Stock Rover’s View feature stands out as a powerful, time-saving toolkit for investors who want to cut straight to the data that matters. With access to more than 700 financial metrics, users can tailor a research workflow around a precise set of questions and focus on the most relevant figures at any given moment. This in-depth guide explains how to leverage Stock Rover Views to its fullest, outlining what Views are, how Table and Tile Views differ, how to sort and customize data, how to manage and organize Views, and how to display Views as tabs for rapid navigation. By following these insights, you can streamline your analysis, improve decision-making speed, and uncover deeper patterns across portfolios, watchlists, screeners, and indices.
What are Views
Views are dynamic containers that hold a named collection of Stock Rover metrics displayed within the Stock Rover Table. They’re designed to be both comprehensive and immediately actionable, presenting a curated set of data that can be used across different research questions. Out of the box, Stock Rover ships with a broad array of Views, but you can also customize existing Views or create entirely new ones to reflect your personal investment approach.
There are two primary types of Views: Table Views and Tile Views. Table Views provide a flexible, spreadsheet-like format that presents tickers alongside a matrix of data across many dimensions—financial, operational, and price performance. They enable investors to compare datasets such as indices, watchlists, screeners, and portfolios side by side. Tile Views, by contrast, present a hybrid of tabular and graphical data in a tile-based display. They still allow for cross-mimulation across multiple metrics but also incorporate charts and other visual elements to facilitate quicker trend recognition.
Stock Rover ships with more than 50 pre-built Views, and it’s possible to import additional Views from the Investor Library. The system organizes Views into folders by investment category, making it easy to locate the exact View you want to use. For example, in the Ratings folder you may find a mix of Table Views and Tile Views, and you can identify a Tile View simply by a name that ends with the word “Tiles.” When you load a particular dataset, such as the results from a screener, you might use a Table View (e.g., Scores) to present the data in a tidy tabular format for analysis.
In practice, the Table is the core workspace: think of the Table as the workbook, the individual Table Views as worksheets, and the metrics displayed in a view as the columns. The rows correspond to the tickers within the chosen dataset—whether that’s a portfolio, a watchlist, a screener, an index, or a list of quotes. While Table Views share a conceptual similarity with Excel worksheets, they are designed for immediate use. Columns are pre-built and readily available, removing the need for constant updates because the data in each View remains current. Selecting a different Table View reveals a different arrangement of columns, enabling you to tailor the data presentation to your current needs.
A practical takeaway is that Views are containers of columns. You can switch between Table Views to reveal the exact set of metrics you want to see together. For instance, by navigating to a specific folder such as Price Performance and selecting a given view like Current Returns, you’ll see a table that focuses on price changes and related information about current returns. This approach lets you keep the most relevant columns grouped together for the task at hand, avoiding clutter and ensuring quick access to essential data.
The core idea behind Views is to provide a fast, consistent way to access the right data without having to assemble a new dataset each time. Whether you’re assessing momentum indicators, analyzing a screener’s results, or comparing multiple datasets side by side, Views streamline the workflow by presenting predefined, ready-to-use columns and charts.
Table Views
Table Views are designed to deliver a flexible spreadsheet-like experience for viewing tickers and their associated data. They enable investors to compare any data set—indices, watchlists, screeners, and portfolios—across multiple dimensions, including financial metrics, operational performance, and price behavior. This format mirrors a traditional spreadsheet in concept, with a workbook-like structure and worksheets represented by the different Table Views.
In Stock Rover, think of the Table as the workbook, the Table Views as worksheets, and the individual metrics as columns. The rows then represent the tickers contained in the selected dataset. A key advantage of Table Views is that they are pre-built with a comprehensive set of columns, carefully organized to cover a broad spectrum of data without requiring ongoing maintenance. This means you can activate a View and immediately begin analyzing data without fuss, because the data displayed is always current and the column arrangement is optimized for quick interpretation.
Because each View is a separate container for a specific set of columns, selecting a different Table View automatically reveals a new configuration of columns. This design makes it easy to switch contexts—whether you’re examining a single stock’s performance, comparing several stocks across a portfolio, or evaluating a group of tickers based on a particular screening criterion. A practical example is the Current Returns view found in a Price Performance folder. This Table View exposes price performance data and related metrics that are relevant when analyzing a stock’s recent contribution to a portfolio. With a couple of clicks, you can switch to this View and view the exact metrics needed for that analysis, while still preserving your other saved Views for different purposes.
