CryptoZeno

Something felt off to me while reading through parts of the @OpenLedger ecosystem yesterday - Not the technology - The incentives.
For years the internet trained people to create publicly and get rewarded through visibility. More views meant more reach, more reach meant more value. Simple system.
But AI quietly broke that relationship. Now valuable knowledge can disappear into models without anyone even noticing when it happened. A niche thread, a technical explanation, a strange dataset, years of pattern recognition from some anonymous person online… suddenly it becomes part of machine behavior somewhere in the background while the original source fades away completely.
That shift feels bigger than people are treating it. The reason $OPEN started standing out to me is because OpenLedger seems strangely focused on restoring economic gravity back to contribution itself instead of only glorifying model performance.
That creates a completely different feeling around participation. The internet today rewards visibility. #OpenLedger feels closer to rewarding usefulness.
That difference sounds small until you really sit with it for a minute. Because if AI keeps expanding the way it currently is, valuable information may stop belonging to the loudest people online and start belonging to the people feeding systems with genuinely effective knowledge underneath the surface.
Weirdly enough, that could create an entirely different type of online economy from the one we’ve been living in for years.

The main benefit of dollar-cost averaging is that it reduces the risk of making a bet at the wrong time. Market timing is among the hardest things to do when it comes to trading or investing. Often, even if the direction of a trade idea is correct, the timing might be off – which makes the entire trade incorrect. Dollar-cost averaging helps mitigate this risk.
If you divide your investment into smaller chunks, you’ll likely have better results than if you were investing the same amount of money in one large chunk. Making a purchase that’s poorly timed is surprisingly easy, and it can lead to less than ideal results. What’s more, you can eliminate some biases from your decision-making. Once you commit to dollar-cost averaging, the strategy will make the decisions for you.
Dollar-cost averaging, of course, doesn’t completely mitigate risk. The idea is only to smooth the entry into the market so that the risk of bad timing is minimized. Dollar-cost averaging absolutely won’t guarantee a successful investment – other factors must be taken into consideration as well.
As we’ve discussed, timing the market is extremely difficult. Even the biggest trading veterans struggle to accurately read the market at times. As such, if you have dollar-cost averaged into a position, you might also need to consider your exit plan. That is, a trading strategy for getting out of the position.
Now, if you’ve determined a target price (or price range), this can be fairly straightforward. You, again, divide up your investment into equal chunks and start selling them once the market is closing in on the target. This way, you can mitigate the risk of not getting out at the right time. However, this is all completely up to your individual trading system.
Some people adopt a “buy and hold” strategy, where the goal is to never sell, as the purchased assets are expected to continually appreciate over time. Take a look at the performance of the Dow Jones Industrial Average in the last century below.
While there are short-term periods of recession, the Dow has been in a continual uptrend. The purpose of a buy and hold strategy is to enter the market and stay in the position long enough so that the timing doesn’t matter.
However, it’s worth keeping in mind that this kind of strategy is usually geared towards the stock market and may not apply to the cryptocurrency markets. Bear in mind that the performance of the Dow is tied to a real-world economy. Other asset classes will perform very differently.
Dollar-cost averaging example
Let’s look at this strategy through an example. Let’s say we’ve got a fixed dollar amount of $10,000, and we think it’s a reasonable bet to invest in Bitcoin. We think that the price will likely range in the current zone, and it’s a favorable place to accumulate and build a position using a DCA strategy.
We could divide the $10,000 up into 100 chunks of $100. Each day, we’re going to buy $100 worth of Bitcoin, no matter the price. This way, we’re going to spread out our entry to a period of about three months.
Now, let’s demonstrate the flexibility of dollar-cost averaging with a different game plan. Let’s say Bitcoin has just entered a bear market, and we don’t expect a prolonged bull trend for at least another two years. But, we do expect a bull trend eventually, and we’d like to prepare in advance.
Should we use the same strategy? Probably not. This investment portfolio has a much larger time horizon. We’d have to be prepared that this $10,000 will be allocated to this strategy for another few years. So, what should we go for?
We could divide the investment into 100 chunks of $100 again. However, this time, we’re going to buy $100 worth of Bitcoin each week. There are more or less 52 weeks in a year, so the entire strategy will be executed in over a little less than two years.
