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  • 63. Comparison of indices DJI, S&P 500, NYSE, NASDAQ and interest rates
  • 62. Predicting the NASDAQ trend from 2016 to 2020 and the S&P 500 from 2017 to 2022
  • 61. Forecasting the NYSE and the DOW Jones Industrial for 2018 to 2022
  • 60. my letters to the prime minister during the 1997 Asian Financial Crisis
  • 59. The way forward
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  • 57. The Calling of the Lord
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  • 42. Banking problems in Malaysia with AmBank
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  • 36. Powerful nontoxic insecticide used in my kitchen for exterminating ants
  • 35. Soybean prices forecast chart 2013 2014 2015 2016
  • 34. Palm Oil price trend prediction 2012 2013 2014
  • 33. NYSE Composite Index prediction of 2015 Bull Run
  • 32. Brent-crude-price-forecast-2012-2013-2014
  • 31. Congratulations-President-Barack-Obama
  • 30. Indian stock exchange nifty index prediction chart
  • 29. Soybean prices commodity chart prediction for day traders and others
  • 28. Huduh is not for malaysia and the errors in huduh
  • 27. My rapeseed commodity chart prediction useful for day traders and others
  • 26. Problems problems and more problems
  • 25. stock chart signals and price action patterns - by Steve Sollheiser
  • 24. Malaysian property prices and the property market
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  • 21. The alternative technical analysis for commodity and stock market analysis
  • 20. Malaysian property price, bubble and crash in 2012
  • 19. The basics of stock market, forex, commodity and financial economy models
  • 18. Gold price and business opportunities
  • 17. US Economic recovery and growth part 4
  • 16. US Economic recovery and growth part 3
  • 15. Gold price forecast trend chart 2011 2012 2013 2014 2015 2016
  • 14. US Economic Recovery and Growth Part 2
  • 13. US Economic Recovery 2009 2010 2011
  • 12. How to predict gold price trend 2011 2015
  • 11. Malaysian property prices and the property bubble
  • 10. Distribution of Wealth Model and Supply and Demand
  • 9. Gold price forecast 2011 2015
  • 8. Explanation of inflation and model of inflation hyperinflation
  • 7. Approximate silver price trend prediction chart june sept 2011
  • 6. how to predict stock and commodity trends
  • 5. Causes of economic crisis recession and high inflation or hyperinflation
  • 4. What is inflation and how to manage inflation
  • 3. Making sound investment decisions
  • 2. forecasting commodity and stock market trends
  • 1. Dr. Peters Loan Calculator
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    « Predicting the NASDAQ trend from 2016 to 2020 and the S&P 500 from 2017 to 2022
    When Gold moves Cash is not King.
    - Dr. Peter Achutha, September 2011
    Books & e-books for sale »


    Comparison of performance between NYSE, DJI, S&P 500 and NASDAQ since 2009

    After publishing my predictions of the S&P 500 and the NASDAQ I looked at performances. In order to compare the performance of these indices I had to normalize them. This meant that I used the price at January 2009 and plotted the ratio of the current price to that of January 2009. For example if the price on January 2009 was 2000 and the price at a later date, say March 2010 was 2200 then that ratio would be 2200/2000 = 1.1. This means that the figure x3.68 in the chart below indicates the final price on December 2017 was 3.68 times the price on January 2009.

    This makes it much easier to compare different indices as shown in the chart below.


    comparision of normalised DJI, S&P 500, NASDAQ, NYSE performance
    comparision of normalised DJI, S&P 500, NASDAQ, NYSE performance
    comparision of normalised DJI, S&P 500, NASDAQ, NYSE performance
    comparision of normalised DJI, S&P 500, NASDAQ, NYSE performance


    NASDAQ gave the best performance during this period

    One would notice that investing in January 2009, close to the bottom of the market, would provide us with an equivalent 10% to 15% return on investment per annum.



    Comparisons of DJI, NYSE, S&P 500 since 1985

    Having done the chart above I decided to look at a longer term performance. That is invest in January 1985 and keep the stock until end of 2017. The chart shows how each of the indices performed.


    comparision of normalised DJI, S&P 500, NYSE performance from 1985
    comparision of normalised DJI, S&P 500, NYSE performance from 1985
    comparision of normalised DJI, S&P 500, NYSE performance from 1985
    comparision of normalised DJI, S&P 500, NYSE performance from 1985


    DJI gave the best performance during this period. The DJI performed at an equivalent of a bank interest rate of 12%. The S&P 500 performed as an equivalent bank interest rate of 11% and the NYSE performed at 10% per annum.



    The American stock indices versus interest rates


    S&P 500 versus interest rates
    S&P 500 versus interest rates
    S&P 500 versus interest rates
    S&P 500 versus interest rates


    I obtained the interest rate data from the St. Louis Fed Reserve - https://fraser.stlouisfed.org/. Let me explain that in order to draw the volume traded curve on the same axis as the S&P 500 index I had divided the volume traded by 50,000,000. This means that the 1000 mark is actually 50,000,000,000 trades.

    I looked at prime interest, S&P 500 price and volume traded trend over the 30 years. It appears that interest rates did not have much impact on the S&P 500 index.

    The initial impression is that high interest rates does dampen the S&P 500 height. When the interest rates were as high as 8% or more the S&P 500 was below 500. This was probably because high interest rates encouraged people to save money instead on risking their savings on stocks and shares. This, I believe, was before the internet existed.

    Looking at the data one can observe that after August / September 2004 the S&P 500 climbed very high even though interest rates were climbing too. This would indicate that interest rates played a minor role in the performance of the S&P 500.

    So I looked at the volume traded figures. It is most likely the internet boom and easy access to trading by many internet brokers and the speculative frenzy in America that caused the S&P 500 to reach historic highs before the crash of 2008. Remember those were the days when everyone was flipping houses, some as many as 5 houses at a time. Many got into 'money making' schemes by trading through internet trading houses. Those who did not know how to trade installed software that automatically trades for them. One of my friends claimed that he was earning 10% per annum with these automatic trading software. The trading volume went up from 100,000 to 1,000,000,000 range prior to 1980 to 30,000,000,000 after 2014 and peaked at 160,000,000,000 in 2009. This shows that after 2004 there was a huge demand for shares. This enormous demand would have made shares prices climb without any inhibitions.

    Personally I doubt that raising interest rates would make the S&P 500 drop as the demand for shares is extremely high. Just image that if each trade was taxed by US$0.01/- (1 cent) the countries debt could be paid off within a year? The excess funds could be used to provide free health care for all and a new air force.

    This article was researched and written by Dr. Peter Achutha, 10th February 2018

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