Automated trading systems open the door to many possibilities for traders, but not all automated trading systems or approaches to automated trading are created equal. You want to find a way to automate the specific trading strategy that works for you. For traders focused on high-speed market opportunities, low latency trading ensures rapid execution and minimizes delays. Automated trading strategies remove emotion from trading. They eliminate human error and allow traders to execute their systems with precision.
When paired with a trading VPS, automated trading strategies enhance efficiency by allowing traders to analyze vast amounts of data quickly and execute trades at the best possible prices without delay.
What is Automated Trading and How Do You Get Started?
There comes a time in a trader’s life when they start feeling overwhelmed with the amount of data to process and the speed at which decisions must be made. Imagine you want to participate in trading but need more time or expertise to monitor the markets constantly. This is where automated trading comes in. So what is it?
What is Automated Trading?
Automated trading, or algorithmic trading, involves computer programs and algorithms to execute trades in financial markets. These programs are designed to:
- Analyze market data automatically
- Identify trading opportunities
- Execute trades without human intervention
Building Blocks of Automated Trading Strategies
Algorithmic trading strategies are built upon several key components that help traders make informed decisions. These building blocks include:
Technical Analysis
Technical analysis involves examining historical price and volume data to identify patterns, trends, and indicators that can help predict future price movements. Traders use technical indicators such as moving averages, oscillators, and chart patterns to generate buy or sell signals.
By analyzing past market data, technical analysis aims to identify opportunities for profitable trades based on the assumption that historical price patterns tend to repeat themselves.
Fundamental Analysis
Fundamental Analysis focuses on evaluating the intrinsic value of a financial asset by studying relevant financial data, economic indicators, and company-specific factors. Traders who employ fundamental analysis consider these factors to assess a company’s or market’s financial health and growth potential:
- Earnings reports
- Balance sheets
- Macroeconomic indicators
This approach aims to identify undervalued or overvalued assets, providing potential opportunities for profitable trades. Factor investing is an example of this.
Sentiment Analysis
Sentiment analysis involves understanding market sentiment by analyzing social media trends, news sentiment, and other sources of information. Traders seek to gauge market participants’ overall mood and perception toward specific assets or markets. By monitoring social media platforms, news articles, and sentiment analysis tools, traders can gain insights into:
- Public opinions
- Investor emotions
- Market expectations
These insights can be used to make informed trading decisions or to identify contrarian opportunities when the market sentiment is overly positive or negative. The AAII sentiment indicator strategy is an example of this.
How Automated Trading Works and How to Use It
With automated trading, you can predict whether a particular market’s price will rise or fall using a type of trade called CFDs.
Contract for Difference
CFD trading is a form of derivative trading where investors speculate on the price movements of underlying assets without owning them. Also, automated trading allows you to replicate the trades of experienced traders. Doing this lets you automate your trading and participate in the market, even if you’re new to trading. To get started, you’ll have to choose a platform that supports automated trading and set the parameters for your trading strategy.
Here’s where it gets interesting. Based on your trading experience and knowledge, you’ll create a set of rules and conditions (parameters) that your custom algorithm will follow when making trades on your behalf. For example, set parameters for the:
- Timing of the trade
- Desired opening and closing prices
- Quantity you want to trade
Trend-Following Strategy
One example of automated trading based on timing, price, and quantity is a trend-following strategy. The algorithm could be programmed to buy a specified amount of, let’s say, Microsoft shares when its 50-day moving average crosses above the 200-day moving average, indicating a potential upward trend.
The Power of Automated Trading
Once your parameters are set, the automated trading strategy will constantly monitor the prices in the financial market. If the predetermined conditions are met, the algorithm will execute trades automatically on your behalf. This allows you to take advantage of specific market events and gain more efficiency.
The Risks of Leveraged Trading
It’s crucial to understand that automated trading involves leveraged trades using CFDs. You only need to deposit a small margin to gain exposure to a larger position. Nonetheless, profits and losses are calculated based on the total size of the position, not just your margin amount. This means losses could exceed your initial deposit if the market moves against you.
While automated trading can be a convenient and efficient way to participate in the markets, it’s crucial to understand the risks involved and manage them effectively.
