Imagine this: You’ve found a reliable trading strategy and are excited to use it in the markets. But when you fire up your trading platform, it’s slow to load, and you must wait several minutes for it to respond. When you place your orders, the market has already moved on. This scenario is too common for traders relying on manual or outdated trading software. If you’re looking to avoid such pitfalls and trade with speed and efficiency, you’ve come to the right place. In this article, we’ll introduce you to algorithmic trading software and best VPS for trading and why you need it to maximize profits and minimize risks.
Trading VPS of QuantVPS can help you achieve your goals by providing a reliable, high-performance environment for running your algorithmic trading software.
What is Algorithmic Trading and How It Works
Algorithmic trading (automated trading, black-box trading, or algo-trading) uses a computer program that follows a defined set of instructions to place a trade. The trade can generate profits at a speed and frequency that is impossible for a human trader. It is one of the most essential innovations in trading in the last few decades. Apart from profit opportunities for the trader, algo-trading renders markets more liquid and trading more systematic by ruling out the impact of human emotions on trading activities.
The defined instructions are based on:
- Timing
- Price
- Quantity
- Any mathematical model
Suppose a trader follows these simple trade criteria:
- Buy 50 shares of a stock when its 50-day moving average goes above the 200-day moving average. (A moving average is an average of past data points that smooths out day-to-day price fluctuations and identifies trends.)
- Sell shares of the stock when its 50-day moving average goes below the 200-day moving average.
Automation for Smarter Trading
Using these two simple instructions, a computer program will automatically monitor the stock price (and the moving average indicators) and place buy and sell orders when the defined conditions are met. The trader no longer needs to monitor live prices and graphs or manually enter the orders. The algorithmic trading system does this automatically by correctly identifying the trading opportunity.
Algorithmic trading aims to automate market analysis and the position management process. Robot trading eliminates the opening of positions under the influence of emotions and helps optimize the distribution of order volumes across different price levels. The essence of algorithmic trading is the automation of routine actions.
Meet Trading Advisors, Your New Best Friend
A trading advisor is a software, a code written according to a manual strategy algorithm. In manual trading, you must search for signals independently and decide about entering or exiting a trade. A typical trading strategy can be translated into code, and the software will perform all your actions. Trading advisors for Forex algorithmic trading can be divided into two groups:
Standard Advisors
The code contains an algorithm for managing transactions to calculate position volume and risk level. If all the specified factors coincide, the robot will perform the required actions based on the conditions specified in the code and settings. If the robot yields a loss, it should be optimized, and the trading algorithm in the code should be corrected.
Neural network
These are algorithms with machine learning based on artificial intelligence. These algorithms find patterns in past price performance and extrapolate them to the current market situation. They analyze the Forex market using mathematical and statistical models and choose the best option—buy or sell. Trading robots are capable of self-learning (machine learning).
Such algorithmic trading systems work with thousands of instruments, selecting their best combination. Institutional investors often use the second type of expert advisor in scalping, where buy and sell orders are completed in a fraction of a second. This type of Forex trading is also called High-Frequency Trading. Standard advisors can be used in any situation, depending on the algorithm embedded in the code.
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How a Trading Algorithm Actually Works
At their core, algorithms are steps for a computer to follow. Brushing your teeth could be distilled into an algorithm, albeit a remarkably complex one considering the orchestration of movements that go into that daily ritual. When Wall Street firms use algorithms, they simply encode logic into the computer. A trading algorithm can be fundamentally driven based on old-fashioned company metrics or quantitative signals.
Such signals include a sweep of buying interest known as momentum or technical factors like a particular stock breaking through a 30-day average price. Or, it can be all three. Algorithms can be complex, taking up thousands of lines, or simple. High-speed trading firms often rely on pared-down algorithms because running a complicated program slows buying and selling by microseconds (one-millionth of a second).
Signals Are The Key To Trading Algorithms
The hardest part for any firm using algorithms is finding the signal on which the apparatus turns. That usually relies on hypothesis-driven research by humans. What is a signal? A quant might analyze stock-market activity and note that activity in one area often leads to activity in another. She would then attempt to capture the phenomenon in an algorithm that acts like a net: it buys at an opportune moment suggested by that signal.
