GesTrading Management : GT Quantitative Absolute Return Program Need help with terms? Snapshot Strategy Charts Statistics & Ratios Performance Tables Badges Show All Year-to-Date N / A Feb Performance -11.63% Min Investment $ 100k Mgmt. Fee 2.00% Perf. Fee 20.00% Annualized Vol 25.63% Sharpe (RFR=1%) -0.46 CAROR - Assets $ 78k Worst DD -27.73 S&P Correlation -0.37 Add Alert Add to Blender Add to Portfolio Add to Watchlist Print Page Growth of 1,000 - VAMI Monthly Performance Export Data Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec YTD DD Past performance is not necessarily indicative of future results. The risk of loss in trading commodity futures, options, and foreign exchange ("forex") is substantial. Period Returns Program / Index Feb Qtr YTD 1yr 3yr 5yr 10yr Since10/2012 GT Quantitative Absolute Return Program -11.63 - - - - - - -17.82 S&P 500 4.31 - - - - - - 175.80 +/- S&P 500 -15.94 - - - - - - -193.63 Strategy Description SummaryThe overall goal of GT Quantitative Absolute Return Program (“GTQA”) is to achieve account appreciation through the use of an on exchange futures and options investment strategy. GesTrading Management, LLC’s objective will be to obtain, relatively high risk-adjusted returns through... Read More Account & Fees Type Managed Account Minimum Investment $ 100k Trading Level Incremental Increase $ 0k CTA Max Funding Factor 1.50 Management Fee 2.00% Performance Fee 20.00% Average Commission $12.00 Available to US Investors Yes Subscriptions High Water Mark Yes Subscription Frequency Daily Redemption Frequency Daily Investor Requirements Any Investor Lock-up Period 0 Trading Trading Frequency 3000 RT/YR/$M Avg. Margin-to-Equity 35% Targeted Worst DD -20.00% Worst Peak-to-Trough 17.59% Sector Focus Diversified Traders Holding Periods Over 12 Months 0% 4-12 Months 0% 1-3 Months 0% 1-30 Days 50.00% Intraday 50.00% Decision-Making Discretionary 0% Systematic 100.00% Strategy Trend-following 80.00% Other 20.00% Composition Stock Indices 50.00% Currency Futures 25.00% Energy 25.00% SummaryThe overall goal of GT Quantitative Absolute Return Program (“GTQA”) is to achieve account appreciation through the use of an on exchange futures and options investment strategy. GesTrading Management, LLC’s objective will be to obtain, relatively high risk-adjusted returns through the use of automated, computer based trading systems. The trading strategy will actually consist of several “micro” automated computer strategies, coupled together, running simultaneously, to create a “macro” trading strategy called the GT Quantitative Absolute Return Program.Investment StrategyGesTrading intends to implement a “black box” trading strategy. In other words the trading strategy will run via computer with no human intervention. Accordingly our trading will be non-discretionary and based on the trading parameters of the models being traded. The only discretion of any type in the system will be the real time monitoring of trades. Human intervention within the trading system will only occur if a system is not functioning as it has been designed. All trading signals will be sent automatically to the execution platform by our trade computers and then executed in the market without any human intervention. A Strategy Made of Strategies GesTrading Management intends to combine four to twelve of its proprietary computer models together to create the overall strategy. Each of these models will represent a standalone systematic; black box computer based trading strategy. In other words the GTQA will consist of a number of micro strategies that trade in unison to make a complete macro strategy. Each of these micro strategies would be classified as "Short Term” and “Systematic,” accordingly the GTQA would be classified as a “Short Term Non-Discretionary Systematic” trading system. The purposes of blending a variety of computerized trading models together will be to attempt to smooth returns and spread risk between various futures contract markets. Each of the micro strategies will typically hold positions for a few minutes or days. On occasion they may call for certain positions to remain open for a few weeks at a time but this will be relatively infrequent within the overall program. GesTrading Management will design and implement micro computer strategies from each of the following futures markets: Equity