This way, we’ll build up a long-term position while the downtrend runs its course. We’re not going to miss the train when the uptrend starts, and we have also mitigated some of the risks of buying in a downtrend.
But keep in mind that this strategy can be risky – we’d be buying in a downtrend after all. For some investors, it could be better to wait until the end of the downtrend is confirmed before entering. If they wait it out, the average cost (or share price) will probably be higher, but a lot of the downside risk is mitigated in return.
Dollar-cost averaging calculator
You can find a neat dollar-cost averaging calculator for Bitcoin on dcabtc.com. You can specify the amount, the time horizon, the intervals, and get an idea of how different strategies would have performed over time. You’ll find that in the case of Bitcoin, which is in a sustained uptrend over the long-term, the strategy would have been consistently working quite well.
Below, you can see the performance of your investment if you’ve bought just $10 worth of Bitcoin every week for the last five years. $10 a week doesn’t seem that much, doesn’t it? Well, as of April 2020, you would’ve invested in total about $2600, and your stack of bitcoins would be worth about $20,000.
The case against dollar-cost averaging
While dollar-cost averaging can be a lucrative strategy, it does have its skeptics as well. It undoubtedly performs best when the markets experience big swings. This makes sense, as the strategy is designed to mitigate the effects of high volatility on a position.
Dollar-cost averaging is a redeemed strategy for entering into a position while minimizing the effects of market volatility. It involves dividing up the investment into smaller chunks and buying at regular intervals.
The main benefit of this strategy is that it alleviates the need to time the market, which can be challenging. Investors who prefer not to actively monitor the markets can still participate effectively using the DCA method.
However, some skeptics argue that dollar-cost averaging may cause investors to miss out on gains during bull markets. That said, missing out on some gains isn't the end of the world dollar-cost averaging remains a convenient and effective investment strategy for many.
#CryptoZeno #VitalikPledgesLeanerEFFewerETHSales

Trading is more than just numbers it is a three-dimensional fight that rages primarily inside the traders themselves. Missing any crucial element can quickly ruin a trader. The trader must first develop a robust trading system that aligns with their personality and risk tolerance. Then they must trade it consistently, with discipline and faith, through ups and downs. But that’s not all. Risk exposure must also be managed carefully through position sizing and limiting open positions. Risk management has to carry the trader through losing streaks and enable survival, giving the chance to even make it to the winning side.
Here are thirty rules that can help the new trader survive that first year in the trading markets or take the unprofitable trader much closer to profitability.
Trade with the right mindset.
TRADER PSYCHOLOGY
Be flexible and go with the flow of the market's price action; stubbornness, egos, and emotions are the worst indicators for entries and exits.Understand that the trader only chooses their entries, exits, position size, and risk, and the market chooses whether they are profitable or not.You must have a trading plan before you start to trade, which has to be your anchor in decision-making.You have to let go of wanting to always be right about your trade and exchange it for wanting to make money. The first step to making money is to cut a loser short the moment you realize you are wrong.Never trade position sizes so big that your emotions take over from your trading plan."If it feels good, don't do it." – Richard WeissmanTrade your biggest position sizes during winning streaks and your smallest position sizes during losing streaks. Not too big and trade your smallest when in a losing streak.Do not worry about losing money that can be made back; worry about losing your trading discipline.A losing trade costs you money, but letting a big losing trade get too far out of hand can cause you to lose your nerve. Cut losses for the sake of your nerves as much as for the sake of capital preservation.A trader can only go on to success after they have faith in themselves as a trader, their trading system as a winner, and know that they will stay disciplined in their trading journey.
Bring your risk of ruin down to almost zero.
RISK MANAGEMENT
Never enter a trade before you know where you will exit if proven wrong.First, find the right stop loss level that will show you that you're wrong about a trade, then set your position size based on that price level.Focus like a laser on how much capital can be lost on any trade first, before you enter, not on how much profit you could make.Structure your trades through position sizing and stop losses so you never lose more than 1% of your trading capital on one losing trade.Never expose your trading account to more than 5% total risk at any one time.Understand the nature of volatility and adjust your position size for the increased risk with volatility spikes.Never, ever, ever, add to a losing trade. Eventually, that will destroy your trading account when you eventually fight the wrong trend.All your trades should end in one of four ways: a small win, a big win, a small loss, or break even, but never a big loss. If you can eliminate the big losses, you have a great chance of eventually achieving trading success.Be incredibly stubborn in your risk management rules; don't give up an inch. Defense wins championships in sports and profits in trading.Most of the time, trailing stops are more profitable than profit targets. We need the big wins to pay for the losing trades. Trends tend to go farther than anyone anticipates.
