Algorithmic TradingAlgo
Algorithmic trading uses computer programs to place orders automatically according to predefined rules.
Much of today's market volume is placed by software, not people clicking buttons. Algorithmic trading turns a set of rules into code that watches the market and trades on its own. It removes hesitation — but it also removes the human safety check.
- Category
- Trading Strategies
- Reading time
- 3 min
- Also called
- Algo trading, Automated trading, Black-box trading
- Updated
Algorithmic trading in plain words
It means letting software place and manage trades on its own, following rules written in advance.1
A trading algorithm reads market data, decides when, where and how much to trade, and sends the orders itself — all in a fraction of a second.2
It is now an integral and permanent part of modern capital markets.2
How an algorithmic strategy works
Write the rules
Define exact entry and exit criteria the program will follow.1
Feed in data
Market data feeds into the algorithm, which checks conditions against its criteria.1
Generate signals
For example, buy when a 20-day average crosses above a 50-day average.1
Control risk
Risk modules control exposure alongside the strategy engine.1
Execute orders
The system implements the trading decision in the market.2
Monitor systems
Watch data quality and latency, which affect performance.1
Worked examples
Example 1 — A crossover bot
+$400A hypothetical bot buys 100 shares at $50 when the 20-day average crosses above the 50-day, and sells at $54 on the reverse cross.
| Entry | $50 |
| Exit | $54 |
| Profit | +$400 |
This is the kind of momentum rule CMC describes for algorithms.1
Example 2 — Mean reversion
−$400A hypothetical algorithm buys when price sits 5% below its average, expecting a return; instead it falls another 4% on a $10,000 position.
| Position | $10,000 |
| Loss | −$400 |
Mean reversion relies on prices tending to return to average, which doesn't always happen in time.1
Example 3 — A system glitch
Monitoring and kill switches matterA hypothetical bot receives a bad data feed and fires 30 unintended orders, losing $1,500 before it is stopped.
| Unintended orders | 30 |
| Loss | −$1,500 |
The SEC highlights the risk of operational or systems failures.2
Algorithmic vs manual trading
| Aspect | Algorithmic | Manual |
|---|---|---|
| Speed | Milliseconds | Seconds or more |
| Emotions | Removed from execution | Present |
| Flexibility | Only what's coded | Judgement |
| Main risk | Bugs, bad data | Human error, bias |
Common uses
Trend rules
Automating Momentum and Moving Average signals.
Mean reversion
Trading Mean Reversion setups systematically.
Market making
Quoting both sides as a Market Maker.
Arbitrage
Capturing gaps, e.g. Exchange-Traded Fund vs its basket.
Advantages and disadvantages
Advantages
- Fast and consistent execution.
- Removes emotion from order placement.
- Can be backtested before use.
- Improves liquidity in normal markets.
Disadvantages
- Substantial risk of capital loss.
- Requires technical knowledge.
- Bugs and outages can be costly.
- May worsen markets in stress.
Going deeper
Read as far as you need. Each level builds on the one before it.
Rules in code
Beginner
Programs trade automatically on predetermined criteria.1
Market effects
Intermediate
The SEC found it improved many measures of market quality in normal conditions but some types may worsen periods of stress.2
System risk
Advanced
It carries substantial risk and needs technical knowledge; data latency and systems failures are real threats.1
Common mistakes
Overfitted code
Tuning the algorithm perfectly to past data.
No kill switch
Letting a broken bot keep trading.
Ignoring costs
Leaving out fees and slippage.
Set and forget
Not monitoring live behaviour.
Check your understanding
Test yourself before moving on. Each answer comes with an explanation.
Key points to remember
- Algorithms trade automatically on fixed rules.
- They are fast and emotion-free in execution.
- They're only as good as their rules and data.
- Systems failures are a real risk.
- Test, monitor and use kill switches.
Frequently asked questions
Can retail traders use algorithms?
Is algorithmic trading the same as high-frequency trading?
Does an algorithm guarantee profits?
Further learning
- Backtesting
Testing rules before going live.
- Mean Reversion
A common algo strategy.
- Momentum
Trend-following rules.
- Slippage
Execution costs for bots.
Sources
This article is written in our own words. The sources below support the specific facts, rules and figures marked with a number in the text. Links open the original publisher’s page.
- CMC Markets. What is algorithmic trading? A complete guide (opens in a new tab) Checked .
- U.S. Securities and Exchange Commission. Staff Report on Algorithmic Trading in U.S. Capital Markets (2020) (opens in a new tab) Checked .
Educational content, not financial advice. Examples use hypothetical prices and simplified costs; actual fees, margin rules and regulations vary by broker, market and country. We are not affiliated with any publisher linked above. Last reviewed . Report an error or request a source credit.