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Managed Futures


The term “Managed Futures” is the name of an asset class, mainly used in conjunction with Hedge Funds. The investment strategy is based on systematic quantitative trading algorithms with listed derivatives. Managers of Managed Futures Funds are also known as Commodity Trading Advisors (“CTA’s") due to their American job title. This job title is derived from trading commodity futures being the main focus of this trading strategy in early times. As of today financial futures have mostly gained much more importance in a Managed Futures portfolio than commodity futures. Since futures contracts could either be bought or sold ("Short-Selling"), Managed Futures Strategies may benefit in bull markets as well as in bear markets.

By this means investors get access to markets which are mostly not considered in an investment portfolio (e.g. commodity markets).

All smn trading models are based on medium to long term trend following. By using a set of independent quantitative models, we target to identify trends in different markets. Investment target of the fund is an optimal risk/reward ratio over a multi-year horizon. Due to the possibilities of futures markets to enter into Long- and Short-Positions it is possible to benefit from both rising and falling prices .

Benefits and risks of Managed Futures

 Benefits of Managed Futures

  • Long- and Short Positions
    Profits could be made in either Bull or Bear markets. In times of economic crisis and political changes futures markets – in opposite to the most traditional markets – offer good revenue potential
  • Dynamic Trading Strategy
    Classic investment funds (equities, bonds, real estate) must be invested by a high percentage. Hence the decision to buy or sell will be transferred to the investor who has to decide whether to be scared of a price slump and hence to sell an investment or rather hold on to it. A dynamic trading strategy does disburden the investor from such decisions which are often timed very badly due to widespread fear or greed (a mass phenomenon).
  • Low correlation to almost all other Asset Classes
    IInvestors can easily identify the historical behaviour of a fund´s trading strategy by looking at the track record of the fund managed by a technical trading system. Of course past performance cannot be guaranteed for the future.
  • Asset Allocation1 improved by additional Markets durch zusätzliche Märkte
    Trading futures offers the possibility to trade globally on different markets. A fund’s AIFM (CTA or investment advisor) can take advantage of opportunities in markets which could not be considered by a classical fund management. This includes primarily commodities.
  • Comprehensive Market Diversification
    Managed Futures-Concepts include comprehensive market diversification, targeting risk diversification by allocating only small risk budgets to individual investment decisions in as many markets as possible, which ideally show low correlation to each other.. Thus the probability of a simultaneous loss of all investment shall be kept to a minimum.

Risks of Managed Futures 

  • Liquidity Constraints
    During specific market situations specific liquidity constraints could cause problems to close unfavourable positions immediately or to enter into favourable positions.
  • Expiration or Depreciation in Value
    Rights out of futures contracts may expire or be depreciated in value since such trade does only give a temporary right. The shorter the period the higher the specific risk.
  • Missing Hedging Options
    Positions to equalize or mitigate the risks of futures positions may not be entered into or only by accepting a loss.
  • Leverage
    The leverage effect is based on the fact that the investor does only have to pay a part of the contract value but he will participate on the price change of the underlying. Thus a minimal price change of the underlying could cause a significant profit or loss in relation to the invested capital by using derivates.
  • Volatility2 on Derivative Markets
    The price of derivatives has again and again been subject to periods of high volatility in the past that may recur in the future. The price movements of futures are influenced by many unpredictable factors.
  • OTC3 Trading
    In opposite to exchanges there are so called OTC markets where the fulfilment risk is only with the counterparty the market participant has entered into an OTC futures contract and not with an exchange or clearing house.



1) Asset Allocation = An investment strategy that aims to balance risk and reward by apportioning a portfolio's assets according to an individual's goals, risk tolerance and investment horizon.

2) Volatility is the range variation during a specific period of e.g. equity prices, commodity prices, interest rates or even shares of investment funds. Volatility is a mathematical measure (in this case: Standard Deviation) as measure of risk of an investment.

3) OTC = Over-the-Counter; such trades are not settled via an exchange. Most exchanges in developed markets do provide strict rules and are subject to prudential supervision of internal and external (even by governments) auditors – regulated exchanges provide more transparency then unregulated markets.

Technical trading systems

A technical trading system is an automated software tool which takes investment decisions based on historic and actual market data. In addition such systems constantly monitor the volatility and size of all positions and hence the risk budget. In case of a breach of predefined limits the system will automatically instruct the necessary size adjustments, independent from any personal opinion of a trader.