Develop a winning trading system that fits your personality.
YOUR TRADING METHOD
"Trade What's Happening...Not What You Think Is Gonna Happen." – Doug GregoryGo long strength; sell weakness short in your time frame.Find your edge over other traders.Your trading system must be built on quantifiable facts, not opinions.Trade the chart, not the news.A robust trading system must either be designed to have a large winning percentage of trades or big wins and small losses.Only take trades that have a skewed risk-to-reward in your favor.The answer to the question, "What's the trend?" is the question, "What's your timeframe?" – Richard Weissman. Trade primarily in the direction that a market is trending in on your time frame until the end, when it bends.Only take real entries that have an edge; avoid being caught up in the meaningless noise.Place your stop losses outside the range of noise so you are only stopped out when you are likely wrong. #CryptoZeno #StablRDepegsAfterAttack

When #Bitcoin was trading at just fifty cents, almost nobody took it seriously. It was a curiosity for cryptographers, libertarians, and a small group of internet idealists. Few could imagine it would one day reshape finance, politics, and power. Even fewer could imagine that one man would build an entire underground economy around it.
That man was Ross Ulbricht.
Today, his story reads less like a crime report and more like a case study in technology, ideology, and unintended consequences. He was given two life sentences, later pardoned, and recently linked to a mysterious transfer of 300 Bitcoin. Whether viewed as a criminal or a pioneer, his impact on crypto history is undeniable.
Ross Ulbricht did not begin his journey as a criminal mastermind. He studied physics and materials science, was deeply interested in economics, and strongly believed that governments exercised far too much control over individual freedom. Bitcoin represented something radical to him: money without permission, value without borders, and trade without centralized oversight.
In 2011, driven by those beliefs, Ross created a website called Silk Road. It was not accessible through normal browsers. Users had to use Tor, a privacy-focused network designed to anonymize traffic. All transactions were conducted exclusively in Bitcoin, and the entire platform was built around anonymity.
Ross vision was a free market without government interference. In his mind, Silk Road was an experiment in economic freedom rather than a criminal enterprise.
The experiment grew far faster than anyone expected. Silk Road attracted more than one hundred thousand users in a short period of time. People bought drugs, fake identification documents, and hacking tools. At one point, a significant portion of all Bitcoin transactions globally flowed through the platform. For many early adopters, Silk Road was their first real exposure to Bitcoin as usable money.
But anonymity is fragile, and ideology does not protect against human error.
Ross operated online under several aliases, the most famous being “Dread Pirate Roberts.” For a long time, his identity remained hidden. Then came a small mistake. He once posted a technical question online using his real email address. That single slip was enough for investigators to begin connecting the dots.
On October 1, 2013, the FBI arrested Ross Ulbricht inside a public library in San Francisco. Agents waited until his laptop was open, then seized it before he could encrypt or lock it. The laptop contained everything. Administrative access to Silk Road, private messages, transaction logs, and access to wallets holding roughly 150 million dollars’ worth of Bitcoin at the time.
In 2015, Ross was convicted on multiple charges, including drug trafficking, money laundering, hacking, and operating a criminal enterprise. The sentence shocked many observers. Two life sentences plus forty years, with no possibility of parole. Even people who believed #SilkRoad was illegal questioned whether the punishment was wildly disproportionate.
The government also seized more than 144,000 Bitcoin from Ross laptop. Those coins were later sold at auction for roughly 334 dollars per Bitcoin, generating about 48 million dollars. Today, those same coins would be worth well over nine billion dollars, making the seizure one of the most expensive mistakes in financial history.
Over time, Ross Ulbricht became more than a prisoner. He became a symbol.
To some, he was a villain who enabled illegal markets. To others, he was a martyr for digital freedom and a warning about state overreach in the age of code. More than half a million people signed petitions calling for a reduced sentence. His name became deeply embedded in crypto culture, representing both its ideals and its risks.