It sells after another pre-set period, capturing a sliver of profits. A long-short portfolio manager trying to write an algorithm could input signals that reflect sales activity at a company (credit card receipts from a vendor like Square, for example) and use that as the signal. Anything can be a signal, including sunspots. The true challenge is making money from them, one of the world’s most competitive sports.
The Mechanics of Trading Algorithms
This algorithm (from the research library of Quantopian, a place where do-it-yourself algorithm writers can try their hand at trading) once would have been the source of big profits. Over time, more researchers discovered rudimentary signals like the one it relies on, so it is no longer a reliable money spinner. The algorithm employs a general statistical arbitrage strategy based on the tendency of overvalued stocks to go back down and the undervalued ones to go up. It could have made a trader millions in the 1970s, 1980s, and early 1990s.
Nowadays, it wouldn’t likely earn much – it might even lose money – because the opportunity has been primarily traded away. That makes the markets one of the greatest games – incredibly difficult but with sometimes huge pay-outs. In some ways, though certainly not in all ways, coming up with a quantitative strategy that makes money is more complex than the work of a scientist because the laws of physics don’t change as physicists make predictions. When an algorithm begins investing money, the opportunity starts to fade instantly. Over time, as others find it, it completely melts away.
Example Of A Simple Trading Algorithm
This Quantopian algorithm is based on “mean reversion,” another saying that prices will return to the average over time. It ranks a list of stocks into companies whose share prices are too high and those that are too low based on a well-used methodology called Bollinger Bands. Then, it sells the high ones and buys the low ones. The idea is that the high ones fall over time, and the low ones rise toward the middle.
The Anatomy Of An Algorithm
It loads several libraries that act like shortcuts. Instead of rewriting the code to find the moving average of a stock, it uses a library with the code already written. Here, it sets the maximum size of a short or long position. These are the kinds of variables an algorithmic trader will experiment with. Each draft of the program can be run through a simulator to see how it performs before you set it loose on the markets.
In this case, the maximum short or long position is proportional to the number of longs and shorts. For example, the maximum size is more significant if only ten positions exist. This considers some critical market factors affecting profitability, including exposure to particular stock sectors and overall market activity. By limiting “beta exposure,” the algorithm prevents trading during volatile periods.
How Do Trading Algorithms Work?
This goes to the heart of the program’s mathematical operation. It takes a ratio of the last close price to the average price over the previous 60 days. The higher the ratio, the higher the price is compared to the mean, and vice versa. This analysis divides stocks into two key categories: those valued too high and those valued too low. Algorithms could be more intuitive. They follow exact directions, so considering these things is crucial to avoid damaging your portfolio.
The final step is a bit of code that takes everything above—exposure to factor risks, variables set by the designer about leverage, and the targeted longs and shorts—and creates an optimal portfolio. The goal is to maximize profits while accounting for potential risks the writer has accepted.
Advantages and Disadvantages of Algorithmic Trading
Algorithmic Trading Advantages. The Upside of the Future of Trading
Algo-trading provides the following advantages:
Best Execution
Trades are often executed at the best possible prices.
Low Latency
Trade order placement is instant and accurate. There is a high chance of execution at the desired levels. Trades are timed correctly and instantly to avoid significant price changes.
No Human Error
Reduces the risk of manual errors or mistakes when placing trades. It also negates human traders’ tendency to be swayed by emotional and psychological factors.
Backtesting
Algo trading can be backtested using historical and real-time data to determine whether it is a viable trading strategy.
Other Advantages
- It has reduced transaction costs.
- Simultaneous automated checks on multiple market conditions.
Algorithmic Trading Disadvantages. The Downside of the Future of Trading
There are also several drawbacks or disadvantages of algorithmic trading to consider:
Latency
Algorithmic trading relies on fast execution speeds and low latency, which is the delay in executing a trade. If a trade is not executed quickly enough, it may result in missed opportunities or losses.
Black Swan Events
Algorithmic trading relies on historical data and mathematical models to predict future market movements. However, unforeseen market disruptions, known as black swan events, can occur, resulting in losses for algorithmic traders.
Dependence on Technology
Algorithmic trading relies on technology, including computer programs and high-speed internet connections. Technical issues or failures can disrupt the trading process and result in losses.