The analogy to Excel remains useful: the Table is the workbook, the Views are the worksheets, and the metrics are the columns. The flexibility of Table Views lies in the fact that you don’t have to manage data structures manually; the columns are pre-built and ready to go. You never have to worry about maintaining data feeds or updating calculations—the data in each View is refreshed automatically. When you navigate within the Views, the table adapts to the chosen View, revealing the relevant columns and metrics for that context.
One practical practice is to remain mindful of the data you want to track most closely. If you’re focusing on momentum, you might want to preserve a consistent set of momentum-related columns in a specific View so that you can compare different stocks across the same metrics. If you’re analyzing valuation, you can keep valuation-focused columns together and switch to a different View that emphasizes growth metrics or risk indicators. The design encourages a modular, consistent approach to data examination, enabling you to work with larger datasets without sacrificing clarity.
In use, you can access Table Views by navigating through the Views library, opening a relevant folder, and selecting a View that suits your current research question. The system’s organization by investment category helps you locate the optimal View quickly, ensuring that even complex datasets are manageable and interpretable. This design supports a high level of customization while maintaining a user-friendly structure that scales with your research needs.
Sorting the Table
Sorting is a fundamental operation in any data table, and in Stock Rover’s Table Views, sorting is a straightforward and powerful way to reorder information to highlight the most relevant items according to a chosen metric. When you want to focus on critical signals such as a stock’s proximity to its 52-week high, sorting becomes an essential tool to quickly rank tickers and identify top candidates.
To illustrate, consider a Momentum View located in the Technicals folder that includes a column for the 52-week High/Low range. If your goal is to identify stocks that are closest to their 52-week high, you can sort the Table View by the 52-week Range column. Sorting is typically accomplished by clicking the target column’s header. To achieve a descending order—where the stocks nearest to their 52-week high appear at the top—you can click the header twice. This approach ensures that the most relevant tickers receive immediate visual emphasis, enabling you to prioritize follow-up analysis.
Once you’ve set the sort order, every time you select the Momentum View, the Table automatically reorders to reflect that same criterion. This automatic re-sorting maintains consistency across sessions, making it easier to monitor changes over time without manually reapplying sort orders. The practical effect is a dynamic, always-relevant leaderboard of tickers arranged by their proximity to a meaningful benchmark, such as their 52-week high, enabling faster decision-making in rapid research scenarios.
Beyond the specific 52-week high metric, you can apply the same sorting logic to any available column that is meaningful for your analysis. The ability to sort by different metrics—to spotlight momentum, volatility, value signals, or price performance—offers a flexible, responsive way to explore large datasets. This capability supports a workflow in which the View itself becomes a living tool: you sort by the metric that matters in the moment and then use that arrangement to guide your next steps, whether that’s data export, deeper screening, or a targeted watchlist refinement.
Best practices for sorting include establishing a default sort that aligns with your primary research objective and keeping a small, stable set of sort criteria to reduce cognitive load when scanning multiple Views. You can also combine sorting with filtering or highlighting rules to draw attention to the most compelling opportunities. The key is to use sorting as a precision instrument for prioritization rather than a cosmetic feature, ensuring that the most critical candidates rise to the top in a repeatable, reliable manner.
Adding and Removing Columns From the Table
Table Views allow you to tailor the metric composition to match your momentum, valuation, or risk assessment strategies. The process of adding and removing columns is intuitive, and Stock Rover provides quick ways to reorganize columns so that related metrics appear together, improving readability and decision speed.
When analyzing momentum indicators, for example, you may want to augment the View with the current price’s relation to the 120-day moving average. To do so, you can search for and add the column Price vs 120-Day Avg (%). The interface presents this metric in the numerical column immediately, often as the leftmost numerical column adjacent to the Rank column. To maintain a tidy, logical grouping of related metrics, you can drag and drop the new column to cluster it with other price trend indicators, such as Price vs 20-Day Avg (%) and Price vs 50-Day Avg (%). This reorganization helps you view all price-mrequency indicators together, facilitating a clearer, quicker interpretation of momentum signals.
There are occasions when you may decide that a particular metric isn’t necessary for your current analysis. For instance, if you rarely focus on a specific long-term tag such as Price vs. 200-day Average, you can remove this column to reduce clutter and keep the View focused on the metrics that matter. The removal process is straightforward: right-click on the column header and select Remove Column. The convenience tip—“Right-click when in doubt”—stems from the many quick options that appear in the context menu, often including actionable operations you might not immediately anticipate.