In 2020, rumors began circulating that President Trump might pardon Ross. Figures close to the administration hinted at discussions behind the scenes. The crypto community was hopeful, but the pardon never came. Still, the idea refused to die.
Even in prison, Ross remained active. He wrote essays, created artwork, and continued to engage with the outside world through his family, who managed his social media presence. Over time, his following grew, especially among crypto-native audiences who saw his imprisonment as symbolic.
Then, unexpectedly, everything changed.
In 2025, Ross Ulbricht was suddenly pardoned. Activists, legal advocates, and crypto-friendly political figures had quietly pushed for years. When he re-emerged, he appeared at major crypto events and received standing ovations. Many described it as the return of a legend.
Not long after, another mystery surfaced. One of Ross old $BTC wallets received 300 BTC, worth more than 30 million dollars at the time. The funds were routed through a mixer designed to obscure their origin. No one knows who sent the Bitcoin or why. Speculation exploded, but no definitive answers emerged.
#RossUlbricht story continues to matter because it forces uncomfortable questions into the open. Can technology truly be neutral? Who ultimately controls the internet? How much power should governments have over code, markets, and individual choice? And can a single person, armed with nothing but an idea and software, reshape the world?
Whether you see Ross as a criminal, a pioneer, or something in between, one thing is certain. His story is not finished.
In an era defined by digital surveillance, financial control, and programmable money, the legacy of Silk Road still echoes. And we may not have seen the last of Ross Ulbricht’s influence on crypto and the internet itself.
#CryptoZeno #StablRDepegsAfterAttack #TrumpSaysIranDealLargelyNegotiated

At first I thought the whole thing around @OpenLedger was just another AI infrastructure narrative trying to survive inside a market already overloaded with “future of AI” promises. The space is flooded with polished concepts right now, so honestly I wasn’t expecting much when I started reading deeper into the ecosystem behind $OPEN
Then something small started bothering me. Almost every AI project talks about what the technology can do, but very few feel connected to actual human behavior. Everything sounds efficient, automated, optimized… yet strangely lifeless at the same time.
That feeling kept getting stronger the more I compared it with what OpenLedger is trying to build.
The ecosystem feels heavily shaped around ongoing contribution instead of passive consumption. Vibecoding, attribution systems, specialized datasets, agent coordination… none of these things become meaningful if people only show up temporarily. The entire structure quietly depends on continuous participation from builders, contributors, and niche communities refining things over long periods of time.
That changes the atmosphere completely. While reading through it, I stopped thinking about AI as software for a minute and started thinking about it more like digital culture forming in slow motion. Small groups refining tiny systems. People improving workflows nobody else cares about. Specialized knowledge becoming economically valuable instead of disappearing into the void like it usually does online.
That’s the first time #OpenLedger actually felt interesting to me beyond market narrative. Not because the technology sounds futuristic.
Because it feels built around human persistence instead of temporary excitement, and honestly that might matter far more later than people realize.

Support and resistance are simple concepts. The price finds a level that it’s unable to break through, with this level acting as a barrier of some sort. In the case of support, price finds a “floor,” while in the case of resistance, it finds a “ceiling.” Basically, you could think of support as a zone of demand and resistance as a zone of supply.
While more traditionally, support and resistance are indicated as lines, the real world cases are usually not as precise. Bear in mind; the markets aren’t driven by some physical law that prevents them from breaching a specific level. This is why it may be more beneficial to think of support and resistance as areas. You can think of these areas as ranges on a price chart that will likely drive increased activity from traders.
Let’s look at an example of a support level. Note that the price continually entered an area where the asset was bought up. A support range was formed as the area was retested multiple times. And since the bears (sellers) were unable to push the price further down, it eventually bounced potentially starting a new uptrend.
Now let’s look at a resistance level. As we can see, the price was in a downtrend. But after each bounce, it failed to break through the same area multiple times. The resistance level is formed because the bulls (buyers) were unable to gain control of the market and drive the price higher, causing the downtrend to continue.
How traders can use support and resistance levels
Technical analysts use support and resistance levels to identify areas of interest on a price chart. These are the levels where the likelihood of a reversal or a pause in the underlying trend may be higher.
