What our trading software code looks like (Automated Trading Part 5) C#

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In this video we are going to have a look at our Trading software Code including C#

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Algorithmic Trading For Forex, What our trading software code looks like (Automated Trading Part 5) C#.

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Share Market Trend Analysis tries to predict trends on the market. If the forecasted trend is bull market run, you can ride that until there is a pattern reversal. As a financier, you can make revenues if you move with the trends and not against it.

Recommended Book for Automated Trading

Professional Automated Trading: Theory and Practice

Book by Eugene A. Durenard

An insider’s view of how to develop and operate an automated proprietary trading network Reflecting author Eugene Durenard’s extensive experience in this field, Professional Automated Trading offers valuable insights you won’t find anywhere else. read more…

Originally published: 2013
Author: Eugene A. Durenard

An Instance of Automated Trading

Royal Dutch Covering (RDS) is noted on the Amsterdam Stock Exchange (AEX) and London Stock Exchange (LSE).1 We start by constructing an algorithm to identify arbitrage opportunities. Here are a few intriguing observations:

AEX sells euros while LSE trades in British extra pound sterling.

Because of the one-hour time difference, AEX opens an hour earlier than LSE adhered to by both exchanges trading concurrently for the next couple of hours and then trading just in LSE during the last hr as AEX shuts.

Can we discover the opportunity of arbitrage trading on the Royal Dutch Covering stock listed on these 2 markets in 2 different currencies?

Needs

A computer program that can check out existing market prices.
Cost feeds from both LSE and AEX.
A foreign exchange (foreign exchange) rate feed for GBP-EUR.

• Order-placing capability that can course the order to the appropriate exchange.
  Backtesting capability on historic cost feeds.
• The computer program ought to do the following:.
• Read the inbound cost feed of RDS stock from both exchanges.
• Using the offered foreign exchange rates, transform the cost of one currency to the various other.
• If there is a big enough cost inconsistency (discounting the brokerage firm prices) resulting in a lucrative chance, then the program ought to put the buy order on the lower-priced exchange and sell the order on the higher-priced exchange.
• If the orders are carried out as desired, the arbitrage earnings will comply with.

Simple and easy! Nevertheless, the practice of Automated trading is not that straightforward to maintain and execute. Keep in mind, if one capitalist can put an algo-generated profession, so can various other market individuals. Subsequently, rates fluctuate in milli- and even split seconds. In the above example, what takes place if a buy profession is carried out but the sell profession does not due to the fact that the sell rates alter by the time the order hits the marketplace? The trader will be entrusted to an open position making the arbitrage method pointless.

There are extra risks and obstacles such as system failing risks, network connection mistakes, time-lags between profession orders and execution and, most important of all, imperfect algorithms. The more complex an algorithm, the extra rigid backtesting is required before it is put into action.

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