International markets 2018 1Q

The following charts plot the performance of a selection of world markets in the first quarter 2018. 

Domestic currency

International markets 2018 1Q

GBP

The returns are GBP-adjusted (i.e. these are returns for a GB pound investor).

International markets 2018 1Q [GBP]

USD

The returns are USD-adjusted (i.e. these are returns for a US dollar investor).

International markets 2018 1Q [USD]

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Chinese New Year 2018 – year of the dog

This coming Friday, 16 February 2018, will be the start of the Chinese New Year.

The following chart plots the average performance of the S&P 500 Index for each animal year since 1950. For example, Ox years started in 1961, 1973, 1985, 1997, 2009; and the average performance of the market in those (Chinese) years was +14.0%.

NB. The Chinese calendar is based on the lunar year cycle and so performance has been calculated for each lunar year – not the corresponding calendar year.

Chinese calendar and S&P 500 [2018]

The Chinese New Year starting this Saturday will be the Year of the dog!

This is very good news for investors, as since 1950 dog years have the strongest average returns of the S&P 500 Index of any of the Chinese zodiac animals. Over the last 50 or so years the average lunar year return for dog years has been an impressive 16.8%.


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Political leader market returns

The following table shows the stock market returns for political leaders since they came into office. The table is ranked by the final column – the compound annual growth rate of the market returns.

For example, Shinzo Abe has been prime minister of Japan for 62 months, over that time the Nikkei 225 Index has risen 111.2%, which is a CAGR of 15.7%.

 

Political Leader Country In Office (months) Stock Market Return (%) Stock Market CAGR (%)
Michel Temer Brazil 18 41.4 27.2
Donald Trump US 13 18.7 17.7
Shinzo Abe Japan 62 111.2 15.7
Narendra Modi India 45 38.4 9.2
Angela Merkel Germany 149 139.5 7.4
Xi Jinping China 64 41.0 6.8
Lee Nak-yeon South Korea 8 4.5 6.6
Malcolm Turnbull Australia 29 16.2 6.5
Theresa May UK 19 7.1 4.4
Mariano Rajoy Spain 75 17.1 2.6
Vladimir Putin Russia 70 -16.4 -3.1
Emmanuel Macron France 9 -4.5 -6.1

 

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Nikkei 225 performance in January

The following chart plots the month returns of the Nikkei 225 Index in January for the period 1980-2017.

Nikkei 225 performance in January [1980-2017]

In the 40 years from 1950 to 1989, the Nikkei 225 Index only fell in January in 6 years. After that, as can be seen in the above chart, the record became quite a bit more patchy. For example, in the 10 years since 2008, the Index has fallen over 8% in January four times.

Further analysis of the Nikkei 225 Index in January over different time periods can be seen in the following table.

Nikkei 225 in January [1980-2017]

In the 68 years from 1950 to 2017 the Index had an average month return in January of 2.5%, and saw positive returns in 69% of years. But since year 2000 this has dramatically changed (as was also the case of the US and UK markets). Since 2000, the Index has had an average return in January of -1.6%, the worst average return of any month in this period.

The following charts plots the cumulative returns for the 12 respective months since 1980 (for more explanation of this chart see here).

Nikkei 225 Index cumulative returns by month [1980-2017]

The cumulative portfolio for January has been highlighted in the above chart.

The cumulative performance of January peaked in 2001, at which point it was the best performing month in the year. Since 2001, the cumulative performance has dramatically under-performed that of other months.

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S&P 500 performance in January

The following chart plots the month returns of the S&P 500 Index for January for the period 1980-2017.

S&P 500 performance in January [1980-2017]

The characteristic of the market in January seems to have changed around the year 2000.

In the 20 years from 1980 to 1999 the S&P 500 index only fell in 5 years. But in the 18 years since 2000 the index has fallen in 10 years.

Further analysis of the S&P 500 Index in January over different periods can be seen in the following table.

S&P 500 in January [1980-2017]

In the 68 years from 1950 to 2017 the Index had an average month return in January of 0.9%, and saw positive returns in 59% of years. But since year 2000 this has dramatically changed, with an average month return of -1.1% and positive returns seen in only 44% of years.

Since 2000, January has the weakest record of performance for the S$P 500 Index.

The following chart plots the cumulative returns from 1980 for 12 portfolios, where each portfolio invests each year exclusively in just one of the 12 respective months. (and is in cash for the other 12 months of the year).

