Dear Respected Members of the TradingView Community,
I start with some straightforward insights. I've executed significant crypto sales this month. However, my decision was not because of any pre-established forecasts. The motivation behind my decision to part with cryptocurrencies like BTC was primarily due to liquidity challenges. I found it increasingly difficult to execute orders without impacting the market by moving prices, widening spreads, or settling for unfavorable market orders. Often, I had to exercise more patience than desired while waiting for the fulfillment of my limit orders. Eventually, when suitable over-the-counter (OTC) opportunities presented themselves, I decided to divest from these challenging assets. It's important to note that this decision was independent of price predictions.
You can consider various factors beyond price movement for an investment choice. Factors such as trading volume, liquidity, spreads, and transaction fees can add value to your decision-making process. The focus points of this discussion are price forecasts, where trading volume is one of the influential variables.
For those of you who have been tracking the trading volume candles from December 20, 2020, to the present, you may have observed a consistent decline in trading volume. Deep Neural Networks (DNN) tend to associate this declining volume with a waning interest in BTC-USD. While the overall trend for BTC has been bullish since November 14, 2022, DNN suggests that this rising trend could be a retracement within a broader bearish development that began on November 15, 2021. The significance of understanding the trend lies in assessing the risk-reward ratio. Generally, positions aligned with the prevailing trend offer a more favorable risk-reward ratio. An adaptive DNN model can add more than programmed indicators as it can adapt to changing market conditions and provide certainty metrics regarding potential trends.
As per my adaptive DNN analysis, there is a 70% probability that the bearish trend will persist, compared to a 30% probability for a bullish trend. However, market dynamics are influenced by multiple trends, each exerting varying degrees of impact at different times. Fuzzy Logic Trading (FLT) reveals that factors associated with the bearish trend currently hold a 60% influence on BTC-USD, with bullish parameters contributing 40%. Probabilities offer insights into potential future scenarios, while membership degrees provide a more nuanced perspective on the actual forces at play within a given scenario.
At present, the price of Bitcoin is approaching a juncture defined by multiple trendlines that may serve as resistance levels. One of these resistance lines previously served as a support level for local bottoms on January 2, 2023, March 13, 2023, and June 12, 2023. However, since Bitcoin breached this support line, it may have transitioned into a resistance line. It is just one example of a trendline that could act as a barrier, given the broader horizontal resistance zone extending between $38,000 and $32,000.
Another notable resistance line within this zone is the trendline connecting the peaks of the bullish retracement tail on April 10, 2023, July 3, 2023, and the present. These examples illustrate the potential resistance trendlines, with the entire zone representing a supply margin where additional barriers may exist. It's worth noting that bullish trends can possess the strength to break through resistance trendlines or zones, transforming them into support trendlines and demand zones.
While an AI-driven analysis suggests a 30% probability of a continuing bullish trend, the market exhibits a 40% bullish influence from external factors such as news and prominent opinions, as determined by my Natural Language Processing (NLP) algorithm and mathematical tools from FLT. Should the BTC price establish a demand zone and initiate an upward trajectory from the support trendlines, the market could witness new local highs, potentially surmounting at least one of the aforementioned resistance trendlines within the supply zone. While this scenario does not guarantee a parabolic surge, it remains a possibility.
On one hand, optimistic investor sentiment could potentially transform even the sharply rising resistance trendline into a support level, as indicated by the blue forecast in the chart. On the other hand, a 70% probability of a continuing bearish trend, as suggested by dynamic DNN, and a 60% bearish influence per FLT, even in the presence of a bullish trend, implies a degree of caution.
