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Bitcoin's Moving Averages (Lucas Daily, Weekly, & Monthly SMAs)Continuing the series, Lucas Numbers are ultimately derived from phi, the golden ratio. I consider them Fibonacci Multiples because I discovered them by taking the ratio of nonsequential numbers along the Fibonacci Sequence. Using daily, weekly, and monthly closes, I have overlaid the SMAs using Lucas Numbers to determine the number of periods to measure. 2 black 1 orange 3 red 4 pink 7 purple 11 dark blue 18 light blue 29 light green 47 black 76 orange 123 red 199 pink 322 purple 521 dark blue 843 light blue 1364 light green 2207 black 3571 orange It shouldn't be surprising to see Lucas Numbers behave similarly to Fibonacci Sequence moving averages.
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by UbiquitousAngles
Bitcoins Moving Averages (Fibonacci Daily, Weekly, Monthly EMAs)We know what to expect, but we might as well show the chart with Exponential Moving Averages. I begin to wonder if the deviations between close moving averages have any significance. Using daily, weekly, and monthly closes, I have overlaid the EMAs using the Fibonacci Sequence to determine the number of periods to measure. Starting with the 5th number of the Fibonacci Sequence: 5 black 8 orange 13 red 21 pink 34 purple 55 dark blue 89 light blue 144 light green 233 black 377 orange 610 red 987 pink 1597 purple 2584 dark blue 4181 light blue We really don't need to consider multiple time frames, but should remain cognizant that using a shorter period to measure the sets will result in more precision given sequential numbers approach phi, the golden ratio.
BNC:BLX
by UbiquitousAngles
Bitcoins Moving Averages (Fibonacci Daily, Weekly, Monthly SMAs)We have taken a look at Daily, Weekly, & Monthly Moving Averages for commonly used numbers given our base 10 system, and discussed the reason for the discrepancies across time frames. Now we take a look at how moving averages change using the Fibonacci Sequence across multiple time frames. Using daily, weekly, and monthly closes, I have overlaid the SMAs using the Fibonacci Sequence to determine the number of periods to measure. Starting with the 5th number of the Fibonacci Sequence: 5 black 8 orange 13 red 21 pink 34 purple 55 dark blue 89 light blue 144 light green 233 black 377 orange 610 red 987 pink 1597 purple 2584 dark blue 4181 light blue Understanding that the next number in the sequence is related to the previous by a factor of phi, the golden ratio, is it really a surprise that these moving averages trend so closely despite changing the time frame?
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by UbiquitousAngles
Bitcoin's Moving Averages (Common Daily, Weekly, & Monthly SMAs)This is a comparison of Simple Moving Averages (SMAs) for commonly viewed periods using closing data for difference periods. I have overlaid the SMAs for the following sets of periods using Daily, Weekly, and Monthly closes. 10 black 20 orange 50 red 100 pink 200 purple 500 dark blue 1000 light blue 1500 light green 2000 black 2500 orange 3000 red 3500 pink 4000 purple 4500 dark blue ... Is there any significance between the relationship between the 100 day, 100 week, and 100 month SMAs? Are you surprised that the 1500 day and 50 month trend so closely? Can one or a group be more useful than others? A necessary consideration when determining the usefulness of multiple moving averages is how they relate to each other. The relationship of these moving averages are baked into the fact that we use numbers in base 10 for the selected set, where as, the periods used have changed based on our accepted grouping of days and divisions of a solar year.
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by UbiquitousAngles
Bitcoin's Moving Averages (Fibonacci, Weekly)Continuing this series on moving averages, here they are using the Fibonacci Sequence. We have already done this for daily closes and other periods. Using weekly closes, I have overlaid the SMAs and EMAs of commonly used sets. The same color represents the same set of periods while the brighter color is the EMA and the duller color is the SMA. Starting with the 5th number of the Fibonacci Sequence: 5 black 8 orange 13 red 21 pink 34 purple 55 dark blue 89 light blue 144 light green 233 black 377 orange ...
