New AI Volatility Edge Platform

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 , , , , , , , , , | 2 Comments

Recession Model Forecast: 12-01-2020

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.

Unfortunately, I have been unable to publish the recession model update for the last two months. I have been swamped finalizing and rolling out 32-bit and 64-bit versions of a new comprehensive option volatility forecasting platform called AI Volatility Edge (AIVE). I devoted the last year to designing AI Volatility Edge - which is an integrated collection of AI models based on the latest machine-learning (ML) algorithms. The AI Volatility Edge platform is available on a subscription basis for professional and non-professional option traders. Please see my initial post for more information about AI Volatility Edge.

Monthly Update

This article updates the diffusion indices, recession slack index, aggregate recession model, and aggregate peak-trough model through November 2020.

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Posted in AI Volatility Edge, Economic Indicators, Fundamental Analysis, In-Depth Article, Market Commentary, Market Timing, Recession Forecasting Model, Risk Management, Strategy Development | Tagged , , , , , , , | Leave a comment

64-Bit AI Volatility Edge Platform Now Available!

A NEW version of the AI Volatility Edge (AIVE) platform is now available and is compatible with 64-bit versions of Excel!

The original AIVE platform is available for use with 32-bit versions of Excel (even if installed on a 64-bit version of Microsoft Windows).

For additional information on the AI Volatility Edge platform, please see the initial AIVE announcement post or the more detailed AI Volatility Edge product page. Both of these pages include links to two AIVE demonstration videos.

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Posted in AI Volatility Edge, Implied Volatility, Option Volatility, Options, Strategy Development, Volatility Forecast | Tagged , , , , , , , , | Leave a comment

Recession Model Updates Resume Next Month: 12-01-2020

I am still working on the rollout of the new AI Volatility Model Edge (AIVE) Platform. The AIVE platform for 32-bit versions of Excel is now available! This version is compatible with 32-bit and 64-bit versions of Microsoft Windows. I am currently exploring the possibility of releasing a version for 64-bit versions of Excel.

The AI Volatility Edge Platform required a full year of research and development. 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 plan to resume publishing the monthly recession model in December.

Brian Johnson

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Posted in AI Volatility Edge, Option Volatility, Options, Recession Forecasting Model | Tagged , , , , , , | Leave a comment

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

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

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

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

Recession Model Forecast: 07-01-2020

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