In Finance, the path to profit is often a winding road, with ups and downs that can confound even the most seasoned investors. While many market participants tend to focus on bullish scenarios, it's essential to understand the various stages of a downtrend. Let's explore these phases and gain some insights from artificial intelligence. Every significant downtrend begins with a subtle sign – a warning of what's to come. Unfortunately, this early signal is soft while the bullish sentiment prevails. This initial warning is crucial for astute investors who pay attention to the nuances of the market. As the uptrend falters and inevitably fails, it becomes evident that the market is in a state of decline. This point often lures individuals into considering an all-in strategy, driven by the conviction that "It always goes back up." This misguided belief can lead to significant losses. Following the decline, there's typically a rally, which sometimes recovers a significant percentage from the previous drop. This rally can be deceptive, luring investors believing that a new bullish trend is underway. However, it's crucial to exercise caution and not be swayed solely by short-term gains. Tragically, the anticipated bullish trend often turns out to be a trap, leading to a prolonged and persistent downtrend. This phase can be particularly challenging for investors who have been misled by the allure of the initial rally.
Moreover, artificial intelligence has made significant strides in the field of market analysis. By employing Dimensionality Reduction (DR) techniques, AI can detect potential bearish butterfly patterns on full-timeframe BTC charts available through pricing engines. Additionally, AI has identified the presence of a bearish Head and Shoulders pattern in the yearly timeframe of 2023. It's important to bear in mind that patterns are essentially estimations of probabilities and potential volatility structures. Any pattern can break in either an upward or downward direction, signaling either a bullish or bearish scenario, respectively.
Examining the Relative Strength Index (RSI) and the spread between the price and Exponential Moving Average (EMA) 20 reveals that they currently fall within a historically and statistically oversold range. Additionally, there is a lack of confirmation for breaching any of the aforementioned resistance lines, let alone the supply zone itself.
In summary, a scalping strategy within the supply zone from the upper trendline to the lower boundary, as depicted in the short position on the chart, could be considered. If the bearish trend persists, other strategies may extend this short position beyond the resistance zone, potentially reaching the EMA 200 at around $25,000, where Bitcoin could encounter an underlying demand zone and various support trendlines.
It's essential to remember that trading decisions should not be solely based on price forecasts. The cryptocurrency market is influenced by various factors, and price is just one of them. This is not intended as investment advice. I encourage you to conduct your research and take full responsibility for your funds. Past performance does not guarantee future results.
In conclusion, understanding the stages of a downtrend is vital for any investor seeking to navigate the complexities of financial markets. Additionally, the integration of AI analysis can provide valuable insights, enhancing our ability to make informed decisions in the ever-evolving world of finance. Remember that no prediction is foolproof, and prudent risk management remains essential in the world of investment.
Warm regards,
Ely
I start with some straightforward insights. I've executed significant crypto sales this month. However, my decision was not because of any pre-established forecasts. The motivation behind my decision to part with cryptocurrencies like BTC was primarily due to liquidity challenges. I found it increasingly difficult to execute orders without impacting the market by moving prices, widening spreads, or settling for unfavorable market orders. Often, I had to exercise more patience than desired while waiting for the fulfillment of my limit orders. Eventually, when suitable over-the-counter (OTC) opportunities presented themselves, I decided to divest from these challenging assets. It's important to note that this decision was independent of price predictions.
You can consider various factors beyond price movement for an investment choice. Factors such as trading volume, liquidity, spreads, and transaction fees can add value to your decision-making process. The focus points of this discussion are price forecasts, where trading volume is one of the influential variables.
For those of you who have been tracking the trading volume candles from December 20, 2020, to the present, you may have observed a consistent decline in trading volume. Deep Neural Networks (DNN) tend to associate this declining volume with a waning interest in BTC-USD. While the overall trend for BTC has been bullish since November 14, 2022, DNN suggests that this rising trend could be a retracement within a broader bearish development that began on November 15, 2021. The significance of understanding the trend lies in assessing the risk-reward ratio. Generally, positions aligned with the prevailing trend offer a more favorable risk-reward ratio. An adaptive DNN model can add more than programmed indicators as it can adapt to changing market conditions and provide certainty metrics regarding potential trends.
