While historically, institutional traders, brokers and big houses had been owning the world of Algorithmic trading, but has the time finally come when a Retail trader can take advantages of Algorithmic Trading. Let’s find out how.
Ben is a computer science grad from an Ivy League college, running his own e-commerce website while earning extra pocket money by programme trading in the derivatives markets. Let’s see how Ben started his own algorithmic desk.
Algorithmic or algo trading is another term for automated trading. All trades are executed by a software based on an algorithm, this algorithm is coded in a programming language based on a back-tested algorithmic trading strategy.
Algorithmic trading offers several advantages over manual trading. Fast trade execution, accuracy, the ability to discard ‘emotions’ while trading and 100% compliance with the decided algorithmic trading strategy are some of the advantages.
So should retail traders get into Algorithmic Trading?
Multiply your profitable trades
The main reason is if you are trading a strategy which is profitable for you, you need to be able to increase the number profitable trades to earn more. In trading, the losses and wins happen together. You come out profitable only when your wins compensate your losses enough so as to account for your efforts and costs. Algorithmic trading is a way to do the same.
Discipline your trading decisions
Another reason is traditionally retail traders have been trading on the gut feeling based on the ‘feel’ of the market. There is nothing wrong with that especially if you are a seasoned player with lot of market insights to be put to use. However, the gut feeling often turns to be wrong, mostly when there is greed and fear involved. When the markets are falling many amateur traders sell quickly as they fear a further crash. Algorithmic trading follows pre-decided entry-exit rules which prevent such emotional trading and hence avoidable losses.
Increase your market reach
One of the main reasons why Quantitative trading has been gaining popularity is because it allows traders to build strategies quantitatively and use modelling techniques to be able to manage risks. This further enables them to trade in instruments such as options and derivatives which are otherwise too volatile for retail players.
We have also covered this topic in a fun way in this article here
Things required to start algorithmic trading
Here’s how we’ll do this, I will list down all the things that are required for you to start your own algorithmic trading and will provide resources to cover each of the following things, sounds ok?
- Trading Strategy: a tested profitable strategy, preferably based on quantitative analysis
- Programming skills: yes, it’s best if you do the programming of your own strategy, outsourcing of this is not recommended
- Trading software: that connects to the exchange and executes trades for you
- Data- live data for trading and historical data for testing your strategy
- Backend infrastructure: server, computers, backup power supply, internet connection etc.
- Co-location facility: to have your servers installed at the location of exchange to minimize the trade execution time. This is required in terms of HFT (High Frequency Trading)
- Regulatory approval: for many exchanges, this is required before you start your algorithmic trading
- Now, let’s consider each of these parameters in detail:
This is the most important part of algorithmic trading. Make sure your strategy has below things ready, this is the standard checklist,
- Clearly defined rules for trade entry, exit, stop loss and take profit
- Portfolio management – strategy that decides which assets to trade
- Risk management – most important aspect of the strategy since someone great once said ‘There are two ways to make money. 1. Don’t lose it & 2. Don’t lose it ’
- Provision to tackle unexpected events – there will be times when your algorithm just won’t know what to make of the market conditions, such times are rare but they can wipe out your entire portfolio, so make sure you know how to factor in this into your algorithms
Apart from this standard checklist, there are many minor things that you’ll need to make sure. Some of these things are related to programming, exchanges, timings and so on. You won’t notice them until you actually start trading.
The Easiest and fastest way to climb this steep ladder of learning is to sign up for online courses. While there are a few good courses available for learning to code algorithmic trading strategies. I’d recommend you check out Quantra, as it will give you the best comprehensive view of trading. They offer many such courses for all levels (beginner, intermediate and expert), you can check it out here
You don’t have to be an expert programmer to code your algorithmic trading strategy, however, basic understanding and prior exposure is a must. There are many languages that you can use for coding your trading strategy. R & Python are most popular among Algo traders because of their vast libraries and support offered by various trading softwares.
We have covered this topic in detail here
When it comes to Algorithmic trading, the number of risks just explodes since there are so many things involved. Here are some of the risks as per their category
Now, I won’t go into details of each as we’ve already covered these risks and ways to mitigate them in detail here.
You must acquaint yourself with different charting techniques and chart based strategies that can be profitably applied in the markets. There are many charting platforms available with advanced charting features and analytics. Some popular charting platforms among traders include:
Features offered by these platforms include real-time scanning, the number of technical indicators, expert advisors, backtesting, company fundamentals, news services, placing trades automatically, forecasting, level 2 data etc. A trader should choose a platform based on his trading style, features, and pricing.
There are two types of data you’ll require to start algorithmic trading.
First, historical data for testing your strategy. You can get historical data for almost all trading assets on either google or yahoo finance for free. Please note that this data is available on larger time scales (day, month, year etc.). While this is fine for low frequency trading strategies. But for HFT or high frequency trading strategies, you will require data for smaller time scales (microsecond, millisecond etc.), such data can be fetched from sites like Global data feeds, Thomas Reuters. However, this data is premium material, so you’ll have to pay for it.
Here is a detailed table on historical data sources – link
Second, live data for live trading, you can get it from the exchange directly or from a broker. For HFT algo trading, getting the tick data from the exchange and as early as possible is recommended, and for low frequency trading you should be fine with the data provided by the broker with an average delay of about a second.
Back end infrastructure & Co-location facility
This blog covers the details and minimum hardware requirements for the setup here.
Some exchanges around the world require you to get approvals before you start algorithmic trading. For example, India’s SEBI (Security and Exchange Board of India) requires you to get an approval of your strategy, to maintain logs for audit and to get re-approvals if you make any changes to your strategy. SEBI does this to make sure the algorithms do not cause undesirable situations in the stock markets.
Again, we’ve covered this in detail in this blog post, go ahead and check it out.
It’s true, that it takes a lot of work before you start your own algo trading desk, but it’s worth doing it solely because of the advantages and the peace of mind during execution. The good news is that we’ve got you covered, Quantra offers online self-paced and interactive courses on each aspect of algorithmic trading. Why don’t you head over and check it out here
If you’re a retail trader or a tech professional looking to start your own automated trading desk, start learning algo trading today! Begin with basic concepts like backtesting strategies, automated trading architecture, market microstructure, strategy backtesting system and order management system. You can also enroll in EPAT which is one of the most extensive algorithmic trading courses available in the industry.
We have noticed that some users are facing challenges while downloading the market data from Yahoo and Google Finance platforms. In case you are looking for an alternative source for market data, you can use Quandl for the same.