Several of the explanatory variables are market-based. These variables respond very quickly to changing market conditions and are never revised. This makes the Trader Edge recession model much more responsive than other recession models. The current *and* historical data in this report reflect the current model configuration with all 21 variables.

The Trader Edge diffusion index equals the percentage of independent variables indicating a recession. With the latest changes, there are now a total of 21 explanatory variables, each with a unique look-back period and recession threshold. The resulting diffusion index and changes in the diffusion index are used to calculate the probit, logit, and neural network model forecasts.

The graph of the diffusion index from 1/1/2006 to 12/1/2018 is presented in Figure 1 below (in red - left axis). The gray shaded regions in Figure 1 below represent U.S. recessions as defined (after the fact) by the National Bureau of Economic Research (NBER). The value of the S&P 500 index is also included (in blue - right axis).

The U.S. economy flirted with entering a recession in early 2016, which was reflected in the deteriorating economic, fundamental, and especially market-based data. The diffusion index, slack index, and recession probability forecasts all captured the weakening conditions. However, the weakness proved to be temporary and the conditions and recession model forecasts improved rapidly. However, some preliminary signs of weakness have reemerged in late 2018. The number of variables indicating a recession remained at two (9.5%) in November; *however, if I update the data through last night's close (12/20/2018), that number would jump to four, with three more variables within 0.15 standard deviations of their respective recession thresholds. *

Please note that past estimates and index values will change whenever the historical data is revised. All current and past forecasts and index calculations are based on the latest revised data from the current data set.

The Trader Edge recession slack index equals the median standardized deviation of the current value of the explanatory variables from their respective recession thresholds. The resulting value signifies the amount of slack or cushion relative to the recession threshold, expressed in terms of the number of standard deviations. Higher slack values signify larger cushions above recessionary threshold levels. While the *median* recession slack index is used in the recession models, I am now including the *mean* recession slack index in the graph as well.

The gray shaded regions in Figure 2 below represent U.S. recessions as defined (after the fact) by the NBER. The *median* recession slack index is depicted in purple and is plotted against the right axis, which is expressed as the number of standard deviations above the recession threshold. The *mean* recession slack index is depicted in blue and is also plotted against the right axis.

The dark-red, horizontal line at 0.50 standard deviations denotes a possible warning threshold for the recession slack index. Many of the past recessions began when the recession slack index crossed below 0.50. Similarly, many of the past recessions ended when the recession slack index crossed back above 0.0.

In mid-2014, the revised median recession slack index peaked at 1.35, far above the warning level of 0.50. The recession slack index declined significantly in 2015 and reached a low of 0.32 in February 2016, before rebounding over the next few months. In early 2017, the median recession index peaked at 1.42, but declined in the fall before rebounding at year-end.

In November 2018, the median recession slack index decreased from a revised value of 0.82 to 0.80. The mean recession slack index declined from 0.88 to 0.76 during the same period. I expect these values to drop significantly in December as well. The recession slack indices are still marginally above the early warning threshold of 0.50, but the gap has narrowed significantly and the trend is definitely negative.

To gain further insight into the slack index, I recently went back and calculated a derivative value: the percentage of variables with increasing slack each month. The possible values range from zero percent to 100 percent. Due to the monthly volatility, I provide the three-month moving average of the percentage of variables with increasing slack in Figure 3, but I personally monitor the monthly percentages as well.

Slack is a standardized value, so it is directly comparable across all variables. More slack indicates a larger cushion relative to a recessionary environment. As a result, we would like to see as many variables as possible with *increasing* slack. Given the diverse nature of the explanatory variables, it is unusual to see more than 60% of the variables with increasing slack or fewer than 40% of the variables with increasing slack. These extreme values are significant and predictive of the near-term direction of economic growth and *often the equity market*.

The 3-month moving average of the percentage of variables with *increasing* slack dropped from 38.1% last month to only 31.7% in November. It is unusual for this value to drop this low. New evidence of economic weakness (or strength) often shows up first in this timely metric. The recent trend is very troubling, especially given the continued decline in the equity markets through late December.

The ability to track small variations and trend changes over time illustrates the advantage of monitoring the continuous recession slack index. The new slack variable will provide additional insight into the near-term direction of the economy and should be used in conjunction with the median recession slack index.

While it is useful to track the actual recession slack index values and percentage of variables with increasing slack, the diffusion percentages and slack index values are also used to generate the more intuitive probit and logit probability forecasts.

The Trader Edge aggregate recession model is the average of four models: the probit and logit models based on the diffusion index and the probit and logit models based on the recession slack index. The aggregate recession model estimates from 1/1/2006 to 12/01/2018 are depicted in Figure 4 below (red line - left vertical axis). The gray shaded regions represent NBER recessions and the blue line reflects the value of the S&P 500 index (right vertical axis). I suggest using a warning threshold of between 20-30% for the aggregate recession model (green horizontal line).

The aggregate recession model probability estimate remained constant at 0.2% in November. According to the model, the probability that the U.S. is *currently* in a recession continues to be extremely remote. However, if the markets do not rebound between now and the end of December, this value will jump next month.

The peak-trough model forecasts are different from the recession model and are much more responsive. The peak-trough models estimate the probability of the S&P 500 being between the peak and trough associated with an NBER recession. The S&P 500 typically peaks before recessions begin and bottoms out before recessions end. As a result, it is far more difficult for the peak-trough model to fit this data and the model forecasts have larger errors than the recession model.

The Trader Edge aggregate peak-trough model equals the weighted-average of nine different models: the probit and logit models based on the diffusion index, the probit and logit models based on the recession slack index, and five neural network models.

The aggregate peak-trough model estimates from 1/1/2006 to 12/01/2018 are depicted in Figure 5 below, which uses the same format as Figure 4, except that the shaded regions represent the periods between the peaks and troughs associated with NBER recessions.

The aggregate peak-trough model probability estimate for 12/01/2018 was 10.4%, which decreased by 1.5% from last month's revised value of 11.9%. As explained above, this is misleading. The market rallied significantly at the end of November, but has declined sharply in December. The peak-trough probability will increase next month (perhaps significantly) if the equity markets do not recover by the end of December.

January and February 2016 marked a potential tipping point in U.S. recession risk, but those conditions proved to be temporary. Conditions have improved significantly since early 2016. The decrease in recession risk has been supported by both market and non-market variables.

U.S. recession risk did not increase in November, but would increase significantly in December if we end the month at current levels. The diffusion index remained constant in November and the recession probabilities remained stable. However, the slack indices declined and the percentage of variables with increasing slack fell precipitously. The peak-trough recession probability remains in low double digits for now, but the recent trend is definitely toward increased weakness.

If the equity markets continue to decline or even remain at current levels, several of the market-based explanatory variables would move into recession territory next month. Stay tuned...

Finally, Hulbert's recent MarketWatch article cited research that used the household equity allocation percentage as a tool for forecasting long-term (10-year) future equity returns. The resulting correlation was so strong (-0.90) that I was compelled to duplicate the research and verify the results myself. I did so and the correlation is correct. It is highly unusual to ever see correlations that high in actual market data. Furthermore, a strong argument can be made for a causal link due to the direct effects of both market valuation and behavioral finance on the household equity allocation percentage.

