You will get an ML model capable of Single Asset, Next-Day Close Price Prediction


Project details
You will get actionable insight over a single asset's next day closing price, validated and tested to be the best performing among a variety of machine learning models. The delivery is broker-agnostic, works with any broker. You will provide an account balance solely used to report the upper-bound of earnings under various assumptions.
Machine Learning Tools
BERT, Keras, NumPy, pandas, PyMC, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, TensorFlow, XGBoostWhat's included
| Service Tiers |
Starter
$50
|
Standard
$75
|
Advanced
$100
|
|---|---|---|---|
| Delivery Time | 1 day | 2 days | 3 days |
Number of Revisions | 0 | 1 | 2 |
Number of Model Variations | 3 | 6 | 6 |
Number of Graphs/Charts | 1 | 1 | 1 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | - | - |
Source Code | - | - | - |
Optional add-ons
You can add these on the next page.
Additional Revision
+$20
Additional Model Variation
(+ 1 Day)
+$5
Additional Scenario
(+ 2 Days)
+$5
Additional Graph/Chart
(+ 1 Day)
+$5
Model Documentation
+$5
Data Source Connectivity
(+ 2 Days)
+$20About Beckett
Data Mining, Machine Learning | Data Analytics, Bespoke Implements
Canon City, United States - 4:26 am local time
Steps for completing your project
After purchasing the project, send requirements so Beckett can start the project.
Delivery time starts when Beckett receives requirements from you.
Beckett works on your project following the steps below.
Revisions may occur after the delivery date.
Asset Selection
Upon your asset selection, I will study the asset and determine a training window. I will capture the price data directly from Yahoo Finance and begin the feature engineering process.
Training/Testing
I will train a selection of models in the training period, and perform validation testing on the most recent window (15/30/45 days). The highest earning model in validation will be ultimately selected for signal generation.