Market Impact
Large algorithmic trades can significantly impact market prices, resulting in losses for traders who cannot adjust their trades in response to these changes. Algo trading is sometimes suspected of increasing market volatility, even leading to flash crashes.
Regulation
Algorithmic trading is subject to various regulatory requirements and oversight, which can be complex and time-consuming to comply with.
High Capital Costs
Developing and implementing algorithmic trading systems can be costly, and traders may need to pay ongoing fees for software and data feeds.
Limited Customization
Algorithmic trading systems are based on pre-defined rules and instructions, which can limit traders’ ability to customize their trades to meet their specific needs or preferences.
Lack of Human Judgment
Algorithmic trading relies on mathematical models and historical data, so it does not consider the subjective and qualitative factors that can influence market movements. This lack of human judgment can disadvantage traders who prefer a more intuitive or instinctive approach.
Algo-Trading Time Scales
Algorithmic trading systems can operate on various timeframes, from milliseconds to weeks or months. The time scale of a strategy is essential for selecting the correct algorithm for your trading style. Some algorithms are designed for short bursts of market activity, while others thrive on longer-term trends.
High-Frequency Trading (HFT)
High-frequency trading (HFT) is a popular algorithmic strategy among large institutional traders. HFT uses powerful computers to transact many orders at breakneck speeds. HFT systems typically hold positions for seconds or minutes before closing them for a profit. These algorithms capitalize on minor price discrepancies in different markets or between related financial instruments.
Since these inefficiencies can quickly disappear, HFT systems require very low latency to execute trades as soon as possible. Because of this, they often run on trading VPS (virtual private servers) near exchange servers to achieve optimal speeds.
Medium-Term Algorithmic Trading Strategies
While HFT systems can operate on timeframes measured in milliseconds, other algorithmic trading systems function on medium-term time scales. These strategies might open and close trades on 15-minute or hourly charts. Others might even target daily candles before executing a trade.
Medium-term algorithms are often designed to capitalize on sudden market movements or reversals after the release of economic data or earnings reports. As such, they can effectively create market liquidity and reduce volatility.
Long-Term Algorithmic Trading Strategies
Long-term algorithmic trading strategies can hold positions for weeks or even months. These systems typically rely on technical indicators to identify trends and reversals on daily or weekly charts.
Longer-term algorithmic strategies automate the trading process, allowing traders to avoid the emotional pitfalls of trading and eliminate the guesswork of systematic trading.
What is the Difference between Automated Trading and Algorithmic Trading?
Automated and algorithmic trading have similarities, but the terms don’t mean the same. Both involve computers executing trades, but automated trading typically refers to any system that automates trade execution, including manual strategies automated through software.
Algorithmic trading refers explicitly to strategies built on complex mathematical models and statistical data. Although all algorithmic trading is automated, not all automated trading is algorithmic.
What Is Algorithmic Trading in Forex?
Algorithmic Forex trading is a method of executing a large order by splitting it into many small parts. These small orders are placed in the market at a certain period and price using unique trading algorithms. Algorithmic trading aims to reduce the cost of executing a large order, reduce its impact on the price, and lower the risk of the order not being filled due to the lack of counter offers.
Automated Trading in Forex
Also, this concept often refers to automatic trading using specific algorithms called Forex automated trading on Forex. Automated Forex trading is a process where trading decisions are made and executed using special software or an algorithm that follows specific pre-defined rules or strategies. An automated trading system aims to profit in the Forex market using various technical analysis indicators, price action patterns, statistical models, artificial intelligence, and other analysis methods.
The Difference Between Automated Trading and Algorithmic Trading
This interpretation is considered from the point of view of the essence of the process. Automated trading implies that robots enter and exit trades for the trader. Algorithmic trading means that an algorithm is used to execute large orders with minimal losses by splitting them. In most sources, automated and algorithmic trading definitions are synonyms used as identical concepts. The essence of Algo trading is making transactions by trading robots.