Index Fixed Income General Commodity (Agricultural, Energy, Metals, Softs, Meats etc.) Foreign Currency Micro Strategy Selection In our experience even the best black box trading strategies will eventually stop performing as market conditions change. To reduce this risk, as noted above, we will run a variety of micro strategies in unison to create the macro GTQA. To determine which strategies should be included within the macro GTQA strategy at any given time GesTrading Management will be continuously monitoring the market. Through this monitoring we will be continuously tracking all of our strategies in order to improve and adapt them. Rather than making changes in real time within our systems we first test our adjustments against historical data that we believe most clearly matches the then prevailing market conditions. Then, after we have shown that the adjustment has performed well during similar market conditions, we may choose to implement our adjustments. In the event no similar market conditions exist we may choose to remove the system from the overall macro strategy blend. Under such a scenario a removed strategy will be replaced with a strategy that we believe will perform better relative to the new market condition. To ensure that we do no run out of micro strategies to fit within the GTQA we are constantly developing new strategies. This allows us to replace older and deteriorated strategies when necessary. It also allows us to add complimentary strategies to our existing strategy portfolio to increase market diversification. Each time we develop a strategy we attempt to use different mathematical and statistical methods both proprietary and well known (such as the Monte Carlo method) to test them. Market Diversification The first step to managing risk, according to modern portfolio theory is market diversification. Thus through our selection of micro strategies that trade a variety of contract markets we believe we have diversified our risk well across the futures market. We believe this as the use of our mathematical trading algorithms allows us to diversify in 3 different ways: Market Diversification: We diversify by trading a variety of liquid futures markets - S&P500, DAX, Crude Oil etc. Different trading philosophies and ideals: Each of our micro trading strategies presents a different trading idea to the overall macro strategy. We believe this will allow GTQA to capture different types of market inefficiencies. Some may be trend-following, mean reverting, swing, etc. Different Time Frames: The differences in time consideration between micro strategies should allow us to capture market inefficiencies. Specifically technical trading strategies may benefit from various support and resistance levels which appear uniquely on 1, 5, 10, 30, 60 etc. minute charts. When designing our micro strategies and determining how to combine them into our macro strategy, the GTQA, we also have an opportunity to weight them. In other words we tend to give less significance to the strategies with what we believe to be the highest risk trades, even if the strategy would be best performer in absolute terms. We believe that over time this weighting will make the GTQA portfolio of micro strategies more robust and stable. This also allows us to take into consideration market correlation between asset classes which in theory should smooth the GTQA’s overall return profile. Risk ManagementRegardless of whether markets rise or fall we will attempt to obtain annual absolute return across different futures asset classes. By combining programs that target different technical trading trends within the equity index, fixed income, general commodity, and foreign currency markets it is our belief that we will be able to smooth the GTQA’s overall return profile. Our internal research has shown that trading across several markets using similar strategies at the same time increases the probability of producing absolute returns. To protect against adverse market moves our strategies will always require stop losses to be in place when orders are executed. Our stop loss levels are generally volatility dependent to ensure a better adaptation to changing market conditions. These levels are programmed into our systems based on the back testing we do prior to deciding to enlist a micro strategy within GTQA. Although stop loss