BNC:BLX
by UbiquitousAngles
Bitcoin's Moving Averages (Lucas, Weekly)Moving right along, here are the averages using Lucas Numbers. Refer to past posts for a look at daily closes and other sequences. Using weekly closes, I have overlaid the SMAs and EMAs of commonly used sets. The same color represents the same set of periods while the brighter color is the EMA and the duller color is the SMA. 2 black 1 orange 3 red 4 pink 7 purple 11 dark blue 18 light blue 29 light green 47 black 76 orange 123 red 199 pink 322 purple 521 dark blue ...
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by UbiquitousAngles
Bitcoin's Moving Averages (Common, Weekly)In a previous post, I introduced moving averages and common periods measured using daily closes. Now we look at the same number of periods measured but each period is one week instead of one day. Using weekly closes, I have overlaid the SMAs and EMAs of commonly used sets. The same color represents the same set of periods while the brighter color is the EMA and the duller color is the SMA. 10 black 20 orange 50 red 100 pink 200 purple 500 dark blue (not yet shown) 1000 light blue 1500 light green 2000 black ... Next we will look at the other sets of periods previously using weekly data instead of daily.
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by UbiquitousAngles
Bitcoin halving analysisMany Traders have attempted to to compare previous halving cycles with the current Halving cycle coming up in April this year. considering that there as only been three previous halvings - the first one back in 2012 which does not give us any very useful data or information, so then there’s really only two Halvings that give us any useful information, the last one in 2020, and the one before that. The last having had a significant pullback prior to it occurring. however, the largest part of this dump was actually caused by the Covid worldwide crisis. Therefore, if we look at where bitcoin’s price looked like it would’ve bottomed out it, had the crisis not occurred, We can see that the bottom happened around five months before the halving. Therefore this shows that this cycle is completely different as we have not seen anything like that happened so far. could it be that we have already seen all of the selling/consolidation happening over the last few months as bitcoin has stepped its way up. This is very different what happened in 2020 with so very strong parabolic rise, and then a big sell-off that big parabolic rise has not really happened. This time it’s been a much more of a steady upward growth. Therefore people might be in for a shock when bitcoin just continues to go up. maybe there will be a small dip after the halving - as in what happened in the 2016, halving cycle.
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by The_Mummy
1
BTC Market Cycle | Repetitive and Predictable Market CycleThe Bitcoin market cycle can be easily predicted by studying historical data. Whenever you seek an idea of where the market is heading, you can always look at the past to gauge the future. However, this doesn't guarantee that the predictions stated here will unfold exactly as described; it's a PREDICTION, not a fact. Let's examine the chart displayed here. The market cycle repeats itself every four years, with our chart divided into four cycles, the fourth being the current cycle we are in. Every four years, Bitcoin undergoes a major event known as Halving, where the number of blocks containing Bitcoins is halved every four years. We started with 50 Bitcoins released in a block every 10 minutes; in 2012, that amount was reduced to 25 BTC. In the following cycle, it was halved again, and this will continue to happen every four years until all Bitcoins are mined. Currently, we are heading towards the fourth halving event, which will see the number of blocks released reduced to 3.125 BTC. Due to this event, the price of Bitcoin appreciates in value every four years. This is driven by supply and demand, as fewer Bitcoins are mined than in the previous four years (reduced supply), creating scarcity and increasing demand. The mining difficulty also increases, causing miners to be reluctant to sell the Bitcoins they've mined, contributing to the price increase. On our chart, we have three completed cycles that look almost identical. The cycles consist of a bull market where the price experiences a significant increase, followed by a bear market where the price drops in the range of 80–85%. This is followed by the first expansion, where we see a slight price increase, followed by the first accumulation phase. Prices move up and down within a specified range during this phase, also known as the consolidation phase. We then move on to the second expansion and the second accumulation, usually forming just before or within the halving period. This not only shows us that the market cycles are similar but also allows us to predict future events. At the time of writing this, we are three months away from the fourth halving, and it appears we have entered the second accumulation phase, as seen in the past three cycles. Prices should trade in a specified range for a few months after the halving. When you examine the halving events on the chart, you can observe that we usually enter the bull run somewhere between 6 to 8 months after the halving. Based on that, we can predict that the next bull run will start between October and December 2024, lasting until the fourth quarter of 2025. In the past, the cycles have been accurate, and we can expect the same unless a global catastrophic event occurs, as seen in March 2020 during the COVID-19 pandemic. In that phase, there was no second expansion as all markets crashed. It is my opinion that this led to the bull run not reaching its full potential. Had we experienced the second expansion, the price would have moved slightly higher before the second accumulation phase, leading to an extended bull run pushing the price near or above $100k. My price prediction at the end of the cycle, assuming world events stay normal, is to see Bitcoin in the range of $120–150K. What do you think the price of Bitcoin at the end of 2025 will be? Like, share, and feel free to leave a comment. Let me know if you agree or disagree with this analysis.