Types of Algorithmic Trading Software
Trading Software Bots
A bot is a program designed to automatically execute trades based on a set of parameters supplied by a human trader. Among the various variables that make up these parameters are:
- Signal to purchase and sell
- The maximum size of a position
- The price that serves as a point to stop
- Exit the trade
The advantage of a bot is that it can execute trades objectively by following a strategy, removing the psychological and emotional aspects of trading that can affect even the most experienced players’ performance.
Signals, Alerts, and Other Tools
Signals are a type of trading alert that notifies traders of profitable opportunities. They are often provided by algorithmic software that scans the market for potential trades and then notifies users.
Signals in Algorithmic Trading
Even though signals are closely linked to the usage of automated bots, algo trading techniques can also rely on external or third-party signals that aren’t always tied to a specific technical configuration. One example would be to trade relevant indices after releasing a major economic report if the report falls short of the consensus forecast. Level II market data, such as bid/ask spreads buy and sell order volumes.
Variables and Relationships
Other related variables could also provide trading signals. In essence, everything that can alter the price of a specific financial instrument can be regarded as a variable to trade on, and a signal is an occurrence in which there is an exploitable relationship between the variable and the price of an index, in one direction or the other.
Third-Party Signal Services
Third-party services that give signals for algorithmic trading are also available. The bot will receive the signal and process it promptly to complete the transaction. These elements can be used to deliver these messages:
- Newsletter
- RSS feed
- Telegram
Copy Trading, Following the Leader
Copy trading is a form of automated trading that involves mirroring the trades of a more experienced trader. Although the strategy is not based on an algorithm (unless the traders used algorithmic trading), placing trades could be classed as algorithmic.
Algorithms monitor the trades of the trader you choose to copy and make changes to your portfolio accordingly.
VPS, The Unsung Hero of Algorithmic Trading
A VPS hosting service runs trading platforms and algorithms in a secure, stable, and low-latency environment. While not software, a VPS facilitates algorithmic trading by ensuring that trading bots or algorithms can operate 24/7 without interruptions due to power outages or hardware failures.
It also reduces latency, improving execution times, critical for high-frequency and algorithmic trading strategies.
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- High-Frequency Trading Platform
- Speedy Trading Servers Alternatives
18 Best Algorithmic Trading Software Platforms
1. QuantVPS
QuantVPS provides high-performance, affordable trading VPS solutions for algorithmic traders. With ultra-low latency of one millisecond, the platform offers fast execution for:
- Crypto
- Forex
- Equities
- Futures
QuantVPS supports significant trading platforms like:
- NinjaTrader
- Interactive Brokers
- TradeStation
- MetaTrader
- Sierra Chart
- Quant Tower
It has a 100% uptime guarantee and 24/7 support to ensure a reliable environment for traders to run their automated strategies continuously and efficiently.
2. TrendSpider
TrendSpider is an algorithmic trading platform that automates technical analysis. It offers comprehensive tools that can appeal to novice and seasoned traders alike. One of the standout features of this platform is its stock chart pattern recognition capabilities, which help traders identify high-probability trading opportunities.
TrendSpider also offers intelligent point-and-click backtesting, so you don’t need to know how to code to get started. With a seven-day free trial for just $9, it’s easy to see if this platform works for you.
3. Trade Ideas
Trade Ideas is one of the most popular algorithmic trading platforms worldwide. It employs three proprietary algorithms that identify stock market opportunities in real-time. The platform caters to traders who favor a hands-off approach but still demand high-quality, actionable stock market insights.
For this reason, Trade Ideas is best for day traders looking to gain an edge in the highly competitive US markets.
4. TradingView
TradingView is best known for its exceptional charting capabilities and wide range of technical indicators. The platform also features a social community that allows traders to share strategies and insights, making it a top pick for those who want to engage with global financial markets.
TradingView automatically detects chart and candlestick patterns and enables auto-trading.
5. Tickeron
Tickeron provides a suite of pre-made algorithms to help traders with varying levels of expertise make informed decisions. The platform also includes artificial intelligence features to help refine investment strategies.
Tickeron uses algorithmic stock chart pattern recognition to predict future trends, providing 45 streams of trading ideas.
6. VectorVest
VectorVest combines fundamental and technical analysis, offering a rich selection of automated trading strategies. With built-in market timing signals, it is suitable for traders looking for software to help streamline their decision-making process.
