Edgewonk is an automated online trading journal for Forex, stocks, Futures, Crypto, and CFD trading. Easily import your trades and the Edgewonk analytics show you how to improve your edge.
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Which is more popular?
Based on our record, NumPy
seems to be more popular. It has been mentioned
122 times
since March 2021.
social mentions
0 vs 122
Trading Journal popularity
100% vs 0%
alternatives listed
240+ vs 189
Base details
Website, pricing, platforms and company facts side by side.
Comprehensive Trade Journaling Edgewonk offers in-depth trade journaling capabilities, allowing traders to log detailed information about each trade including entry/exit points, strategy used, and emotional state, which helps in identifying patterns and improving performance.
Advanced Analytics The platform provides robust analytics and statistics on trading performance, such as win rate, risk-reward ratio, and drawdown analysis, giving traders actionable insights to refine their strategies.
Customizable Tags and Strategies Users can create custom tags and strategies to categorize trades, making it easier to analyze specific setups or approaches and understand what works best for their trading style.
Psychological Insights Edgewonk includes tools to track emotional and psychological factors affecting trading decisions, helping traders recognize and manage biases like fear or overconfidence.
One-Time Purchase Model Unlike many trading tools that require subscriptions, Edgewonk offers a one-time purchase price, which can be cost-effective for long-term use without recurring fees.
Possible disadvantages
Steep Learning Curve New users may find the interface and features overwhelming initially, requiring time to learn how to fully utilize the journaling and analytics tools effectively.
Manual Data Entry Trades often need to be entered manually or imported with some effort, which can be time-consuming compared to platforms with automatic broker integration.
Limited Broker Integrations Edgewonk supports import from a limited number of brokers, and users with unsupported brokers may need to format data manually before importing.
Dated User Interface Some users feel the software's design and user interface could be more modern and intuitive compared to newer trading journal competitors.
No Mobile App Edgewonk lacks a dedicated mobile application, limiting on-the-go access and requiring users to rely on a desktop or web browser for journaling and analysis.
Performance NumPy operations are executed with highly optimized C and Fortran libraries, making them significantly faster than standard Python arithmetic operations, especially for large datasets.
Versatility NumPy supports a vast range of mathematical, logical, shape manipulation, sorting, selecting, I/O, and basic linear algebra operations, making it a versatile tool for scientific and numeric computing.
Ease of Use NumPy provides an intuitive, easy-to-understand syntax that extends Python's ability to handle arrays and matrices, lowering the barrier to performing complex scientific computations.
Community Support With a large and active community, NumPy offers extensive documentation, tutorials, and support for troubleshooting issues, as well as continuous updates and enhancements.
Integrations NumPy integrates seamlessly with other libraries in Python's scientific stack like SciPy, Matplotlib, and Pandas, facilitating a streamlined workflow for data science and analysis tasks.
Possible disadvantages
Memory Consumption NumPy arrays can consume large amounts of memory, especially when working with very large datasets, which can become a limitation on systems with limited memory capacity.
Learning Curve For users new to scientific computing or coming from different programming backgrounds, understanding the intricacies of NumPy's operations and efficient usage can take time and effort.
Limited GPU Support NumPy primarily runs on the CPU and doesn't natively support GPU acceleration, which can be a disadvantage for extremely compute-intensive tasks that could benefit from parallel processing.
Dependency on Python Since NumPy is a Python library, it depends on the Python runtime environment. This can be a limitation in environments where Python is not the primary language or isn't supported.
Indexing Complexity Although NumPy's slicing and indexing capabilities are powerful, they can sometimes be complex or unintuitive, especially for multi-dimensional arrays, leading to potential errors and confusion.
Analysis
An editorial look at what each product does well and who it suits.
E
EdgewonkNumPy
No analysis of Edgewonk yet.
Overall verdict
Yes, NumPy is considered good. It is a foundational library in the Python ecosystem for numerical computing and is used globally by researchers, engineers, and data scientists.
Why this product is good
NumPy is widely regarded as a good library because it offers fast, flexible, and efficient array handling that is integral to scientific computing in Python. It provides tools for integrating C/C++ and Fortran code, useful linear algebra, random number capabilities, and a vast collection of mathematical functions. Its array broadcasting capabilities and versatility make complex mathematical computations straightforward.
Recommended for
Scientists and researchers working with large-scale scientific computations.
Data scientists engaged in data analysis and manipulation.
Engineers and developers needing performance-optimized mathematical computations.
Before March 2021, Edgewonk was only available for download. But in March, developers released Edgewonk 3.0, an online web-based solution. However, it is only available with a single subscription plan of $169.
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and...
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and...
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image...
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages
Familiarity with Python as a language is assumed; if you need a quick...
- Source: dev.to
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about 1 year ago
AI starts with math and coding. You don’t need a PhD—just high school math like algebra and some geometry. Linear algebra (think matrices) and calculus (like slopes) help understand how AI models work. Python is the main language for AI,...
- Source: dev.to
/
over 1 year ago
An online trade logging platform that does it all! Logging, charting, sharing, trade management, risk analysis and many more! The best trading journal to find and visualize your trading edge.
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Figure Eight