Market psychology plays a huge part in the formation of support and resistance levels. Traders and investors will remember the price levels that previously saw increased interest and trading activity. Since many traders may be looking at the same levels, these areas might bring increased liquidity. This often makes the support and resistance zones ideal for large traders (or whales) to enter or exit positions.
Support and resistance are key concepts when it comes to exercising proper risk management. The ability to consistently identify these zones can present favorable trading opportunities. Typically, two things can happen once the price reaches an area of support or resistance. It either bounces away from the area or breaks through it and continues in the direction of the trend potentially to the next support or resistance area.
Entering a trade near a level of support or resistance area may be a beneficial strategy. Mainly because of the relatively close invalidation point where we usually place a stop-loss order. If the area is breached and the trade is invalidated, traders can cut their loss and exit with a small loss. In this sense, the further the entry is from the zone of supply or demand, the further the invalidation point is.
Something else to consider is how these levels may react to changing context. As a general rule, a broken area of support may turn into an area of resistance when broken. Conversely, if an area of resistance is broken, it may turn into a support level later, when it’s retested. These patterns are sometimes called a support-resistance flip.
The fact that the previous support zone acts as resistance now (or vice versa) confirms the pattern. As such, the retest of the area may be a favorable place to enter a position.
Another thing to consider is the strength of a support or resistance area. Typically, the more times the price drops and retests a support area, the more likely it is to break to the downside. Similarly, the more times the price increases and retests a resistance area, the more likely it is to break to the upside.
So, we’ve gone through how support and resistance works when it comes to price action. But what other types of support and resistance are out there? Let’s go over a few of them.
Psychological support and resistance
The first type we’ll discuss is called psychological support and resistance. These areas don’t necessarily correlate with any technical pattern but exist because of how the human mind tries to make sense of the world.
In case you haven’t noticed, we live in a staggeringly complex place. As such, we inadvertently try to simplify the world around us so we can make more sense of it and this includes rounding numbers up. Have you ever thought to yourself that you have a craving for 0.7648 of an apple? Or asked a merchant for 13,678,254 grains of rice?
A similar effect is at play in the financial markets. It’s especially true for cryptocurrency trading, which involves easily divisible digital units. Buying an asset at $8.0674 and selling it at $9.9765 just isn’t processed the same as buying it at $8 and selling at $10. This is why round numbers can also act as support or resistance on a price chart.
Well, if only it’d be that simple! This phenomenon has become well-known over the years. As such, some traders might try to “frontrun” obvious psychological support or resistance areas. Frontrunning, in this case, means placing orders just above or below an anticipated support or resistance area.
Take a look at the example below. As the DXY approaches 100, some traders place sell orders just below that level to make sure those orders are filled. Because so many traders expect a reversal at 100 and many frontrun the level, the market never reaches it and reverses just before.
Trend line support and resistance
If you’ve read our classical chart patterns article, you’ll know that patterns will also act as barriers for price. In the example below, an ascending triangle keeps the price contained until the pattern breaks to the upside.
You can use these patterns to your advantage and identify areas of support and resistance that coincide with trend lines. They can be especially useful if you manage to spot them early, before the pattern is fully developed.
Moving average support and resistance
Many indicators may also provide support or resistance when they interact with the price.
One of the most straightforward examples of this are moving averages. As a moving average acts as support or resistance for the price, many traders use it as a barometer for the overall health of the market. Moving averages may also be useful when trying to spot trend reversals or pivot points.
Fibonacci support and resistance
Levels outlined by the Fibonacci retracement tool may also act as support and resistance.
In our example below, the 61.8% Fibonacci level acts as support multiple times, while the 23.6% level acts as resistance.
We’ve discussed what support and resistance are, and some of their different types. But what’s the most effective way to build trading strategies around them?
A key thing to understand is a concept called confluence. Confluence is when a combination of multiple strategies are used together to create one strategy. Support and resistance levels tend to be the strongest when they fall into multiple of these categories that we’ve discussed.
Let’s consider this through two examples. Which potential support zone do you think has a higher chance to actually act as support?