VectorVest offers:
- Algorithmic trading signals
- Options analysis
- Strategic insights
7. eToro
eToro is a reputable platform that offers algorithmic trading through its innovative copy trading feature. Several financial bodies regulate the global broker, with over 21 million users worldwide.
Furthermore, eToro provides access to a diverse range of markets, including:
- Cryptocurrencies
- Stocks
- ETFs
- Commodities
- Index funds
8. Dash 2 Trade
Crypto assets are among the most popular for trading with an algorithmic platform. The high market volatility makes it difficult to make trading decisions manually, so many investors and traders use algorithmic tools to help them.
Dash 2 Trade is a new toolset that is the next best platform for cryptocurrency enthusiasts who want to use algorithmic trading strategies.
9. Webull
Webull is a commission-free platform that provides access to MetaTrader 4, MetaTrader 5, and various other advanced charting tools. This makes the platform an excellent option for traders conducting thorough technical analysis.
The Webull platform has an intuitive design that makes it easy to navigate. Moreover, the platform offers interest on uninvested cash, allowing users to earn even without investing or trading.
10. Upstox Algo Lab
Upstox Algo Lab is similar to Streak. It offers some elements to practice before risking real money:
- User-friendly interface
- Various pre-built strategies
- Paper trading
The Program features an intuitive interface for:
- Creating and testing algorithmic trading strategies
- Built-in calculators
- Backtesting options
- Advanced charting tools
- Technical indicators for in-depth analysis
- Library of pre-built strategies.
11. TradeStation
TradeStation offers traders a professional platform on which to trade equities, ETFs, options, futures, and cryptocurrency. The powerful platform is suitable for both beginners and advanced traders.
New traders will appreciate the YouCanTrade educational resource, while advanced traders will enjoy the powerful scanning tools and ease with which complex trade orders can be placed.
12. Stock Market Guides
Stock Market Guides has already done all the work for you. With their algorithmic trading software, you don’t have to create or code your algorithms. They’ve already done years of researching and backtesting to find the most potent algos possible for their service.
13. Interactive Brokers
Interactive Brokers (IBKR) has two pricing tiers.
- IBKR Lite: Is designed for retail investors looking to trade U.S. equities and ETFs commission-free
- IBKR Pro: It charges $0.005 per share (including exchange fees) or tiered commissions between $0.0005 and $0.0035 per share (plus exchange fees).
14. Coinrule
Coinrule algorithmic trading platform offers four tiers of plans.
- Starter Plan: Provides up to $3,000 per month in trade volume free of charge.
- Hobbyist Plan: Charges $29.99 monthly (or $359 per year)
- Trader Plan: Charges $59.99 per month (or $719 per year)
- Pro Plan: Charges $449.99 per month (or $5,399 per year)
Coinrule focuses on cryptocurrency and allows users to create bots that follow prescribed trading rules.
15. PowerX Optimizer
PowerX Optimizer, algo trading software, possesses numerous tools you can’t find on other platforms and also provides unique views that can give traders an edge. In particular, the Wheel feature helps traders manage and collect option premiums.
16. Mindful Trader
Mindful Trader is a service run by Eric Ferguson where he shares the stock and option trades he makes in real time. Eric’s trading strategies are all based on algos that he developed.
17. Botsfolio
Botsfolio offers a free tier and a paid tier that costs 0.5% of your account value yearly (i.e., a $10,000 account costs $50 per year).
With Botsfolio, traders select their trading strategy, apply a risk level, and let the software do the rest.
18. QuantConnect
QuantConnect is powerful algo trading software, but it’s not exactly intuitive. And that’s okay. This algo trading platform is not designed for beginners. It’s meant for seasoned veterans focused on technical charting and programmatic trading.
Key Features of an Algorithmic Trading Platform
Algorithmic trading requires thorough analysis. Therefore, platforms must offer a range of advanced tools to make price predictions, spot emerging trends, and highlight potential trading opportunities. Several different tools and features could be used in algorithmic trading. Below, we will explain a few more important things to look out for.
Automated Trading
Automated trading involves using AI and ML to passively execute trades on your behalf. It is a common misconception that automated and algorithmic trading go hand in hand. Most automated trading platforms will use algorithms to place trades; not all algorithmic platforms are automated.
