Best trading algorithms strategies for the future

In today's modern technological world, technology has become an essential part of our lives. From taking morning bed tea to the last dessert, we completely rely on technology. Among this robotic world, trading businesses have made significant progress, although they face a high barrier to entry. However, algorithmic trading has largely replaced human practices. Furthermore, it helps to obtain more profits than human practices can achieve.

Algorithmic Trading?

Algorithmic trading is a quantitative trading procedure. In this trading strategy, buying and selling are done according to specified algorithms. These are computer-oriented directions used for problem-solving. Computer programs are required to write and execute these algorithms and are built with complex higher-level algorithms.

These automated systems execute the processes according to instructions preprogrammed into them. These algorithms incorporate high-frequency technology, enabling hundreds of thousands of executions within a few seconds. This Programmatic trading makes intraday trading incredibly efficient, as speed will be impossible to achieve without this.

Trading strategies

Trading strategies are methods that employ an automated, systematic approach in the trading market, utilizing powerful computer algorithms to execute trades. These strategies aim to optimise the decision-making process by using an algorithm for the automatic execution of the data when certain criteria are met. These systematic approaches provide consistent results.

They can be aligned according to specified objectives, such as managing risk, reacting to market inefficiencies, or improving trade execution. As automated trading relies on programmed instructions, it requires more careful and strategic approaches. These instructions are based on quantity, timing, price or mathematical models. There are various famous trading strategies.

1) Trend following strategy

It's a widespread strategy that follows trends, channel breakouts, price movements and technical signs. It's a simple and easy strategy, as it doesn't involve any predictions or price forecasting. Trades rely on desirable trends without getting involved in complex predictive analysis.

Pros

·       Don’t require greater times

·       Low transaction cost

Cons

·       False breakouts

·       Low hit rates

2) Arbitrage Opportunities

In an arbitrage opportunities strategy, the trader buys and sells the assets across different markets to capitalize on price variations and generate profits. The price variation can be small and short-lived, but it becomes significant for larger volumes. It is leveraged by hedging the funds and sophisticated investors.

Pros

·       Market efficiency

·       Income diversification

Cons

·       Transaction cost issue

·       Regulatory risks

3) Index Fund Rebalancing

Index fund rebalancing aims to capitalize on the price fluctuations of stocks that are added to or removed from the market index. These funds track a market index by buying and selling stocks, managing tracking error within certain tolerance levels. Traders can break down the affected stock and price movements by buying and selling these stocks.

Pros

·       Take profits as you earn

·       Tracks risk in check and close to the instructed level

Cons

·       Rebalancing can create tax obligations 

·       Can't guarantee the correctness of assumptions for initial allocation

4) Mathematical Model-Based Strategies

This modelling strategy is based on mathematical tools and models to analyse and predict financial markets, phenomena, and instruments. Mathematical representations are used to construct economic variables, relationships, procedural insight, make assumptions, and facilitate easy decision-making in the finance field.

Pros

·       Quick and easy to produce

·       Simply complex situations

Cons

·       Only works in certain situations

·       Do not include all aspects of the problem

5) Trading Range (Mean Reversion)

Trading range involves a challenge to generate profit by trading an asset as it returns to its average value or towards extreme levels. This strategy is used for performing statistical analysis of the market environment. The mean reversion strategy is employed for stock evaluation, particularly when discrepancies exist between an asset's market capitalization and its actual value.

Pros

·       Defined rewards and risks

·       Flexible strategy

Cons

·       Limited profit margin

·       Continuous trading can lead to high transaction costs

6) Volume-Weighted Average Price (VWAP)

The average price of a stock is weighted by its trade volume in the VWAP (Volume-Weighted Average Price) strategy. It is used to calculate the average price over a specific period for a stock. Investors can compare the benchmark price of stock with the current price, making their decision-making process easier regarding entry and exit from the market.

Pros

·       Better trade execution

·       Intraday support and resistance

Cons

·       Limited applicability

·       Inflexibility of time frames

7) Time-Weighted Average Price (TWAP)

This method breaks down larger orders into smaller parts by dividing the time between the start and end times. The objective is to execute the orders' mean price from start to end, thereby reducing market impact.

Pros

·       Easy calculation

·       Perfect solution for large transactions

Cons

·       More primitive

·       Very predictive, which can make it weak to other traders

8) Percentage of Volume (POV)

This trading approach utilises the trading volume of the financial markets by following a set of proportions for order execution. The primary objective of the percentage of volume strategy is to optimize trading costs and minimize the impact of market price fluctuations. It is useful for large trades that are spread over time to hedge against price volatility.

Pros

·       Greater control

·       Flexible and customizable

Cons

·       Depends on accurate data

·       Market manipulation issue

9) Implementation Shortfall risk

In the trading world, implementation shortfall is a basic concept that every trader should be aware of. It compares the decision price and the execution price of a trade. Implementation shortfall consists of four components: realised opportunity cost, market impact cost, delay cost and missed trade opportunities cost.

 Pros

·       Enhanced risk assessment

·       Incorporation of loss magnitude

Cons

·       Complexity

·       Model complexity

Final remarks

As financial markets evolve with technological advancements, trading algorithms have reshaped modern investment styles. These different trading strategies offer efficiency, speed and objectivity which humans can never achieve. Each trading strategy has its strengths and limitations. The main strengths and weaknesses are a reduction in transaction costs, more effective risk management, and precise exploitation of market opportunities. However, to implement these strategies successfully, careful planning and a thorough understanding of the market are required. The future of trading does not only depend on automatic algorithms, but also on technology strategic alignment and strong financial insights.