After adding and rearranging the desired columns, the resulting Momentum View is precisely tailored to highlight the momentum information you want to see, in the order you prefer. This approach ensures that there is no extraneous data cluttering your view and that the most relevant metrics are presented prominently. The same principle applies to other Views: identify your essential metrics, group them coherently, and remove any items that do not contribute to your immediate research question. The outcome is a lean, focused dashboard that accelerates your analysis and reduces cognitive load during deep-dive reviews.
Best practices for managing columns include: map related metrics together to minimize context switching, maintain consistency across multiple Views that share a common goal (e.g., momentum or valuation), and periodically review column relevance to ensure the View continues to reflect your current research priorities. While the default Views are well-constructed, personal customization can dramatically improve your ability to extract insights from large datasets.
Tile Views
Tile Views offer a different way of presenting data by integrating tabular data with graphical representations. The goal of Tile Views is to provide a compact, visually intuitive display that can show both numbers and charts in a single, easily scannable interface. While you can configure a Tile View to show only tabular data, only graphical data, or a combination of both, the standard use case is to present tabular metrics alongside price or fundamentals charts. This combination can help you identify patterns and trends that might not be as evident in a pure tabular view.
Tile Views are particularly useful for comparing multiple data points across a dataset, as the tile-based layout supports side-by-side analysis of several metrics. Stock Rover ships with around seven out-of-the-box Tile Views, and you can customize or create additional Tile Views to generate a diverse array of data content and presentation formats. The naming convention within the Views library helps you distinguish between Tile Views and Table Views: for example, a Score Tiles view clearly indicates that the View is tile-based, while a similarly named Scores Table would indicate a Table View. This naming scheme makes it easy to differentiate the format at a glance while maintaining consistent labeling across related Views.
The flexibility of Tile Views extends to how data is displayed within each tile. A Tile View can combine a tabular component with a chart component, where you can compare different datasets across multiple tickers and timeframes. The charts can be configured to display price movements, relative performance, or any other metric that can be charted in Stock Rover. The combination of tabular data and charts allows analysts to quickly spot correlations or divergences between metrics, aiding in faster hypothesis generation and testing.
From a design perspective, Tile Views provide a compact, information-dense layout that can be especially helpful when you are scanning a large universe of stocks and need to quickly identify candidates that meet specific visual criteria. The balance between tabular clarity and graphic insight makes Tile Views a powerful complement to Table Views. By leveraging Tile Views, you can maintain an information-rich interface that still remains readable on smaller screens, ensuring that you don’t lose essential context when you need to analyze on the go or on a compact display.
Modifying a Tile View
Tile Views offer a high degree of configurability, enabling you to customize several aspects of their presentation to match your analytical goals. When you adjust a Tile View, you can decide whether to display tabular data, the chart, or both, and you can optimize the chart for readability and impact.
Key configuration options include:
- The decision to display either the tabular data, the chart, or both.
- The chart’s display size and scale to balance detail with overall visibility.
- The specific metrics to display within the tile and the charting preferences to reflect your research focus.
- The date range of the chart to capture different horizons, from short-term momentum to longer-term trends.
In a typical workflow, you might start by selecting the Scores Tiles view and then access the Settings to refine the data presentation. You can add additional metrics to the tabular data by selecting an option such as “Additional Metrics” and choosing the metric you want to incorporate, like “Overall Ratings vs. Peers.” You can also include a benchmark, such as the S&P 500, in the price chart to provide context for performance comparisons.
With just a few clicks, the Scores Tiles view can be configured to display exactly the information you need. For instance, if your goal is to focus on price movements, you might switch the display to show only price charts, eliminating the tabular data momentarily. This can simplify the visual analysis and make it easier to spot chart patterns across multiple tickers. Alternatively, you can maintain both charts and a curated set of metrics to preserve a richer, more comprehensive view.
Tile Views are highly adaptable for a range of analytical scenarios. You can tailor them to emphasize different aspects of a dataset, such as momentum, quality, valuation, or growth, while ensuring that the presentation remains visually coherent. By adjusting what’s displayed and how it’s presented, you can create a highly specialized, visually engaging dashboard that aligns with your current research priorities.