Some algorithmic trading platforms require traders to formulate the strategies and then deploy them utilizing an API. This is not ideal for less-experienced traders. Therefore, checking that platforms offer automated trading features that will execute algorithmic trading on your behalf is essential.
Research and Analysis Tools
Traders need to combine research and analysis with algorithmic trading. Knowing the market helps you spot opportunities, understand your software, and exit bad trades early. Experienced traders use multiple tools, but beginners should focus on mastering a few before expanding. Traders rely on two types of analysis: fundamental and technical, each needing different tools.
- Technical analysis tools are typically found within the charting feature of a trading platform.
- Standard technical analysis tools include:
- Moving averages
- Trading volume
- Bollinger bands
- MACDs
- EMAs
Fundamental analysis tools are usually found on a trading platform’s main dashboard. These tools include market news, information about a project, and expert price predictions.
Demo Account
Algorithmic trading is challenging to perfect and can be very risky. Therefore, using a demo trading account to practice trading without putting any real money at risk is a good idea. Demo trading platforms are simulated trading environments that use virtual (fake) money to create a realistic trading environment where you can practice. A demo account will usually offer the same features as a live trading account, which allows traders to practice using different strategies and tools.
The best demo accounts are free to use and can be accessed anytime. This allows traders to switch between live and demo trading to practice new strategies and techniques. Use a demo account for as long as possible before live trading.
Mobile App
The ability to manage trades on the go is an appealing feature that shouldn’t be overlooked. The best algorithmic trading platforms should offer a mobile app that allows traders to manage their trades, conduct analysis, and execute trades from anywhere.
In a volatile market, it is important that you are able to exit a trade at any time if the market direction changes and your trade becomes unsuccessful.
Payment Methods
Payments and withdrawal methods are another vital component when choosing a platform. Some banks have restricted the amount of funds deposited into trading platforms. Therefore, it is helpful to choose from various alternative payment methods such as:
- PayPal
- Skrill
- Neteller
Customer Service
Good customer service options make it easy to solve problems if they arise. It should be considered a red flag if a platform needs better customer service because this could leave you with no way of getting any help or support. The best platform will provide a variety of customer support options, such as:
- Live chat
- Phone support
It may also be helpful to find a platform that offers a Telegram group so that you can connect with other platform users who can answer your queries.
11 Popular Algorithmic Trading Strategies
Algorithmic trading executes orders using automated pre-programmed trading instructions accounting for variables such as time, price, and volume. Institutional investors and hedge funds widely use algorithmic trading to buy and sell large orders. Executing trades based on algorithms helps minimize the market impact of such orders and improves the average trade execution’s price. With the rise of retail Forex trading, individual traders can now take advantage of algorithmic trading by using expert advisors (EAs) to automate their Forex trading strategies.
An expert advisor is a manual strategy turned into code. Therefore, a Forex algorithmic trading strategy is the same system used in manual trading. Some strategies may seem complicated to novice traders, so they are turned into automated expert advisors. Some techniques considered difficult to apply and manage manually are discussed below.
1. Trend-Following Strategies
A trend-following strategy is a trading system built on the tendency of high and low prices to fluctuate in a specific direction over a long period. The goal is to determine the beginning of a trend at the moment of a price reversal or price exit from a flat and enter a trade in its direction. This system is based on the overall market sentiment.
The most straightforward algorithm of a trend-trading robot for currency pairs:
- It determines overbought/oversold zones based on oscillators. A reversal with subsequent movement to the opposite zone is most likely in these zones.
- It analyzes signals sent by trend indicators, such as the position of moving averages relative to the price of a foreign currency.
- It identifies potential zones of order congestion that may impede trend movement.
- It calculates relative volatility according to the corresponding indicator. An increase in volatility is the probability of a new trend. If all signals coincide, the EA enters a trade or places a pending order in the direction of the trend.
2. Arbitrage Opportunities
Arbitrage is a trading strategy that suggests you make money on the difference in the price of one currency pair in different markets or types of trading platforms. For example, you buy BTC on one cryptocurrency exchange and sell it on another, provided the difference yields a profit.
