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Secrets of financial market forecasting
Introduction to the modified Hurst nominal model
There has been much debate about the usefulness of cyclical analysis in the financial markets during recent years.Most remain skeptical until a healthy correction begins to unfold in the markets and I speak of the stock market in particular. People temporarily begin to gain interest in cyclical analysis in order to find some way to explain the ‘unexpected’ decline that is unfolding. All is once again forgotten until the next significant correction occurs and the cycle continues. This analytical approach has found better hospitality in the commodity market considering that commodity cycles are more evident and do not experience much high translation and hence they are obvious. The irony is that market speculators and academics accept that the corrections are most likely due to cyclical forces but refuse to accept that the advances are due to the same forces as they continue to believe their obsolete models of fundamentals driving prices rather than mood driving prices. In this short manual I will share with you my discoveries in the field of cyclical analysis in relation to the financial markets. This paper is not meant to be for sale rather it is meant for the few individuals that I believe are worthy of acquiring this knowledge in hope that they use it responsibly.
J.M. Hurst’s work on cyclical analysis interms of the financial markets is certainly one of the most comprehensive explanations in print. I have expanded upon J.M. Hurst’s ideas myself by adding several larger cycles that are longer than the infamous 54 year cycle discovered by Nikolai Konratieff in the 1920s. The new cycles discovered are indeed present in historical prices of stocks and commodities as the principle of commonality would suggest. I also expanded on J.M. Hurst’s work by added a phenomena I call ‘a similar cyclical circumstance’ which looks at cycles within cycles or ‘wheels within wheels’. This new discovery, after some tweaking,allows us to obtain unsmoothed projection lines based on past price history that correlate with the future by over 90 percent. The similar cyclical circumstance phenomena also allows us to forecast with 90% accuracy when fat tails are likely to occur in the market under consideration provided we have enough price history. The similar cyclical circumstance phenomena also answers the long debated and problematic principle of variation which is the sudden change of cycle length relative to the current average period. In fact most ofour forecast will be based on an approximate of the length of the cycle we are attempting to forecast rather than the recent average length of the cycle. This will be looked at in greater depth once we proceed through this manual.
Let us now begin by first stating what the average period of the cycles being studied are. Hurst has presented cycles as short as 5 days to as long as 18 years. I believe he made no mention of the 54year cycle that Nikolai Konratieff discovered which I certainly cannot take credit for. The great thing about cyclical analysis is that the largest cycle in the model is related to its one larger cycle by a factor of two or three hence if one has the data he can easily determine what the larger cycles are based on FLD analysis , VTL analysis and spectral analysis. I believe I can take credit for discovering three larger cycles than the 54 year wave. Those are the 162 year, 324 year and 972 year. If one knows what cycle we are in,taking into context the larger cycles as large as one could go, he will know what lies ahead for the future of nations, wars, economics and markets. An example would be: if we are currently in the second 54 year cycle of the first162 year cycle of the second 324 year cycle of the 972 year cycle. One only needs to find that same cycle in the past to know with extremely high accuracy what lies ahead in terms of prices and events. This is why acquiring the skill of isolating cycles is extremely important to practice this lost, forbidden and mystical art.
The table above is a visual illustration ofthe modified and simplified nominal cyclic model. The largest cycle that I am aware of is the 972 year cycle. I would like to state that these cycles have nothing to do with ‘astrological’ cycle periods. The cause of the cycles is not of interest to us at this current point in time. What we need to be concerned with is the fact that these periods are averages of cycles that are very much present in the price histories of commodities and stocks. What is also worth emphasizing is that these cycles’ presence in the price chart is due to the mood of the public, world, and speculators which are simply reflected in the barometers of social mood which are the stock market or commodity market indexes.
Methodsof cycle isolation
The analytical process begins with the isolation of component cycles of the price history. It is important to note that this process is the most important process in this analytical approach and MUST be done correctly in order to gain accurate results. We will go through this process step by step by isolating the cycles in the Gold market as anexample. It is important to isolate the cycles as far back as the data goes rather than simply on 180 price bars as presented by J.M. Hurst. If variation in cycle length causes confusion, the price history can be dissected into portions in order to aid the cycle isolation process mentioned below. The reason for phasing the entire price history is to be able to use the phenomena of similar cyclical circumstances. If one wants to obtain a projection line of the current 20 week cycle one will have to take its position in context of as many of the larger cycles as the data allows and find this 20 week cycle’s counterpart in the past. This 20 week cycle (could be several rather than only one) found in the price history will be used as our input to obtain a projection line to forecast direction, a model to forecast volatility and price targets based on amplitude ratios.