Benefits of Forex Algorithmic Trading
Algorithmic trading improves efficiency, speed, and accuracy by automating trading decisions
and execution. Since it is packaged as Expert Advisors that run autonomously on a trading terminal, algorithmic trading allows retail traders to better respond to market opportunities and mitigate risk.
The Power of Backtesting and 24/7 Trading
Backtesting methods against past data enable traders to make educated decisions and boost performance. Notably, algorithmic trading continues around the clock, even when you fall asleep. So, you will likely take advantage of profitable trading opportunities during each forex market hour.
Leveraging VPS for Uninterrupted Trading
While Expert Advisors can run autonomously on the trading terminal, they need the terminal to be online 24/7 to trade 24/7. Traders use QuantVPSs, which allow them to host their trading terminals in 24/7 data centers.
Getting Started with Automated Trading
- Choose a Trading Platform: Select a reliable and user-friendly platform that supports automated trading. One popular option is MetaTrader4.
- Use algorithmic trading software: Consider using algorithmic trading software. Several platforms provide tools and libraries for:
- Backtesting
- Optimization
- Executing automated strategies
- Backtest Your Strategy: Before deploying your automated strategy in the live market, backtest it using historical data. This will help you evaluate its:
- Performance
- Profitability
- Risk management
- Start with a Demo Account: Begin by practicing with a demo account provided by your broker or trading platform. This allows you to test and refine your strategy in a risk-free environment before using real money.
- Monitor and Adjust: Once your automated strategy is live, closely monitor its performance and make necessary adjustments based on market conditions and feedback from backtesting.
Related Reading
- How to Automate Trading
- Introduction to Algorithmic Trading
- Trading Risk Management
- How to Set Up Algorithmic Trading
20+ Best Automated Trading Strategies
1. Direct Market Access: Cutting Out the Middleman
Direct Market Access (DMA) eliminates the need for intermediaries between buyers and sellers by connecting them directly with liquidity providers and exchanges. This trading approach allows for more rapid order execution, reduced trading expenses, and greater transparency. With DMA, traders control the order book and make transactions at particular prices by entering orders at the appropriate times. Institutional investors and high-frequency traders frequently use this algo due to its efficiency and quickness.
Pros
- It offers rapid order execution and helps reduce trading costs.
- It provides greater transparency.
Cons
It requires high speed and technology costs, increases exposure to market volatility, and, due to direct control, carries the risk of erroneous trades.
2. Forex Scalping: Quick Profits for Fast Traders
Using a forex scalping algorithm, traders enter and exit positions quickly to profit from slight price fluctuations. During a single trading session, a scalper might make hundreds of trades, each with a modest profit goal. Effective risk management, speedy decision-making, and precise order execution are the pillars of this algorithmic strategy.
The Demanding Nature of Scalping
Notably, you must be highly focused and self-disciplined to monitor the market and quickly respond to price fluctuations closely. Scalping can be lucrative if you have a high success rate and a good risk-reward ratio, even if your transaction earnings are modest. Remember, you must pick currency pairings with low spreads and employ a swift trading platform when scalp.
Pros
It generates quick profit from slight price fluctuations, helps in effective risk management, and offers a high potential for numerous small profits.
Cons
- It requires intense focus and self-discipline.
- It tends to be sensitive to trading costs and spreads.
- It can be vulnerable to significant losses if not managed properly.
3. Statistical Trading Strategy: Let the Numbers Do the Talking
Statistical traders employ mathematical models and statistical analysis to spot patterns and trends in market data. They compile and analyze massive amounts of price data to create algorithms reliably forecast price direction. These algorithms may employ statistical methods like moving averages and regression analysis.
Statistical trading can be used across several timeframes, providing traders with actionable insights based on historical data. This technique relies heavily on accurate backtesting and optimization to guarantee success in real-world trading.
Pros
- It employs mathematical models and data analysis.
- It provides actionable insights across different timeframes.
- It helps in systematic and disciplined trading.
Cons
- It relies on accurate backtesting and optimization.
- It may struggle to predict unprecedented market events.
- It may not capture complex market dynamics.
4. Market Sentiment Trading Strategy: The Market’s Mood Matters
Market sentiment algorithms involve analyzing investor sentiment and mood to make trading decisions. Traders use sentiment indicators, social media analysis, and news sentiment to gauge the market’s emotional state. Positive sentiment suggests bullish moves, while negative sentiment indicates bearish movements.
