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Profitable trading strategies start with a consistent approach to the market. Consistency is difficult for many investors because decisions about money can be very emotional. Diversification is essential, but many investors have difficulty diversifying a portfolio. Additionally, money management and/or allocation of funds in a portfolio are crucial in order to balance risk. These three key elements are the primary reason why so many traders are turning to systems.

• What is a System:

A system is a method of trading, using objective entry and exit criteria, based on parameters validated by historical testing on quantifiable data. A system can be as simple as entering a 10 point stop on every new position or as complex as using fractal analysis to signal trades. In common terms, a system is derived from technical analysis of current and past price action in an attempt to forecast price direction. Using a computer, these results can be tested through millions of permutations to generate objective trading signals. When a developer’s computerized trading signals are combined with sound money management principles, a “trading system” is created. Investors use these systems to trade the futures and/or securities markets to satisfy their individual desire to control and customize their investment program.

• Why Should I Trade a System:

A computerized trading system is able to process an enormous amount of information and data in an extremely short period of time. It is then able to use that analysis to produce a trading signal that is void of influences other that what it has been programmed to utilize. The system doesn’t care when Janet Yellen is talking. The system doesn’t panic when the S&Ps are limit down. The system is unaware of your particular emotional state at any particular moment. Trading the futures and equity markets using an objective trading system helps improve performance. Trading systems provide discipline to overcome the fear and greed that paralyze traders and prevent them from making proper decisions by removing the pressure of making specific buy/sell decisions on a trade-by-trade basis. Each order placed is governed by a pre-determined set of rules that does not deviate based on anything other than market action. A system will also include specific money management parameters and the mechanical placement of these orders ensures those rules are being followed.

The higher the risk, the higher the possible returns

There is no way around this axiom. System trading involves a set amount of risk and a set return.

The main measurement of a system’s risk is the drawdown. This is the maximum amount of money a trader would have lost if they started the system at its equity peak and stopped trading the system at its equity bottom. Because of the ability to “back-test” a system, traders have the opportunity to study all of the strategy aspects (such as the track record, frequency of trade, number of profitable trades versus losing traders and draw-downs) before actually trading. You should always focus on the drawdown first and find a system that revolves around those numbers. From there, you can look at the profits and decide if it is something that you are comfortable with. Emotional traders look at drawdown and hope they will not happen again. In reality, when you look at drawdown, you need to be able to handle at least that much. Some traders like to add about 30% to the previous historical drawdown before they stop trading that particular system. This way they have given the system a little breathing room, and can handle a new MAX drawdown if that occurs. If you study the back tested results carefully and base your decision to start trading a system using the drawdown and profit, you are hoping that history will repeat itself. If you want history to repeat, don’t be surprised if and when the drawdown happens again. If you are anticipating a specific positive return, you should also expect the inverse as well.

• Intervening in an attempt to outperform the system

One of the most common ways that traders negatively influence the performance of a trading system is by intervening and deviating from the signals. I can usually tell you the exact moment when a system will come out of or begin its drawdown. The exact minute a drawdown will end is the exact moment the trader tries to outperform the system by “moving to the sidelines”. Time and time again, when a client stops trading the system, the system magically pulls out of the drawdown. Likewise, when clients start calling up, adding contracts and leveraging up on a system that is on a winning streak, it usually starts its drawdown immediately thereafter. Whether this is a real life example of statistical “reverting to the mean” or just a case of Murphy’s Law, I don’t know. It is definitely a case of letting emotions enter into an arena where they do not belong. The end result is that when a trader interjects his own opinions and biases into the system in attempt to better the returns, they have almost always ended up underperforming the system.

A broker can assist you in placing the system orders in the market as an objective third party. Using a broker eliminates the temptation to deviate from the system. Brokers stare at their screens all day so traders do not have to follow the markets. This insures that proper orders are placed and maintained as the system directs.

Types of System Platforms: Black Box, Grey Box, White Box.