Essential for the success of such a system is the trader's willingness and ability to execute the generated trading signals with a high level of discipline. The discipline to rigorously take losses as defined by the system and let profits run is often a huge psychological problem for many traders (mental trading problems). As this is the main cause for poor trading results in discretionary trading, this aspect has been automated by technical trading systems to avoid the disadvantages of such human weaknesses.

The development of the smn trading system is based on practical trading experience. It predominantly considers the typical human approach and tries to put a high emphasis on the strengths and limitations of this approach. Especially in times when human nature is vulnerable to greed, fear and panic, the disciplined execution of trading signals by the systematic program are an important basis for success .

Benefits of technical trading systems 

  • Verification
    The applicability of the rules can be verified by historical data and statistical tests.
  • Objectivity
    Objective rules prevent from trading decisions based on emotions.
  • Risk control
    Technical trading systems take into account a set of different risk factors and have predefined rules for constantly monitoring risk budgets.
  • Independence
    Performance does not depend on key people and their personal condition (e.g. illness) and emotions
  • Diversification
    The trading strategy can be applied to a variety of markets.
  • High capacity
    Possibility to simultaneously trade a multitude of different markets.

Risks of technical trading systems

  • Historical data
    The development of technical trading systems is usually based on historical data and tested via different simulations and real trading. Past performance is not a reliable indicator for future results and therefore there is no guarantee for any profit.
  • Sideways markets without any significant trends
    Markets without distinctive trends can lead to false signals and this will increase trading fees. Losses may occur.
  • Computer breakdown
    During a breakdown of computer systems the trading may be interrupted and necessary trades can e.g. either not be executed or executed only with delay.
  • Discretionary element
    Regardless of a high degree of automated computer based processes some interventions by the investment manager are not completely avoidable. Above all the selection of markets (inclusion or exclusion of markets) and decisions about (necessary) modifications of the trading system must be based on discretionary decisions.

Elements of a trading system

Many traders fail by the attempt to implement a trading system because they are seeking for the Holy Grail, a special indicator which identifies every trend and also signalizes the ideal entry and exit events. It would be great if markets would work that simple. . In fact it has proven much more efficient to focus on the analysis of every single element of a trading system and to finally combine them to an overall solution.


Entry (opening of a position) 

There is a wide range of indicators which basically can be used to identify trends. The tricky part is to find an Entry-Logic which identifies a new trend as early as possible and at the same time avoids too much false signals. Examples for such indicators are: Moving Average Crossover, Channel Breakout, Stochastic Crossover, Pattern Recognition or Commodity Channel Index.


The risk of an open position can be defined by two ways:

Initial risk: Difference between the market entry price and the Risk-Control-Stop price

Equity risk: Difference between market price and the Stop defined by the Exit-strategy

Trading systems are using fixed Stops (e.g. defined percentages) as well as Stops calculated by market volatility to define the maximum tolerable loss in the respective position (Risk Budget). The difficulty to find the ideal Stop is to achieve the right balance between setting a tight limit to reduce the single market risk and to avoid to be stopped out too early .

Money Management

The objective of Money Management (Risk Management) is finding an optimal balance between portfolio risk and return potential. A good trading system targets to preserve capital rather than maximise profits. Due to the leverage embedded in futures contracts it is possible to move a high market exposure with limited capital. Therefore it is highly important to determine the size of a position by the risk related to the position and not by its possible returns.

What are the main questions related to Money Management?

  • What is the risk of an investment in a market (monitoring of volatility)?
  • How much of the fund´s total risk can be invested into that market?
  • What is the maximum risk in all other markets that might be highly correlated? 
  • What shall be the overall risk of the portfolio?

The main goal of sound Money Management is mainly the control of risk. Important figures to evaluate portfolio risk are the Maximum Drawdown, the Standard Deviation (average percentage of variation). Another useful measure is "Margin to Equity", which reflects the percentage of the total capital (margin) used as collateral at brokers or futures exchanges. Futures funds limit their margin to a certain percentage of their total capital available. The Margin to Equity Ratio is commonly used as a measure to compare the risk level, different Managed Futures managers are ready to take.

