Claude 3.7 vs. ChatGPT: Coding Trading Strategies Compared

The world of algorithmic trading is rapidly evolving, with Artificial Intelligence (AI) playing an increasingly significant role. AI models are now capable of generating code for trading strategies, offering traders a powerful tool to automate and optimize their approaches. But, with so many AI options, it’s important to know which ones are actually good. This article compares Claude 3.7 to other AI platforms like ChatGPT, to see what the future of algorithmic trading holds. It’s time to discover which AI reigns supreme in the art of coding profitable trading strategies.

Introducing Claude 3.7

Anthropic has recently introduced Claude 3.7, hailed as a potential Game-changer in the future of coding, particularly for trading strategies.

This cutting-edge AI model promises enhanced capabilities in generating complex and profitable algorithmic trading solutions. But the real question is, can Claude 3.7 actually deliver on its promises when it comes to coding strategies that lead to profits? In this article, we will be testing Claude 3.7. This article aims to put Claude 3.7 to the test, comparing it against the current industry leaders like ChatGPT and other models. Ultimately, it helps traders decide which AI is actually the best for trading strategy coding.

Head-to-Head with Industry Leaders: Claude 3.7 vs. ChatGPT

In the fast-paced world of AI-driven trading, it’s crucial to know how the latest tools compare against established benchmarks. ChatGPT has been a dominant force in AI-assisted coding for quite some time. This article compares Claude 3.7 directly with ChatGPT and other AI models, providing a clear understanding of its strengths and weaknesses. Through real-world testing on TradingView, we will reveal which AI model truly comes out on top in generating profitable and efficient trading algorithms. We've put together a tier list of coding AI for profitable trading strategies based on prior testing as you can see here:

TradingView: The Algorithmic Arena

To ensure a fair and accurate comparison, this analysis leverages TradingView, a popular Charting platform among traders.

TradingView provides the ideal environment for backtesting and evaluating the profitability of trading strategies. By using TradingView, we can assess each AI model's ability to generate robust algorithms that perform well under realistic market conditions. This testing ground allows for a transparent, data-driven comparison, and is the key to figuring out Claude 3.7’s true potential.

Prompt 1: Basic Trend-Following Strategy

The initial test involves prompting Claude 3.7 to code a basic trend-following strategy. The strategy should utilize the Exponential Moving Average (EMA) and Moving Average Convergence Divergence (MACD) on the one-hour timeframe with a basic risk management.

The results were:

1. Opening the code panel, as always with Claude, it separated the code into it’s own easy to read container.
2. The core components of the strategy included a dual EMA crossover system (13/48) to determine direction and signal.
3. MACD settings were correct to signal Momentum.
4. Instructions were given for trailing stop placement and the code has been updated accordingly.
5. Volume confirmation as another decision point.

After reviewing the code, a backtest of the strategy was done using TradingView. Although the model produced a functional, correct strategy, after a backtest the strategy was not immediately profitable and adjustments would need to be made. This model will be added to the existing tier list accordingly.

Prompt 2: NNFx Model

For the Second trading strategy, Claude 3.7 was tasked to build a strategy according to the NNFx non-nonsense forex model.

This is known for it’s alternative style of building an Algo. The goal was to explore if the software can "think outside the box" and give a strategy using unique indicators:

1. Instead of the typical indicators like RSI and MACD, for example, it implemented what’s known as the ichimoku cloud. Not many algos or trading strategies are built this way.
2. Volume and price action

After compiling the code it worked well and looked very good! The tester then performed an extensive back test to figure out the long term profitability of this model, and found that, out-of-the-box, there was a degree of profitability. After entering the NNFx strategy, Claude has done such an insane job. This cemented Claude as a top coder.

Prompt Engineering

Clarity and Specificity: Provide precise instructions regarding your requirements. The more detail you provide the less debugging will be needed after the code compiles. Indicator Preferences: Specificy what indicators and confirmation signals you want to use. Do you want to use traditional or unique indicators?

TradingView

Implement Backtesting: After compiling your code, make sure you accurately test any strategy compiled. Understand Key metrics: Look at your profit factors, trading styles and max draw down for maximum performance. Don’t use too much of your equity at once.

Claude 3.7 and ChatGPT

Claude 3.7 Pricing: Claude has different levels of access based on usage. Pricing can vary widely depending on context and code compiled. ChatGPT Pricing: ChatGPT operates on a similar pricing structure to Claude, with potential variances.

Technical Capabilities

Claude is known for these functionalities:

• Code Generation: Creates code for trading strategies on tradingview or any coding environment.
• Data Analytics: Has the ability to determine whether or not the trading strategies that the coded worked or didn’t work. You can analyze your performance within the software to see if what you want to compile worked or not.
• Prompt Reading/Understading: The bot can easily understand and compile your strategies. It is very easy to use so you can compile what you want to compile.

Trading Strategy Automation

AI Models are used so that you can easily code your trading strategies out-of-the-box. This allows for strategies that are more profitable and time efficient without learning how to code. As these Models get smarter, that will continue to get the case.