Based on the most recent data, the regression model indicates that the expected annual price return of the S&P 500 index for the next 10 years has dropped below zero (-0.41%), with an expected drawdown in that period of 36% (from 12/1/2018 levels). In other words, the expected price return of the SPX is now negative over the next 10 years, *and* it is likely that an investor would have the opportunity to purchase the SPX at 64% of its current value sometime in the next 10 years. The risk/return trade off for holding periods as short as three years look equally unattractive, albeit with lower correlations.

I completed a similar historical regression analysis using the "Buffett Indicator", which is the ratio of equity market capitalization to GDP. The correlation is not quite as strong, but is still very significant (-0.74). The Buffett Indicator regression model currently indicates that the expected *annual* price return of the S&P 500 index for the *next 10 years* is significantly negative (-4.8%), with an expected drawdown in that 10-year period of almost 60% (-54%) (from 12/1/2018 levels).

Overvalued securities can *always* become more overvalued - especially in the near-term. That said, history offers compelling evidence that bullish equity positions today will face significant headwinds over the coming years. In addition, it is especially troubling that almost all domestic and international equity markets have suffered dramatic drawdowns in the past 12 months, some as large as 25% to 30%.

Unlike human prognosticators, the Trader Edge recession model is completely objective and has no ego. It is not burdened by the emotional need to defend past erroneous forecasts and will always consistently apply the insights gained from new data.

Brian Johnson

Copyright 2018 Trading Insights, LLC. All rights reserved.

]]>Several of the explanatory variables are market-based. These variables respond very quickly to changing market conditions and are never revised. This makes the Trader Edge recession model much more responsive than other recession models. The current *and* historical data in this report reflect the current model configuration with all 21 variables.

The Trader Edge diffusion index equals the percentage of independent variables indicating a recession. With the latest changes, there are now a total of 21 explanatory variables, each with a unique look-back period and recession threshold. The resulting diffusion index and changes in the diffusion index are used to calculate the probit, logit, and neural network model forecasts.

The graph of the diffusion index from 1/1/2006 to 11/1/2018 is presented in Figure 1 below (in red - left axis). The gray shaded regions in Figure 1 below represent U.S. recessions as defined (after the fact) by the National Bureau of Economic Research (NBER). The value of the S&P 500 index is also included (in blue - right axis).

The U.S. economy flirted with entering a recession in early 2016, which was reflected in the deteriorating economic, fundamental, and especially market-based data. The diffusion index, slack index, and recession probability forecasts all captured the weakening conditions. However, the weakness proved to be temporary and the conditions and recession model forecasts improved rapidly. However, some preliminary signs of weakness have reemerged in late 2018. The number of variables indicating a recession increased from one (4.8%) to two (9.5%) in October.

Please note that past estimates and index values will change whenever the historical data is revised. All current and past forecasts and index calculations are based on the latest revised data from the current data set.

The Trader Edge recession slack index equals the median standardized deviation of the current value of the explanatory variables from their respective recession thresholds. The resulting value signifies the amount of slack or cushion relative to the recession threshold, expressed in terms of the number of standard deviations. Higher slack values signify larger cushions above recessionary threshold levels. While the *median* recession slack index is used in the recession models, I am now including the *mean* recession slack index in the graph as well.

The gray shaded regions in Figure 2 below represent U.S. recessions as defined (after the fact) by the NBER. The *median* recession slack index is depicted in purple and is plotted against the right axis, which is expressed as the number of standard deviations above the recession threshold. The *mean* recession slack index is depicted in blue and is also plotted against the right axis.

The dark-red, horizontal line at 0.50 standard deviations denotes a possible warning threshold for the recession slack index. Many of the past recessions began when the recession slack index crossed below 0.50. Similarly, many of the past recessions ended when the recession slack index crossed back above 0.0.

In mid-2014, the revised median recession slack index peaked at 1.35, far above the warning level of 0.50. The recession slack index declined significantly in 2015 and reached a low of 0.32 in February 2016, before rebounding over the next few months. In early 2017, the median recession index peaked at 1.42, but declined in the fall before rebounding at year-end.

In October 2018, the median recession slack index decreased from a revised value of 1.10 to 0.90, which represents a significant 0.20 standard deviation decline in a single month. The recession slack indices are still above the early warning threshold of 0.50, but the gap has narrowed and the trend is negative.

To gain further insight into the slack index, I recently went back and calculated a derivative value: the percentage of variables with increasing slack each month. The possible values range from zero percent to 100 percent. Due to the monthly volatility, I provide the three-month moving average of the percentage of variables with increasing slack in Figure 3, but I personally monitor the monthly percentages as well.

Slack is a standardized value, so it is directly comparable across all variables. More slack indicates a larger cushion relative to a recessionary environment. As a result, we would like to see as many variables as possible with *increasing* slack. Given the diverse nature of the explanatory variables, it is unusual to see more than 60% of the variables with increasing slack or fewer than 40% of the variables with increasing slack. These extreme values are significant and predictive of the near-term direction of economic growth and *often the equity market*.

The 3-month moving average of the percentage of variables with *increasing* slack dropped from 49.2% last month to only 38.1% in October. Only 14.3% of the variables showed *increasing* slack in October. This was the lowest percentage of variables with *increasing* slack in a single month since the Great Recession of 2008-2009. New evidence of economic weakness (or strength) often shows up first in this timely metric. The recent trend is troubling.

The ability to track small variations and trend changes over time illustrates the advantage of monitoring the continuous recession slack index. The new slack variable will provide additional insight into the near-term direction of the economy and should be used in conjunction with the median recession slack index.

While it is useful to track the actual recession slack index values and percentage of variables with increasing slack, the diffusion percentages and slack index values are also used to generate the more intuitive probit and logit probability forecasts.

The Trader Edge aggregate recession model is the average of four models: the probit and logit models based on the diffusion index and the probit and logit models based on the recession slack index. The aggregate recession model estimates from 1/1/2006 to 11/01/2018 are depicted in Figure 4 below (red line - left vertical axis). The gray shaded regions represent NBER recessions and the blue line reflects the value of the S&P 500 index (right vertical axis). I suggest using a warning threshold of between 20-30% for the aggregate recession model (green horizontal line).

The aggregate recession model probability estimate increased from 0.1% to 0.2% in October. According to the model, the probability that the U.S. is *currently* in a recession continues to be extremely remote.

The peak-trough model forecasts are different from the recession model and are much more responsive. The peak-trough models estimate the probability of the S&P 500 being between the peak and trough associated with an NBER recession. The S&P 500 typically peaks before recessions begin and bottoms out before recessions end. As a result, it is far more difficult for the peak-trough model to fit this data and the model forecasts have larger errors than the recession model.

The Trader Edge aggregate peak-trough model equals the weighted-average of nine different models: the probit and logit models based on the diffusion index, the probit and logit models based on the recession slack index, and five neural network models.

The aggregate peak-trough model estimates from 1/1/2006 to 11/01/2018 are depicted in Figure 5 below, which uses the same format as Figure 4, except that the shaded regions represent the periods between the peaks and troughs associated with NBER recessions.

The aggregate peak-trough model probability estimate for 11/01/2018 was 10.8%, which increased 4.9% from last month's revised value of 5.9%.

January and February 2016 marked a potential tipping point in U.S. recession risk, but those conditions proved to be temporary. Conditions have improved significantly since early 2016. The decrease in recession risk has been supported by both market and non-market variables.

U.S. recession risk remains relatively low, but increased in October. The diffusion index and recession probabilities all increased, while the slack indices declined sharply. The peak-trough recession probability remains in low double digits for now, but the recent trend is toward weakness.