Arbitrage Forex traders profit by buying an asset where it’s cheaper and selling it where it’s more expensive within a short time. This strategy can involve either price differences across exchanges (spatial arbitrage) or price changes over time (time arbitrage).
Arbitrage works due to market inefficiencies, like when prices don’t match an asset’s actual value or when information between exchanges is delayed. For example, one platform updates prices faster than another, creating an opportunity to profit from the difference, even after accounting for the spread.
3. Index Fund Rebalancing
This strategy is suitable for long-term stock investors. The idea is to review and adjust the portfolio structure constantly. When prices fall, unprofitable shares are sold, and profitable ones are repurchased.
Peculiarities of rebalancing in the stock market:
- You need to wait out the drawdown.
- Calculating an instrument’s share in a portfolio correctly requires considering the level of risk and following risk management.
- You need to determine overbought and oversold states of assets.
Manual rebalancing in trading is challenging. You need to decide when to rebalance, but doing it monthly risks selling good stocks during dips and buying overpriced ones. Rebalancing yearly might delay selling poor assets. Managing risk is easier with knowing mathematical tools. Automated systems simplify this by using algorithms with models like Sharpe, alpha, and beta to find the best asset mix. They also analyze historical data to predict losses and sell underperforming assets while buying undervalued ones. Unlike manual rebalancing, this process runs continuously for better results.
4. Mathematical Model-Based Strategies
Algorithmic Forex trading strategies are based on mathematical and statistical laws. These Forex strategies use standard deviation, variance, correlation, etc. For example:
- The regression model method uses statistical regression to analyze the relationship between stock prices and other variables.
- The spectrum analysis model is built on non-standard digital indicators tracking price noise at different intervals.
- The Monte Carlo model allows you to generate many random market conditions scenarios and estimate the probability and consequences of various outcomes.
- Quantum models combine arbitrage, quantitative analysis, and high-speed trading. Building such models manually and doing calculations is pointless. The robot does all this and then offers the optimal solution for calculations-based trades.
5. Trading Range (Mean Reversion)
Range trading is an algorithmic Forex strategy that uses a price channel to determine when to enter or exit trades. A price channel consists of two parallel lines that contain price movements within a certain range.
The strategy is based on the idea that prices tend to move within a range and eventually return to their average (the middle of the channel). The further away from this average the price is, the more likely it is to reverse.
The simplest version of this strategy works like this:
- The algorithm identifies support and resistance levels using tools like:
- Standard deviation
- Moving averages
- Bollinger Bands
- Fractal
- It opens trades when the price bounces off the channel’s borders or breaks out briefly and reverses.
- If the breakout leads to a new trend and the channel expands, pending orders can be placed to catch the new trend.
- The lot is calculated by the specified settings.
- The trade is exited when the price reaches the middle of the trading range. Alternatively, the position can be closed in parts: 50% is closed when the price reaches the middle of the channels, and the rest is closed when the price reaches the opposite border of the range.
6. Volume-Weighted Average Price (VWAP)
The trading model is based on analyzing horizontal and vertical trading volumes:
- Vertical volumes show the trading volume for a particular time. They mean trading volumes on a specific candlestick.
- Horizontal volumes show trading volumes at a certain price level. They mean the number and volume of transactions at a specific price.
- Key analysis tools are volume indicators and market depth. The robot can:
- Determine the key support and resistance levels.
- Manage pending orders by emerging counter orders.
- Identify potential trends based on changing volumes. Quotes and volumes in the market depth change dynamically.
In short time frames, the change can occur within a few seconds. The trader cannot track the market data changing at such a speed, and here, an Expert Advisor is of great use.
7. Percentage of Volume (POV)
This algorithmic trading automatically determines the transaction volume, which will not significantly impact the price. Placing a large order without counter orders can dramatically change costs and increase market volatility.
The robot splits the order and places small orders as counter orders appear. Thus, it gradually satisfies counterparties’ requests until the entire order is executed.
8. Implementation Shortfall
The implementation Shortfall strategy helps minimize the gap between the expected and actual trade prices and can also be used for auto-hedging. Instead of focusing on counter-order volume, it manages trade size based on the spread. When the spread is wide (low liquidity), entering trades becomes less favorable. On the other hand, building large positions with a narrow spread is better, expecting the spread to widen for future sales.
