CFD. Kurz für englisch "Contract for Difference", Differenzkontrakt. Ein CFD ist eine Zahlungsvereinbarung, deren Wert sich aus der Differenz der Kurse des. Was ist CFD-Trading? Hier finden Sie eine ausführliche Erklärung zum Handel mit CFDs in einfachen und verständlichen Worten. Der Einstieg in den CFD Handel sollte erst nach gründlicher Vorbereitung erfolgen. Für die meisten Anleger sind vollständig außerbörsliche Handelsplattformen.
Fällt der Basiskurs gar noch weiter, entstehen für den Anleger erhebliche Nachschusspflichten. Durch die Presse ging ein Fall, in dem ein deutscher Anleger im Jahr 2.
Dies erhöht jedoch das Totalverlustrisiko für den Anleger, da schon kurzzeitige, rein vorübergehende Kursschwankungen zum zwangsweisen Exit aus einer gehaltenen Position und damit zum Totalverlust der eingesetzten Sicherheit führen.
Mit Differenzkontrakten können Anleger sowohl auf steigende als auch auf fallende Kurse setzen siehe auch Long und Short.
Daher besteht noch mehr als bei standardisierten Anlageformen Anleihen, Aktien, Optionsscheinen die Gefahr, dass der Anleger die genauen Konditionen nicht versteht, und deswegen für ihn unvorteilhafte Anlageentscheidungen trifft.
Abschlag gegenüber dem Kapitalmarktzins und die Kommissionen bei bis zu 0,2 Prozent. Bezogen auf die Sicherheitsleistung betrugen die laufenden Finanzierungskosten dann bis zu 2.
Da CFDs in der Regel gehebelte Geschäfte sind, können schon in kurzer Zeit sehr hohe Verluste entstehen, die sogar weit über den anfänglichen Einsatz hinausgehen können.
Dies birgt das Potential, Aufträge von Kunden zu einem wesentlich ungünstigeren Kurs auszulösen, um dadurch mit einer erhöhten Gewinnspanne ein Gegengeschäft einzugehen.
Wegen der hohen Verlustrisiken kritisieren die europäischen Aufsichtsbehörden für Wertpapiere und Banken diese Derivate als hoch spekulativ und raten vor allem unerfahrenen Klein- und Privatanlegern davon ab.
Januar die Abwicklung der Entschädigungsfälle für Gläubiger, die bis zu Schon zuvor war der unregulierte Handel kritisiert worden.
Aber auch dieses Angebot stand von Anfang an in der Kritik. In diesen Fällen muss der Anleger seine Gewinne eigenverantwortlich in seiner persönlichen Steuererklärung angeben.
Gewinne und Verluste können dabei in aller Regel verrechnet werden, sodass nur die tatsächlichen Gewinne versteuert werden. Auch mit Optionsscheinen , Futures und Hebelzertifikaten können Basiswerte mit hohem Hebel gehandelt werden.
Thus, high order Gauss integration quadratures are employed, since they achieve the highest accuracy with the smallest number of computations to be carried out.
At the time there are some academic CFD codes based on the spectral element method and some more are currently under development, since the new time-stepping schemes arise in the scientific world.
In the boundary element method, the boundary occupied by the fluid is divided into a surface mesh. High-resolution schemes are used where shocks or discontinuities are present.
Capturing sharp changes in the solution requires the use of second or higher-order numerical schemes that do not introduce spurious oscillations.
This usually necessitates the application of flux limiters to ensure that the solution is total variation diminishing.
In computational modeling of turbulent flows, one common objective is to obtain a model that can predict quantities of interest, such as fluid velocity, for use in engineering designs of the system being modeled.
For turbulent flows, the range of length scales and complexity of phenomena involved in turbulence make most modeling approaches prohibitively expensive; the resolution required to resolve all scales involved in turbulence is beyond what is computationally possible.
The primary approach in such cases is to create numerical models to approximate unresolved phenomena. This section lists some commonly used computational models for turbulent flows.
Turbulence models can be classified based on computational expense, which corresponds to the range of scales that are modeled versus resolved the more turbulent scales that are resolved, the finer the resolution of the simulation, and therefore the higher the computational cost.
If a majority or all of the turbulent scales are not modeled, the computational cost is very low, but the tradeoff comes in the form of decreased accuracy.
In addition to the wide range of length and time scales and the associated computational cost, the governing equations of fluid dynamics contain a non-linear convection term and a non-linear and non-local pressure gradient term.