If the equity markets continue to decline, the effects would be captured by several market-based explanatory variables - long before they are evident in the economic data. Stay tuned...

Finally, Hulbert's recent MarketWatch article cited research that used the household equity allocation percentage as a tool for forecasting long-term (10-year) future equity returns. The resulting correlation was so strong (-0.90) that I was compelled to duplicate the research and verify the results myself. I did so and the correlation is correct. It is highly unusual to ever see correlations that high in actual market data. Furthermore, a strong argument can be made for a causal link due to the direct effects of both market valuation and behavioral finance on the household equity allocation percentage.

Based on the most recent data, the regression model indicates that the expected annual price return of the S&P 500 index for the next 10 years has dropped below zero (-1.15%), with an expected drawdown in that period of 38% (from 11/1/2018 levels). In other words, the expected price return of the SPX is now negative over the next 10 years, *and* it is likely that an investor would have the opportunity to purchase the SPX at 62% of its current value sometime in the next 10 years. The risk/return trade off for holding periods as short as three years look equally unattractive, albeit with lower correlations.

I completed a similar historical regression analysis using the "Buffett Indicator", which is the ratio of equity market capitalization to GDP. The correlation is not quite as strong, but is still very significant (-0.74). The Buffett Indicator regression model currently indicates that the expected *annual* price return of the S&P 500 index for the *next 10 years* is significantly negative (-6.4%), with an expected drawdown in that 10-year period of almost 60% (-58.9%) (from 11/1/2018 levels).

Overvalued securities can *always* become more overvalued - especially in the near-term. That said, history offers compelling evidence that bullish equity positions today will face significant headwinds over the coming years. In addition, it is especially troubling that almost all non-US equity markets have suffered dramatic drawdowns in the past 12 months, some as large as 25% to 30%.

Unlike human prognosticators, the Trader Edge recession model is completely objective and has no ego. It is not burdened by the emotional need to defend past erroneous forecasts and will always consistently apply the insights gained from new data.

Brian Johnson

Copyright 2018 Trading Insights, LLC. All rights reserved.

]]>Several of the explanatory variables are market-based. These variables respond very quickly to changing market conditions and are never revised. This makes the Trader Edge recession model much more responsive than other recession models. The current *and* historical data in this report reflect the current model configuration with all 21 variables.

The Trader Edge diffusion index equals the percentage of independent variables indicating a recession. With the latest changes, there are now a total of 21 explanatory variables, each with a unique look-back period and recession threshold. The resulting diffusion index and changes in the diffusion index are used to calculate the probit, logit, and neural network model forecasts.

The graph of the diffusion index from 1/1/2006 to 10/1/2018 is presented in Figure 1 below (in red - left axis). The gray shaded regions in Figure 1 below represent U.S. recessions as defined (after the fact) by the National Bureau of Economic Research (NBER). The value of the S&P 500 index is also included (in blue - right axis).

The U.S. economy flirted with entering a recession in early 2016, which was reflected in the deteriorating economic, fundamental, and especially market-based data. The diffusion index, slack index, and recession probability forecasts all captured the weakening conditions. However, the weakness proved to be temporary and the conditions and recession model forecasts have improved significantly in the past two years. The number of variables indicating a recession remained constant at one (4.8%) in September.

Please note that past estimates and index values will change whenever the historical data is revised. All current and past forecasts and index calculations are based on the latest revised data from the current data set.

The Trader Edge recession slack index equals the median standardized deviation of the current value of the explanatory variables from their respective recession thresholds. The resulting value signifies the amount of slack or cushion relative to the recession threshold, expressed in terms of the number of standard deviations. Higher slack values signify larger cushions above recessionary threshold levels. While the *median* recession slack index is used in the recession models, I am now including the *mean* recession slack index in the graph as well.

The gray shaded regions in Figure 2 below represent U.S. recessions as defined (after the fact) by the NBER. The *median* recession slack index is depicted in purple and is plotted against the right axis, which is expressed as the number of standard deviations above the recession threshold. The *mean* recession slack index is depicted in blue and is also plotted against the right axis.

The dark-red, horizontal line at 0.50 standard deviations denotes a possible warning threshold for the recession slack index. Many of the past recessions began when the recession slack index crossed below 0.50. Similarly, many of the past recessions ended when the recession slack index crossed back above 0.0.

In mid-2014, the revised median recession slack index peaked at 1.35, far above the warning level of 0.50. The recession slack index declined significantly in 2015 and reached a low of 0.32 in February 2016, before rebounding over the next few months. In early 2017, the median recession index peaked at 1.42, but declined in the fall before rebounding at year-end.

In September 2018, the median recession slack index decreased from a revised value of 1.11 to 1.01 and the mean recession slack index remained constant at 1.14. The recession slack indices are comfortably above the early warning threshold of 0.50.

To gain further insight into the slack index, I recently went back and calculated a derivative value: the percentage of variables with increasing slack each month. The possible values range from zero percent to 100 percent. Due to the monthly volatility, I provide the three-month moving average of the percentage of variables with increasing slack in Figure 3, but I personally monitor the monthly percentages as well.

Slack is a standardized value, so it is directly comparable across all variables. More slack indicates a larger cushion relative to a recessionary environment. As a result, we would like to see as many variables as possible with *increasing* slack. Given the diverse nature of the explanatory variables, it is unusual to see more than 60% of the variables with increasing slack or fewer than 40% of the variables with increasing slack. These extreme values are significant and predictive of the near-term direction of economic growth and *often the equity market*.

The 3-month moving average of the percentage of variables with *increasing* slack increased from 46.0% last month to 49.2% in September. New evidence of economic weakness (or strength) often shows up first in this timely metric. The recent troubling trend in the slack index reversed sharply in August and remained stable in September.

The ability to track small variations and trend changes over time illustrates the advantage of monitoring the continuous recession slack index. The new slack variable will provide additional insight into the near-term direction of the economy and should be used in conjunction with the median recession slack index.

While it is useful to track the actual recession slack index values and percentage of variables with increasing slack, the diffusion percentages and slack index values are also used to generate the more intuitive probit and logit probability forecasts.

The Trader Edge aggregate recession model is the average of four models: the probit and logit models based on the diffusion index and the probit and logit models based on the recession slack index. The aggregate recession model estimates from 1/1/2006 to 10/01/2018 are depicted in Figure 4 below (red line - left vertical axis). The gray shaded regions represent NBER recessions and the blue line reflects the value of the S&P 500 index (right vertical axis). I suggest using a warning threshold of between 20-30% for the aggregate recession model (green horizontal line).

The aggregate recession model probability estimate remained constant at 0.1% in September. According to the model, the probability that the U.S. is *currently* in a recession continues to be extremely remote.

The peak-trough model forecasts are different from the recession model and are much more responsive. The peak-trough models estimate the probability of the S&P 500 being between the peak and trough associated with an NBER recession. The S&P 500 typically peaks before recessions begin and bottoms out before recessions end. As a result, it is far more difficult for the peak-trough model to fit this data and the model forecasts have larger errors than the recession model.

The Trader Edge aggregate peak-trough model equals the weighted-average of nine different models: the probit and logit models based on the diffusion index, the probit and logit models based on the recession slack index, and five neural network models.

The aggregate peak-trough model estimates from 1/1/2006 to 10/01/2018 are depicted in Figure 5 below, which uses the same format as Figure 4, except that the shaded regions represent the periods between the peaks and troughs associated with NBER recessions.

