New AI Volatility Edge Platform

Posted on November 11, 2020 by

Volatility is arguably the single most important option concept, effectively determining the price of almost every derivatives instrument. The AI Volatility Edge platform uses the latest in machine learning algorithms to identify and quantify real-time volatility pricing anomalies that can be exploited with strategies based on SPX, NDX, and RUT index options, VIX futures, and VIX options. The AI Volatility Edge (AIVE) platform provides forecasts and relative value analysis across the entire term structure of volatilities.

Why is volatility so important? Because volatility is synonymous with the value of the option. If you could forecast the future distribution of returns, you would be able to estimate the current value of every option. If you could forecast implied volatility (IV - the market’s estimate of volatility) in the future, you would be able to estimate the future value of volatility indices and the future value of every option. If your estimates of the future return distribution and future implied volatilities diverged materially from the market’s estimates, you could design option and volatility index futures strategies to exploit those targeted pricing anomalies and earn excess risk-adjusted returns.

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Posted in AI Volatility Edge, Implied Volatility, Market Timing, Option Volatility, Options, Video | Tagged , , , , , , , , , | 6 Comments

No Recession Model Post this Month (10-01-2020)

Posted on October 30, 2020 by

I have been working on a new volatility project for the past year and I am in the final stages of building, testing, and releasing a comprehensive AI Volatility Modeling platform. This new tool uses the latest in machine learning algorithms to identify and quantify real-time volatility pricing anomalies that can be exploited with strategies based on SPX, NDX, and RUT index options, VIX futures, and VIX options. The platform provides real-time forecasts and relative value analysis across the entire term structure of volatilities.

I hope to release the new AI Volatility model very soon. Please see TraderEdge.Net for updates.

I plan to resume publishing the monthly recession model in November.

Brian Johnson

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Posted in Economic Indicators, Fundamental Analysis, Implied Volatility, Market Commentary, Market Timing, Option Volatility, Options, Recession Forecasting Model, Risk Management, Strategy Development, Volatility Forecast | Tagged , , , , , , , , , , | Leave a comment

Recession Model Forecast: 09-01-2020

Posted on September 26, 2020 by

I made a number of significant improvements to the recession model in January of 2020. If you missed the January recession model post, or if you would like to review the improvements to the models, please revisit the Recession Model Forecast: 01-01-2020. In the following months, I reduced the number of input variables in all of the peak-trough neural network models and expanded the number of individual models. I also further constrained the models, which made them even more robust - especially when interpreted as a single aggregate peak-trough forecast. Finally, due to the very large discrete changes in the economic data due to COVID-19, I capped the maximum standardized deviation above the recession threshold, which is particularly important when reporting the mean standardized deviation. No changes were made to any of the explanatory variables.

I also recently developed a SEIR model for COVID-19, with variables for the magnitude and timing of social distancing restrictions, as well a probabilistic variable for decaying immunity. The results were ominous and are not fully reflected in equity prices, especially after the very large rebound from the March 23rd lows in the last few months. I explained the Coronavirus model in an in-depth article titled: "New Coronavirus Model and the Economy," which I posted on April 1, 2020.

Monthly Update

This article updates the diffusion indices, recession slack index, aggregate recession model, and aggregate peak-trough model through August 2020. The explanatory variables are now capturing the effects of COVID-19 on the market and on the U.S. economy. Continue reading →

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Posted in Economic Indicators, Fundamental Analysis, Market Commentary, Market Timing, Recession Forecasting Model, Risk Management, Strategy Development | Tagged , , , , , , , , , | 1 Comment

Recession Model Forecast: 08-01-2020

Posted on August 23, 2020 by

I made a number of significant improvements to the recession model in January of 2020. If you missed the January recession model post, or if you would like to review the improvements to the models, please revisit the Recession Model Forecast: 01-01-2020. In the following months, I reduced the number of input variables in all of the peak-trough neural network models and expanded the number of individual models. I also further constrained the models, which made them even more robust - especially when interpreted as a single aggregate peak-trough forecast. Finally, due to the very large discrete changes in the economic data due to COVID-19, I capped the maximum standardized deviation above the recession threshold, which is particularly important when reporting the mean standardized deviation. No changes were made to any of the explanatory variables.

I also recently developed a SEIR model for COVID-19, with variables for the magnitude and timing of social distancing restrictions, as well a probabilistic variable for decaying immunity. The results were ominous and are not fully reflected in equity prices, especially after the very large rebound from the March 23rd lows in the last few months. I explained the Coronavirus model in an in-depth article titled: "New Coronavirus Model and the Economy," which I posted on April 1, 2020.

Monthly Update

This article updates the diffusion indices, recession slack index, aggregate recession model, and aggregate peak-trough model through July 2020. The explanatory variables are now capturing the effects of COVID-19 on the market and on the U.S. economy. Continue reading →

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Recession Model Forecast: 07-01-2020

Posted on July 25, 2020 by

I made a number of significant improvements to the recession model in January of 2020. If you missed the January recession model post, or if you would like to review the improvements to the models, please revisit the Recession Model Forecast: 01-01-2020. In the following months, I reduced the number of input variables in all of the peak-trough neural network models and expanded the number of individual models. I also further constrained the models, which made them even more robust - especially when interpreted as a single aggregate peak-trough forecast. Finally, due to the very large discrete changes in the economic data due to COVID-19, I capped the maximum standardized deviation above the recession threshold, which is particularly important when reporting the mean standardized deviation. No changes were made to any of the explanatory variables.

