CVNA RSI

What is CVNA?

Carvana was founded in 2012 by Ernie Garcia III, Ryan Keeton, and Ben Huston as a subsidiary of DriveTime before spinning off and going public in 2017. Based in Phoenix, Arizona, the company disrupted the traditional, often-hated car dealership model by moving the entire buying process online. They are best known for their massive, multi-story Car Vending Machines that serve as both automated pick-up points and high-visibility marketing tools.

The core business model revolves around an end-to-end e-commerce platform where customers can browse, finance, purchase, and trade in vehicles. Beyond simple sales, they generate significant revenue from secondary services, such as originating auto loans and selling vehicle protection plans. Their 2022 acquisition of ADESA's US physical auction business was a game-changer, providing them with a massive network of physical locations to process and store inventory closer to customers.

Historically, Carvana's path has been volatile. They grew at breakneck speed during the pandemic, only to face a liquidity crisis in late 2022 as interest rates rose and car prices fluctuated. However, they have since pulled off a remarkable turnaround by restructuring debt and focusing heavily on unit economics. They have moved from burning cash to generating positive adjusted EBITDA, largely by optimizing their reconditioning processes and cutting logistics waste.

Looking ahead to 2026, Carvana is focused on profitable growth. The goal is to leverage the ADESA infrastructure to create a hyper-efficient, national logistics network that can support much higher volumes with lower overhead. By 2026, expect them to lean further into technology-driven reconditioning and expanded third-party marketplace services. Their outlook is centered on being the most cost-efficient operator in the used car space, betting that their digital-first approach will finally achieve the scale needed for long-term, sustainable profitability in a more stable interest rate environment.

What is RSI?

The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and magnitude of price changes. Developed by J. Welles Wilder, RSI ranges from 0 to 100 and helps traders identify overbought or oversold conditions in an asset.

For CVNA, monitoring the RSI provides valuable insights into potential trend reversals and entry/exit points. When the RSI drops below 30, Carvana Co. is typically considered oversold, suggesting the asset may be undervalued. Conversely, an RSI above 70 indicates overbought conditions.

Understanding CVNA RSI Signals

• Oversold (RSI below 30): When CVNA RSI falls below 30, it suggests the asset may have been sold off excessively and could be due for a bounce. This is often viewed as a potential buying opportunity, though it's important to consider other factors and not rely solely on RSI.
• Overbought (RSI above 70): An RSI above 70 indicates CVNA may be overbought, potentially signaling a pullback or consolidation phase. Traders often use this as a signal to take profits or wait for better entry points.
• Divergences: When CVNA price makes new highs or lows but RSI doesn't confirm these moves, it can signal weakening momentum and a possible trend reversal.

Daily vs Weekly RSI for CVNA

This page displays both daily and weekly RSI for CVNA. The daily RSI responds quickly to short-term price movements, making it useful for day traders and swing traders. The weekly RSI provides a broader perspective on momentum trends, helping longer-term investors identify major oversold or overbought conditions.

By analyzing both timeframes together, you can better understand Carvana Co.'s momentum at multiple levels and make more informed trading decisions.

Historical RSI Oversold Analysis

Above, we track historical instances when CVNA RSI dropped below 30 (oversold territory). Reviewing these past oversold levels helps identify patterns and understand how Carvana Co. has historically responded to oversold conditions. Many traders use these historical reference points to gauge potential support levels and timing for entry positions.