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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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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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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Recession Model Forecast: 06-01-2020

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 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

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

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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New Coronavirus Model and the Economy

I included a brief coronavirus update in my most recent recession model post, but it has since become clear that the speed, breadth, and longevity of the coronavirus will be the principal determinants of all near-term and long-term asset prices: equities, credit instruments, commodities, real estate, etc. As a result, I decided to develop an epidemiological model to simulate future coronavirus scenarios, under a wide range of assumptions. The intermediate goal of developing the model is to understand the likely speed, breadth, and longevity of the virus under different scenarios and be able to quantify the future effects of policy intervention and treatment initiatives. The ultimate goal is to use these new insights to evaluate the probable future impact on the economy and asset prices.  Continue reading

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Recession Model Forecast: 03-01-2020

Coronavirus Implications

Before proceeding with the model results this month, I need to explain how and when the coronavirus (COVID-19) will affect the recession model forecasts. The coronavirus is an unprecedented, discrete, exogenous event that will severely affect the global economy and has already roiled the financial markets. While quantitative models like the recession models are invaluable, they are unable to model unique external events, especially one of this speed, breadth, and magnitude. Even under normal circumstances, integrating judgement with quantitative analysis is essential; in this case, it is even more critical. Continue reading

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