Forex algorithmic strategies are all the rage. Banks, hedge funds and proprietary trading firms employ armies of computer programmers to develop complex formulae to trade equities, bonds, currencies and commodities.
Also Read:– Businessslash
As a CFD trader in India, you might be forgiven for thinking that algorithmic strategies are not suitable for your needs or just not relevant to you. After all, with no access to the major stock exchanges thanks to strict foreign investment regulations, many algorithmic strategies are useless when applied to only one market – the Indian capital markets.
Traders who use algorithmic trading represent about 10% of all traders but account for about 70% of all equity orders placed globally. Algorithmic trading uses automated software programs that communicate directly with financial exchanges.
The main difference between CFDs India algorithmic trading and the more traditional form of manual/discretionary Forex trading is that algorithmic trading places trades based on algorithms/models rather than using the direct input of the trader’s assessment of market conditions.
Algorithm-based trading has been around for years – it was introduced to Forex in the early 1990s but only gained popularity in late 2000 when central banks and hedge funds realised its benefits.
Algorithmic strategies are all about finding a mathematical edge over the markets by building models that consider multiple parameters. Every time new information about any currency pair becomes available. It can be fed into these models, using this information to generate buy or sell signals.
These signals are then automatically sent to the market, where they are acted upon by automated execution software (trading robots) that are programmed to automatically enter or exit a trade when certain conditions are reached.
Algorithmic trading strategies are usually classified into three major categories: trend following, mean reversion, and breakout. I will now provide an overview of these three categories- this should give you enough knowledge to understand the rest of the article about algorithmic Forex strategies for Indian traders.
These strategies identify trends in currency prices and attempt to ride those trends by buying at the beginning of a price rise and selling at the beginning of a price decline. They tend to be very popular during intense economic climates but can be difficult to implement during more sluggish periods as there is less momentum in the market.
These strategies identify the middle point or average price between the high and low prices and place buys and sell orders at specific fixed amounts above and below this price. They are based on the assumption that financial instruments will eventually revert to their mean value. Mean reversion strategies tend to be more popular among traders who use multiple time-frames because they often produce unspectacular results alone when used with a one-time frame.
These strategies involve identifying possible breakout points in currency prices, which occur when a currency pair moves through an identified support or resistance level. These models are generally considered more complex than the other two categories but offer potentially higher profits.
Any trader needs to perform extensive back-testing of any trading strategy they implement on their account. It’s the only way to ensure that an algorithmic trading system meets its potential and increases profits over time. Back-testing involves running historical data through a computer program to see how well a system worked under past market conditions, so it is no surprise that most traders without programming knowledge prefer software programs such as TradeStation, Saxo bank or MetaTrader.
Ultimately, all types of traders can benefit from algorithmic strategies because they can automate specific repetitive tasks and leave more time for analysis and planning – but whether or not these benefits outweigh the costs of implementation depends on your circumstances.