Sentiment analysis can complement other trading strategies by providing additional context and insights into the prevailing market sentiment. It’s important to note that market sentiment can be subjective and may not always reflect the true market direction. Therefore, forex traders should use sentiment analysis with other technical and fundamental analysis tools for more accurate decision-making.
Pros
- It provides additional context and insights
- Complements other trading strategies
- Useful for short-term market movements
Cons
- It is subjective and not always accurate.
- It may lead to an overreliance on emotional market sentiment.
- It does not account for fundamental factors.
5. Mean Reversion Strategy: Trading Price Deviations
The premise of the mean reversion strategy is that prices will eventually return to their average level. Traders typically anticipate a reversion to the mean when an asset’s price deviates dramatically from its historical average. They employ technical indicators like the Relative Strength Index (RSI) and Bollinger Bands to spot overbought and oversold positions.
When the price of an asset reaches a new extreme, investors sometimes bet on a return to the mean by taking opposite positions. Although successful in range markets, mean reversion trading necessitates vigilant risk management due to the possibility of sustained price deviations from the mean.
Pros
- It takes advantage of price deviations from the mean
- Can be profitable in range-bound markets
- Helps spot clear entry and exit points
Cons
It requires vigilant risk management. It may cause you to suffer during strong trending markets and has the potential for prolonged price deviations.
6. Machine Learning Trading Strategy: Smart Trading for the Future
The use of machine learning and artificial intelligence (AI) for algorithmic trading in the forex market is becoming increasingly popular. It helps forex traders create more nuanced and responsive trading models. Algorithms trained by machine learning can go through mountains of data, pick out fine trends, and optimize investment strategies based on past results.
The Power of Machine Learning in Algorithmic Trading
Automatic learning from new data allows AI-powered algorithmic trading systems to refine their decision-making gradually. These algorithms may employ neural networks, support vector machines, and other AI methods to detect market tendencies and produce trading signals. Because of their flexibility and adaptability, machine-learning AI trading systems are well-suited for the ever-evolving financial markets.
Pros
- It enables nuanced and responsive trading models.
- Can process vast amounts of data.
- Detect trends.
- Adapt to changing market conditions.
Cons
It can be complex to implement and fine-tune. It may overfit historical data. It cannot improve interpretability in model decisions.
7. Market-Making Strategy: Providing Liquidity for Profit
Traders or brokerages who act as market makers are responsible for maintaining the market’s liquidity by constantly quoting buy and sell prices. They earn money on the spread between the buying and selling prices, known as the bid-ask spread. Even if there is no immediate buyer or seller, they buy or sell at the prices they have quoted.
This makes trading easier for everyone by reducing the gap between the bid and the ask price. Because of the possibility of exposure to market volatility and unexpected price moves, market-making strategy calls for cutting-edge technology, such as advanced algorithms and appropriate risk management.
Pros
- It helps maintain market liquidity, generates revenue from bid-ask spreads, and simplifies trading for all market participants.
- It increases exposure to market volatility and unexpected price moves, requires advanced algorithms and risk management.
- Could involve potential conflicts of interest.
8. Auto Hedging Trading Strategy: Protecting Positions from Losses
Auto-hedging is a risk management method involving equivalent trades to cancel out any possible losses in a position. If a trader’s position is vulnerable to large negative price changes, an auto-hedging algorithm will immediately arrange a hedge trade to protect the investment.
Traders anticipate that their portfolios will be safer from the effects of rapid market volatility by doing so. Institutions and trading firms with substantial market exposure frequently use auto hedging. The technique relies on constant market tracking and the speed with which one can place hedging bets.
Pros
- It helps manage risk and protects investments.
- It reduces portfolio exposure to market volatility.
- It is suitable for institutions and large trading firms.
Cons
- It requires constant market monitoring.
- It may cause you to incur additional trading costs.
- It can sometimes limit potential profits.
9. News-based Trading Strategy: Responding to Market Shocks
In news-based trading, trading decisions follow the market’s reaction to news and economic developments. When major news is released, traders often rush, which can result in price changes. News-based traders use algorithms to decipher news headlines, economic data releases, and other events that can move markets.
When specific parameters are met, the system automatically opens positions. Notably, market volatility and slippage around significant news events pose a risk to traders who rely on news to make money.