The advantage of technical trading systems is the high level of risk control:

  • diversification through the variety of markets traded reduces dependency on a single market
  • numerous possibilities to trade allows to reduce the risk of a single trade to marginal levels 
  • the historical reviewability helps in getting valuable data about the risk of a strategy and allows conclusions for the setup of the risk management systems 
  • correlation analysis shows the total risk of high correlated markets (e.g. bond markets) 


The secret of a successful trading strategy is, beside Money Management, a well elaborated Exit-Logic. The well known slogan „Ride your winners, cut your losses“ can only be realized by few traders and investors, because it is part of human nature to take profits quickly and to avoid losses. The use of a technical trading system helps to avoid this typical mistake, because emotions are not part of the highly automated and standardised systematic approach.

Re-Entry Rules

Only the use of Re-Entry-Rules completes a trading system: If a position in a market gets closed, a point of Re-Entry has to be defined. Such rules are developed to ensure not to miss long term trends only because of bad timing at the first attempt.

Risk of Over-Optimisation (“Curve-Fitting”)

Technical trading requires the analysis of historical data. The common hypothesis "the better the result of a simulation, the better the strategy", should be handled with great care. If this hypothesis was true, everyone could become wealthy who is able to implement a trading strategy, which has been successful in the past: This is clearly not the case and unfortunately one has to admit that based on modern technology it is more than simple to create a methodology which has done very well in a set of historic data.

Most implementations follow the same scenario: A trader buys the latest available testing software, adds some indicators and optimizes various system parameters. This approach is know as „Curve Fitting“.

Impressed by the fantastic historical results the trader starts to trade the program. After the first sequences of false signals the trader has doubts and starts to optimize the already optimized parameters again. This process will be repeated until the trader loses his patience or he runs out of money. Curve Fitting is a great danger, because thousands of parameters can be analysed by using a computer and it’s very likely that some of them look profitable, but it’s very unlikely that the future replicates the past exactly.

While developing the smn trading system we have been very careful to avoid such optimization failures. Every market is treated the same way. We have proofed the significance of our functions and parameters by long time real trading experiences rather than by tremendous historical simulated return.

A trading strategy using trend following

Experience has shown that by using trend following programs significant revenues are achievable on a long term basis. Trend following assumes that markets frequently show strong trends whereas during phases of lateral trends it is tough to avoid false signals. The major challenge in developing a successful trend following system is to generate as few as possible false signals during lateral trends by still catching the significant trends to gain high profits. A good trend following program must be primarily designed to not miss the profits from significant trends. Good opportunities often exist only once a year. Hence it is crucial to be disciplined and to follow strict rules when executing the generated signals. Any trend missed has a negative impact to the overall revenue.

Since we cannot look into the future false signals can’t be avoided. The long term hit ratio of a trading system typically is marginally below 50% and the ratio from an average profit to an average loss is between 2:1 and 3:1 (Source: SMN; calculation based on historical trade data of SMN Diversified Futures Fund; 10 years look back period) which means that on average the system gains twice to triple as much on a profitable trade then it loses in a false trade.

Trend following vs. contrarian trading

Profits from trend following can only be achieved in a volatile market environment in connection with an identified trend. Anti-cyclical (contrarian) trading – enter into positions – is problematic because it is very difficult to predict or find the turning points in a market. The probability to enter a position on high or low is outmost impossible but catching a trend sooner or later is much more likely from a probability point of view.

Trend following vs. efficient market theory1

The well known “Efficient Market Theory” states that all information available is already priced into current market prices. According to this hypothesis it is impossible for a market participant to gain above average profits. As a result no advantages, neither by technical nor by fundamental analysis, could be achieved to other market participants.

We strongly believe that this theory is not valid for all markets and all market environments.. Market volatility is based e.g. on human reactions (greed, panic), news can be interpreted differently by different individuals and it should be assumed that an experienced trader has a better chance to succeed than a newcomer. All these aspects could not exist if all markets were efficient.

Statistical studies show that markets do not follow a normal, Gaussian, distribution over a longer period. Would the theory be valid, markets would offer far less trending phases, statistically. Drastic price slumps – e.g. 1987, 2001 to 2003 or 2007/2008 – would not even exist.

Short term price fluctuations occur by more or less incidental buy or sell activities of market participants. Big moves on the contrary are usually caused by important events (e.g. interest policy of central banks, economic downturn – boom). In the long run markets are definitely ddriven by economic fundamentals. Therefore it is possible to earn extraordinary profits by using a long term trend following trading strategy .

1) The efficient-market hypothesis “EMH” was developed by professor Eugene Fama as a mathematical-statistical theory of economics and summarized in 1970.