However, buying everything at once with a narrow spread can break risk management rules, while buying in parts as the spread widens may result in higher costs. The strategy aims to balance speed and market impact by managing trade size according to the spread and keeping risk at acceptable levels.
9. Beyond the Usual Trading Algorithms
Counter orders algorithm. The strategy is trading Forex robots against robots. It comes down to identifying the algorithms of large traders and placing counter orders. The robot of an institutional investor, for example, a hedge fund, places orders to buy an instrument at certain price levels. Let’s assume it is gaining a position in parts not to influence the Forex market. Your robot finds such orders, finds the security cheaper, buys it, and sells it to the robot of an institutional investor. The difference in prices is your profit.
The strategy is a cross between volume trading and arbitrage. Automated tools are indispensable since such transactions are done in a split second.
10. High-Frequency Algo Trading
High-frequency algorithmic trading is HFT trading, which involves an automatic system opening and closing trading positions within a fraction of a second. The essence of algorithmic trading comes down to making money on the slightest price movement, allowing retail traders to make money on numerous transactions without holding them. This requires compliance with several conditions:
- Spread from 0 points. Speculative trading works if there is almost no commission. Therefore, such robots are launched exclusively on ECN accounts.
- Order execution speed. The average speed in the market is 200-300 milliseconds. The ideal speed for stock trading and trading Forex is a maximum of 30-50 milliseconds.
- The HFT strategy requires a trader to use considerable computing power. Therefore, high-frequency trading is employed mainly by institutional investors with computer access to powerful servers. The strategy’s disadvantage is the costs of regulators and the trading platform.
11. Front Running
The Front Running strategy implies that the robot places an order to buy or sell an asset before a large order from the market maker, in the expectation or with the goal that the large order will play the role of support/resistance.
- Market-depth orders are automatically analyzed for instant liquidity. An order is executed if it’s near the Bid/Ask price and much larger than the average market volume. The strategy expects the price to rebound several times before large orders are fully filled.
- Scalpers also use front running, making many quick trades to profit from small price changes. Since this strategy relies on market depth, it’s important to have a broker providing at least 20×20 levels of market depth.
How To Choose An Algo Trading Strategy
Compliance Matters: Code and Platform Compatibility
When choosing an algorithmic trading strategy, you must first consider the compliance of the code with your platform of choice. For instance, code written in C# cannot be run in MT4 and MT5. Conversely, something other than an MQL-based Expert Advisor will be suitable for the cTrader platform. If you use a trading strategy compatible with your trading platform, you will save time and money.
Understand the Risks: The Higher the Return, the Greater the Risk
The allure of algorithmic trading is that it can produce automated profits with little input from the trader. However, the reality is that algorithmic trading can be risky.
The higher the desired return, the greater the risk of losing money you will have to take. For example, risks increase if you launch several EAs at once or one EA on several instruments.
Know Your EA: Understand How It Works
You must understand what indicators, signals, time intervals, and finance instruments the EA works on. How it manages positions, stops losses, take profits, and other parameters. You should know what each parameter in the settings means and is responsible for.
Check Past Performance Under Different Market Conditions
It is necessary to check how the EA has performed in the past and present under different market conditions. You should understand how it reacts to increased:
- Volatility
- Sharp price movements
- News
The Algorithm for Choosing an EA: Tester, Different Assets, Settings
Choosing an EA involves the following algorithm: run it in a tester, run it on different assets and timeframes, and try various combinations of settings. Then, look at what interval, under what conditions, and which EA has the best result.
Don’t Rush to Buy: Free EAs Can Be Just As Good
Additional tips for trading currencies and other assets: Don’t rush to take paid Expert Advisors. These may be slightly modified free ones. Most robots are unprofitable not because they are “bad” but because algorithmic Forex traders do not know how to work with them. Set them up and adjust them to specific assets and time frames.
Paid EAs Have Their Benefits
Still, paid EAs have benefits. They should include a history of transactions on a real account. The seller can also help adapt the expert advisor to and optimize a specific task.
Start With a Manual Strategy, The Best EAs Are Algorithmic Versions of Successful Strategies
The best option is an Expert Advisor developed using a successful manual strategy.
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