Support 1 coincides with:
a previous resistance areaan important moving averagea 61.8% Fibonacci levela round number in the price
Support 2 coincides with:
a previous resistance areaa round number in the price
If you’ve been paying attention, you’ll correctly guess that Support 1 has a higher chance of holding the price. While this may be true, the price could also fly through it. The point here is that the probability of it acting as support is higher than it is for Support 2. With that said, there are no guarantees when it comes to trading. While trading patterns can be helpful, past performance does not imply future performance, so you should be prepared for all possible outcomes.
Historically, the setups that are confirmed by multiple strategies and indicators tend to provide the best opportunities. Some successful confluence traders might be very picky about what setups they enter and it often involves a lot of waiting. However, when they do enter trades, their setups tend to work out with a high probability.
Even so, it’s always essential to manage risk and protect your capital from unfavorable price movements. Even the strongest looking setups with the best entry points have a chance of going the other way. It’s important to consider the possibility of multiple scenarios, so you don’t fall into false breakouts or bull and bear traps.
#CryptoZeno #BitcoinETFsShed$1.26BInSixDays

Basically, Momentum Oscillator is a technical indicator that measures and showcases the strength or speed of a price movement. The MOM indicator compares the most recent price to a previously determined price and measures the velocity of the price change. Traders choose whether a price momentum is increasing/decreasing to identify entry and exit points.
Despite being the oscillator-type indicator, MOM is unbounded, which means that there are no overbought or oversold levels on the chart to be looking at. That being said, the MOM indicator should be paired with RSI or Stochastic Oscillator to find out the actual asset’s value compared to its true value.
Momentum Indicator Formula
The momentum indicator may be defined as the pace of change in the price of a financial instrument over a given time frame. Essentially, the Momentum Oscillator showcases the difference between two prices: the most recent closing price in relation to a previous closing price from any time range.
MOM Formula: (Current Close/Close N Periods Ago)*100
The default “N” value configurations are set to 10 periods. However, a trader can easily change it in the indicator’s settings tab.
The indicator plots the calculated values on the trading chart as a single line.
In short, if today’s price is the same as it was, say, 10 days ago, the indicator plots its value at the zero line; consequently, if today’s price is higher than it was 10 days ago, the indicator plots above the zero line and vice versa.
Note: Zero line isn’t included in the chart by default. You have to add it yourself.
The MOM indicator oscillates around the zero line, and when it crosses it, some investors might consider this a possible entry or exit signal.
A market where the price changes with large price jumps means the momentum increases and the MOM indicator increases. When the price changes with smaller jumps, the momentum declines, and the MOM indicator starts going down.
How to Read Momentum Indicator?
Let’s not forget that the concept of momentum comes from physics because all the statements below are based on laws and patterns on how objects gain and lose momentum:
If the Momentum Oscillator makes a new high, we expect to see a new high made in price. As traders, we want to buy the next pullback since the price starts gaining upward momentum.We expect lower prices if a new low on the MOM chart is made. As traders, we want to go short on the next price bar since the price starts gaining a downward momentum.If a price makes new lower lows, but the MOM indicator makes higher lows, the market’s downward momentum is weakening- also known as a bullish divergence. As traders, this may be the time to enter the position.If a price makes new lower lows, but the MOM indicator makes higher lows, the market’s downward momentum is getting weaker – it is also known as a bullish divergence. As traders, we might want to enter the position.Imagine you are throwing an object up. Before it falls down to you, its upward momentum slows, and it changes direction. The same rule applies to price – a price trend slows down before it changes direction.
Remember that seeing price momentum increase is a sign, not a guarantee, that the current direction will continue.
Momentum Oscillator Trading Strategy
MOM Strategy #1: Zero Line Crossover
The simplest basic Momentum Indicator trading strategy is watching for when the MOM indicator crosses the Zero Line.
Below is the BTC/USDT chart with a MOM indicator attached:
Seeing a price crossing above Zero Line implies that an asset is gaining an upward momentum and is commonly viewed as a bullish signal.Seeing a price crossing below Zero Line implies that an asset is gaining a downward momentum and is commonly viewed as a bearish signal.
The premise behind this strategy is solely based on the fact that the Zero Line indicates that the price is the same as N periods ago, and the assets’ price rising or falling causes the Momentum Oscillator to cross the Zero Line from below or above accordingly.