BNC:BLXLong
by TeeBusa
68
Benford's Law (The Law of Anomalous Numbers)In a previous post we discussed the significance of price levels. Prior highs and lows are often revisited, sometimes more than once and act as resistance and support. Like a magnet these major and minor highs and lows appear to attract and repel price over time. With this information we drew trendlines creating channels in order to anticipate future price levels. To view a growing price chart over a long period of time is impractical using an Arithmetic scale for price. For the most part, all analysis is done using a Logarithmic scale instead. This allows us to view the percent change uniformly. To understand the drawback of an arithmetic chart, consider how it may look for prices to change from 2 to 10 then 10 to 50. The move from 2 to 10 is only a difference of 8 units, whereas, 10 to 50 is 40 units. The percent change is the same, as is the rate of change assuming the same amount of time eclipsed. Logarithmic charts allow for a better gauge on momentum, but our understanding of numbers as they relate to each other may still be incorrect. The Law of Anomalous Numbers or Benford's Law states that given a data set that does not have built in constraints or parameters to influence the output of data, the leading digit will follow a power law distribution. The larger the data set and orders of magnitude covered, the greater the conformity to this distribution. We may have assumed that the most likely outcome of leading digits in a data set would be uniform, but this would be incorrect.  As a percentage the expected distribution of leading digits using numbers in base 10 is as follows: P(1) = 30.1% P(2) = 17.6% P(3) = 12.5% P(4) = 9.7% P(5) = 7.9% P(6) = 6.7% P(7) = 5.8% P(8) = 5.1% P(9) = 4.6% It should be noted that the shape of this distribution holds regardless of the base of the number system used. Using base 10, the median leading digit of the distribution is 3.16. This means that half of all data points should fall between 1.00 and 3.16 while the other half fall between 3.16 and 9.99. Without this understanding, we might have otherwise expected 5.5 to be the median leading digit as in the case of a uniform distribution. The chart above shows equal spacing between price levels on a logarithmic chart. They can be found by taking the square root of 10 (= 3.16), then taking the square root of 3.16 (= 1.78) then cubing 1.78 (= 5.62). Midpoints play a significant role in my analysis and is the basis for using these numbers. 1.0 black 1.78 light blue 3.16 red 5.62 dark blue This organizes the expected distribution into quarters. Over time the actual distribution of leading digits observed should gravitate towards the distribution of Benford's Law. While I have had my doubts about the validity of using these numbers as price levels, I couldn't keep this to myself given its apparent relevance.