These nonlinear equations must be solved numerically with the appropriate boundary and initial conditions. An ensemble version of the governing equations is solved, which introduces new apparent stresses known as Reynolds stresses.
This adds a second order tensor of unknowns for which various models can provide different levels of closure. It is a common misconception that the RANS equations do not apply to flows with a time-varying mean flow because these equations are 'time-averaged'.
In fact, statistically unsteady or non-stationary flows can equally be treated. There is nothing inherent in Reynolds averaging to preclude this, but the turbulence models used to close the equations are valid only as long as the time over which these changes in the mean occur is large compared to the time scales of the turbulent motion containing most of the energy.
Large eddy simulation LES is a technique in which the smallest scales of the flow are removed through a filtering operation, and their effect modeled using subgrid scale models.
This allows the largest and most important scales of the turbulence to be resolved, while greatly reducing the computational cost incurred by the smallest scales.
Regions near solid boundaries and where the turbulent length scale is less than the maximum grid dimension are assigned the RANS mode of solution.
As the turbulent length scale exceeds the grid dimension, the regions are solved using the LES mode. Therefore, the grid resolution for DES is not as demanding as pure LES, thereby considerably cutting down the cost of the computation.
Direct numerical simulation DNS resolves the entire range of turbulent length scales. This marginalizes the effect of models, but is extremely expensive.
The coherent vortex simulation approach decomposes the turbulent flow field into a coherent part, consisting of organized vortical motion, and the incoherent part, which is the random background flow.
The approach has much in common with LES, since it uses decomposition and resolves only the filtered portion, but different in that it does not use a linear, low-pass filter.
Instead, the filtering operation is based on wavelets, and the filter can be adapted as the flow field evolves. Goldstein and Vasilyev  applied the FDV model to large eddy simulation, but did not assume that the wavelet filter completely eliminated all coherent motions from the subfilter scales.
This approach is analogous to the kinetic theory of gases, in which the macroscopic properties of a gas are described by a large number of particles.
PDF methods are unique in that they can be applied in the framework of a number of different turbulence models; the main differences occur in the form of the PDF transport equation.
The PDF is commonly tracked by using Lagrangian particle methods; when combined with large eddy simulation, this leads to a Langevin equation for subfilter particle evolution.
The vortex method is a grid-free technique for the simulation of turbulent flows. It uses vortices as the computational elements, mimicking the physical structures in turbulence.
Vortex methods were developed as a grid-free methodology that would not be limited by the fundamental smoothing effects associated with grid-based methods.
To be practical, however, vortex methods require means for rapidly computing velocities from the vortex elements — in other words they require the solution to a particular form of the N-body problem in which the motion of N objects is tied to their mutual influences.
A breakthrough came in the late s with the development of the fast multipole method FMM , an algorithm by V. Rokhlin Yale and L. This breakthrough paved the way to practical computation of the velocities from the vortex elements and is the basis of successful algorithms.
They are especially well-suited to simulating filamentary motion, such as wisps of smoke, in real-time simulations such as video games, because of the fine detail achieved using minimal computation.
Software based on the vortex method offer a new means for solving tough fluid dynamics problems with minimal user intervention.
Among the significant advantages of this modern technology;. The vorticity confinement VC method is an Eulerian technique used in the simulation of turbulent wakes.
It uses a solitary-wave like approach to produce a stable solution with no numerical spreading. VC can capture the small-scale features to within as few as 2 grid cells.
Within these features, a nonlinear difference equation is solved as opposed to the finite difference equation.
VC is similar to shock capturing methods , where conservation laws are satisfied, so that the essential integral quantities are accurately computed.
The Linear eddy model is a technique used to simulate the convective mixing that takes place in turbulent flow.
It is primarily used in one-dimensional representations of turbulent flow, since it can be applied across a wide range of length scales and Reynolds numbers.
This model is generally used as a building block for more complicated flow representations, as it provides high resolution predictions that hold across a large range of flow conditions.
The modeling of two-phase flow is still under development. Different methods have been proposed, including the Volume of fluid method , the Level set method and front tracking.
This is crucial since the evaluation of the density, viscosity and surface tension is based on the values averaged over the interface. Discretization in the space produces a system of ordinary differential equations for unsteady problems and algebraic equations for steady problems.
Implicit or semi-implicit methods are generally used to integrate the ordinary differential equations, producing a system of usually nonlinear algebraic equations.
