Analyzing Netflix's Stock with GPT

See prompt details with latest prediction

Introduction

Netflix, Inc., a significant player in the entertainment industry, has experienced notable fluctuations in its stock price. Using GPT Analyst, an AI-powered platform, market shifts have been analyzed with a high degree of precision. The model's trading approach, which involved making a trading decision on the first market day of each month, demonstrated an annualized return that exceeded a simple buy-and-hold strategy by 52.62%. The plot below illustrates the performance of this strategy compared to the buy-and-hold approach for the stock.

• Stock Annualized Return: 70.26%

• Prompt Annualized Excess Return: 52.62%

• Prompt Sharpe Ratio: 1.65

• Prompt Maximum Draw-down: 13.68%

These figures suggest that the model's trading strategy achieved high returns with relatively low risk, as indicated by the Sharpe Ratio, which measures risk-adjusted performance. The Maximum Draw-down figure of 13.68% reflects the extent of peak-to-trough decline, indicating that the strategy effectively limited significant losses during the evaluation period, despite the inherent volatility of the stock market.

This case study examines an analysis of Netflix's stock, the prompt used for generating trading signals, an evaluation of the model's historical performance, and areas where the strategy could potentially be refined.

The Technical Trading Prompt

The prompt provided to GPT Analyst focused on evaluating different perspectives regarding Netflix's stock. The scenarios considered were:

• Positive: Reflecting a belief that the stock could appreciate.

• Neutral: Maintaining cash reserves due to market unpredictability.

• Negative: Speculating that the stock might depreciate.

The model was supplied with a range of financial data, including:

• The 52-week low and high

• The 200-day and the 50-day moving averages

• Daily closing prices

• Quarterly EBIT

• Quarterly total revenue

• Recent news relevant to Netflix's stock performance was also included.

A monthly evaluation strategy was chosen due to the significant computational costs and time requirements of running the GPT 3.5-turbo model daily. This approach balances detailed analysis with practical implementation, allowing the model's insights to be utilized efficiently while managing resource constraints.

Exceptional Performance

The back-test was conducted over a period from November 4, 2019, to June 3, 2024, covering a total of 56 months.

The plot below provides a statistical analysis of the trading strategy performance of GPT Analyst. The strategy showed a 3.5 sigma likelihood when compared to randomized trading strategies with a similar distribution of long, cash, and short positions. Statistically, a 3.5 sigma event corresponds to an occurrence probability of approximately 0.023% (or about 1 in 4,300).

This exceptional performance suggests that GPT Analyst has a statistically significant ability to outperform random chance in back-tests. In total, we conducted back-tests for 200 different stocks, resulting in only a 6% probability of observing such an event by chance, calculated as 100% × (1 - 0.9997²⁰⁰). These results suggest that the model identifies underlying market trends and anomalies, which could contribute to more informed trading strategies.

Decision & Reasoning Examples

Let us examine the analysis and reasoning provided by GPT Analyst regarding long, cash, and short positions, based on prevailing market conditions and technical indicators. For instance:

• January 3, 2022: Neutral: Based on the provided market statistics, the NFLX stock has been relatively stable with fluctuations within a certain range. The 52-week low and high prices indicate some volatility, but the moving averages suggest a somewhat stable trend. The quarterly EBIT and total revenue have shown some fluctuations but overall remain at healthy levels. However, without any recent news that might impact the stock in the short term, predicting a clear direction for the stock price is challenging. Some analysts note that holding cash could be a way to mitigate exposure to market uncertainties during such periods.

• April 4, 2022: Negative: Based on the market statistics provided, Netflix (NFLX) appears to be encountering challenges in the streaming service industry due to intense competition and rivalry. Recent developments, such as GROM Social Enterprises Inc. producing new animated series and the launch of Wondermind for mental wellness, may not have a direct short-term impact on NFLX. Additionally, uncertainties surrounding the fallout from Will Smith's incident at the Academy Awards and its potential effect on movie studios could contribute to volatility in the entertainment industry. Observers have noted that NFLX's stock has recently traded below the 200-day and 50-day moving averages, which some analysts interpret as a potential indicator of continued downward pressure.

• June 6, 2022: Positive: Based on the market statistics provided, Netflix's stock is currently trading at a historically low price, which some analysts might interpret as notable. The company's ability to deliver unexpected hits like 'Interceptor' highlights its content strength, potentially attracting new subscribers and driving growth. Additionally, the recent funding round for Religion of Sports reflects a broader trend towards sports content consumption, which could influence Netflix's competitive positioning. While there are inherent risks associated with content production, Netflix's diverse library and adaptability suggest it remains a strong player in the streaming market. Observers have noted these factors as potentially relevant to future stock performance.

See prompt details with latest prediction

The reasoning showcases the ability of GPT Analyst to analyze multiple data points and recent news events to identify potential trends or patterns. Nevertheless, we noticed a lack of recent news summaries on many decision days, which motivated us to analyze news availability in more detail.

Distribution of News Summaries for Netflix Stock

One key limitation identified during the back-test, spanning November 2019 to June 2024, was that historical news summaries were only available from March 2022 onward. This resulted in the first 28 trading simulations being conducted without the benefit of recent news context. Across the 56 trading simulations, only the final 28 incorporated news summaries, with an average of 19.5 news items per decision.

The current prompt, which aggregates news from the past 72 hours, may not fully capture the context of news events occurring between simulations. Additionally, important news with potential long-term relevance may be processed and forgotten too quickly. These observations suggest that refining how news is utilized could be a focus for future versions of GPT Analyst.

Conclusion & Outlook

The analysis of Netflix using GPT Analyst highlights the potential of AI-driven financial modeling to identify patterns and generate insights related to trading strategies. The case study illustrates the platform's capability to analyze complex market scenarios and provide data-driven observations. However, there is room for improvement, particularly in enhancing the tracking and updating of relevant news summaries for a given date.

We plan to explore the performance of GPT Analyst on Netflix through two aspects:

• Enhancing news summary aggregation to provide greater context for market analysis.

• Testing the model in a live trading simulation to evaluate its real-time predictive capabilities.

Stay tuned for our follow-up article!