The View Manager
For more substantial changes to your Views, including significant design overhauls, creating new Views, or reorganizing how Views are grouped and accessed, you will want to use the View Manager. The View Manager is accessible via the Modify View option in the pull-down menu adjacent to any View. This tool provides a centralized interface to manage and customize your Views.
The View Manager consists of two panes:
- Views (Modify): This pane allows you to organize your Views, browse through View folders, and select a specific View to modify.
- Table View (the view name is where you modify the selected View’s columns): This pane shows the current configuration for the chosen View, including which metrics are displayed as columns and their arrangement.
Within the View Manager, you can perform a range of actions to tailor the Table View to your needs:
- Add one or more metrics as columns to the selected View.
- Reorder columns via drag-and-drop to place the most important metrics in the most accessible positions.
- Remove columns that are not relevant to your current analysis.
These capabilities enable you to design highly customized, purpose-built Views that align precisely with your research questions, from momentum and value strategies to risk assessments and portfolio diagnostics. By leveraging the View Manager, you can implement sweeping changes across multiple Views in a coherent, organized fashion, maintaining consistency in how metrics are displayed and interpreted.
The practical result of using the View Manager is a set of Views that reflect your evolving research priorities. For example, you might modify a Scores View by adding a metric such as “Overall Ratings vs. Peers,” positioning it after the Company name to emphasize qualitative assessments in the context of a company’s identity. The View Manager makes such tweaks straightforward, allowing you to implement and test different configurations quickly.
Modifying a View
In Stock Rover, you can modify a View to adjust the columns it displays, the order of those columns, and the inclusion or exclusion of specific metrics. The process typically involves selecting one or more metrics to add as columns, rearranging their positions with drag and drop, and removing any columns that are unnecessary for your current analysis. This flexibility is essential for maintaining a highly targeted data presentation that matches your evolving research questions.
A practical example is the Scores View. Suppose you want to highlight an additional dimension of analysis by adding the metric “Overall Ratings vs. Peers” and placing it after the Company name. This change can provide a quick visual cue about how a company stacks up against its peers, complementing other data in the table. After making such modifications, you can review the updated View to confirm that it aligns with your intended analytical narrative and decision-making framework.
The modification workflow is designed to be intuitive and efficient, encouraging experimentation. You can create an iterative loop: modify a View, evaluate its usefulness on real data, and adjust again based on what you observe. This process supports a dynamic approach to research, enabling you to refine the data presentation in response to new insights or shifting investment objectives.
Creating a New View
If none of the pre-existing Views precisely match your research needs, you can create a new View from scratch. The process begins by selecting the pull-down next to a View and choosing Create View. You’ll be prompted to select the type of View you want to create. For example, you might choose a Table View if you want a traditional spreadsheet-like presentation, or you might opt for a Tile View if you prefer a mixed tabular-and-graphical layout.
Once you’ve chosen the type, the new View will be added to your first View folder—My Favorites, or another folder you designate. You’ll name the View to reflect its purpose, such as My Dividend View or another descriptive label that captures the goal of the View. After naming, you can select the metrics to include in the View and arrange them in the desired order through drag-and-drop. A Save action completes the creation process.
As an illustration, you could create a View named My Dividend View and populate it with a set of dividend-related metrics, such as dividend yield, payout ratio, dividend growth rate, and related price-performance metrics. You can then save the View and test it against actual dividend-screened data to ensure it provides the right balance of information and readability. The key point is that user-created Views are fully integrated into Stock Rover in the same way as the built-in Views, allowing you to treat your custom configurations as native components of the platform.
The creation workflow is designed to be approachable and productive, enabling you to move quickly from concept to a tangible, working View. By naming your View clearly and selecting a coherent set of metrics, you can build a powerful, reusable resource that streamlines your ongoing research and analysis across multiple sessions and datasets. The result is a personalized, efficient environment that makes it easier to access exactly the data you need when you need it.
Organizing Folders and Views
Organizing your Views and their containing folders is essential for maintaining a scalable, efficient research workflow. The Views (Modify) pane provides a straightforward interface for arranging your Views and their folders. You can drag and drop both folders and individual Views to adjust their order, which is particularly useful if you want to position your most commonly used Folders at the top of the hierarchy or ensure quick access to your favorite analyses.