The way that systems are categorized usually falls into one of three types. The term Black Box has been used in conjunction with trading systems primarily to indicate systems where the user has no knowledge of the process code or ability to manipulate the inputs. Grey Box usually refers to systems where the process coding in unknown, but the user has the ability to control specific scenarios, and can allow for optimization that will alter the outcome of the signals from one set of variables to another. A White box system’s source code is open and the strategy revealed. All inputs and variables can be manipulated. The type of system purchased really depends on what the intended use is. If someone is already an accomplished programmer, and has the ability to understand the intricacies of the indicators and strategies, a white box may prove to be a valuable tool. The trader may be able to install some of his own methodology to enhance the program and improve performance. For most individuals however, this added flexibility might have some unintended and ultimately negative outcomes. Unless you are extremely knowledgeable in proper back-testing procedures and statistical analysis, what may happen is that you have taken what was initially a robust system, and by changing the inputs or data, produced a system that is over optimized and curve fit to the specific time period. The end result will be a system that, even though the hypothetical results may look impressive, once the theory is put into practice the system fails to perform as expected because of slight changes in market conditions. The important point is not so much the type of box that you are trading, it is that your are trading a system that has been developed and tested correctly, and that fits your individual trading style and risk, reward, and capitalization perimeters.

The Potential Benefits of System Trading:

To help traders control and customize investment decisions, systems:

1. Provide historical risk and return parameters.
2. Control trading by eliminating fear, greed and indecision.
3. Provide consistent and specific trading signals.
4. Preserve capital by applying money management techniques.
5. Customize a portfolio for specific needs with your risk-reward parameters and capitalization.

The Potential Risk of System Trading:

There are some risks associated with systems.

1. Systems may be slow to adapt to changing market conditions.
2. Traders must maintain the discipline to execute every trading signal.
3. Traders must allocate the time and infrastructure to monitor the system.
4. Have the proper capitalization to withstand the potential drawdowns.
5. Hypothetical past performance of any system is not necessarily indicative of futures results.

In conclusion, It is important to find the system that is best for you by taking into consideration your specific capitalization, specific trading properties of the system, and the emotional impact of the trading methodology.

Making Sense out of Trading System Results:

With the glut of new trading systems coming on the market over the past few years, and the frequency of advertisements touting incredible gains; traders now need, more than ever, a way to compare different trading systems. Simply looking at which system has performed the best over a given period of time can be an incredibly dangerous proposition.

The problem inherent in comparing different systems is their infinitely complex structures. This is truly comparing apples to oranges. For example, one system may trade Nasdaq 100 futures 12 times a day for an annual return of 50% after commissions; and another system may trade Gold futures once in a year for an annual return of 50% after all costs. On the surface, an investor would be equally as wise to invest in either of these trading systems. There are of course, a couple of glaring omissions from this analysis, mainly that VOLATILITY and DRAWDOWN is not taken into consideration.

The investing public tends to focus only on returns. Best performance is a relative term that depends on what the individuals intended outcome is. Traders are fixated with returns, but it is even more important to think about how returns
equate with the risk RISK. The goal is to maximize return per a given unit of risk.

But how can traders measure risk? Should they simply look at a system’s historical max drawdown? Should they consider the volatility of returns? Luckily, the mathematicians have figured most of this out for us, devising numerous statistics for measuring the risk of an investment. There have been entire careers, doctorates, and government studies on the subject, but we should be able to give a brief overview in this space.

Standard Deviation

The most common form of risk is variance, measured most often by Standard Deviation. The standard deviation is a statistic that illustrates how closely all the various points of data are clustered around the mean in a sample of data. When the examples are pretty tightly bunched together and the bell-shaped curve is steep, the standard deviation is small. When the examples are spread apart and the bell curve is relatively flat, that tells you have a relatively large standard deviation.