The best performing month over this period has been April, investing in just the month of April each year would have grown an investment of $100 in 1980 to $179 in 2017.

The worst month has been September (the bottom line in the following chart): a $100 investing just in the month of September would be worth $76 by 2017.

 

S&P 500 Index cumulative returns by month [1980-2017]

The cumulative portfolio for January has been highlighted in the above chart.

It can see that by year 2000, January was the strongest of all the months in the year, but that record changed after 2000. By 2017 the $100 would have grown to 130.

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International markets 2017

The following charts plot the performance of a selection of world markets in  2017.

Domestic currency

International markets 2017 Full Year Return

The following table gives a summary of performance for the fourth quarter, second half and full year in 2017.

International markets 2017 Summary 2

GBP

The following chart plots the GBP-adjusted returns (i.e. these are the returns for a GB pound investor) for the full year 2017.

International markets 2017 Full Year Return [GBP]

USD

The following chart plots the USD-adjusted returns (i.e. these are returns for a US dollar investor) for the full year 2017.

International markets 2017 Full Year Return [USD]

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Trumponomics

The Market Likes Trump

 

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Long-term trend of the Dow Jones Industrial Average

What can the very long term tell us about the trend of the US equity market?

1900-2017

The chart below plots the month-end values of the DJIA (Dow Jones Industrial Average) from 1900 to the present day.

In January 1900 the DJIA had a value of 66 points, and in December 2017 (the time of writing) a value of 24,651.

Long-term trend of DJIA [1900-2017] 01

The above chart may be useful as a visual record of actual values of the DJIA, but it is not very helpful in discerning any underlying trend of the index.

Because the values of the DJIA vary so greatly over the period from 1900, it is more useful to plot them on a semi-log chart, where the Y-axis has a logarithmic scale. This is done in the following chart.

Long-term trend of DJIA [1900-2017] 02

This starts to look more useful.

To this chart we can now add a trendline (as has been done in the chart below).

Long-term trend of DJIA [1900-2017] 03

Regression analysis was used to fit a straight line of best fit to the values of the DJIA.

[Side note: although the trendline in the above chart is a straight line, it is useful to remember that this is an exponential line of best fit because the Y-axis is logarithmic.]

Obviously, the trendline does not perfectly match the DJIA values, but the fit is not bad. R-squared (R2) is a statistical measure of how close the data are to the fitted regression line. In this case the R2 value is 0.93. which is surprisingly high given the supposed nature of random-walk equity prices. 

We can use the equation of the fitted line to calculate trendline values of the DJIA at any time, including the future. The following table gives the calculated trend values for the current day and a few arbitrary dates in the future.

Long-term trend of DJIA - forecast from 1900

The calculated trend value of the DJIA for today (15 December 2017) is 11,941. The current actual level of the DJIA is 24,651, which means the DJIA is currently trading at a 106% premium to its trend value. Or, expressing this another way, the DJIA has to fall 52% to equal it’s long-term trend value.

As already mentioned, the table also calculates future trend values for the DJIA. For example, the DJIA trend value in December 2020 will be 13,928. And by December 2030 the DJIA trend value (23,142) will still be just below the current actual level of the DJIA index.

How much faith can we have in these calculated trendline values?

Well, the above trendline was fitted to DJIA data for the period from 1900 to today. Let’s see how the calculations change if we fit a trendline to DJIA data from 1919, just after the First World War.

1919-2017

So, the following chart is similar to the previous chart, except this time the time range is shorter at 1919-2017.

Long-term trend of DJIA [1919-2017]

By shortening the time range, the line of best fit now has an R2 of 0.94, a slight improvement on that for the previous chart (0.93). This means that we can have slightly more confidence that the DJIA actual values will be close the calculated  trend values.

Visually, we can see that the DJIA has been closer to this trendline in the last few years since the financial crisis in 2008, than the trendline calculated for the period from 1900..

As before, the following table shows the trend values calculated using the equation of the new line of best fit on the DJIA data from 1919.

Long-term trend of DJIA - forecast from 1919

This time the calculated trend value of the DJIA for today (15 December 2017) is 15,129. With the current actual level of the DJIA at 24,651, this means the DJIA is currently trading at a 63% premium to its trend value. Or, alternatively, the DJIA has to fall 39% to equal it’s long-term trend value.

