Definitions
Algorithmic trading is know by some other names also, such as automated trading or black box trading. Such a style involves using a computer programme that follows a defined set of instructions (or an algorithm) to place a trade. In principle, the trade can generate profits at a speed and frequency that is impossible for a human trader.
Apart from the profitability principle, algo trading also renders markets more liquid. It also enables trading to be more systematic by eliminating emotional biases form trading decisions.
Set of Instructions: What are they?
A defined set of instructions is called an algorithm. A trader could be following a set of simple instructions such as buying a stock at a moving average crossover such as the 50 DMA intersecting the 200 DMA from below and exit when the stock breaches the 50 DMA.
The computer program will monitor the stock price and transact ie buy or sell when the defined conditions are met. This releases the trader from having to monitor live prices and graphs in order to put through an order. The algorithm does this automatically.
Advantages and Disadvantages of Algorithmic Trading
Advantages
- Efficient execution
- Low latency, trade order placement is instant and correctly timed to avoid price changed
- Low transaction costs
- Concurrent checking of different market parameters
- No human operational or emotional errors
- Backtesting is possible with algo systems
Disadvantages
- Black swan events keep occurring in the markets, and these market disruptions can result in losses for algorithmic traders
- Dependence on technology. Algo trading depends on computer programs and high speed internet connections. If there are any disruption I these it can result in losses.
- Market Impact of algorithmic trading is high. Large orders can shift market prices which can result in losses for traders who are unable to adjust to them in time. Algorithmic trading also increases market volatility and is thought to have been the cause of some “flash crashes”.
- Algorithmic trading apparatus are expensive and involve high capital costs.
- Lack of human judgement. The models depend on historical data and mathematical models. It doesnot take into account qualitative factors and subjective judgements which could have an influence on the markets.
Algorithmic Trading: Time Scales
Algo trading can be used by many kinds of market participants. Algo trading does tend to get associated with High Frequency Trading or HFT’s as it is called, but this association is not encompassing and there are many other styles of investing where Algo trading can be used.
- Mid to long term investors and buy side firms such as pension funds, mutual funds and insurance companies use algos when they do not want stock prices with their discrete high volume investments.
- Short term traders and sell side participants such as brokers, arbitrageurs and speculators also benefit from algos to create and maintain liquidity in the markets.
- Systematic traders such as trend folllowers, hedge funds and pairs traders use algos to programme their trading rules to enable the programmes to trade automatically.
- Smartvalues is a systematic algo in the third category.
Therefore, algo trading provides a more systematic approach to active trading methods than those based on trader intuition or instinct.
Algorithmic Trading Strategies
The most common forms of algorithmic trading are:
- Trend following strategies: This is the most common algorithmic strategy designed to follow trend through technical indicators. These are easy to construct and execute as they do not require any prediction.
- Arbitrage Opportunities: These are opportunities that arise from mispricing in securities in two different exchanges or in the statistical parameters of two securities giving rise to what is called statistical arbitrage.
- Index Fund Rebalancing: Index funds have defined periods of rebalancing when they have to bring their holdings in line with the index. This creates profitable opportunities for algo traders.
- Mathematical Model Based strategies: Proven mathematical models (eg delta neutral strategy) can be done through multiple trades. Algo trading facilitates tis kind of trading.
Algo trading can also be used for other kinds of trading strategies such as mean reversion trades, VWAP trades and TWAP trades.
Conclusion
Algo trading combines computer software and financial markets to buy and sell securties based on a code. The duration of trades can vary and indeed the power of computing has been harnessed to perform high frequency trading. With a variety of strategies prevalent that rely of algo trading, this phenomenon is proliferating in the financial markets. This is a trend that is going to continue.