In relation to trading system returns, a high standard deviation is telling you that you can expect a wide range of returns, from down 50% to UP 80% and several points in between. Similarly, low Standard Deviation values occur when returns are stable. This measure is often referred to as Volatility. Investors relate volatility with risk, as a high level of volatility implies that at any one point the investor could be experiencing the 50% DOWN period or the 80% UP period from the above example. This uncertainty of what the returns will be in the next period is why Standard deviation is used as a measure of risk.
Staying with the above example, many investors would rather sacrifice the 80% return if it meant they could also eliminate the chance of a 50% loss. In a trading system where there is a lower volatility of returns, meaning lower Volatility, many of the extreme points have been removed, meaning a lower standard deviation, smoother equity curve, and more consistent results.

Armed with this measure of risk, all the investor needs to do is find the investment with the lowest possible standard deviation, correct? NO. A standard deviation of ZERO can be achieved with a trading system losing 15% every month, or by a system making 100%. Remember, it is the variance from the monthly returns, not the returns themselves. Thus a low standard deviation means little more than the returns have been fairly steady, and says nothing about the returns.

Sharpe Ratio:

To help with this flaw in the Standard Deviation, Nobel Laureate William Sharpe developed the Sharpe Ratio, which relates risk with return. Sharpe theorized that the expected return of an investment equals the rate on a risk-free security plus a risk premium. If this expected return does not match or outperform the required return then the investment should not be undertaken. He assigned a premium to risk by assuming risk = volatility (a very Big assumption) and measuring volatility with Standard Deviation. The return portion of the Sharpe ratio therefore measures the rate of return OVER the risk free rate. The risk free rate is usually equal to the annualized rate of 90 day US T-Bills, an investment backed by the full weight of the US government and widely considered the safest investment in the world.

The Sharpe ratio therefore measures a trading system’s excess return per a given unit of risk, as measured by the Standard Deviation. Thus, through a little hard work, we finally have our measure of Return per unit of Risk, and have a tool for measuring the Apples and Oranges of the Trading System Industry. The ratio is used to evaluate the quality rather than the quantity of the returns of an investment. This ratio means little by itself, and should be used instead as a measuring stick when comparing various trading systems.

A Higher Sharpe Ratio = More Return per unit of Risk (as measured by volatility)
A Lower Sharpe Ratio = Less Return per unit of Risk (as measured by volatility)

Please note that the Sharpe ratio does not measure only downside risk (deviation), it also measures big moves to the upside. Thus a system which has equity spikes, with some months only returning 2% or 3% and other returning 80% or higher will rank quite low as measured by the Sharpe ration, but may in fact be a very profitable system.

Does the wise investor merely have to go out and find the trading System with the highest comparable Sharpe ratios? I wish it were that simple, and so does the developer of System A.

The reason we can’t merely look at the Sharpe Ratio is that it has a flaw. The Sharpe ratio doesn’t take into account the max drawdown a trading system has experienced. It views risk as the standard deviation only, a mistake made famous by the brains behind Long Term Capital Management’ collapse. (I highly recommend Roger Lowenstein’s book, When Genius Failed : The Rise and Fall of Long-Term Capital Management). The max drawdown of a system simply can’t be ignored.

Sterling Ratio:

There is more to risk than volatility and the Sterling Ratio attempts to tackle that problem by incorporating a separate measure of risk named drawdown. A drawdown is any losing period during a system’s performance record and equals the percentage difference between an equity peak and an equity valley. Many traders think of a drawdown as the max amount of loss they must endure before a system returns to its winning ways. For example, a trader who starts trading a system with $25,000; watches her equity climb to $50,000, fall to $40,000, then rebound to make new equity highs at $55,000 has had a $10,000, or 20%, Drawdown (50 K – 40 K = 10 K). For the trader who started the system with 25K on the day after it reached 50 K, the 10 K drawdown represents a 40% Drawdown. Basing the max drawdown on the minimum recommended account balance is referred to as ‘Start –Trade’ drawdown. We use the ‘start-trade’ drawdown as its Max Drawdown level.

