Section 3 - Chapter 20 - Basics of Cycle Analysis
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ADVANCED CONCEPTS IN CHARTING - Section 3 - Chapter 20 - Basics of Cycle Analysis
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Section 3 - Chapter 20 - Basics of Cycle Analysis
- 1. Basic of Cycle Analysis CMT LEVEL - I
- 3. Notable Cycles • Kondratieff Wave - A Kondratieff Wave is a long-term economic cycle believed to result from technological innovation and produce a long period of prosperity. This theory was founded by Nikolai D. Kondratieff. • Kondratieff believed that these cycles involved periods of evolution and self- correction. Also known as "Kondratiev waves," "supercycles," "K-waves," "surges" or "long waves.“ • The Juglar cycle is a fixed investment cycle of 7 to 11 years identified in 1862 by Clément Juglar. cycle one can observe oscillations of investments into fixed capital and not just changes in the level of employment of the fixed capital (and respective changes in inventories), as is observed with respect to Kitchin cycles.
- 4. Notable Cycles • KUZNETS CYCLE: A cycle of economic activity lasting between 15 and 20 years that acquired the name of the first economist to study it, Nobel Prize laureate Simon Kuznets. The Kuznets cycle is attributed to investment in housing and building construction and is well know among professionals in the real estate market. • The Presidential Election Cycle Theory is a theory developed by Yale Hirsch that states that U.S. stock markets are weakest in the year following the election of a new U.S. president. According to this theory, after the first year, the market improves until the cycle begins again with the next presidential election. • Kitchin cycle - is a short business cycle of about 40 months discovered in the 1920s by Joseph Kitchin. This cycle is believed to be accounted for by time lags in information movements affecting the decision making of commercial firms.
- 5. Sequences (Non Linear Cycles) Fibonacci and Lucas Natural Squares Spiral Calendar Benner
- 6. Notable Cycles • Fibonacci and Lucas- Leonardo Pisano , also known as Fibonacci discover the natural growth function known as “PHI” 0,1,1,2,3,5,8,13,21,……..etc. • Mathematical Francois Lucas helped to bring attention to another summation series that produces sequences: 0,2,1,3,4,7,11,18,29,…… etc • Keep in mind that these sequences can apply to bars , calendar days , weeks ,months & so forth
- 7. Natural Sequences • A Natural Square is the product of any number multiplied by itself : 1*1 = 1 , 2*2 = 4 , 3*3=9 1,4,9,16,25,36,49….etc. Spiral Calendar – Carolyn identifies that historical pivots within financial markets are sometimes related to non linear cycle: the relationship between Fibonacci and Lucas sequences The Benner Cycle includes: -an 11 year cycle in corn and pig prices with peaks alternating every 5 and 6 years. -cotton prices which moved in a cycle with peaks every 11 years. -a 27 year cycle in pig iron prices with lows every 11, 9, 7 years and peaks in the order 8, 9, 10 years. Samuel Benner was a prosperous farmer who was wiped out financially by the 1873 panic. When he try to discern the causes of fluctuations in markets, he came across a large degree of cyclicality.
- 8. Detrending • Detrending a forecasting model means to remove the effects of accumulating data sets from a trend to show only the absolute changes in values and to allow potential cyclical patterns to be identified. •This is done using regression and other statistical techniques. •Detrending can be utilizes to isolate any cycle but is most commonly employed with seasonal analysis. • Detrending is the act of removing the trend from a time series with the goal of isolating cyclical activity.
- 10. Variables to Consider • First , Statistical outliers damage the result of Detrending , Use a median in place of mean in the calculations to improve Detrending results and reduce the effect of statistical outliers. • Second , be aware that significant changes in price levels over period of time can erroneously influence Detrending results.
- 11. Percentage Change Method • Step 1 – We apply Percentage changes in the monthly mean from previous month in Row no 16 • The Percentage of Months with a positive return is listed in row 17 • Figure 16.7 shows the output from the percentage change method to detrend cash cotton . • The graph on the left plots the monthly percentage changes • The graph on the right shows the seasonal pattern as an index or equity curve
- 15. Moving Average Method • Apply a moving average approach to Detrending the same cash cotton data. • Column F is the mean of Column C & D. • We create 12 month moving average of Column F shown in Column G • Column I is the Average of Two Adjacent CMA’s placed in the time period . • We can detrend the data by subtracting Column F , Resulting in the seasonal Adj Factor in Column J. • The “Seasonal Index” in Column K is the ratio of Column F divided by Column I. • Mean & Median is Calculated in Row 16 & Row 17 in Figure 16.9 • Figure 16.10 shows output of the moving average Detrending method. Mean Calculation on Left & Median Calculations on the right .