To participate in algo trading, you need a computer programmed with instructions (called algorithms). The full name of this concept is algorithmic trading, although some traders call it automated trading.
Trading in algorithms can increase profit-making since artificially intelligent computers are faster, more accurate, and less impulsive than the human brain.
Here are algo trading tips to get you started.
Understanding Algo Trading
The pre-programmed instructions used in algo trading depend on price, timing, volume, and other systematic equations that make automated trading more effective. That’s why the definition of a computer algorithm is a formula that solves a problem!
Computer algorithms can increase market liquidity, decrease the negative impact of impulse trading, and any probability for human oversight also gets programmed into the formula for even greater success.
Algorithmic trading operates most efficiently using high-frequency trading (HFT), a technology allowing many thousands of trades each second. This astonishing speed means more profit on larger orders, especially when automated trades happen across multiple markets and rules.
Algo Trading Technology
The computer programming behind algorithmic trading goes beyond downloading the right software. Here’s what’s involved:
- In-depth knowledge of computer programming is required, specifically in formulating trading strategies. Trading software does exist, but experienced programmers have the know-how to backtest the system and fix any bugs.
- Backtesting of the system is crucial before trading goes live.
- Backtesting works by trialing the algorithms on previous stock market data to gauge its success and profitability.
- A secure network with login access to various trader platforms is necessary.
- External market data must be constantly available for the algorithms to monitor and perform automated trades.
Once all of the sophisticated technology and complex programming are in place, let’s take a glimpse at simple algo trading in action.
Algo Trading in Action
Here’s a basic trading premise to demonstrate how automated trading formulations get programmed to go to work.
- A trader purchases a quantity of stock that has gone above the 200-day moving average at the 50-day mark.
- If the 50–day moving average falls below the 200-day moving average on that particular stock, the trader sells a quantity of the shares.
As a simple algorithm, the trader’s computer monitors stock prices (including moving averages) and conducts a buy/sell when the defined conditions (price and averages) occur.
Where Is Algo Trading Used
Algorithmic trading is now widely utilized in many trading and investment scenarios, such as:
- Insurance, pension fund, or mutual fund long-term investment portfolios use automated trading for large stock purchases instead of large-volume investment purchases that can artificially influence the markets.
- Short-term trading speculators and brokerage houses use algo trading to create ample seller liquidity in the markets.
- Hedge fund companies and systematic traders or trend followers benefit significantly from the efficiency of programming their trading rules into algo trading, allowing market-neutral strategies like matching exchange-traded funds (ETFs).
Algo Trading Tips Strategies
Algorithmic trading is designed to increase profits from trading opportunities and decrease costs through automation.
Let’s examine how algo trading works in various trading strategies:
Automated trades are common in trend-trading strategies without price forecasting or predictive analysis. Trend-trade strategies include channel breakouts, price level moments, and, precisely, moving averages, probably the most popular trend-trading strategy.
Buying stocks low from one market and reselling them higher in another market creates a risk-free, price differential profit scheme called arbitrage. Algo trading formulas monitor price differentials and order immediately.
Algorithmic trading offers fast trades at the best profit margin during defined periods when index funds get rebalanced to par with benchmarks. Index fund rebalancing can provide trades of 20 to 80 basis points depending on the stock, making this an excellent profit opportunity for traders.
Delta neutral strategies use proven math concepts to perform secure trades with positive and negative offsets, resulting in zero (neutral) changes in the price of an asset (typically marketable securities).
Mean Reversion Price Ranges
Mean reversion is a strategy that assumes the price of an asset may rise or fall temporarily, but prices revert to their average (mean) value in time. Algo trading formulas monitor when prices go high or low, and buying or selling is automatic during these periods.
VWAP means volume-weighted average price, a strategy used on large trade orders. The algorithm uses historical volume data to sell chunks of a trade at the right time, to achieve as close to the VWAP as possible.
TWAP means the time-weighted average price, a strategy also used to sell chunks of a larger trade order in measured slots of an equal amount of time. This strategy assumes that the average price causes less market impact.
This strategy uses a defined percentage of volume (POV) in the algorithm to fulfill partial orders until whole trades get executed entirely. This step can increase or decrease according to market participation levels and when the stock price reaches a defined limit.
Advantages of Algo Trading
Algorithmic trading requires high-level technology and complex programming knowledge.
Here’s a refresher on the advantages of successfully programmed and backtested algo trading:
- The algorithm monitors all incoming data and makes automated trades at the best price possible.
- Automated trade orders are instant and accurate because the algorithm is set at desired limits.
- The timing of automated trades is programmed at the exact time to guard against sudden and significant drops in value.
- Automation generally ensures reduced costs in trading transactions.
- Automated trades simultaneously monitor multiple markets with multiple rules.
- Automation reduces the possibility of manual errors in trading.
- When algo trading gets backtested properly, the viability of all trading strategies can be foolproofed against historical and real-time data.
- Unlike their human counterparts, automatic trading makes no mistakes based on emotional or psychological triggers.
Learn Algo Trading Tips
It’s best to learn algo trading carefully and obtain current guidance and hands-on experience from industry pros, full-time traders, or market authorities.
Check these algo trading tips to get you started.
Online Tutorials and Blogs
When you Google “creating trading algorithms,” you will find blogs and video tutorials that explain how to create a trading algorithm and test it using actual market data. The blog or tutorials you select should explain strategies like mean reversion and use them as examples in the algorithm to be adequate for learning purposes.
Hard Copy Books
Some people find it easier to absorb a hard copy book on complex subjects like algo trading. To find the right book for your skill level, do a Google search on “essential books for algorithmic trading.”
For beginners to algo trading, search for entry-level books by Dr. Ernest Chan.
Other Resources on Algo Trading
You can always search online learning portals for introductory courses on algo trading. Training websites are also a good resource, and many offer online podcasts, webinars, or workshops to explain their algo trading courses and instruction methods.