The basis of a winning strategy and its implementation in development lies in the effectiveness of the trading idea. The idea is the essential basis on which to work to implement or develop the strategy on one or more financial instruments. The idea must have already been applied manually on real financial markets or be new but logical. It must also be functional on instruments of the same family at the same time; a crude idea must be able to function indiscriminately, except for possible variables linked to the value of the single instrument, on products of the same category; for example: S&P, NASDAQ and DOW JONES.

New ideas must respond to a selection of logical criteria. The lack of these criteria would give the strategy random or too random results not worthy of consideration.

Of the raw strategy over 8/12 years without any kind of optimization using specific software with historical data and without any filter. If the raw test result is already good and stable, you can move on to the next step.

The positive results are analyzed to verify with a series of parameters, above all the stability of the profit and the drawdown periods with an initial risk analysis. If the parameters respect our coefficients it will be possible to proceed with the further implementation phases.

Sometime filters related to the “Theory of time spans” are introduced. They will serve to immediately improve the results of the strategy which automatically incorporates the extraordinary contributions of this theory.

The technical filters will serve to select a part of the operation within the sentiment deriving from them.

With the application of our mathematical and statistical filters, we logically intervene within the range of the trading process of the financial instrument

In this step, some of our proprietary techniques are applied for closing profit operations and for exiting in STOP LOSS in addition to the use of the AC STOP almost always by default.

In this second back-testing, a new check of the final results of the strategy is carried out simultaneously with a risk calculation. Only if satisfactory will we proceed to the next step.

At this point, action is taken to verify whether the strategy could be positively affected by artificial intelligence and machine learning applications; in fact, a strategy that is already very effective, logical and not hyper-optimized, will hardly receive a contribution from these two scientific branches; therefore it will actually be verified if their use can give a real contribution of improvement or it will be just completely random.

The results are checked again by checking the effectiveness of the strategy in all phases of the market: this third and final back-testing will be the final one to define the effectiveness of the strategy.

Calculation of the input sizes with the introduction of quantitative techniques: in this step the possible input sizes will be established which are part of some of our proprietary techniques aimed at improving the drawdown of the strategy.

Here we proceed with the analysis of the strategy with respect to the execution of limit or stop orders; each strategy prevails over one another with the consequent difference in sustainability.

In this phase, proprietary stress tests are carried out which define the results of the back-testing with great confidence. The performance resulting from the back-testing will be very close to that of the real market

The strategy will be codified for the automatic passage of orders in the real market and consequent evaluation of the maximum possible volumes of use of the same with respect to the financial instrument used

We support the entire life cycle of systematic trading, from development and construction of the programmatic strategy to back-testing, live simulation and automated algorithmic management of orders by integrating all processes with advanced proprietary studies

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