A widely recommended practice is to create a Favorites Folder populated with your most frequently used Views. This approach reduces navigation time and keeps your primary analysis tools readily accessible. You can implement this by using the pull-down menu next to Views to create a new folder, then dragging and dropping Views to place them within the new folder. You can also reorder folders to ensure that the most important categories appear first in the tree.
In a practical example, you might move a Portfolio Performance View into your newly created My Favorites folder and rearrange the Growth folder to follow the Dividends folder. These kinds of reorganizations help you streamline your workflow, making it faster to access your go-to analyses during routine checks or while conducting a comprehensive review. Creating a well-structured folder scheme not only saves time but also supports consistency across sessions, which is valuable when you’re comparing results over time or sharing your setup with collaborators in a team environment.
The benefit of organizing folders and views goes beyond mere aesthetics. A logical, intuitive structure reduces cognitive load and helps you maintain a repeatable research process. By consolidating your most valuable analyses into a single, easy-to-navigate location, you can maintain focus on the strategic questions you want to answer rather than spending time locating the right View. Over time, a well-ordered Views library becomes a powerful asset that accelerates research, enables more consistent comparisons, and improves collaboration by providing a clear, shareable structure of analyses.
Showing Views as Tabs
Stock Rover offers an option to display Views within a folder as individual tabs at the top of the table rather than as a dropdown menu. This feature can significantly speed up navigation when you want to switch quickly between multiple Views within a folder.
To enable tabbed Views, you navigate to the account name dropdown located in the top right corner of the Stock Rover interface and select Preferences. In the Update Preferences window, you can check the box labeled Show tabs for each table view, then save your changes. Once enabled, the Views inside a folder appear as easily clickable tabs, allowing you to switch among them with a single click.
Using tabs can be particularly advantageous when you’re working with a few core Views that you access frequently within a folder. Rather than opening a dropdown menu and scrolling through a long list, you can jump directly to the desired View. This simple interface enhancement can contribute to faster decision-making, reduced interaction friction, and a smoother overall workflow, especially when you’re performing focused, time-sensitive research tasks.
Configuring Views to show as tabs in a folder also invites a more streamlined testing of different View configurations. When you’re evaluating how a particular dataset behaves under slightly different metric compositions, having tabbed access makes it easier to compare the results side by side in rapid succession. The user experience is improved through clearer visibility, easier comparison, and a more intuitive sense of control over your analytical environment.
Onward and Upward
By now, you should feel equipped to begin leveraging Views as a central component of your Stock Rover research routine. The Views feature is designed to be a friendly, powerful helper that helps you tailor a data presentation that matches your inquiry, your portfolio, and your investment philosophy. Whether you start from a pre-existing View, adjust a Table View to align with your momentum or valuation focus, or build a new View from scratch to capture a unique perspective, the system is designed to accommodate a wide range of research styles.
Getting started with Views means recognizing that you can mix and match tables, tiles, and graphs to create dashboards that reflect your precise analysis needs. Truly effective use comes from experimentation: trying different column combinations, reorganizing the metrics, and testing how your new View behaves against real market data. The goal is to develop a consistent, repeatable workflow that helps you extract meaningful insights quickly and accurately, without losing sight of the broader investment narrative.
If you need additional guidance, Stock Rover’s help resources cover Views and Tables in greater depth. You can explore these topics to deepen your understanding of how to optimize your VIEWS strategy, how to create new Views, and how to tailor your View organization to your unique research workflow. The system is designed to be scalable, so as your analysis grows more complex, your Views can evolve to accommodate larger datasets, more metrics, and more sophisticated comparisons.
Conclusion
Stock Rover Views provide an essential framework for researchers and investors who require rapid access to a broad spectrum of metrics while preserving clarity and focus. With two main formats—Table Views and Tile Views—along with a robust set of tools to sort, add or remove columns, modify tile configurations, manage and reorganize Views, and enable tabbed navigation, you can build a personalized analytic environment that aligns with your specific research questions and decision-making needs. The View Manager and the ability to create new Views further extend the platform’s power, allowing you to adapt the interface to your evolving strategies and preferences. By organizing your Views into purposeful folders and embracing tabbed navigation, you can significantly streamline your workflow, accelerate analysis, and unlock smarter, more efficient investment insights. Continuous exploration and customization of Views will help you maximize the platform’s capabilities while maintaining a consistent, scalable research process that supports rigorous, data-driven decision-making across your investment journey.