The aggregate peak-trough model probability estimate for 10/01/2018 was 6.5%, which increased 0.4% from last month's revised value of 6.1%.

January and February 2016 marked a potential tipping point in U.S. recession risk, but those conditions proved to be temporary. Conditions have improved significantly since early 2016. The decrease in recession risk has been supported by both market and non-market variables.

U.S. recession risk remains low. The sharp increase in June was surprising, but it proved to be temporary. The diffusion index remained constant in September, and the slack indices remained stable. The peak-trough recession probability remained safely in single-digits.

However, it is very important to note that the equity markets have declined significantly since the beginning of October, which will not affect the recession probability forecasts until next month. If the equity markets do not rebound before the end of October, it will be very interesting to see the effect on the market-sensitive explanatory variables in the model. Stay tuned...

The U.S. equity market continues to be overvalued and global event risk continues to be elevated. This recent *MarketWatch* article suggests that "*There are only two other times in history when stocks were more expensive than today*." On a related topic, Mark Hulbert's latest *MarketWatch* article demonstrated that the *Russell 2000's current P/E ratio is actually 78.7*, not the more commonly reported value of 25.6.

Finally, Hulbert's recent MarketWatch article cited research that used the household equity allocation percentage as a tool for forecasting long-term (10-year) future equity returns. The resulting correlation was so strong (-0.90) that I was compelled to duplicate the research and verify the results myself. I did so and the correlation is correct. It is highly unusual to ever see correlations that high in actual market data. Furthermore, a strong argument can be made for a causal link due to the direct effects of both market valuation and behavioral finance on the household equity allocation percentage.

Based on the most recent data, the regression model indicates that the expected annual price return of the S&P 500 index for the next 10 years is only 0.1%, with an expected drawdown in that period of 35% (from 10/1/2018 levels). In other words, the expected price return of the SPX is negligible over the next 10 years, *and* it is likely that an investor would have the opportunity to purchase the SPX at 66% of its current value sometime in the next 10 years. The risk/return trade off for holding periods as short as three years look equally unattractive, albeit with lower correlations.

I completed a similar historical regression analysis using the "Buffett Indicator", which is the ratio of equity market capitalization to GDP. The correlation is not quite as strong, but is still very significant (-0.74). The Buffett Indicator regression model currently indicates that the expected *annual* price return of the S&P 500 index for the *next 10 years* is significantly negative (-3.70%), with an expected drawdown in that 10-year period of over 50% (from 10/1/2018 levels).

Overvalued securities can *always* become more overvalued - especially in the near-term. That said, history offers compelling evidence that bullish equity positions today will face significant headwinds over the coming years. It is also troubling that equity returns in emerging markets, EAFA, and China have all been significantly negative for the past 12 months.

Unlike human prognosticators, the Trader Edge recession model is completely objective and has no ego. It is not burdened by the emotional need to defend past erroneous forecasts and will always consistently apply the insights gained from new data.

Brian Johnson

Copyright 2018 Trading Insights, LLC. All rights reserved.

]]>*and* historical data in this report reflect the current model configuration with all 21 variables.

The graph of the diffusion index from 1/1/2006 to 9/1/2018 is presented in Figure 1 below (in red - left axis). The gray shaded regions in Figure 1 below represent U.S. recessions as defined (after the fact) by the National Bureau of Economic Research (NBER). The value of the S&P 500 index is also included (in blue - right axis).

The U.S. economy flirted with entering a recession in early 2016, which was reflected in the deteriorating economic, fundamental, and especially market-based data. The diffusion index, slack index, and recession probability forecasts all captured the weakening conditions. However, the weakness proved to be temporary and the conditions and recession model forecasts have improved significantly in the past two years. The number of variables indicating a recession remained constant at one (4.8%) in August.

*median* recession slack index is used in the recession models, I am now including the *mean* recession slack index in the graph as well.

*median* recession slack index is depicted in purple and is plotted against the right axis, which is expressed as the number of standard deviations above the recession threshold. The *mean* recession slack index is depicted in blue and is also plotted against the right axis.

In August 2018, the median recession slack index increased significantly from a revised value of 0.82 to 1.12. After the rebound in August, the recession slack indices are comfortably above the early warning threshold of 0.50.

*increasing* slack. Given the diverse nature of the explanatory variables, it is unusual to see more than 60% of the variables with increasing slack or fewer than 40% of the variables with increasing slack. These extreme values are significant and predictive of the near-term direction of economic growth and *often the equity market*.

The 3-month moving average of the percentage of variables with *increasing* slack increased dramatically from 39.7% last month to 47.6% in August. The percentage of variables with increasing slack increased from 28.6%, to 47.6%, to 66.7% in the last three months. New evidence of economic weakness (or strength) often shows up first in this timely metric. The recent troubling trend in the slack index reversed sharply in August.

The Trader Edge aggregate recession model is the average of four models: the probit and logit models based on the diffusion index and the probit and logit models based on the recession slack index. The aggregate recession model estimates from 1/1/2006 to 9/01/2018 are depicted in Figure 4 below (red line - left vertical axis). The gray shaded regions represent NBER recessions and the blue line reflects the value of the S&P 500 index (right vertical axis). I suggest using a warning threshold of between 20-30% for the aggregate recession model (green horizontal line).

The aggregate recession model probability estimate remained constant at 0.1% in August. According to the model, the probability that the U.S. is *currently* in a recession continues to be extremely remote.

The aggregate peak-trough model estimates from 1/1/2006 to 9/01/2018 are depicted in Figure 5 below, which uses the same format as Figure 4, except that the shaded regions represent the periods between the peaks and troughs associated with NBER recessions.

The aggregate peak-trough model probability estimate for 9/01/2018 was 6.0%, which dropped 3.0% from last month's revised value of 9.0%. The decline in the aggregate peak-trough probability estimate is consistent with the improvement in the recession slack index. .

U.S. recession risk remains low. The sharp increase in June was surprising, but it proved to be temporary. The diffusion index remained constant in August, and the slack indices bounced back significantly. The peak-trough recession probability dropped back to 6% in August after spiking to 10.8% in June.

The U.S. equity market continues to be overvalued and global event risk continues to be elevated. This recent *MarketWatch* article suggests that "*There are only two other times in history when stocks were more expensive than today*." On a related topic, Mark Hulbert's latest *MarketWatch* article demonstrated that the *Russell 2000's current P/E ratio is actually 78.7*, not the more commonly reported value of 25.6.

Based on the most recent data, the regression model indicates that the expected annual price return of the S&P 500 index for the next 10 years is only 0.2%, with an expected drawdown in that period of 34% (from current levels). In other words, the expected price return of the SPX is negligible over the next 10 years, *and* it is likely that an investor would have the opportunity to purchase the SPX at 66% of its current value sometime in the next 10 years. The risk/return trade off for holding periods as short as three years look equally unattractive, albeit with lower correlations.

I completed a similar historical regression analysis using the "Buffett Indicator", which is the ratio of equity market capitalization to GDP. The correlation is not quite as strong, but is still very significant (-0.74). The Buffett Indicator regression model currently indicates that the expected *annual* price return of the S&P 500 index for the *next 10 years* is significantly negative (-3.60%), with an expected drawdown in that 10-year period of over 50% (from current levels).

Overvalued securities can *always* become more overvalued - especially in the near-term. That said, history offers compelling evidence that bullish equity positions today will face significant headwinds over the coming years. It is also troubling that equity returns in emerging markets, EAFA, and China have all been negative for the past 12 months.

