Algo Trading

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Algo Trading

The Forex market has always been known as a challenging place for traders. With high volatility and unpredictable price action, it’s not uncommon to see traders lose their entire account in just a few minutes.
To make things more difficult, market signals are often weak, fragmented and inconsistent – which makes algorithmic trading a great idea for the Forex market. However, algorithmic trading is not without its difficulties.
Once you have chosen your strategy, you need to code it and test it before implementing it into your trading system. Furthermore, there are many other factors to consider before you get started with automated trading systems.

KEY TAKEAWAYS

  • Method of order execution using pre-programmed automatic trading instructions, taking into account variables such as time, price and volume, is known as algo trading.
  • With algo trading, traders can run the algorithms based on past data to see if it would've worked in the past. It lets the user remove any flaws of a trading system before trying it out live.
  • Trend-following Strategies - one of the most common algo trading strategies to follow trends in moving averages, channel breakouts, price level movements, and related technical indicators.
  • algo trading has gained in importance in recent years in the financial industry, and this trend is likely to proceed.

Algo Trading Strategies

A sophisticated algorithm should ideally take into account many factors and analysis, such as movements of price, market volatility, chart analysis and other nonetheless important factors. There are many strategies that are widely used for trading and they vary greatly in many complex ways.

Strategies mentioned below are considered Best algo Trading Strategies.

  • Index Fund Rebalancing - Rebalancing is a process where the underlying assets of funds are readjusted according to current market conditions. For example, a pension fund is supposed to be a combination of 50% stocks and 50% bonds. In a few years the value of stocks increases, and now compromises 75% of the portfolio. During rebalancing, some of the stocks are sold, in order to bring back the portfolio to the original 50-50 allocation, and the trader profits. These rebalancing transactions are now automatized by algorithms.
  • High frequency arbitrage - buying a dual-listed stock at a lower price in one market and simultaneously selling it at a higher price in another market offers the price differential as risk-free profit or arbitrage. Same can be done for stocks vs. futures instruments. Implementing an algorithm to identify such price differentials and placing the orders efficiently allows profitable opportunities.
  • Trading Range (Mean Reversion) - strategy is based on the concept that the high and low prices of an asset are a temporary phenomenon and they will revert to their mean value (average value) periodically. Identifying and defining a price range and implementing an algorithm based on it allows trades to be placed automatically when the price of an asset breaks in and out of its defined range.
  • Trend-following Strategies - one of the most common algo trading strategies to follow trends in moving averages, channel breakouts, price level movements, and related technical indicators. These are the easiest and simplest strategies to implement through algo trading because these strategies do not involve making any predictions or price forecasts. Trading is initiated as soon as the desired trends appear, which are easy and simple to implement using algorithms, without going into the complexity of predictive analysis. Using 50- and 200-day moving averages is a popular trend following strategy.
  • Mathematical Model-based Strategies - Proven mathematical models, allow trading on a combination of options and the underlying security. Delta neutral (mathematical model) is a portfolio strategy consisting of multiple positions with offsetting positive and negative deltas—a ratio comparing the change in the price of an asset, usually a marketable security, to the corresponding change in the price of its derivative—so that the overall delta of the assets in question totals zero.
  • Time Weighted Average Price (TWAP) - the aim of this strategy is to execute the order close to the average price between the start and end times thereby minimizing market impact. Time-weighted average price strategy breaks up a large order and releases smaller chunks of the order to the market using evenly divided time slots between a start and end time.
  • Volume-weighted Average Price (VWAP) - The idea behind this strategy is somewhat the same as the Time Weighted Average Price (TWAP)- volume-weighted average price strategy breaks up a large order and releases smaller chunks of the order to the market using stock-specific historical volume profiles. The goal is to execute the order close to the volume-weighted average price (VWAP).
  • Percentage of Volume (POV) - until a trade order is fully executed, this algorithm continues to send partial orders according to a certain participation rate and according to the trading volume in the markets. This strategy submits orders, based on the user-defined percentage and increases or decreases this participation rate when the stock price reaches levels the trader has set.
  • Implementation Shortfall - This strategy's goal is to minimize the execution cost of an order by trading off the real-time market, which helps saving on the cost of the order and benefiting from the opportunity cost of delayed execution. The strategy will increase the targeted participation rate when the stock price moves favorably and decrease it when the stock price moves adversely.

Benefits of algo Trading

The main reasons algo trading has become so popular are because of its advantages in speed, accuracy and lower cost compared to manual trading.

  • Speed is one of the advantages of algo-trading. Trades are being executed automatically and with great speed, since they are planted and written beforehand.
  • Quantity of indicators - trading with algorithms has the advantage of scanning and executing on multiple indicators at a speed that no human could do - trades can be analyzed and executed faster, hence more opportunities are available at better prices.
  • Accuracy - computer automatically executing trades, which does rule out human error. For instance buying the wrong currency pair, or for the wrong amount.
  • Emotions are not going to stand in the way of rational decisions, thankfully everything is already automated and algorithm is running its course.
  • Ability to backtest - With algo trading, traders can run the algorithms based on past data to see if it would've worked in the past. It lets the user remove any flaws of a trading system before trying it out live.
  • Reduced transaction costs - with algo-trading traders don’t have to spend so much time analysing and monitoring markets.