forex

An algorithmic trader needs to be mindful of potential fraud by the broker. Part of the weekly algorithm should include a check to see if the amount of transaction errors when the trader is losing money occurs in the same proportion as when the trader would have made money.

While the growth in electronic trading has stimulated the application of Algorithmic Trading, it has lead to some abuses of the term as well as the scale and mode of its application, more so perhaps in the context of foreign exchange trading as in any other asset class. In part this may be explained because the buy side institutions and proprietary trading groups increasingly demand the ability to develop and customise complex trading strategies in place of ‘off the shelf’ algorithms. They require the ability to access not just multiple markets, but to trade across asset classes, through a range of applications.

Algorithmic trading—placing a buy or sell order of a defined quantity into a quantitative model that automatically generates the timing of orders and the size of orders based on goals specified by the parameters and constraints of the algorithm—is not applied exclusively to programme trades to achieve better execution in the foreign exchange asset class. The term is applied to facilities such as black box, white box trading, quantitative trading and programme trading. While they are all perceived as a mechanism, which theoretically could one day dis-intermediate the human trader entirely. They are all different but share commonality only to the extent they deploy algorithms in their application:

• A black box is a closed system as far as understanding about how it works. The user has to have blind faith in the system writers’ skills and track record.
• A white box is the opposite. It is open to the user‘s understanding. The basic concepts regarding the philosophy and thinking that has gone into this trading system are explained in the training package.
• Programme trading is a generic term for a variety of stock market strategies whose aim is to automatically rebalance the weightings of assets in a portfolio by shifting the holding of shares, options, and futures. They are triggered and implemented automatically, once the parameters have been set.
  • A quantitative trading is the application of mathematical models to assist the activities of traders.
    Fx differs from financial instruments in the application of algorithmic trading:
    
• Foreign exchange is a commodity not a financial instrument, though it can be packaged into a financial instrument, principally as an exchange traded instrument.
• As a commodity foreign exchange is not exchange traded. It is traded OTC (Over The Counter) worldwide in an unquantified number of locations only constrained by the availability and depth of liquidity.
• • Foreign exchange is overwhelmingly conducted on a proprietary basis not on an agency basis.
  • Foreign exchange has too many tradable permutations for the application of the Algorithmic rules, which apply to financial instruments, unless the objective is as specific as trading a single block of currency to a single value date. Money managers have far more complex requirements, since they might be trading not one currency block but several blocks and even several blocks that might be broken out across hundreds of accounts. Between the blocks there are netting and aggregation opportunities that do not exist in equities due to the definition of how equity works. To this may be attributed a failure in deployment of order management systems (OMS) for trading FX.
  • Banking consolidation has ensured that liquidity is controlled at the price at which liquidity is available. They are not, as yet, enthusiastic about the adoption of algorithmic trading in the foreign exchange markets.

MiFID (the EU Market in Financial Instruments Directive) through its introduction of pre-trade transparency may accelerate the deployment of algorithmic trading in financial instruments but it will not apply to foreign exchange unless it is packaged as a financial instrument. So where is algorithmic trading heading in the foreign exchange market?

Historically, the major banks have controlled the price spread in the foreign exchange markets. Algorithmic trading eases that power away from them. It enables end buyers and sellers to time their entry and exit to the market. The major banks may limit access to trading platforms in the short term but ultimately they will encounter competition investigation. Electronic FX is gradually being adopted, perhaps more slowly than across other asset classes, but that heralds the growth of algorithmic trading.

Hedge funds appear to be the drivers of algorithmic trading on the buy side of the business. They are dependent on the major banks for a range of services. Have they yet proved themselves as more than a passing investment fashion? Mainstream adoption of algorithmic trading by corporate treasuries would substantially alter the buy side of the foreign exchange market. It would be a more efficient, faster, consolidated, cost-effective way for corporate treasuries to satisfy their foreign exchange demands. This may be the answer to more widespread adoption of algorithmic trading in the form of timed entry and exit in to the foreign exchange markets.