I also recently developed a SEIR model for COVID-19, with variables for the magnitude and timing of social distancing restrictions, as well a probabilistic variable for decaying immunity. The results were ominous and are not fully reflected in equity prices, especially after the very large rebound from the March 23rd lows in the last few months. I explained the Coronavirus model in an in-depth article titled: "New Coronavirus Model and the Economy," which I posted on April 1, 2020.

Monthly Update

This article updates the diffusion indices, recession slack index, aggregate recession model, and aggregate peak-trough model through June 2020. The explanatory variables are now capturing the effects of COVID-19 on the market and on the U.S. economy. Continue reading →

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Recession Model Forecast: 06-01-2020

Posted on June 20, 2020 by

I made a number of significant improvements to the recession model in January of 2020. If you missed the January recession model post, or if you would like to review the improvements to the models, please revisit the Recession Model Forecast: 01-01-2020. In the following months, I reduced the number of input variables in all of the peak-trough neural network models and expanded the number of individual models. I continued to work with the neutral network models in May 2020, further constraining the models, which made them even more robust - especially when interpreted as a single aggregate peak-trough forecast. Finally, due to the very large discrete changes in the economic data due to COVID-19, I capped the maximum standardized deviation above the recession threshold, which is particularly important when reporting the mean standardized deviation. No changes were made to any of the explanatory variables.

I also recently developed a SEIR model for COVID-19, with variables for the magnitude and timing of social distancing restrictions, as well a probabilistic variable for decaying immunity. The results were ominous and are not fully reflected in equity prices, especially after the very large rebound from the March 23rd lows in April and May month-to-date. The growth rate in new Coronavirus cases is only slightly less than my model estimates during the social distancing phase. I documented the model results in an in-depth article titled: "New Coronavirus Model and the Economy," which I posted on April 1, 2020.

Monthly Update

This article updates the diffusion indices, recession slack index, aggregate recession model, and aggregate peak-trough model through May 2020. The explanatory variables are now capturing the effects of COVID-19 on the market and on the U.S. economy. Continue reading →

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Recession Model Forecast: 05-01-2020

Posted on May 23, 2020 by

I made a number of significant improvements to the recession model in January of 2020. If you missed the January recession model post, or if you would like to review the improvements to the models, please revisit the Recession Model Forecast: 01-01-2020. Last month, I reduced the number of input variables in all of the peak-trough neural network models and expanded the number of individual models. I continued to work with the neutral network models this month, further constraining the models, which made them even more robust - especially when interpreted as a single aggregate peak-trough forecast. No changes were made to any of the explanatory variables.

I also recently developed a SEIR model for COVID-19, with variables for the magnitude and timing of social distancing restrictions, as well a probabilistic variable for decaying immunity. The results were ominous and are not fully reflected in equity prices, especially after the very large rebound from the March 23rd lows in April and May month-to-date. The growth rate in new Coronavirus cases is only slightly less than my model estimates during the social distancing phase. I documented the model results in an in-depth article titled: "New Coronavirus Model and the Economy," which I posted on April 1, 2020.

Monthly Update

This article updates the diffusion indices, recession slack index, aggregate recession model, and aggregate peak-trough model through April 2020. Most of the explanatory variables are now capturing the effects of COVID-19 on the market and on the U.S. economy - however, there are still a few data series that have more pronounced delays. Continue reading →

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Recession Model Forecast: 04-01-2020

Posted on April 27, 2020 by

I made a number of significant improvements to the recession model in January of 2020. If you missed the January recession model post, or if you would like to review the improvements to the models, please revisit the Recession Model Forecast: 01-01-2020. Earlier this month, I reduced the number of input variables in all of the peak-trough neural network models and expanded the number of individual models to 12. This further constrained the models and made them even more robust - especially when interpreted as single aggregate peak-trough forecast. No changes were made to any of the explanatory variables.

I also recently developed a SEIR model for COVID-19, with variables for the magnitude and timing of social distancing restrictions, as well a probabilistic variable for decaying immunity. The results were ominous and are not fully reflected in equity prices, especially after the 31% rebound from the March 23rd lows to late April. The growth rate in new Coronavirus cases very closely matches my model estimates during the social distancing phase. I documented the model results in an in-depth article titled: "New Coronavirus Model and the Economy," which I posted on April 1, 2020.

Monthly Update

This article updates the diffusion indices, recession slack index, aggregate recession model, and aggregate peak-trough model through March 2020. When interpreting the results, please be aware that the economic effects of COVID-19 will not be fully reflected in all of the explanatory variables (due to reporting lags in the economic data) until May or even June. However, a number of the variables are already capturing these effects, particularly the market-based variables.

The current 26-variable model has a diverse set of explanatory variables and is quite robust. Each of the explanatory variables has predictive power individually; when combined, the group of indicators is able to identify early recession warnings from a wide range of diverse market-based, fundamental, technical, and economic sources.

Several of the explanatory variables are market-based. These variables are available in real-time (no lag), which means they respond very quickly to changing market conditions. In addition, they are never revised. This makes the Trader Edge recession model more responsive than many recession models. The current and historical data in this report reflect the current model configuration with all 26 variables. Continue reading →

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Posted in Economic Indicators, Fundamental Analysis, Market Commentary, Market Timing, Recession Forecasting Model, Risk Management, Strategy Development | Tagged , , , , , , , , | Leave a comment