Long Term. As mentioned above, a filter and different stop values further differentiate the index version.
Using an extended portfolio and extensive test-period (back to 1980 or contract inception) in the development of a system's rules and values helps to ensure that none will be chosen that favor an anomalous choice of markets, i.e. curve-fitting is inherently reduced. Additionally, all of the primary entry values consist of Fibonacci numbers, reducing the extent to which optimization is possible. I don't believe there's any magic to Fibonacci, but by limiting the range of values from which to choose, one limits the amount of curve-fitting possible (e.g. rather than choosing the best value from 1-25, Fibonacci allows only to choose between 1, 3, 5, 8, 13, and 21). Further, both in testing and in the final choices, the dollar values for stops were limited to increments of 250-1000, reducing the "fine-tuning" that can occur at this stage.
I believe strongly that a system should be as simple as possible, avoiding special rules that fit only a few situations or periods: the coding for AXIOM is 35 lines, utilizing only those rules and values that work on a variety of markets over time.
Two numbers are the key ingredients of my rule and parameter choices: return per risk and k-ratio. I treat the maximum drawdown as the primary risk number, and I measure this using Monte Carlo software. This program allows me to determine not just the maximum drawdown of the single historical equity curve, but to vary that curve thousands of times. From this, I can determine the average maximum drawdown, average percent drawdown, and their standard deviations. Relying on the single historical equity curve leaves one open to jerry-rigging an artificially low max drawdown and high profit that is dependent upon that specific equity curve for its good numbers. By tossing the trades together in randomly different orders, such a weakness can be uncovered. The development of AXIOM was predicated upon this approach. I then divide the net return by two times the average max drawdown to determine the reward per risk. A parameter set may have lower profit, but if it achieves that profit at a lower risk, then I choose it.
The k-ratio, developed by Lars Kestner, measures equity curve smoothness by calculating the deviation of trades in an equity curve from the linear regression line of that curve. According to him, "The K-ratio detects inconsistency in returns" and measures "the consistency of results through time." Essentially, it quantifies the "swinginess" of the equity curve. Investors prefer an equity "curve" that approaches an ascending line, implying less risk. Kestner states that typical values of the ratio fall between -5 and +5 (the higher, the better), & that he looks "for systems with an average K-ratio of 1.0 or better for individual commodities..." AXIOM Long Term's single-commodity k-ratios are from 1.5 to 5, with portfolio k-ratios from 6 to 15.
These two numbers provided most of the basis for my choice of the specifics of AXIOM. Consequently, AXIOM has a high return per risk ratio, and its equity curves exhibit evenness, as evidenced by high k-ratios.
The Power of Diversification
AXIOM Long Term allows the investor to trade sensibly through the combination of low-correlation markets that reduce overall risk. By the intelligent addition of diversified commodities, one can reduce average maximum drawdown, while increasing net profit. This is the ideal of investing, and TradingVisions further embodies this principle by offering systems that trade a variety of time-frames, markets, and approaches.
Clients are welcome to construct their own portfolios or to use these suggested ones (account funding is a subjective decision; generally, we recommend a minumum of 2-3 times the maximum drawdown).
The following portfolios have been chosen after considerable research into domestic and global markets. The first run of choices was markets with sufficient volume that have exhibited higher long-term uniformity in their equity curves, as measured by their k-ratio values. The second screen sorted the remaining markets into their commodity groups. The third screen measured correlations of prices and equity curves. Markets within a commodity group have relatively lower correlations with markets in other groups than within their own group, so the best portfolios contain markets from a mix of groups.The Starter portfolios generally have the most consistent performers of each market group, the Mid-size have the top two, and the Full has the top three.