Brian Johnson

Copyright 2018 Trading Insights, LLC. All rights reserved.

]]>*and* historical data in this report reflect the current model configuration with all 21 variables.

The graph of the diffusion index from 1/1/2006 to 8/1/2018 is presented in Figure 1 below (in red - left axis). The gray shaded regions in Figure 1 below represent U.S. recessions as defined (after the fact) by the National Bureau of Economic Research (NBER). The value of the S&P 500 index is also included (in blue - right axis).

The U.S. economy flirted with entering a recession in early 2016, which was reflected in the deteriorating economic, fundamental, and especially market-based data. The diffusion index, slack index, and recession probability forecasts all captured the weakening conditions. However, the weakness proved to be temporary and the conditions and recession model forecasts have improved significantly in the past two years. However, after data revisions, the number of variables indicating a recession remained constant at one (4.8%) in July. Note, *prior to economic data revisions*, two variables indicated a recession in June.

*median* recession slack index is used in the recession models, I am now including the *mean* recession slack index in the graph as well.

*median* recession slack index is depicted in purple and is plotted against the right axis, which is expressed as the number of standard deviations above the recession threshold. The *mean* recession slack index is depicted in blue and is also plotted against the right axis.

In July 2018, the median recession slack index increased from a revised value of 0.78 to 0.87. The mean recession index also increased in July, from 0.89 to 0.93. The July recession slack indices are still above the early warning threshold of 0.50, but the recession slack indices are well below the values in most of 2017 and 2018.

*increasing* slack. Given the diverse nature of the explanatory variables, it is unusual to see more than 60% of the variables with increasing slack or fewer than 40% of the variables with increasing slack. These extreme values are significant and predictive of the near-term direction of economic growth and *often the equity market*.

The 3-month moving average of the percentage of variables with *increasing* slack increased from 39.7% last month to 41.3% in July. While the 3-month moving average is still quite low, the percentage of variables with increasing slack increased from 28.6% last month to 52.4% in June. While hardly impressive, 52.4% was the highest monthly value in the past seven months. New evidence of economic weakness (or strength) often shows up first in this timely metric.

The Trader Edge aggregate recession model is the average of four models: the probit and logit models based on the diffusion index and the probit and logit models based on the recession slack index. The aggregate recession model estimates from 1/1/2006 to 8/01/2018 are depicted in Figure 4 below (red line - left vertical axis). The gray shaded regions represent NBER recessions and the blue line reflects the value of the S&P 500 index (right vertical axis). I suggest using a warning threshold of between 20-30% for the aggregate recession model (green horizontal line).

The aggregate recession model probability estimate remained constant at 0.1% in July. According to the model, the probability that the U.S. is *currently* in a recession continues to be extremely remote.

The aggregate peak-trough model estimates from 1/1/2006 to 8/01/2018 are depicted in Figure 5 below, which uses the same format as Figure 4, except that the shaded regions represent the periods between the peaks and troughs associated with NBER recessions.

The aggregate peak-trough model probability estimate for 8/01/2018 was 8.5%, which dropped 2.2% from last month's revised value of 10.7%. The aggregate peak-trough probability of 8.5% is low, but is still higher than most of 2017 and 2018.

U.S. recession risk remains *relatively* low, but the sharp rise in June was surprising. The recession risk moderated somewhat in July, but is still higher than most of 2017 and 2018. The diffusion index remained constant in July, and the slack indices bounced back slightly from their interim lows in June. The percentage of variables with increasing slack has been low or very low for five consecutive months, but did begin to creep back up in July. The peak-trough recession probability dropped slightly in July after spiking to 10.7% in June.

The U.S. equity market continues to be overvalued and global event risk continues to be elevated. This recent *MarketWatch* article suggests that "*There are only two other times in history when stocks were more expensive than today*." On a related topic, Mark Hulbert's latest *MarketWatch* article demonstrated that the *Russell 2000's current P/E ratio is actually 78.7*, not the more commonly reported value of 25.6.

Based on the most recent data, the regression model indicates that the expected annual price return of the S&P 500 index for the next 10 years is only 1.2%, with an expected drawdown in that period of 32% (from current levels). In other words, the expected price return of the SPX is negligible over the next 10 years, *and* it is likely that an investor would have the opportunity to purchase the SPX at 68% of its current value sometime in the next 10 years. The risk/return trade off for holding periods as short as three years look equally unattractive, albeit with lower correlations.

I completed a similar historical regression analysis using the "Buffett Indicator", which is the ratio of equity market capitalization to GDP. The correlation is not quite as strong, but is still very significant (-0.74). The Buffett Indicator regression model currently indicates that the expected *annual* price return of the S&P 500 index for the *next 10 years* is significantly negative (-2.60%), with an expected drawdown in that 10-year period of over 47% (from current levels).

Overvalued securities can *always* become more overvalued - especially in the near-term. That said, history offers compelling evidence that bullish equity positions today will face significant headwinds over the coming years.

Brian Johnson

Copyright 2018 Trading Insights, LLC. All rights reserved.

]]>*and* historical data in this report reflect the current model configuration with all 21 variables.

The graph of the diffusion index from 1/1/2006 to 7/1/2018 is presented in Figure 1 below (in red - left axis). The gray shaded regions in Figure 1 below represent U.S. recessions as defined (after the fact) by the National Bureau of Economic Research (NBER). The value of the S&P 500 index is also included (in blue - right axis).

The U.S. economy flirted with entering a recession in early 2016, which was reflected in the deteriorating economic, fundamental, and especially market-based data. The diffusion index, slack index, and recession probability forecasts all captured the weakening conditions. However, the weakness proved to be temporary and the conditions and recession model forecasts have improved significantly in the past two years. However, the number of variables indicating a recession increased from one to two out of 21 (9.6%) in June, which is the highest diffusion index reading since the recession scare in 2016.

*median* recession slack index is used in the recession models, I am now including the *mean* recession slack index in the graph as well.

*median* recession slack index is depicted in purple and is plotted against the right axis, which is expressed as the number of standard deviations above the recession threshold. The *mean* recession slack index is depicted in blue and is also plotted against the right axis.

In June 2018, the median recession slack index declined sharply from a revised value of 1.16 to 0.78, while the mean or average recession slack index decreased from a revised value of 1.16 to 0.88. The June mean and median recession slack indices are still above the early warning threshold (0.50), but both readings are the lowest since 2016.

*increasing* slack. Given the diverse nature of the explanatory variables, it is unusual to see more than 60% of the variables with increasing slack or fewer than 40% of the variables with increasing slack. These extreme values are significant and predictive of the near-term direction of economic growth and *often the equity market*.

The 3-month moving average of the percentage of variables with *increasing* slack increased from 39.7% last month to 42.9% in June, but only because of dropping off an abysmally low number of 23.8% from four months ago. In June, only 33.3% of the explanatory variables had increasing slack. The 3-month moving average of the percentage of variables with *increasing* slack has remained below 50% for the past five consecutive months. New evidence of economic weakness (or strength) often shows up first in this timely metric.

The Trader Edge aggregate recession model is the average of four models: the probit and logit models based on the diffusion index and the probit and logit models based on the recession slack index. The aggregate recession model estimates from 1/1/2006 to 7/01/2018 are depicted in Figure 4 below (red line - left vertical axis). The gray shaded regions represent NBER recessions and the blue line reflects the value of the S&P 500 index (right vertical axis). I suggest using a warning threshold of between 20-30% for the aggregate recession model (green horizontal line).