The Sterling ratio looks at a trading system’s returns in relation to its max drawdown. The max drawdown is simply the largest percentage drawdown that has occurred over the performance history of the trading system. Thus, we have another method for comparing the Apples and Oranges of trading systems. Like the Sharpe ratio, the Sterling ratio means little by itself, and should be used as a measuring stick against other trading systems instead.

A Higher Sterling Ratio = More Return per unit of Risk (as measured by drawdown)
A Lower Sterling Ratio = Less Return per unit of Risk (as measured by drawdown)

A couple of main ingredients for assessing a trader’s risk profile are their investment objectives, maximum acceptable loss, and investment time frame. A trader with a very long investment time frame can take on more volatility in returns in exchange for higher annual returns. However, an individual in retirement, for example, with a very short investing time frame, must sacrifice some percentage of return in exchange for less volatility. The short-term dangers of volatility are very real; even an excellent long-term investment can be a disaster for you if your time horizon is short. For an example, look no further than the Nasdaq, where short-term moves can be devastating.

Diversification reduces volatility more efficiently than most people understand: the volatility of a diversified portfolio is less than the average of the volatilities of its component parts. A scientific way to attain a diversified portfolio is by using the Sharpe Ratio to invest in lowly correlated systems.

Consistency, Diversification and Money Management Using a portfolio approach.

Investing in trading system is a valuable diversification tool in that it presents the opportunity for investment returns that are not correlated with other investments such as the stock and bond markets. One of the key tenets of Modern Portfolio Theory, as developed by Nobel Prize economist Dr. Harry M. Markowitz, is that more efficient portfolios can be created by diversifying among asset categories with low to negative correlations. Using a combination of several trading systems can greatly reduce portfolio volatility risk when properly allocated and managed.

Deciding on investing in a trading program is the first step in attempting to diversify your portfolio and lowering overall portfolio risk. The next step is diversifying between multiple trading systems. As has been mentioned earlier, investment decisions are based on risk/reward analysis. The advanced trader continuously adjusts and manages his or her risk downward, while always trying to increase reward. This delicate balancing act is the sole difference between successful and unsuccessful traders.
The successful trader reduces his or her risk by trading a basket of trading systems. This basket must contain several trading systems that are lowly correlated. In order to achieve this low correlation between systems, the trader must look at the three main aspects which comprise trading system risk.

Trading System Risk Components:

Market Specific Risk: The market or markets on which a trading system is run is the main component of a trading system’s risk profile. A trading system may trade the Wheat, the Nasdaq, Crude Oil, or any number of commodities, equities or derivatives. Market specific risk becomes a problem when a fundamental event affects the entire market or complex. The classic example of this is a surprise fed rate cut. The S&P market will gyrate wildly both up and down in this scenario, causing many technical trading systems to return invalid signals and results. Such major fundamental events can make protective stops and money management levels useless, as the market encounters such events as limit moves. A trader who diversifies by trading five different S&P programs has not escaped the market specific risk. That trader is still at risk of suffering major losses based on an event outside of the control of each system. To eliminate market specific risk, the trader should utilize trading systems that use their logic on not only several different markets, but several market complexes as well. Simply diversifying into soybeans, wheat and soy meal, for example, still leaves your portfolio at risk of severe losses in the face of a complex wide fundamental event such as drought or disease. The more prudent approach is to diversify across market complexes and into the grains, energies, softs, indices, and financials.

Strategy Specific Risk: The strategy or strategies on which the trading system is based comprise the second element of risk. There is a multitude of trading strategies available, and one may see no correlation between them upon first review. Most indicators can be separated onto three categories, oscillator based, trend based and momentum based. Almost every trading system is built around some variant of one of these three methodologies. Oscillator based systems tend to perform well in choppy, sideways markets. Trend based systems do well in long-lived directional markets. Momentum systems tend to do well in swing trading markets that run hard in a certain direction, but only for short periods. Overloading your system-trading portfolio with too many of one type of system opens your portfolio up to the risk associated with that type of strategy, and may only function in that specific market condition. A diversified portfolio that contains a portion allocated to each type of system should overcome the individual systems limitations and be able to take advantage of whichever market condition is prevalent at a particular time.

