Shopify Stock Market Value
| SHOP Stock | CAD 136.33 5.61 4.29% |
| Symbol | Shopify |
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.
| 12/16/2024 |
| 03/16/2025 |
If you would invest 0.00 in Shopify on December 16, 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 90 days. Shopify is related to or competes with Lightspeed Commerce, Enbridge, Air Canada, BlackBerry, and Toronto Dominion. 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 | (0.05) | |||
| Maximum Drawdown | 16.52 | |||
| Value At Risk | (6.00) | |||
| Potential Upside | 3.67 |
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 | (0.07) | |||
| Jensen Alpha | (0.27) | |||
| Total Risk Alpha | 0.1214 | |||
| Treynor Ratio | 12.08 |
Shopify Backtested Returns
Shopify owns Efficiency Ratio (i.e., Sharpe Ratio) of -0.0834, which indicates the firm had a -0.0834 % 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 (0.07), variance of 9.85, and Coefficient Of Variation of (1,199) to confirm the risk estimate we provide. The entity has a beta of -0.0225, which indicates not very significant fluctuations relative to the market. As returns on the market increase, returns on owning Shopify are expected to decrease at a much lower rate. During the bear market, Shopify is likely to outperform the market. At this point, Shopify has a negative expected return of -0.26%. Please make sure to validate Shopify's maximum drawdown, potential upside, kurtosis, as well as the relationship between the value at risk and skewness , to decide if Shopify performance from the past will be repeated at some point in the near future.
Auto-correlation | -0.13 |
Insignificant reverse predictability
Shopify has insignificant reverse predictability. Overlapping area represents the amount of predictability between Shopify time series from 16th of December 2024 to 30th of January 2025 and 30th of January 2025 to 16th of March 2025. 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 -0.13 indicates that less than 13.0% of current Shopify price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.13 | |
| Spearman Rank Test | 0.44 | |
| Residual Average | 0.0 | |
| Price Variance | 238.59 |
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 |
Pair Trading with Shopify
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Shopify position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Shopify will appreciate offsetting losses from the drop in the long position's value.The ability to find closely correlated positions to Shopify could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Shopify when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Shopify - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Shopify to buy it.
The correlation of Shopify is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Shopify moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Shopify moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Shopify can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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.