Pros
- It capitalizes on market reactions to news events
- Strictly follows predefined parameters
- Suggests quick entry and exit opportunities.
Cons
- It carries market volatility and slippage risks during news events.
- It heavily relies on timely and accurate news sources.
10. Arbitrage Trading Strategy: Profiting from Price Discrepancies
Using an arbitrage strategy, you can make money by taking advantage of price fluctuations on various exchanges and financial markets. Speculators purchase an asset in one market and immediately sell it in another for a profit. Trading currency pairs across multiple brokers or forex markets is a common form of arbitrage.
The arbitrage strategy necessitates rapid execution and low-latency connections to take advantage of temporary pricing differences. Essentially, arbitrage possibilities can be identified and traded quickly with the help of an automated system, limiting losses and maximizing gains.
Pros
- It exploits price discrepancies for profit and can be automated for quick execution.
- It requires fast execution and low-latency connections.
- It may be subject to potential regulatory and market limitations and offer limited opportunities in efficient markets.
11. Stealth Trading Strategy: Keeping Trades Under the Radar
The stealth trading approach aims to make as little noise as possible when making trades. Due to the size of the order, market prices may shift in a way that is unfavorable to the trader when a large order is placed. Stealth trading algorithms split massive orders into smaller, less apparent pieces to avoid substantially impacting the market. Traders lessen their exposure to slippage and price manipulation by conducting transactions in private.
Pros
- It minimizes market impact and slippage.
- Provides more favorable execution for large orders.
- Reduces the risk of front-running.
Cons
- It may need help splitting and managing large orders.
- Miss the optimal entry and exit points.
- Sometimes not accurately predict market reactions.
12. High-Frequency Trading (HFT) Strategy: Speed Is Everything
High-frequency trading involves executing many trades quickly to take advantage of small price movements. HFT firms use ultra-fast computers and low-latency connections to gain an edge in the market. HFT strategies exploit little price discrepancies, often holding positions for a fraction of a second to a few seconds.
HFT has revolutionized trading, but it also faces criticism for potential market instability and the advantages it provides to firms with the fastest technology. Although this algorithmic strategy is becoming increasingly popular, brokerage and prop firms mainly do not allow traders to use High-frequency trading.
Pros
- It helps you take advantage of small price movements.
- It requires high-speed execution for quick profits.
- Offers access to market data and trends in real time.
Cons
- It has the potential for market instability and flash crashes.
- It involves the use of expensive technology and infrastructure requirements.
- Due to its speed advantages, it may not be accessible to all traders.
13. Trend Following Strategy: Go with the Flow
Traders using this method monitor price changes and market patterns for clues about when to enter and leave trades. Traders who follow trends anticipate and attempt to profit from sustained price shifts in one direction.
The Role of Technical Analysis in Algorithmic Trading
Traders employ technical indicators, chart patterns, and price action analysis to spot developing trends and possible trend reversals. Although trend-following algorithmic trading can be successful in rising markets, they may suffer in falling markets or markets with excessive volatility.
Pros
- It helps traders profit from sustained price shifts in one direction.
- It employs technical indicators for trend identification.
- It produces straightforward entry and exit signals.
Cons
- It may not perform in volatile or choppy markets.
- Lead to delayed signals during trend reversals.
- Struggle to differentiate between genuine trends and false signals.
14. Iceberging Trading Strategy: Concealing Orders to Mitigate Risk
The Iceberg algorithmic strategy involves placing a huge order in the market without disclosing the complete order size. A portion of the order is placed in the market for all to see, but the remainder (the substantial part) remains unseen and needs to be executed. When one section is complete, the next section is disclosed to process the order.
Institutional traders, or those with large order sizes, frequently adopt this method to mitigate the potential for adverse price movements caused by the simultaneous execution of numerous orders.
Pros
- It enables you to conceal large orders to avoid price impact.
- It is suitable for large institutional traders.
- It mitigates the risk of slippage.
Cons
- Managed hidden order sizes may take time.
- They have the potential for incomplete execution.
- May limit the visibility of market depth.
15. Volume-Weighted Average Price (VWAP) Strategy: Judging Trade Quality
To calculate the average price of a forex pair over a given period, traders employ an algorithmic trading approach known as the Volume Weighted Average Price (VWAP). The volume-weighted average price (VWAP) is determined by adding up the prices of all trades throughout the specified time, multiplying by the total volume of those trades, and then dividing by that amount.