The aggregate recession model probability estimate increased from 0.1% to 0.2% in June. According to the model, the probability that the U.S. is *currently* in a recession continues to be extremely remote.

The aggregate peak-trough model estimates from 1/1/2006 to 7/01/2018 are depicted in Figure 5 below, which uses the same format as Figure 4, except that the shaded regions represent the periods between the peaks and troughs associated with NBER recessions.

The aggregate peak-trough model probability estimate for 7/01/2018 was 12.2%, which more than doubled last month's probability estimate of 5.3%. The aggregate peak-trough probability is still relatively low, but represents the highest peak-trough recession probability since 2016.

U.S. recession risk remains *relatively* low, but the sharp rise in June was surprising. The diffusion index increased, the slack indices dropped sharply, the percentage of variables with increasing slack has been low or very low for five consecutive months, and the peak-trough recession probability more than doubled in June. The magnitude and consistency of the changes in June are troubling, especially given the relative overvaluation of the U.S. equity market. The next few months of model forecasts will be very instructive.

*MarketWatch* article suggests that "*There are only two other times in history when stocks were more expensive than today*." On a related topic, Mark Hulbert's latest *MarketWatch* article demonstrated that the *Russell 2000's current P/E ratio is actually 78.7*, not the more commonly reported value of 25.6.

Based on the most recent data, the regression model indicates that the expected annual price return of the S&P 500 index for the next 10 years is only 1.2%, with an expected drawdown in that period of 32% (from current levels). In other words, the expected price return of the SPX is negligible over the next 10 years, *and* it is likely that an investor would have the opportunity to purchase the SPX at 68% of its current value sometime in the next 10 years. The risk/return trade off for holding periods as short as three years look equally unattractive, albeit with lower correlations.

I completed a similar historical regression analysis using the "Buffett Indicator", which is the ratio of equity market capitalization to GDP. The correlation is not quite as strong, but is still very significant (-0.74). The Buffett Indicator regression model currently indicates that the expected *annual* price return of the S&P 500 index for the *next 10 years* is significantly negative (-2.50%), with an expected drawdown in that 10-year period of over 47% (from current levels).

Overvalued securities can *always* become more overvalued - especially in the near-term. That said, history offers compelling evidence that bullish equity positions today will face significant headwinds over the coming years.

Brian Johnson

Copyright 2018 Trading Insights, LLC. All rights reserved.

]]>*and* historical data in this report reflect the current model configuration with all 21 variables.

The graph of the diffusion index from 1/1/2006 to 6/1/2018 is presented in Figure 1 below (in red - left axis). The gray shaded regions in Figure 1 below represent U.S. recessions as defined (after the fact) by the National Bureau of Economic Research (NBER). The value of the S&P 500 index is also included (in blue - right axis).

The U.S. economy flirted with entering a recession in early 2016, which was reflected in the deteriorating economic, fundamental, and especially market-based data. The diffusion index, slack index, and recession probability forecasts all captured the weakening conditions. However, the weakness proved to be temporary and the conditions and recession model forecasts have improved significantly in the past two years. The number of variables indicating a recession is currently one out of 21 (4.8%), which was unchanged from last month.

*median* recession slack index is used in the recession models, I am now including the *mean* recession slack index in the graph as well.

*median* recession slack index is depicted in purple and is plotted against the right axis, which is expressed as the number of standard deviations above the recession threshold. The *mean* recession slack index is depicted in blue and is also plotted against the right axis.

In May of 2018, the recession slack index increased from a revised value of 1.08 to 1.17, while the mean or average recession slack index increased from a revised value of 1.14 to 1.18. Both the mean and median recession slack indices are still significantly above the early warning threshold (0.50).

*increasing* slack. Given the diverse nature of the explanatory variables, it is unusual to see more than 60% of the variables with increasing slack or fewer than 40% of the variables with increasing slack. These extreme values are significant and predictive of the near-term direction of economic growth and *often the equity market*.

The 3-month moving average of the percentage of variables with *increasing* slack increased from 34.9% last month to 41.3% in May. However, both of these values are unusually low. The 3-month moving average of the percentage of variables with *increasing* slack has remained below 50% for the past four months. New evidence of economic weakness (or strength) often shows up first in this timely metric.

The Trader Edge aggregate recession model is the average of four models: the probit and logit models based on the diffusion index and the probit and logit models based on the recession slack index. The aggregate recession model estimates from 1/1/2006 to 6/01/2018 are depicted in Figure 4 below (red line - left vertical axis). The gray shaded regions represent NBER recessions and the blue line reflects the value of the S&P 500 index (right vertical axis). I suggest using a warning threshold of between 20-30% for the aggregate recession model (green horizontal line).

The aggregate recession model probability estimate remained constant at 0.1% in May. According to the model, the probability that the U.S. is *currently* in a recession continues to be extremely remote.

The peak-trough model forecasts are different from the recession model. The peak-trough models estimate the probability of the S&P 500 being between the peak and trough associated with an NBER recession. The S&P 500 typically peaks before recessions begin and bottoms out before recessions end. As a result, it is far more difficult for the peak-trough model to fit this data and the model forecasts have larger errors than the recession model.

The aggregate peak-trough model estimates from 1/1/2006 to 6/01/2018 are depicted in Figure 5 below, which uses the same format as Figure 4, except that the shaded regions represent the periods between the peaks and troughs associated with NBER recessions.

The aggregate peak-trough model probability estimate for 6/01/2018 was 5.3%, which decreased by 1.7% from last month's revised value of 7.0%. The aggregate peak-trough probability remains low.

U.S. recession risk remains very low. There is very limited evidence of near-term economic weakness in the explanatory variables, although the abnormally low percentage of variables with increasing slack is worth monitoring.

As I have repeatedly emphasized, recessions are not the only source of pullbacks in the equity markets -- as we saw in early February. The U.S. equity market continues to be overvalued and global event risk continues to be elevated. This recent *MarketWatch* article suggests that "*There are only two other times in history when stocks were more expensive than today*." On a related topic, Mark Hulbert's latest *MarketWatch* article demonstrated that the *Russell 2000's current P/E ratio is actually 78.7*, not the more commonly reported value of 25.6.

Based on the most recent data, the regression model indicates that the expected annual price return of the S&P 500 index for the next 10 years is slightly less than zero, with an expected drawdown in that period of 36% (from current levels). In other words, the expected price return of the SPX is 0% per year over the next 10 years, *and* it is likely that an investor would have the opportunity to purchase the SPX at 64% of its current value sometime in the next 10 years. The risk/return trade off for holding periods as short as three years look equally unattractive, albeit with lower correlations.

I completed a similar historical regression analysis using the "Buffett Indicator", which is the ratio of equity market capitalization to GDP. The correlation is not quite as strong, but is still very significant (-0.74). The Buffett Indicator regression model currently indicates that the expected *annual* price return of the S&P 500 index for the *next 10 years* is significantly negative (-4.33%), with an expected drawdown in that 10-year period of over 50% (from current levels).

Overvalued securities can *always* become more overvalued - especially in the near-term. That said, history offers compelling evidence that bullish equity positions today will face significant headwinds over the coming years.

Brian Johnson

Copyright 2018 Trading Insights, LLC. All rights reserved.

]]>*and* historical data in this report reflect the current model configuration with all 21 variables.