Applying a Newton or Picard iteration produces a system of linear equations which is nonsymmetric in the presence of advection and indefinite in the presence of incompressibility.
Such systems, particularly in 3D, are frequently too large for direct solvers, so iterative methods are used, either stationary methods such as successive overrelaxation or Krylov subspace methods.
Krylov methods such as GMRES , typically used with preconditioning , operate by minimizing the residual over successive subspaces generated by the preconditioned operator.
Multigrid has the advantage of asymptotically optimal performance on many problems. Traditional [ according to whom? By operating on multiple scales, multigrid reduces all components of the residual by similar factors, leading to a mesh-independent number of iterations.
For indefinite systems, preconditioners such as incomplete LU factorization , additive Schwarz , and multigrid perform poorly or fail entirely, so the problem structure must be used for effective preconditioning.
CFD made a major break through in late 70s with the introduction of LTRAN2, a 2-D code to model oscillating airfoils based on transonic small perturbation theory by Ballhaus and associates.
CFD investigations are used to clarify the characteristics of aortic flow in detail that are otherwise invisible to experimental measurements.
To analyze these conditions, CAD models of the human vascular system are extracted employing modern imaging techniques.
A 3D model is reconstructed from this data and the fluid flow can be computed. Blood properties like Non-Newtonian behavior and realistic boundary conditions e.
Therefore, making it possible to analyze and optimize the flow in the cardiovascular system for different applications. In a more recent trend, simulations are also performed on GPU's .
These typically contain slower but more processors. For CFD algorithms that feature good parallellisation performance i.
Lattice-Boltzmann methods are a typical example of codes that scale well on GPU's. From Wikipedia, the free encyclopedia. This article includes a list of references , but its sources remain unclear because it has insufficient inline citations.
Please help to improve this article by introducing more precise citations.
CFDs cannot be used to reduce risk in the way that options can. Similar to options, covered warrants have become popular in recent years as a way of speculating cheaply on market movements.
CFDs costs tend to be lower for short periods and have a much wider range of underlying products. In markets such as Singapore, some brokers have been heavily promoting CFDs as alternatives to covered warrants, and may have been partially responsible for the decline in volume of covered warrant there.
This is the traditional way to trade financial markets, this requires a relationship with a broker in each country, require paying broker fees and commissions and dealing with settlement process for that product.
With the advent of discount brokers, this has become easier and cheaper, but can still be challenging for retail traders particularly if trading in overseas markets.
Without leverage this is capital intensive as all positions have to be fully funded. CFDs make it much easier to access global markets for much lower costs and much easier to move in and out of a position quickly.
All forms of margin trading involve financing costs, in effect the cost of borrowing the money for the whole position. Margin lending , also known as margin buying or leveraged equities , have all the same attributes as physical shares discussed earlier, but with the addition of leverage, which means like CFDs, futures, and options much less capital is required, but risks are increased.
The main benefits of CFD versus margin lending are that there are more underlying products, the margin rates are lower, and it is easy to go short.
Even with the recent bans on short selling, CFD providers who have been able to hedge their book in other ways have allowed clients to continue to short sell those stocks.
Some financial commentators and regulators have expressed concern about the way that CFDs are marketed at new and inexperienced traders by the CFD providers.
In particular the way that the potential gains are advertised in a way that may not fully explain the risks involved.
For example, the UK FSA rules for CFD providers include that they must assess the suitability of CFDs for each new client based on their experience and must provide a risk warning document to all new clients, based on a general template devised by the FSA.
The Australian financial regulator ASIC on its trader information site suggests that trading CFDs is riskier than gambling on horses or going to a casino.
There has also been concern that CFDs are little more than gambling implying that most traders lose money trading CFDs. There has also been some concern that CFD trading lacks transparency as it happens primarily over-the-counter and that there is no standard contract.
This has led some to suggest that CFD providers could exploit their clients. This topic appears regularly on trading forums, in particular when it comes to rules around executing stops, and liquidating positions in margin call.
Although the incidence of these types of discussions may be due to traders' psychology where it is hard to internalise a losing trade and instead they try to find external source to blame.
This is also something that the Australian Securities Exchange, promoting their Australian exchange traded CFD and some of the CFD providers, promoting direct market access products, have used to support their particular offering.
They argue that their offering reduces this particular risk in some way. If there were issues with one provider, clients could easily switch to another.
Some of the criticism surrounding CFD trading is connected with the CFD brokers' unwillingness to inform their users about the psychology involved in this kind of high-risk trading.