This approach aims to give investors an indicator of the market average price against which they may judge the quality of their trades’ prices. Traders widely use VWAP to predict market movement and identify probable support and resistance levels.
Pros
- It reflects the market average price.
- It helps identify potential support and resistance levels.
- It is useful for judging trade execution quality.
Cons
- It may need to work better in illiquid markets.
- It heavily relies on accurate volume data.
- It lags behind real-time price movements.
16. Index Funds Rebalancing: Profiting from Market Inefficiencies
All index funds must get their holdings in line with the index they are trying to mimic in a set amount of time. Algorithmic traders can profit from this rebalancing by focusing on the assets that must be purchased immediately before the rebalancing period, creating an arbitrage opportunity. Algorithms are ideal for carrying out these deals since they allow optimal time and pricing.
Pros
- It exploits arbitrage opportunities during rebalancing.
- Offers optimal timing and pricing with algorithms.
- Has the potential for consistent profits.
Cons
- It is limited to specific timeframes and rebalancing periods.
- It requires accurate tracking of index changes.
- It may generate small profits.
17. Time-Series Momentum (Trend-Based): Riding the Wave of Market Trends
Time-series momentum focuses on whether a specific market is moving up or down. This strategy prioritizes assets based on their past performance. Traders keep growing assets. They get rid of those showing negative momentum. How it works In short, “buy high, sell higher.” Traders buy and keep assets showing positive growth during a specific period.
The key to success is identifying winning/losing assets early in the up/down cycle. Key features include:
- Timing is Critical: Success often hinges on precise timing, meaning the difference between profit and loss.
- Trend Analysis: Regularly review whether a trend is continuing or showing signs of reversal to make informed decisions.
- Data Aggregation:
- Combine historical data with current market parameters to gain actionable insights.
- Identify patterns that help predict potential shifts in market trends.
- Market Insights:
- Automation tools collect and process market data efficiently.
- Highlight early indicators of potential changes in trend direction, giving traders a competitive edge.
A time-series momentum strategy generates profits for most implementations, making extreme profits possible. Still, it is market-dependent, requiring expertise and constant risk control. Portfolio diversification and rebalancing are critical for hedging risks.
18. Cross-Sectional Momentum: Focusing on Relative Performance
This momentum strategy takes relative performance into account. It means concentrating on top-performing assets while shorting bottom-market performers. Just like time-series momentum, cross-sectional momentum works for up markets. How it works “Buy best, sell worst.” Traders approach momentum from a slightly different angle. They list top X market performers and cut off Y laggards based on past performance.
Timing is less critical: traders assign the same number of assets to each portfolio. Key features Neither momentum strategies perform well in down markets. Hence, it is essential to identify established, actual trends in both cases.
The Role of Trading Software and Momentum Strategies
Trading software helps automatically gather relevant market data and generate insights. Traders make sense of data reports and then decide. Or they simply create automated sales/purchases upon reaching pre-determined values.
Is it profitable? Cross-sectional momentum shows the best results in currency markets. Combining cross-sectional and time-series momentum as part of a hedging strategy makes sense.
19. Dollar-Cost Averaging: The Steady Path to Market Returns
Dollar-cost averaging regularly invests equal sums in the same asset over a certain period. It aims to lower long-term asset costs. Price at a certain point does not matter for this strategy; consistency is crucial.
How it Works
Traders spend a fixed amount of money every time instead of the entire sum within a single session. They buy a different number of assets each time, depending on their market price at the purchase time. Traders profit from market declines.
Key Features
Dollar-cost averaging allows a decrease in median purchase costs per asset. Sticking to the initial plan increases investing discipline and minimizes regrets. Hence, traders can set up an automated purchase of selected positions.
Is it profitable? Yes, it is regarded as the best strategy for novices and those not interested in continually monitoring the market. It removes the pitfalls of inopportune timing and counterproductive decisions backed by investors’ emotions.
20. Day Trading Automation: Algorithmic Trading for Short-Term Strategies
Day trading strategy targets short-term market volatility. Traders enter and exit positions within the same day. In extreme cases, they hold a position for only seconds. How it works Traders must determine profit and stop-loss levels. They may sell a position upon reaching a pre-determined level or decide on a more complex technique.
