DVN Stock Forecast: DVN Increased by 110.59% with an Accuracy of 100%

Executive Summary

The purpose of this Devon Energy Corporation (DVN) stock forecast report is to present the results of the live forecast performance evaluation for the DVN stock by the I Know First AI Algorithm. The evaluation period is from 20th July 2021 to 20th November 2022. The corresponding returns distribution of the stock is shown below:

The DVN Stock Report Highlights:

  • The highest average return is 110.59% on a 1-year time horizon
  • Predictions reach up to a 100% hit ratio
  • Every signal group has hit ratios above 55% for all time horizons

About the I Know First Algorithm

The I Know First self-learning algorithm analyzes, models, and predicts the stock market. The algorithm is based on Artificial Intelligence (AI) and Machine Learning (ML) and incorporates elements of Artificial Neural Networks and Genetic Algorithms.

The system outputs the predicted trend as a number, positive or negative, along with a wave chart that predicts how the waves will overlap the trend. This helps the trader to decide which direction to trade, at what point to enter the trade, and when to exit. Since the model is 100% empirical, the results are based only on factual data, thereby avoiding any biases or emotions that may accompany human-derived assumptions.

The human factor is only involved in building the mathematical framework and providing the initial set of inputs and outputs to the system. The algorithm produces a forecast with a signal and a predictability indicator. The signal is the number in the middle of the box. Predictability is the number at the bottom of the box. At the top, a specific asset is identified. This format is consistent across all predictions.

Our algorithm provides two independent indicators for each asset – Signal and Predictability.

The Signal is the predicted strength and direction of the movement of the asset. Measured from -inf to +inf.

Predictability indicates our confidence in that result. It is a Pearson correlation coefficient between past algorithmic performance and actual market movement. Measured from -1 to 1.

You can find a detailed description of our heatmap here.

The Stock Market Forecast Performance Evaluation Method

We perform evaluations on the individual forecast level. It means that we calculate what would be the return of each forecast we have issued for each horizon in the testing period. Then, we take the average of those results by strategy and forecast horizon.

For example, to evaluate the performance of our 1-month forecasts, we calculate the return of each trade by using this formula:

This simulates a client purchasing the asset based on our prediction and selling it exactly 1 month in the future.

We iterate this calculation for all trading days in the analyzed period and average the results.

Note that this evaluation does not take a set portfolio and follow it. This is a different evaluation method at the individual forecast level.

The Hit Ratio Method

The hit ratio helps us to identify the accuracy of our algorithm’s predictions.

Using our Daily Forecast asset filtering, we predict the direction of the movement of different assets. Our predictions are then compared against the actual movements of these assets within the same time horizon.

The hit ratio is then calculated as follows:

For instance, a 90% hit ratio for a predictability filter with a top 10 signal filter would imply that the algorithm correctly predicted the price movements of 9 out of 10 assets within this particular set of assets.

The Benchmarking Method – S&P 500 Index

In order to evaluate our algorithm’s performance in comparison to the US market, we used the S&P 500 index as a benchmark.

The S&P 500 measures the stock performance of the largest 500 companies by market cap listed on different stock exchanges in the United States. It is one of the most followed equity indices and is frequently used as the best indicator for the overall performance of US public companies, and the US market as a whole. The S&P 500 is a capitalization-weighted index, the weight of each company in the index is determined based on its market cap divided by the aggregate market cap of all the S&P 500 companies.

For each time horizon, we compare the S&P 500 performance with the performance of our forecasts.

DVN Stock Forecast Performance Evaluation – Overview

Devon Energy Corporation is an independent energy company engaged primarily in the exploration, development and production of oil and natural gas. The company’s oil and gas operations are mainly concentrated in the onshore areas of North America, primarily in the United States. Devon Energy Corporation was incorporated in 1971 and is headquartered in Oklahoma City, Oklahoma.

In this report, we conduct testing for the DVN Stock that I Know First covers by its algorithmic forecast. The period for evaluation and testing is from 20th July 2021 to 20th November 2022. During this period, we were providing our clients with daily forecasts in time horizons spanning from 3 days to 1 year which we evaluate in this report.

As can be seen in the column chart above, our algorithm provided positive returns for most of the time horizons. We can notice that as the forecasting horizon expands, the average returns tend to become higher from 0.89% for the 3-day horizon to 110.59% for the 1-year horizon.

According to the chart above, all the signal groups across all time horizons gave a hit ratio greater than 55%. It should be noted that as the time horizon gets longer, the I Know First hit ratio increases from 55% for the 3-day horizon to 100% for the 1-year horizon.

DVN Stock Forecast: Conclusion

This report looked at the live performance forecast of I Know First data for Devon Energy Corporation stock from 20th July 2021 to 20th November 2022. Data from Figures 1 and 2 above shows I Know First was able to generate a positive average return from 0.89% for the 3-day horizon to 110.59% for the 1-year horizon. Moreover, the DVN hit ratio increases from 55% for the 3-day horizon to 100% for the 1-year horizon.