Steps of cycle isolation
1. Obtaining accurate price data of weekly/daily duration as far back as possible
2. Utilize spectral analysis and wavelet technology in order to find the most prominent cycle that is related to the modified nominal cyclic model
3. Obtain an approximate for the other cycles in the modified nominal cyclic model based on harmonicity
4. Put together the initial cyclic model of the instrument under consideration
5. Begin the isolation process of the larger cycles by starting from a prominent low making sure that the harmonics of the large cycle are present and evident using the harmonic wave tool
6. Step down to the smaller cycles and use their approximate length obtained from spectral analysis to aid in the isolation
7. Make sure the harmonics of the cycles isolated are present utilizing the harmonic wave tool
8. Continue the process till the chart is completed ‘phased’
Phasing example: Gold market
Step1
Obtaining an accurate price history of the Gold market is not challenging. I have obtained my price history from http://stooq.com. This website has a surprisingly large database of historical price data for many commodities, currencies and most global stock indices. I would very much recommend this source since they have data that goes back centuries in some cases. We will look at first look at the weekly chart of Gold followed by the daily plot.
Step2, 3 & 4
The picture above is the spectrum analysis results of a weekly chart of Gold starting from 1971. The most prominent peak in the periodogram has a period of approximates 7.5 years. This periodogram peak corresponds to the nominal 9 year cycle. Here we are given a hint that the cycles are most likely running shorter than average in the prices of Gold. After validating this cycle using the wavelet module we will begin to determine the approximate lengths of the other cycles based on the principle of harmonicity.
The wavelet diagram above confirms our interpretation of the periodogram. since this cycle has been active from the beginning of this time series. Let us now put together what Hurst called the initial cyclic model
Step5, 6, 7 & 8
In the following charts the 18 year, 9year, 54 month and 18 month cycles will be isolated. I have checked the smaller harmonics of the 18 month cycle to make sure the right troughs are selected. I chose not to present such detailed analysis here in order to save time and space. I write this manual assuming that you have acquired the skill of phasing analysis. For more detailed explanation on phasing kindly refer Hurst’s cycles course.
The chart above is a daily plot of the spot price of Gold. The horizontal lines are of the length of the nominal 9 yearcycle which is currently running short at approximately 7.49 years as per the peak in the periodogram. Notice how accurate the cycle length extracted is. All the horizontal lines depicted significant troughs in price. Before arbitrarily labelling the toughs based on this rough estimate we would have to make sure the harmonics are present within the isolated cycles. We know that the nominal 9 year cycle should ideally be divided in two 54 month cycle that should each have three 18 month cycles. Let us now take a look at each cycle individually in order to determine the validity of the potential troughs that were isolated with the aid of the initial cyclic model. Other horizontal lines of the lengths of the other cycles in the initial cyclic model should also be used in order to isolate the subdivisions of the 9 year nominal wave. I enjoy using the harmonic wave tool rather than horizontal lines which are the preferred course for people who are new to phasing analysis
The chart above shows the phasing analysis of the first nominal 9 year wave off the low in 1977. We can see that the 9 year cycle subdivided into two 54 month cycles each of which subdivided into three 18 month cycles. We can now move on to the next cycle.
The second 9 year nominal wave’s subdivisions are quite clear as well. Notice how nicely the second harmonic wave depicts the trough of the first 54 month cycle within this nominal 9 year wave. The first 18 month cycle of the second 54 month cycle is longer than average but is a good fit in context of the larger cycles. It is worth mentioning that the 9 year cycle trough formed a straddle since it was not the extreme low within the cycle, Identifying a straddle is not difficult if one looks at the subdivisions prior to making any conclusions on the location of the trough of a particular cycle. We can now move on to the next cycle.
The chart above shows the first 54 month cycle of the following nominal 9 year wave. Notice how nicely the third harmonic of the harmonic wave tool depicts the troughs of the 18 month waves within this 54 month cycle. Let us now take a look at the bigger picture to see how this 54 month cycle fits in context of the 9 year cycle.
As evident on the chart above, the second harmonic of the harmonic wave tool of the 9 year wave nicely depicts the trough of the 54 month wave. It is worth mentioning that the 9 year cycle trough formed a straddle once again and was not the extreme low within the cycle.
The nominal 9 year wave presented above has subdivided ideally into two 54 month cycles. The trough of the first cycle is exactly at the midpoint of the cycle. Each of the 54 month cycles has subdivided into three nominal 18 month waves.
The final 9 year cycle has the trough of the 54 month cycle exactly at the midpoint of the cycle. The harmonics of the 54 month cycle are ideal where each of the 18 month cycles are almost equal in length. Spectral analysis cycle isolation would have led to profitable trades in this cycle since there was little variation within this 9 year nominal wave.
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