A well-thought-out strategy and risk management, including a maximum loss limit, are critical when a trader wants to stay safe after several unsuccessful bids.
Key Features
Traders use various software to spot trends and potential entry points. They can set up automated sales/purchases as part of an automated trading strategy.
Constant manual chart monitoring can be exhausting, especially when dealing with several positions simultaneously—but not for software. Is it profitable?
This strategy only suits some. It requires extensive market knowledge, dedication, and a cool head. Also, traders must remember that taxes and transactional costs decrease profit margins. (For instance, IT Craft helps develop and maintain trading platforms. It offers trade bots that always count commissions to eliminate end users’ losses.)
21. Black Swan Catchers: Profiting from the Unpredictable
A black swan event is a financial term for an unpredictable event that lies beyond normal expectations but has potentially disastrous outcomes. In his famous writings, Nicholas Taleb describes the Global Financial Crisis as a black swan event. Another more recent example is the COVID-19 pandemic.
Capitalizing on Black Swan Events
Catching a black swan, so to speak, is an investment strategy that leverages the intense market volatility following such an event. It involves finding speculative markets like options contracts and others that traditionally skyrocket whenever a black swan appears.
Harnessing Algorithmic Trading for Tail Risk Strategies
These so-called tail risk strategies can benefit enormously from using algorithmic trading to monitor market levels, identify black swan events, and trigger investment in the opportunities these events leave behind.
22. Inverse Volatility: A Counterintuitive Strategy for a Risky Market
Inverse volatility strategy is often used with markets for exchange-traded funds (ETFs). This strategy involves buying inverse volatility ETFs to hedge against portfolio risk by gaining exposure to volatility. Doing so makes it no longer necessary to buy options.
Using Inverse Volatility ETFs for Stable Markets
Investors can see substantial returns if volatility remains low. An inverse volatility ETF bets on market stability as the prevailing condition. This strategy’s practical use includes using a specific metric: the Cboe Volatility Index (VIX). When an ETF’s benchmark volatility rises, it loses value.
Using algorithmic trading to monitor an ETF’s volatility on the VIX can help automate buy and sell orders to limit losses and maximize gains.
Related Reading
- Best Automated Trading Platform
- Automated Trading System
- High-Frequency Trading Algorithm
- Algorithmic Trading Strategies
- Futures Trading Algorithms
How to Pick the Best Forex Algorithmic Trading Strategy
Selecting the right strategy depends on various factors. The best forex algorithmic trading strategy is the one that best fits the trader’s objectives and risk appetite. You must also consider the current market climate, leverage cutting-edge tools and accurate data, and diversify your trading portfolio while choosing the best algorithmic strategy.
To improve trading success in algorithmic trading, you must maintain a high level of flexibility and continue to educate yourself about the foreign exchange market and algorithmic trading.
The Importance of Backtesting and Risk Management
Regardless of the strategies, you must still program your Forex algorithm into an expert advisor or a trading robot to automate your trades. To do that, you need in-depth knowledge about forex algorithmic trading courses. Successful algorithmic trading strategies often involve diversifying the portfolio and allocating capital effectively.
Here are key considerations:
Diversification
Implementing risk management techniques, such as stop-loss orders or position sizing, can help control the downside risk of individual trades and the overall portfolio. Still, keep in mind that most strategies perform worse when implemented. We recommend trading smaller and more diverse to mitigate the risk of losses.
Real-Time Monitoring and Execution
Building a robust trading infrastructure involves creating a secure and reliable platform that can handle the demands of live trading. This includes implementing scalable and high-performance servers, establishing connections to relevant exchanges or liquidity providers, and integrating data feeds for real-time market updates. We recommend renting space on a remote server, which you can access from your computer or device.
Related Reading
- Automated Futures Trading Strategies
- Best Automated Futures Trading Software
- Backtesting Trading Strategies
- Best Algorithmic Trading Software for Beginners
- MT4 Trade Copier
Deploy a Trading VPS Today
Running automated trading strategies requires a trading VPS, which provides a reliable computer to run a trading platform 24/7 without downtime and lag. For this reason, many traders opt for a virtual private server (VPS).
A VPS remote computer allows you to run off-site trading software for your algorithm. This will enable you to access your algorithm from anywhere, and because the VPS is hosted in a data center, it will have a much more stable internet connection than your home computer.