Sold by: ElectrifAi LLCÂ
Deployed on AWS
Generate simulations of interest rate predictions using market information. This model has a 30-year prediction.
Overview
Generate simulations of interest rate predictions using market information. Since mortgage terms can be 30 years, this model has a 30-year prediction. The model using the Monte Carlo simulation, a simulation model that shows some fluctuation among three scenarios to generate a record path. If you look at the past, present and future, you have three curves. For each curve, you have many scenarios. This simulation generates each scenario. To preview our machine learning models, please Continue to Subscribe. To preview our sample Output Data, you will be prompted to add suggested Input Data. Sample Data is representative of the Output Data but does not actually consider the Input Data. Our machine learning models return actual Output Data and are available through a private offer. Please contact info@electrifai.net for subscription service pricing. SKU: INTRT-PS-RMG-AWS-001
Highlights
- Generate simulations of interest rate predictions using market information. Since mortgage terms can be 30 years, this model has a 30-year prediction.
- Using the data input of information gathered from government website, the baseline historical data points generate insights on the three curves.
Details
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Delivery method
Latest version
Deployed on AWS
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Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.2xlarge Inference (Batch) Recommended | Model inference on the ml.m5.2xlarge instance type, batch mode | $0.00 |
ml.p2.16xlarge Inference (Real-Time) Recommended | Model inference on the ml.p2.16xlarge instance type, real-time mode | $0.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $0.00 |
ml.m5.large Inference (Batch) | Model inference on the ml.m5.large instance type, batch mode | $0.00 |
ml.p2.xlarge Inference (Real-Time) | Model inference on the ml.p2.xlarge instance type, real-time mode | $0.00 |
ml.p3.16xlarge Inference (Real-Time) | Model inference on the ml.p3.16xlarge instance type, real-time mode | $0.00 |
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
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Version release notes
Initial Release
Additional details
Inputs
- Summary
Input: One comma separated (CSV) file. Reference file: sample.csv
- Input MIME type
- text/csv
https://github.com/ElectrifAi/model-aws-interest-rate-model/blob/master/sample.csv
https://github.com/ElectrifAi/model-aws-interest-rate-model/blob/master/sample.csv
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
Input: One comma separated (CSV) file. Reference file: sample.csv | A comma separated (CSV) file containing below input fields:
- month_tag: year month
- IR: interest rate | Type: FreeText | Yes |
Resources
Vendor resources
Support
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