This guide will help you design algorithmic trading strategies to control your emotions while you let a machine do the trading for you. Why would you want to use high-frequency algorithmic trading strategies? What types of algorithmic bots are the best? All will be revealed in this algorithmic trading strategy guide. By the end of this guide, you’ll learn the secret ingredients you need to develop profitable Forex algorithmic trading strategies.
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With the advancement of electronic trading, algorithmic trading became more popular in the past 10 years. Algo trading first started in the 1980s. Today, it accounts for nearly 70% of all trading activities in developed markets.
If you want to enhance your knowledge of quantitative trading, we recommend you read Algorithmic Trading Winning Strategies and Their Rationale by Ernest P. Chan. Ernest wrote one of the best algorithmic trading strategies books. What sets this insightful book apart from others is the emphasis on algorithmic trading strategies examples as opposed to just theory.
Let’s now answer some of the most common types of questions:
- What are forex algorithmic trading strategies?
- How do they work?
- Who should trade forex algo strategies?
- And when should you be using forex algorithmic trading strategies?
Let’s get started.
What is Algorithmic Trading?
Algorithmic trading is a technique that uses a computer program to automate the process of buying and selling stocks, options, futures, FX currency pairs, and cryptocurrency.
On Wall Street, algorithmic trading is also known as algo-trading, high-frequency trading, automated trading or black-box trading. These terms are often used interchangeably.
If you want to learn how high-frequency trading works, please check our guide: How High-frequency Trading Works – The ABCs.
Basically, the algorithm is a piece of code that follows a step-by-step set of operations that are executed automatically. The step-by-step operations are based on the inputs that you have programmed into it. The input variable can be something like price, volume, time, economic data, and indicator readings. Any kind of variance of those input variables can be used.
After these criteria are satisfied, a buy or sell order will be executed.
Next, you’ll learn how trading algorithms work. You’ll also learn what you need to do to execute your trade in a fully automated manner:
How Algorithmic Trading Works?
Algorithmic trading works by following a three-step process:
- Have a trading idea.
- Convert your trading idea into a trading strategy.
- The trading strategy is converted via an algorithm.
Once the algorithmic trading program has been created, the next step is backtesting. Backtesting involves using historical price data to check its viability. If the algorithm gives you good backtested results, consider yourself lucky you have an edge in the market. Finding an edge in the market and then coding it into a profitable algorithmic trading strategy is not an easy job.
Learn how to backtest a trading strategy using our Backtesting Trading Strategy.
The first (and most important) step in algorithmic trading is to have a proven profitable trading idea. Before you learn how to create a trading algorithm you need to have an idea and strategy.
After you find an edge in the market, you need to have competence and proficiency. The best algorithmic traders have competency and proficiency in these three areas:
- Trading and financial market knowledge.
- Quantitative analysis or modeling.
- Programming skills.
What are the best programming languages used in algorithmic trading?
Python algorithmic trading is probably the most popular programming language for algorithmic trading. Matlab, JAVA, C++, and Perl are other algorithmic trading languages used to develop unbeatable black-box trading strategies.
Right now, the best coding language for developing Forex algorithmic trading strategies is MetaQuotes Language 4 (MQL4).
Let’s do a recap of the things you need to develop your algorithmic trading strategies PDF:
- A trading strategy based on quantitative analysis.
- Pick the right algorithmic trading software that connects to the exchange and executes automatically trades for you.
- Live data for trading.
- Historical price data for backtesting your algo.
- IT infrastructure for high-frequency trading. Examples include a powerful computer to handle advanced mathematical models, servers, backup power, fast internet connection.)
- Colocation facility to have your servers installed at the location of the stock exchange (Eg. NYSE, if you trade stocks). This will help minimize trade execution and will give you an advantage over the competition. Colocation is often used in high-frequency trading.
Let’s now see who the market players are. Who is most prone to use algorithmic trading in the trading landscape?
Who Uses Algorithmic Trading?
In essence, any experienced trader with coding skills can use programmed trading strategies to trade on his behalf. An individual trader can code his own algo-trading robot to do more than just to open buy and sell orders. Algorithms can be used for much more complex things like:
- To produce complex mathematical calculations.
- Forecast market movements.
- Generate trading signals.
- Risk Management
The most proficient algorithmic traders are big institutions and smart money. Hedge funds, investment banks, pension funds, prop traders and broker-dealers use algorithms for market making. These guys make up the tech-savvy world elite of algorithmic trading.
Note: Nowadays market making is done through machine learning. You can learn more on this topic by reading an intelligent market making strategy in algorithmic trading PDF.
Moving forward, we’re going to dive into the types of algorithmic trading strategies.
Introduction to Algorithmic Trading Strategies
Some algorithmic trading strategies are used to generate profits. Others are used for order filling. Throughout this algorithmic trading guide, going to focus on profit-seeking algorithms. We’re not as concerned with algorithmic order management or order filling algorithms.
Order filling algorithms execute large numbers of stock shares or futures contracts over a period of time. The order filling algorithms are programmed in a way to break a large-sized order into smaller pieces. This way it won’t move the market against the position taken.