So, first, it would seem that the trendline calculated on data from 1919 gives a closer approximation for today’s actual value of the DJIA than that calculated from 1900.

And, second, it seems that the trendline equations are quite sensitive to the exact time period analysed. In which case, let’s look at another example, this time DJIA data starting from 1946, just after the Second World War.

1946-2017

The following chart is as before, but this time the time range analysed is shorter: 1946-2017.

Long-term trend of DJIA [1946-2017]

The R2 (at 0.95) has again marginally increased for this line of best fit on this shorter period. Which suggests that the calculated trendline better fits the actual DJIA data.

And, visually, we can see that the  DJIA has been even closer to the trendline in the last few years since the financial crisis in 2008 than for the previous two time periods.

Broadly, the DJIA index traded very close to the trend line in the years 1946-1954, then the index traded above the trend. But from 1965 the index traded largely in a sideways pattern, and so by 1969 it crossed over the rising trendline to trade beneath it. Although the great bull market started in 1982, it wasn’t until 1995 that the index moved definitively back above the trendline. The market fell during the dot-com crash, but despite that the DJIA bounced off the trendline and did not fall below it. The index managed to stay above the trendline until the credit crunch in 2008, when the DJIA crashed down through the trendline. By 2011, the index had recovered to the trendline and then traded close to it for a number of years until the start of 2017 when the DJIA grew strongly and diverged from the trendline.

The following table shows the trend values calculated using the equation of the new line of best fit on the DJIA data from 1946.

Long-term trend of DJIA - forecast from 1946

This time the calculated trend value of the DJIA for today (15 December 2017) is 19,396. With the current actual level of the DJIA at 24,651, this means the DJIA is currently trading at a 27% premium to its trend value. Or, alternatively, the DJIA has to fall 21% to equal it’s long-term trend value.

And now, with this new trendline, the calculated trend value will be close to the current level of DJIA by December 2020.

So, the trendline of DJIA data from 1946 is not doing a bad job at estimating the current actual value of the Index.

Finally, let’s look at what happens when we calculate a trendline for the DJIA from 1971 – a somewhat arbitrary date, but chosen as the year that the Bretton Woods system ended and the US dollar became a fiat currency.

1971-2017

The following chart is as before, but this time the time range analysed is shorter: 1971-2017.

Long-term trend of DJIA [1971-2017]

As can be seen, for fairly long periods the DJIA traded close to the calculated trend values. And, for the first time in this analysis, the calculated trendline is currently above the level of the DJIA.

Again, and finally, the following table shows the trend values calculated using the equation of the new line of best fit on the DJIA data from 1971.

Long-term trend of DJIA - forecast from 1971

For this final period, the calculated trend value of the DJIA for today (15 December 2017) is 25,733. With the current actual level of the DJIA at 24,651, this means the DJIA is currently trading at a 4% discount to its trend value.

Summary

The following table summarises the  premiums that the DJIA is currently trading at over its calculated trend value, for the four different time periods.

For example, as a reminder, at the time of writing the DJIA Index is trading at a 106% premium to its trend value as calculated for data from 1900.

Long-term trend of DJIA - summary

So, which trendline do you choose? 

That, of course, is the big question.

If you think that data from the period 1900 to today is representative of the long-term trend of the DJIA Index and, importantly, that this trend is likely to continue, then this is the trendline to choose, with its indication that the DJIA is currently 106% “over-valued”. As such, you will be concerned that the DJIA is currently at risk of a large fall to move back towards its long-term trend value.

Alternatively, if you think that the time period of 1971 to today is more representative of the long-term trend of the DJIA Index, then you will be happy with the current level of the DJIA as it close to its trend value.

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Volatility of markets in 2017

The following chart shows the volatility of various markets so far in 2017.

Volatility In 2017

Not difficult – or surprising – to spot the most volatile market here.

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GBP and USD in 2017 3Q

GBP

The following chart gives the changes in currency rate for the UK pound for the third quarter 2017. For example, the UK pound increased 2.8% against the US Dollar in 3Q 2017.

GBP forex rates 3Q 2017

USD

The following chart gives the changes in currency rate for the US dollar for the third quarter 2017. For example, the US dollar fell 302% against the Euro in 3Q 2017.

USD forex rates 3Q 2017

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