The graph of the diffusion index from 1/1/2006 to 5/1/2018 is presented in Figure 1 below (in red - left axis). The gray shaded regions in Figure 1 below represent U.S. recessions as defined (after the fact) by the National Bureau of Economic Research (NBER). The value of the S&P 500 index is also included (in blue - right axis).

The U.S. economy flirted with entering a recession in early 2016, which was reflected in the deteriorating economic, fundamental, and especially market-based data. The diffusion index, slack index, and recession probability forecasts all captured the weakening conditions. However, the weakness proved to be temporary and the conditions and recession model forecasts have improved significantly in the past two years. The number of variables indicating a recession is currently one out of 21 (4.8%), which increased from zero last month.

*median* recession slack index is used in the recession models, I am now including the *mean* recession slack index in the graph as well.

*median* recession slack index is depicted in purple and is plotted against the right axis, which is expressed as the number of standard deviations above the recession threshold. The *mean* recession slack index is depicted in blue and is also plotted against the right axis.

In mid-2014, the revised median recession slack index peaked at 1.27, far above the warning level of 0.50. The recession slack index declined significantly in 2015 and reached a low of 0.32 in February 2016, before rebounding over the next few months. In early 2017, the median recession index peaked at 1.41, but declined in the fall before rebounding at year-end.

In April of 2018, the recession slack index decreased from a revised value of 1.13 to 1.07, while the mean or average recession slack index increased from a revised value of 1.13 to 1.14. Both the mean and median recession slack indices are still significantly above the early warning threshold (0.50).

*increasing* slack. Given the diverse nature of the explanatory variables, it is unusual to see more than 60% of the variables with increasing slack or fewer than 40% of the variables with increasing slack. These extreme values are significant and predictive of the near-term direction of economic growth and *often the equity market*.

The 3-month moving average of the percentage of variables with *increasing* slack dropped from 38.1% to 34.9% in April. Both of these values are unusually low. New evidence of economic weakness (or strength) often shows up first in this timely metric.

The Trader Edge aggregate recession model is the average of four models: the probit and logit models based on the diffusion index and the probit and logit models based on the recession slack index. The aggregate recession model estimates from 1/1/2006 to 5/01/2018 are depicted in Figure 4 below (red line - left vertical axis). The gray shaded regions represent NBER recessions and the blue line reflects the value of the S&P 500 index (right vertical axis). I suggest using a warning threshold of between 20-30% for the aggregate recession model (green horizontal line).

The aggregate recession model probability estimate increased from 0.0% to 0.1% in April. According to the model, the probability that the U.S. is *currently* in a recession continues to be extremely remote.

The peak-trough model forecasts are different from the recession model. The peak-trough models estimate the probability of the S&P 500 being between the peak and trough associated with an NBER recession. The S&P 500 typically peaks before recessions begin and bottoms out before recessions end. As a result, it is far more difficult for the peak-trough model to fit this data and the model forecasts have larger errors than the recession model.

The aggregate peak-trough model estimates from 1/1/2006 to 5/01/2018 are depicted in Figure 5 below, which uses the same format as Figure 4, except that the shaded regions represent the periods between the peaks and troughs associated with NBER recessions.

The aggregate peak-trough model probability estimate for 5/01/2018 was 7.0%, which was up by 3.4% from last month's revised value of 3.6%. While still very low, this was the largest monthly increase in the last 18 months.

U.S. recession risk remains very low. There is very limited evidence of near-term economic weakness in the explanatory variables, although the abnormally low percentage of variables with increasing slack is worth monitoring.

As I have repeatedly emphasized, recessions are not the only source of pullbacks in the equity markets -- as we saw in early February. The U.S. equity market continues to be overvalued and global event risk continues to be elevated. This recent *MarketWatch* article suggests that "*There are only two other times in history when stocks were more expensive than today*." On a related topic, Mark Hulbert's latest *MarketWatch* article demonstrated that the *Russell 2000's current P/E ratio is actually 78.7*, not the more commonly reported value of 25.6.

Based on the most recent data, the regression model indicates that the expected annual price return of the S&P 500 index for the next 10 years is approximately zero, with an expected drawdown in that period of 36% (from current levels). In other words, the expected price return of the SPX is 0% per year over the next 10 years, *and* it is likely that an investor would have the opportunity to purchase the SPX at 64% of its current value sometime in the next 10 years. The risk/return trade off for holding periods as short as three years look equally unattractive, albeit with lower correlations.

I completed a similar historical regression analysis using the "Buffett Indicator", which is the ratio of equity market capitalization to GDP. The correlation is not quite as strong, but is still very significant (-0.74). The Buffett Indicator regression model currently indicates that the expected *annual* price return of the S&P 500 index for the *next 10 years* is significantly negative (-4.62%), with an expected drawdown in that 10-year period of over 50% (from current levels).

*always* become more overvalued - especially in the near-term. That said, history offers compelling evidence that bullish equity positions today will face significant headwinds over the coming years.

Brian Johnson

Copyright 2018 Trading Insights, LLC. All rights reserved.

]]>*and* historical data in this report reflect the current model configuration with all 21 variables.

The graph of the diffusion index from 1/1/2006 to 4/1/2018 is presented in Figure 1 below (in red - left axis). The gray shaded regions in Figure 1 below represent U.S. recessions as defined (after the fact) by the National Bureau of Economic Research (NBER). The value of the S&P 500 index is also included (in blue - right axis).

The U.S. economy flirted with entering a recession in early 2016, which was reflected in the deteriorating economic, fundamental, and especially market-based data. The diffusion index, slack index, and recession probability forecasts all captured the weakening conditions. However, the weakness proved to be temporary and the conditions and recession model forecasts have improved significantly in the past two years. The number of variables indicating a recession is currently zero out of 21 (0.00%), which remained unchanged from last month.

*median* recession slack index is used in the recession models, I am now including the *mean* recession slack index in the graph as well.

*median* recession slack index is depicted in purple and is plotted against the right axis, which is expressed as the number of standard deviations above the recession threshold. The *mean* recession slack index is depicted in blue and is also plotted against the right axis.

In mid-2014, the revised median recession slack index peaked at 1.27, far above the warning level of 0.50. The recession slack index declined significantly in 2015 and reached a low of 0.32 in February 2016, before rebounding over the next few months. In early 2017, the median recession index peaked at 1.41, but declined in the fall before rebounding at year-end.

In March of 2018, the recession slack index increased from 1.17 to 1.27, which is misleading, because the mean or average recession slack index declined from 1.21 to 1.15 in March. Both the mean and median recession slack indices are still significantly above the early warning threshold (0.50).

*increasing* slack. Given the diverse nature of the explanatory variables, it is unusual to see more than 60% of the variables with increasing slack or fewer than 40% of the variables with increasing slack. These extreme values are significant and predictive of the near-term direction of economic growth and *often the equity market*.

The 3-month moving average of the percentage of variables with *increasing* slack dropped from 33.3% to 28.6% in March. Only 28.6% of the variables experienced *increasing* slack in March, which is abnormally low, especially after a similarly poor performance in February. New evidence of economic weakness (or strength) often shows up first in this timely metric.

The Trader Edge aggregate recession model is the average of four models: the probit and logit models based on the diffusion index and the probit and logit models based on the recession slack index. The aggregate recession model estimates from 1/1/2006 to 4/01/2018 are depicted in Figure 4 below (red line - left vertical axis). The gray shaded regions represent NBER recessions and the blue line reflects the value of the S&P 500 index (right vertical axis). I suggest using a warning threshold of between 20-30% for the aggregate recession model (green horizontal line).

