Shopify Stock Market Value
SHOP Stock | USD 72.26 1.75 2.36% |
Symbol | Shopify |
Shopify Price To Book Ratio
Is Shopify's industry expected to grow? Or is there an opportunity to expand the business' product line in the future? Factors like these will boost the valuation of Shopify. If investors know Shopify will grow in the future, the company's valuation will be higher. The financial industry is built on trying to define current growth potential and future valuation accurately. All the valuation information about Shopify listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
Quarterly Earnings Growth 4.858 | Earnings Share 0.1 | Revenue Per Share 5.509 | Quarterly Revenue Growth 0.236 | Return On Assets 0.0147 |
The market value of Shopify is measured differently than its book value, which is the value of Shopify that is recorded on the company's balance sheet. Investors also form their own opinion of Shopify's value that differs from its market value or its book value, called intrinsic value, which is Shopify's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because Shopify's market value can be influenced by many factors that don't directly affect Shopify's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between Shopify's value and its price as these two are different measures arrived at by different means. Investors typically determine if Shopify is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Shopify's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.
Shopify 'What if' Analysis
In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to Shopify's stock what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of Shopify.
03/26/2024 |
| 04/25/2024 |
If you would invest 0.00 in Shopify on March 26, 2024 and sell it all today you would earn a total of 0.00 from holding Shopify or generate 0.0% return on investment in Shopify over 30 days. Shopify is related to or competes with Zoom Video, C3 Ai, Salesforce, Workday, Snowflake, Intuit, and Datadog. Shopify Inc., a commerce company, provides a commerce platform and services in Canada, the United States, Europe, the Mi... More
Shopify Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure Shopify's stock current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess Shopify upside and downside potential and time the market with a certain degree of confidence.
Information Ratio | (0.06) | |||
Maximum Drawdown | 21.49 | |||
Value At Risk | (3.85) | |||
Potential Upside | 4.52 |
Shopify Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Shopify's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Shopify's standard deviation. In reality, there are many statistical measures that can use Shopify historical prices to predict the future Shopify's volatility.Risk Adjusted Performance | (0.01) | |||
Jensen Alpha | (0.28) | |||
Total Risk Alpha | (0.48) | |||
Treynor Ratio | (0.04) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Shopify's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Shopify Backtested Returns
Shopify owns Efficiency Ratio (i.e., Sharpe Ratio) of -0.05, which indicates the firm had a -0.05% return per unit of risk over the last 3 months. Shopify exposes twenty-three different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please validate Shopify's Risk Adjusted Performance of (0.01), coefficient of variation of (3,826), and Variance of 8.4 to confirm the risk estimate we provide. The entity has a beta of 2.3, which indicates a somewhat significant risk relative to the market. As the market goes up, the company is expected to outperform it. However, if the market returns are negative, Shopify will likely underperform. Shopify has an expected return of -0.15%. Please make sure to validate Shopify treynor ratio, kurtosis, as well as the relationship between the Kurtosis and day typical price , to decide if Shopify performance from the past will be repeated at some point in the near future.
Auto-correlation | -0.3 |
Weak reverse predictability
Shopify has weak reverse predictability. Overlapping area represents the amount of predictability between Shopify time series from 26th of March 2024 to 10th of April 2024 and 10th of April 2024 to 25th of April 2024. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Shopify price movement. The serial correlation of -0.3 indicates that nearly 30.0% of current Shopify price fluctuation can be explain by its past prices.
Correlation Coefficient | -0.3 | |
Spearman Rank Test | -0.37 | |
Residual Average | 0.0 | |
Price Variance | 2.62 |
Shopify lagged returns against current returns
Autocorrelation, which is Shopify stock's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting Shopify's stock expected returns. We can calculate the autocorrelation of Shopify returns to help us make a trade decision. For example, suppose you find that Shopify has exhibited high autocorrelation historically, and you observe that the stock is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
Current and Lagged Values |
Timeline |
Shopify regressed lagged prices vs. current prices
Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If Shopify stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Shopify stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Shopify stock over time.
Current vs Lagged Prices |
Timeline |
Shopify Lagged Returns
When evaluating Shopify's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Shopify stock have on its future price. Shopify autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, Shopify autocorrelation shows the relationship between Shopify stock current value and its past values and can show if there is a momentum factor associated with investing in Shopify.
Regressed Prices |
Timeline |
Shopify Investors Sentiment
The influence of Shopify's investor sentiment on the probability of its price appreciation or decline could be a good factor in your decision-making process regarding taking a position in Shopify. The overall investor sentiment generally increases the direction of a stock movement in a one-year investment horizon. However, the impact of investor sentiment on the entire stock market does not have solid backing from leading economists and market statisticians.
Investor biases related to Shopify's public news can be used to forecast risks associated with an investment in Shopify. The trend in average sentiment can be used to explain how an investor holding Shopify can time the market purely based on public headlines and social activities around Shopify. Please note that most equities that are difficult to arbitrage are affected by market sentiment the most.
Shopify's market sentiment shows the aggregated news analyzed to detect positive and negative mentions from the text and comments. The data is normalized to provide daily scores for Shopify's and other traded tickers. The bigger the bubble, the more accurate is the estimated score. Higher bars for a given day show more participation in the average Shopify's news discussions. The higher the estimated score, the more favorable is the investor's outlook on Shopify.
Shopify Implied Volatility | 67.12 |
Shopify's implied volatility exposes the market's sentiment of Shopify stock's possible movements over time. However, it does not forecast the overall direction of its price. In a nutshell, if Shopify's implied volatility is high, the market thinks the stock has potential for high price swings in either direction. On the other hand, the low implied volatility suggests that Shopify stock will not fluctuate a lot when Shopify's options are near their expiration.
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Shopify in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Shopify's short interest history, or implied volatility extrapolated from Shopify options trading.
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When determining whether Shopify is a good investment, qualitative aspects like company management, corporate governance, and ethical practices play a significant role. A comparison with peer companies also provides context and helps to understand if Shopify Stock is undervalued or overvalued. This multi-faceted approach, blending both quantitative and qualitative analysis, forms a solid foundation for making an informed investment decision about Shopify Stock. Highlighted below are key reports to facilitate an investment decision about Shopify Stock:Check out Shopify Correlation, Shopify Volatility and Shopify Alpha and Beta module to complement your research on Shopify. To learn how to invest in Shopify Stock, please use our How to Invest in Shopify guide.You can also try the Equity Valuation module to check real value of public entities based on technical and fundamental data.
Complementary Tools for Shopify Stock analysis
When running Shopify's price analysis, check to measure Shopify's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Shopify is operating at the current time. Most of Shopify's value examination focuses on studying past and present price action to predict the probability of Shopify's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Shopify's price. Additionally, you may evaluate how the addition of Shopify to your portfolios can decrease your overall portfolio volatility.
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Shopify technical stock analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, stock market cycles, or different charting patterns.