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by UbiquitousAngles
1
Bitcoin's Moving Averages (Lucas Numbers)Lucas Numbers This is the final set of numbers for periods that we'll analyze in this series. In previous posts we discussed the significance of phi, the golden ratio, 0.618 and how Lucas Numbers relate to the Fibonacci Sequence. Using daily closes, I have overlaid the SMAs and EMAs. The same colors represent the same set of periods while the brighter color is the EMA and the duller color is the SMA. 2 black 1 orange 3 red 4 pink 7 purple 11 dark blue 18 light blue 29 light green 47 black 76 orange 123 red 199 pink 322 purple 521 dark blue 843 light blue 1364 light green 2207 black 3571 orange Next we will take a look at the same Moving Averages but using weekly closes instead of daily closes.
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by UbiquitousAngles
Bitcoin's Moving Averages (Fibonacci Sequence)The Fibonacci Sequence In a previous post we discussed phi, the Golden Ratio, 0.618. Adjacent numbers along the Fibonacci Sequence trend toward this ratio. Growth and decay can be witnessed through this proportion. Using daily closes, I have overlaid the SMAs and EMAs. The same colors represent the same set of periods while the brighter color is the EMA and the duller color is the SMA. Starting with the 5th number of the Fibonacci Sequence: 5 black 8 orange 13 red 21 pink 34 purple 55 dark blue 89 light blue 144 light green 233 black 377 orange 610 red 987 pink 1597 purple 2584 dark blue 4181 light blue Next we will take a look at Moving Averages using Lucas Numbers and conclusions will be saved for later.
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by UbiquitousAngles
Bitcoin's Moving Averages (Human Cycle)The Human Cycle In the previous post, we looked at standard or commonly used moving averages due to the simplicity of calculation given our base 10 number system. Now we consider if the cycles we experience as humans on earth provide us insight into the patterns seen on the charts. Using daily closes, I have overlaid the SMAs and EMAs. The same colors represent the same set of periods while the brighter color is the EMA and the duller color is the SMA. 7 black (1 week) 30 orange (1 month) 91 red (1 quarter) 183 pink (half year) 274 purple (3 quarters) 365 dark blue (1 year) 548 light blue (1 and a half years) 730 light green (2 years) 1095 black (3 years) 1461 orange (4 years) 1826 red (5 years) 2191 pink (6 years) 2556 purple (7 years) 2922 dark blue (8 years) 3287 light blue (9 years) 3652 light green (10 years) 4914 black (all available data through 2023) Next we will take a look at Moving Averages using the Fibonacci Sequence and conclusions will be saved for later.
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by UbiquitousAngles
Bitcoin's Moving Averages (Intro with Common)Moving Averages provide us with a dynamic metric to monitor current price in relation to past periods. A Simple Moving Average (SMA) is the average closing price for a set number of periods. An Exponential Moving Average (EMA) weights the most recent closing prices more than the closing prices toward the beginning of the set number of periods. The current price in relation to a moving average provides us with information about what to expect from the market and can often act as resistance and support when approached. The purpose of this post is to introduce moving averages and provide a chart with as much unfiltered information as possible. Conclusions will be drawn another time. Using daily closes, I have overlaid the SMAs and EMAs of commonly used sets. The same colors represent the same set of periods while the brighter color is the EMA and the duller color is the SMA. Since we are accustomed to using numbers in base 10, these are some of the most commonly considered sets: 10 black 20 orange 50 red 100 pink 200 purple 500 dark blue 1000 light blue 1500 light green 2000 black 2500 orange 3000 red 3500 pink 4000 purple 4500 dark blue 5000 light blue (TradingView wouldn't let me add a set any higher than 4999) While we are accustomed to using these numbers, we aren't confined. In a separate post I will overlay both SMAs and EMAs again, but will instead use sets that are more familiar to the cycles we experience as humans on earth, such as, 1 Week, 1 Month, 1 Year, etc. In the posts to follow, I will do the same using the Fibonacci Sequence then once more with Lucas Numbers. Finally, I will do it all again considering Weekly then Monthly closes. Later on we'll draw conclusions on which moving averages consistently appear to have the most relevance and when to expect changes in price given moving average positioning.
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by UbiquitousAngles