The aggregate recession model probability estimate remained constant at 0.0% in March. According to the model, the probability that the U.S. is *currently* in a recession continues to be extremely remote.

The peak-trough model forecasts are different from the recession model. The peak-trough models estimate the probability of the S&P 500 being between the peak and trough associated with an NBER recession. The S&P 500 typically peaks before recessions begin and bottoms out before recessions end. As a result, it is far more difficult for the peak-trough model to fit this data and the model forecasts have larger errors than the recession model.

The aggregate peak-trough model estimates from 1/1/2006 to 4/01/2018 are depicted in Figure 5 below, which uses the same format as Figure 4, except that the shaded regions represent the periods between the peaks and troughs associated with NBER recessions.

The aggregate peak-trough model probability estimate for 4/01/2018 was 3.3%, which was down 0.5% from last month's revised value of 3.8%.

U.S. recession risk remains very low. There is very limited evidence of near-term economic weakness in the explanatory variables, although the abnormally low percentage of variables with increasing slack is worth monitoring.

As I have repeatedly emphasized, recessions are not the only source of pullbacks in the equity markets -- as we saw in early February. The U.S. equity market continues to be overvalued and global event risk continues to be elevated. This recent *MarketWatch* article suggests that "*There are only two other times in history when stocks were more expensive than today*." On a related topic, Mark Hulbert's latest *MarketWatch* article demonstrated that the *Russell 2000's current P/E ratio is actually 78.7*, not the more commonly reported value of 25.6.

Based on the most recent data, the regression model indicates that the expected annual price return of the S&P 500 index for the next 10 years is approximately zero, with an expected drawdown in that period of 35% (from current levels). In other words, the expected price return of the SPX is 0% per year over the next 10 years, *and* it is likely that an investor would have the opportunity to purchase the SPX at 65% of its current value sometime in the next 10 years. The risk/return trade off for holding periods as short as three years look equally unattractive, albeit with lower correlations.

I completed a similar historical regression analysis using the "Buffett Indicator", which is the ratio of equity market capitalization to GDP. The correlation is not quite as strong, but is still very significant (-0.74). The Buffett Indicator regression model currently indicates that the expected *annual* price return of the S&P 500 index for the *next 10 years* is significantly negative (-3.94%), with an expected drawdown in that 10-year period of over 50% (from current levels).

*always* become more overvalued - especially in the near-term. That said, history offers compelling evidence that bullish equity positions today will face significant headwinds over the coming years.

Brian Johnson

Copyright 2018 Trading Insights, LLC. All rights reserved.

]]>*and* historical data in this report reflect the current model configuration with all 21 variables.

The graph of the diffusion index from 1/1/2006 to 3/1/2018 is presented in Figure 1 below (in red - left axis). The gray shaded regions in Figure 1 below represent U.S. recessions as defined (after the fact) by the National Bureau of Economic Research (NBER). The value of the S&P 500 index is also included (in blue - right axis).

The U.S. economy flirted with entering a recession in early 2016, which was reflected in the deteriorating economic, fundamental, and especially market-based data. The diffusion index, slack index, and recession probability forecasts all captured the weakening conditions. However, the weakness proved to be temporary and the conditions and recession model forecasts have improved significantly in the past two years. The number of variables indicating a recession is currently zero out of 21 (0.00%), which remained unchanged from last month.

The Trader Edge recession slack index equals the median standardized deviation of the current value of the explanatory variables from their respective recession thresholds. The resulting value signifies the amount of slack or cushion relative to the recession threshold, expressed in terms of the number of standard deviations. Higher slack values signify larger cushions above recessionary threshold levels.

The gray shaded regions in Figure 2 below represent U.S. recessions as defined (after the fact) by the NBER. The median recession slack index is depicted in purple and is plotted against the right axis, which is expressed as the number of standard deviations above the recession threshold.

In mid-2014, the revised median recession slack index peaked at 1.28, far above the warning level of 0.50. The recession slack index declined significantly in 2015 and reached a low 0.34 in February 2016, before rebounding over the next few months. In early 2017, the median recession index peaked at 1.41, but declined in the fall before rebounding at year-end.

In January of 2018, the recession slack index jumped from 1.16 to 1.37. Unfortunately, the improvement proved to be temporary. In February, the median recession slack index gave up all of its January gains and dropped back to 1.16. While the median recession slack index is still significantly above the early warning threshold (0.50), the one-month decline of 0.21 standard deviations is notable.

*increasing* slack. Given the diverse nature of the explanatory variables, it is unusual to see more than 60% of the variables with increasing slack or fewer than 40% of the variables with increasing slack. These extreme values are significant and predictive of the near-term direction of economic growth and *often the equity market*.

The 3-month moving average of the percentage of variables with *increasing* slack dropped from 50.8% to 44.4% in February. Only 33.3% of the variables experienced *increasing* slack in February, which is abnormally low. New evidence of economic weakness (or strength) often shows up first in this timely metric.

The Trader Edge aggregate recession model is the average of four models: the probit and logit models based on the diffusion index and the probit and logit models based on the recession slack index. The aggregate recession model estimates from 1/1/2006 to 3/01/2018 are depicted in Figure 4 below (red line - left vertical axis). The gray shaded regions represent NBER recessions and the blue line reflects the value of the S&P 500 index (right vertical axis). I suggest using a warning threshold of between 20-30% for the aggregate recession model (green horizontal line).

The aggregate recession model probability estimate remained constant at 0.0% in February. According to the model, the probability that the U.S. is *currently* in a recession continues to be extremely remote.

The aggregate peak-trough model estimates from 1/1/2006 to 3/01/2018 are depicted in Figure 5 below, which uses the same format as Figure 4, except that the shaded regions represent the periods between the peaks and troughs associated with NBER recessions.

The aggregate peak-trough model probability estimate for 3/01/2018 was 3.8%, which was up 0.5% from last month's revised value of 3.3%.

U.S. recession risk remains very low. There is very limited evidence of near-term economic weakness in the explanatory variables, although the magnitude of the one-month decline in the slack index was surprising.

*MarketWatch* article suggests that "*There are only two other times in history when stocks were more expensive than today*." On a related topic, Mark Hulbert's latest *MarketWatch* article demonstrated that the *Russell 2000's current P/E ratio is actually 78.7*, not the more commonly reported value of 25.6.

Based on the most recent data, the regression model indicates that the expected annual price return of the S&P 500 index for the next 10 years is now negative, with an expected drawdown in that period of over 36% (from current levels). In other words, the expected price return of the SPX is less than 0% per year over the next 10 years, *and* it is likely that an investor would have the opportunity to purchase the SPX at 64% of its current value sometime in the next 10 years. The risk/return trade off for holding periods as short as three years look equally unattractive, albeit with lower correlations.

I completed a similar historical regression analysis using the "Buffett Indicator", which is the ratio of equity market capitalization to GDP. The correlation is not quite as strong, but is still very significant (-0.74). The Buffett Indicator regression model currently indicates that the expected *annual* price return of the S&P 500 index for the *next 10 years* is significantly negative (-4.76%), with an expected drawdown in that 10-year period of over 50% (from current levels).

*always* become more overvalued - especially in the near-term. That said, history offers compelling evidence that bullish equity positions today will face significant headwinds over the coming years.

Brian Johnson

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