But not all crossover points are reliable entry or exit signals. To help reduce the number of false signals, consider making MOM’s period length values higher, examine the overall market trend or apply price patterns.
MOM Strategy #2: Divergence Trading + EMA
The MOM indicator can also assist in detecting divergences on the chart. A divergence occurs when price movement differs from the evolution of the indicator, in our case, the Momentum Oscillator. Similar to other momentum indicators, like Stochastic or RSI oscillators, a divergence in the MOM indicator can hint at a potential price direction change.
There are 2 categories of price divergences: hidden divergence and classic (also known as regular) divergence. In contrast to classic divergence, which detects trend reversal, hidden divergence detects trend continuation.
Here we made a comprehensive cheat sheet that explains the difference between classic and hidden divergence:
Now that we got acquainted with the fundamentals of divergence trading let’s look at the MOM divergence trading example.
Aside from a Momentum Oscillator, we also attached a 200-period EMA to the chart to spot the direction of the long-term market trend.
The basic 200-EMA rule is when the price trades above the 200-period Exponential Moving Average. It is considered an uptrend, implying that we should take a long position. Conversely, when the price is trading below the 200-day Exponential Moving Average, it is considered to be in a downtrend, implying that we should take a short position.
Suppose the price of an asset is trading above the 200-period EMA, suggesting an uptrend. In that case, traders may search for bullish divergence signals (both hidden and regular) on the lower side of the Momentum Oscillator. On the other hand, if the price is trading below the 200-period EMA, suggesting a downtrend, traders should look for bearish divergence signals (both hidden and regular) on the higher side of the Momentum Oscillator.
Our ADA/BNB chart shows that a market is trading in an uptrend, indicating that we should search for bullish divergence patterns. We have 2 MOM divergence signals: one hidden bullish divergence that suggests the continuation of the current trend and one classic bullish divergence.
Remember, if you plan to incorporate Momentum Oscillator into your trading strategy, consider using additional technical indicators and filters to reduce the market noise and avoid overtrading.
Other Popular Momentum Indicators
The class of momentum indicators includes some of the world’s well-known technical indicators, like RSI, MACD, William %R, ADX, and Stochastic RSI. In this section, we are going to cover each of these briefly.
Moving Average Convergence Divergence (MACD)
MACD is truly the most popular trend-following momentum indicator that calculates the difference between two exponential moving averages and plots them on a chart in the form of two lines (MACD line & Signal line) and a histogram. The indicator is mostly used to identify a change in the market trend direction, confirm and identify trading signals, and momentum shifts in the asset’s price.
Relative Strength Index (RSI)
RSI is probably the most beloved momentum indicator among traders from the stock and crypto markets. The indicator oscillates on a scale between 0 and 100. With the help of the Relative Strength Index, traders can spot overbought and oversold market conditions, identify support/resistance levels, potential reversal, etc. Overall, RSI is the second most used trading indicator for a reason.
Stochastic RSI (SRSI)
Stochastic RSI combines two widely recognized technical indicators: RSI and Stochastic. Like the Relative Strength Index, Stochastic RSI helps traders identify overbought and oversold market conditions. SRSI is more sensitive to price fluctuations than the famous RSI indicator. By using RSI values in combination with the Stochastic formula, traders can determine whether the current RSI value is overbought or oversold.
Williams Percent Range (Williams %R)
The Williams Percent Range is another widely recognized momentum indicator that displays where the most recent closing price is in relation to the highest and lowest prices of a specific time period. The Williams %R indicator oscillates between 0 and -100 and measures the strength of a market trend. Like the Stochastic RSI, Williams %R is a more sensitive version of RSI and is ideal for usage in volatile markets.
Average Directional Index (ADX)
Last but not least – the ADX indicator. The Average Directional Index is a momentum-based indicator that was developed to evaluate the strength of a current market trend. The indicator is calculated using a series of directional movement indicators (DMI) which measure the strength and direction of price movements and then plotted as a single line on the chart that ranges from 0 to 100.
As traders, we can confidently state that momentum indicators are an essential tool in any trader’s toolbelt. MOM is a perfect indicator to find out the current trend and direction of the market. It doesn’t matter how good the indicator is. Before making a trade, you should also utilize one or a few other indicators to confirm patterns and signals.
#CryptoZeno #momentum