The most popular algorithmic orders and techniques used by the smart money are:
- Time Slice
The herd mentality is to follow the big money. If you understand how a big-size order can impact the market, you know that if the whole street knows your intentions, you ultimately won’t get the desired price.
If you intend to buy ABC stock and the whole street jumps to buy it, the stock price will be artificially pumped higher. This is a classic case of supply and demand.
Next, we’re going to outline the best algorithmic strategies. What are the most common trading strategies used in algo trading? Keep reading.
What are the Best Algorithmic Trading Strategies
We have a large array of algorithmic trading strategies examples. We’re going to give you a broad list so you can see big trends.
Broadly speaking, most high-frequency algorithmic trading strategies will fit into one of the highlighted categories:
- Momentum strategies
- Mean reversion strategies
- Sentiment based strategies
- Statistical arbitrage strategies
- Market making strategies
The Algorithmic Trading Winning Strategies and Their Rationale book will teach you how to implement and test these concepts into your own systematic trading strategy.
Algorithmic Trading Momentum Strategy
Momentum-based algos simply follow when there is a spike in volatility or momentum ignition. The algo jumps on that momentum spike with buy or sell orders and a tight stop. The idea behind the momentum-based algorithms is simple. Once the ball starts rolling, it will continue to do so until it finds some type of resistance.
You can determine the market momentum by using indicators and price statistics.
One very simple automated trading algorithm used in the S&P 500 E-mini futures is programmed to feed buy orders when Emini S&P 500 makes a new intraday high after the open.
Discover some secrets and techniques developed by a 35-year veteran trader to day trade Emini futures: Day Trading Strategies Emini Futures.
Mean-Reversion Algorithmic Strategy
The mean reversion system is another type of algorithmic system which operates under the premise that the market is ranging 80% of the time. The price usually gravitates towards its mean price.
Algorithmic traders use the historical price data to determine the average price of a security. They then open buy or sell orders in anticipation of the current price coming back to the average price.
Algorithmic Trading Sentiment Strategy
The sentiment-based algorithm is a news-based algorithmic trading system that generates buy and sell trading signals based on how the actual data turns out. These algorithms can also read the general retail market sentiment by analyzing the Twitter data set. The goal of this algorithm is to predict future price movement based on the action of other traders.
You need to have a firm understanding of how the financial markets operate and strong skills to develop sentiment trading algorithms.
Market Making Algorithmic Trading Strategy
The market makers, also known as the liquidity providers, are broker-dealers that make a market for an individual instrument. This can be stock, bonds, commodities, currencies, and cryptocurrencies. The main job of a market-making algorithm is to supply the market with buy and sell price quotes. Marketing making algos can also be used for matching buy and sell orders.
One of the most popular market-making algorithmic strategies implicates to simultaneously place buy and sell orders. These types of market-making algorithms are designed to capture the spreads.
Statistical Arbitrage Algorithmic Trading Strategy
Most statistical arbitrage algorithms are designed to exploit statistical mispricing or price inefficiencies of one or more assets. Statistical arbitrage strategies are also referred to as stat arb strategies and are a subset of mean reversion strategies.
Stat arb involves complex quantitative models and requires big computational power.
The most popular form of statistical arbitrage algorithmic strategy is pairs trading strategy. Pairs trading is a strategy used to trade the differentials between two markets or assets. Pairs trading is essentially taking a long position in one asset while at the same time taking an equal-sized short position in another asset.
Make sure you check out what is our favorite arbitrage trading bot: How to Make Money from Arbitraging Trading Software before reading on.
Forex Algorithmic Trading Strategies
FX algorithmic trading strategies help reduce human error and the emotional pressures that come along with trading. The goal is to build smarter algorithms that can compete and beat other high-frequency trading algorithms.
Most traders don’t have money to pay for powerful computers and expensive collocation servers. Competing against other HFT trading algorithms is like competing against Usain Bolt.
So, how can you compete with other quants?
What’s the secret to winning this race?
Like Sun Tzu said in The Art of War: “Keep your friends close and your enemies closer.”
The best way to follow this principle is to analyze how other Forex algorithms behave and study their moves.
For example, a dirty secret and standard practice used by many algos is the momentum ignition strategy. This algo seeks to cause a rapid spike in the price above a certain key level. Typically this algorithm incorporates support and resistance, swing high/low, pivot points or other key technical indicators. This action will induce other traders to trade off the back of that move.
The Forex chart below shows you the Forex momentum ignition algorithm in action:
You can train and program your Forex algorithm to respond to this type of behavior. If you have superior programming skills you can build your Forex algorithmic system to sniff out when other algos are pushing for momentum ignition.
Final Words – Algorithmic Trading Strategies
Developing your algorithmic trading strategy takes time, but the advantages and the peace of mind you get makes it worth it. This is a very competitive space that requires having superior knowledge and programming skills to be able to develop high-frequency trading algorithms.
The rise of high-frequency trading robots has led to a cyber battle that is being waged on the financial markets. Forex algorithmic trading strategies have also brought to life several other trading opportunities that an astute trader can take advantage of.
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