Factors such as the fear of losing that translates into neutral and even losing positions  become a reality when the users change from a demonstration account to the real one.
This fact is not documented by the majority of CFD brokers. Criticism has also been expressed about the way that some CFD providers hedge their own exposure and the conflict of interest that this could cause when they define the terms under which the CFD is traded.
One article suggested that some CFD providers had been running positions against their clients based on client profiles, in the expectation that those clients would lose, and that this created a conflict of interest for the providers.
A number of providers have begun offering CFDs tied to cryptocurrencies. The volatility of the cryptocurrency markets and the leverage of CFDs has proved a step too far in some cases with Coindesk  reporting that UK based Trading was forced to suspend trading of Bitcoin Cash CFDs in November resulting in significant losses for some clients when trading recommenced and the market had moved against them.
CFDs, when offered by providers under the market maker model, have been compared  to the bets sold by bucket shops , which flourished in the United States at the turn of the 20th century.
These allowed speculators to place highly leveraged bets on stocks generally not backed or hedged by actual trades on an exchange, so the speculator was in effect betting against the house.
Bucket shops, colourfully described in Jesse Livermore 's semi-autobiographical Reminiscences of a Stock Operator , are illegal in the United States according to criminal as well as securities law.
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Uw CFD broker financiert voor u de positie en vraagt een deel van de waarde daarvan als onderpand om eventuele verliezen af te dekken.
Leverage maakt dat u op CFD's veel hogere rendementen kunt boeken dan op andere beleggingen. Wanneer u in aandelen handelt, kunt u nooit meer verdienen dan de waardestijging van het aandeel in een bepaalde periode.
Als u voor EUR. Als u echter met EUR. Op dezelfde manier betekent een hogere leverage ook een hoger risico. Het is daarom van belang om weloverwogen beslissingen te nemen en uw maximale verlies altijd te beperken door middel van een 'stop loss'.
U kunt contracts for difference zowel 'long' als 'short' afsluiten. Een long contract wil zeggen dat u speculeert op waardestijging van het onderliggende goed.
Het is alsof u het onderliggende goed gekocht had. Als de waarde bij verkoop hoger is dan bij aankoop, krijgt u het verschil uitgekeerd.
Het voordeel van long en short contracten is dat u zowel bij stijgende als bij dalende koersen geld kunt verdienen. En vaak laten markten in een periode zowel stijgingen als dalingen zien.
Als u in de dalen long contracten weet af te sluiten en op de toppen short contracten, dan profiteert u dubbel. Omdat u door leverage met CFD's in veel grotere posities kunt handelen dan u normaal zou kunnen met uw vermogen, worden door de meeste CFD brokers financieringskosten in rekening gebracht.
Dit zijn de kosten van het kapitaal dat nodig zou zijn om uw positie te kopen. Als u een long positie neemt betaalt u de financieringskosten aan uw broker.
Als u een short positie neemt betaalt de broker u. De financieringskosten hebben voor contracts for difference doorgaans de orde van grootte van een paar procent per jaar.
De kosten worden meestal per dag berekend, maar pas na de eerste 48 uur dat u uw positie open hebt. Omdat het om samengestelde interest draait kunt u het percentage niet simpelweg door het aantal dagen in een boekjaar delen.
U kunt als volgt de financieringskosten berekenen. Let op, hier volgt een stuk lastige wiskunde!
Klik hier om dit gedeelte over te slaan. Vervolgens trekt u van het resultaat 1 af en drukt het getal weer uit als een percentage.
Als u dit percentage vermenigvuldigt met de totale grootte van uw positie krijgt u de financieringskosten per dag. De huidige koers is EUR. Door de 50x leverage heeft u echter slechts EUR.
Als u na 48 uur de positie nog open heeft, trekt uw broker deze 39 ct. Omgekeerd, had u een short positie ingekomen, dan had u dit bedrag dagelijks bijgeschreven gekregen.
In de praktijk hoeft u eigenlijk geen aandacht te besteden aan de financieringskosten. Omdat u posities meestal slechts korte tijd open houdt, blijven de financieringskosten laag en binnen 48 uur zelfs 0.
Om succesvol te handelen is het belangrijker om uw koersdoelen goed te kiezen. Dat wil zeggen, op het moment dat u een CFD koopt besluit u:.
De meest gemaakte fout door amateur-traders is om te snel winst te nemen en bang te zijn voor verlies.