and/or resting orders may not always protect against loss within fast moving or gapping markets, we believe they are the best way to attempt to protect against adverse market moves during most market conditions. GesTrading Management also believes that every trading strategy has a maximum trading capacity. In other words each system can only trade a certain number of contracts without impacting the overall macro results of the GTQA negatively. We believe that this limit is reached when the number of contracts the overall macro GTQA strategy trades in a specific market becomes so large that the market cannot absorb enough contracts at the overall price parameters called for within the GTQA. To combat this if the GTQA strategy reaches its capacity limit, we have developed a proprietary algorithm that allows for us to manipulate the capacity of the micro strategies with a minimal effect on the overall macro strategy’s performance. Technological Risk Management In addition at all times an actual human will be continuously monitoring trade execution, open positions and orders, and generally monitoring the GTQA for any errors. Such errors may include incidents related to a loss of internet, power, connectivity to the FCM, or any other factor which might cause our trading systems to improperly execute orders for your account. In order to reduce the risk of error, although the systems will be monitored at all times, GesTrading Management uses third party servers to host its trading systems. These servers have been specifically designed for strategy hosting. It is on these servers where our trading algorithms (micro strategies) are hosted and encrypted. The strategies will be running on multiple machines further reducing the risk of a technical failure. Compare to: {{result.name}} {{result.description}} Index: Chart Type: AUM & Cumulative Returns Cumulative Returns Distribution Rolling Past performance is not necessarily indicative of future results. The risk of loss in trading commodity futures, options, and foreign exchange ("forex") is substantial. Compare to: Index: Select an Index Hang Seng Russell 2000 DAX FTSE 100 S&P 500 Index 10-Year Note VIX S&P 500 Monthly Annual Reward Average RoR: Max Gain: Gain Frequency: Average Gain: Gain Deviation: Risk Standard Deviation: Worst Loss: Loss Frequency: Average Loss: Loss Deviation: Reward/Risk Sharpe Ratio: (RF=1%) Skewness: Kurtosis: Reward Compound RoR: Average RoR: Max Gain: Gain Frequency: Average Gain: Gain Deviation: Risk Standard Deviation: Worst Loss: Loss Frequency: Average Loss: Loss Deviation: Reward/Risk Sharpe Ratio: (RF=1%) Skewness: Kurtosis: Past performance is not necessarily indicative of future results. The risk of loss in trading commodity futures, options, and foreign exchange ("forex") is substantial. Note: Figures shown in the Monthly column are the greatest figures (or worst for losses/drawdowns) for any particular month. The Annual figures are the greatest for any calendar year. Drawdown Report Depth Length (Mos.) Recovery (Mos.) Peak Valley -27.73 15 - 11/1/2012 2/1/2014 Show More Consecutive Gains Run-up Length (Mos.) Start End 16.06 1 6/1/2013 6/1/2013 13.71 2 10/1/2012 11/1/2012 3.64 2 10/1/2013 11/1/2013 3.24 1 2/1/2013 2/1/2013 Show More Consecutive Losses Run-up Length (Mos.) Start End -18.25 3 12/1/2013 2/1/2014 -13.72 3 3/1/2013 5/1/2013 -10.81 3 7/1/2013 9/1/2013 -7.49 2 12/1/2012 1/1/2013 Show More Time Windows Analysis 1 Month3 Month6 Month Number of Periods17.0015.0012.00 Percent Profitable35.2946.6725.00 Average Period Return-0.89-2.43-5.34 Average Gain6.093.947.31 Average Loss-4.70-8.01-9.55 Best Period16.0611.228.09 Worst Period-12.79-18.25-17.60 Standard Deviation7.407.768.74 Gain Standard Deviation6.623.620.77 Loss Standard Deviation4.535.765.00 Sharpe Ratio (1%)-0.13-0.35-0.67 Average Gain / Average Loss1.290.490.77 Profit / Loss Ratio0.710.430.26 Downside Deviation (10%)5.387.8111.18 Downside Deviation (5%)5.187.209.61 Downside Deviation (0%)5.137.059.23 Sortino Ratio (10%)-0.24-0.47-0.70 Sortino Ratio (5%)-0.19-0.37-0.61 Sortino Ratio (0%)-0.17-0.35-0.58 Top Performer Badges Index Award Type Rank Performance Period Past performance is not necessarily indicative of future results. The risk of loss in trading commodity futures, options, and foreign exchange ("forex") is substantial. x {{title}} x {{title}} Add Cancel