It is also important to take into account the effects different time frames have on the performance of different strategies. A daily chart showing several days of choppy market action may be a beautifully trending market to a 30 min chart. The same trading strategy, therefore, may have two very distinctly different performance records on each of these charts. When looking to diversify between strategies, be sure to pay attention to the time frame on which the strategy is applied as two similar strategies may lower their correlation by trading on different time frames.

Leverage Risk: The final type of risk associated with trading systems is the money management risk associated with deciding how many contracts or shares to execute each signal. The most dangerous mistake traders make is diversifying between systems, but allocating too much risk to one particular system. For instance, a trader may have 8 different systems trading everything from soybeans to the Nasdaq. The situation may be that this trader will be doing one lots of each market with each of the signals that the system generates. However, it must be taken into consideration that the risk associated with one contract of the Nasdaq is roughly 35 times that of Corn. The trader should risk 2%-5% of equity on every trade regardless of which system generated the signal. If one system is trading 1 lots of the Nasdaq, the system that is trading soybeans should allocate a comparable number of contracts, in this case at least 20, based on the risk that each position will be exposed.

Trading a single system is like owning one stock or one mutual fund. You may do very well, or you may do poorly based solely on the management and performance of a single entity. Trading a single trading system is very similar. The trader that uses several non-correlated systems has added the element of diversification, and greatly reduces portfolio volatility risk. The end result can be a much smoother equity curve as losses in one system can be offset by profits I another.

By trading multiple trading systems across different markets and time frames, the trader may reduce market specific and complex specific risk. By trading systems with different entry and exit strategies, the trader reduces system specific risk. By trading the appropriate number of contracts per signal or trading system in accordance with preset risk levels, the trader reduces leverage risk.

Strengths of Trend Following Systems

Historically, traders have had the most success with trend following systems. Trend following systems, in their most basic form, use some type of formula or chart pattern to determine when a tradable direction has been established. The underlying purpose of these calculations is to attempt to filter out the underlying “noise” in the market to reveal true direction in whatever time frame you are working with. The formulas used can be something as relatively simple s a two period moving average crossover or can incorporate indicators as complex as exponential smoothing, parabolic and volatility sensitive inputs.

Traders attempt to profit from these calculations by establishing trading rules and incorporating them into a systematic method of entering and exiting the market. Usually this involves some technique for buying the market when prices are above a certain level or selling when prices are below a certain level. Aggressive traders can use a short-term time frame, while more conservative traders and money managers normally use longer time periods. One of the problems with a system of this type is traders tend to want to “cut profits short and let losses run”.

Trend following systems will show many open profits, and traders usually cash in early. This is exactly the opposite of what should be done. You should not limit upside potential by placing an arbitrary, non-systematic exit point on the trade. The grand majority of index trading systems are non-adaptive, taking fixed profits and fixed losses, even in the face of wildly gyrating price movements and volatility. This fixes profit and limits returns. The mantra of trend following systems is “cut losses, and let profits run”. Successful trend following systems are designed to take small losses, while they allow for maximum profit by remaining in the market for large moves. These large moves are the underlying strength of a diversified, trend following system.

Reasons to include Alternative Investments in an investment portfolio:

1. Balance portfolio volatility risk. This is possible because of the low to slightly negative correlation of managed futures with equities and bonds.
2. Enhance the investment portfolio. Including a balanced futures program improves overall diversification. This claim is substantiated by extensive bank of academic research, beginning with the landmark study of Dr. John Lintner
3. Ability to profit in any economic environment. Diversified managed futures accounts can take advantage of price trends, both positive and negative, during periods of hyperinflation as well as during deflationary times.
4. Participate in global markets. Managed futures accounts can participate in worldwide markets, with profit potential and risk reduction among a broad array of non-correlated markets