As per my adaptive DNN analysis, there is a 70% probability that the bearish trend will persist, compared to a 30% probability for a bullish trend. However, market dynamics are influenced by multiple trends, each exerting varying degrees of impact at different times. Fuzzy Logic Trading (FLT) reveals that factors associated with the bearish trend currently hold a 60% influence on BTC-USD, with bullish parameters contributing 40%. Probabilities offer insights into potential future scenarios, while membership degrees provide a more nuanced perspective on the actual forces at play within a given scenario.
At present, the price of Bitcoin is approaching a juncture defined by multiple trendlines that may serve as resistance levels. One of these resistance lines previously served as a support level for local bottoms on January 2, 2023, March 13, 2023, and June 12, 2023. However, since Bitcoin breached this support line, it may have transitioned into a resistance line. It is just one example of a trendline that could act as a barrier, given the broader horizontal resistance zone extending between $38,000 and $32,000.
Another notable resistance line within this zone is the trendline connecting the peaks of the bullish retracement tail on April 10, 2023, July 3, 2023, and the present. These examples illustrate the potential resistance trendlines, with the entire zone representing a supply margin where additional barriers may exist. It's worth noting that bullish trends can possess the strength to break through resistance trendlines or zones, transforming them into support trendlines and demand zones.
While an AI-driven analysis suggests a 30% probability of a continuing bullish trend, the market exhibits a 40% bullish influence from external factors such as news and prominent opinions, as determined by my Natural Language Processing (NLP) algorithm and mathematical tools from FLT. Should the BTC price establish a demand zone and initiate an upward trajectory from the support trendlines, the market could witness new local highs, potentially surmounting at least one of the aforementioned resistance trendlines within the supply zone. While this scenario does not guarantee a parabolic surge, it remains a possibility.
On one hand, optimistic investor sentiment could potentially transform even the sharply rising resistance trendline into a support level, as indicated by the blue forecast in the chart. On the other hand, a 70% probability of a continuing bearish trend, as suggested by dynamic DNN, and a 60% bearish influence per FLT, even in the presence of a bullish trend, implies a degree of caution.
In Finance, the path to profit is often a winding road, with ups and downs that can confound even the most seasoned investors. While many market participants tend to focus on bullish scenarios, it's essential to understand the various stages of a downtrend. Let's explore these phases and gain some insights from artificial intelligence. Every significant downtrend begins with a subtle sign – a warning of what's to come. Unfortunately, this early signal is soft while the bullish sentiment prevails. This initial warning is crucial for astute investors who pay attention to the nuances of the market. As the uptrend falters and inevitably fails, it becomes evident that the market is in a state of decline. This point often lures individuals into considering an all-in strategy, driven by the conviction that "It always goes back up." This misguided belief can lead to significant losses. Following the decline, there's typically a rally, which sometimes recovers a significant percentage from the previous drop. This rally can be deceptive, luring investors believing that a new bullish trend is underway. However, it's crucial to exercise caution and not be swayed solely by short-term gains. Tragically, the anticipated bullish trend often turns out to be a trap, leading to a prolonged and persistent downtrend. This phase can be particularly challenging for investors who have been misled by the allure of the initial rally.
Moreover, artificial intelligence has made significant strides in the field of market analysis. By employing Dimensionality Reduction (DR) techniques, AI can detect potential bearish butterfly patterns on full-timeframe BTC charts available through pricing engines. Additionally, AI has identified the presence of a bearish Head and Shoulders pattern in the yearly timeframe of 2023. It's important to bear in mind that patterns are essentially estimations of probabilities and potential volatility structures. Any pattern can break in either an upward or downward direction, signaling either a bullish or bearish scenario, respectively.
Examining the Relative Strength Index (RSI) and the spread between the price and Exponential Moving Average (EMA) 20 reveals that they currently fall within a historically and statistically oversold range. Additionally, there is a lack of confirmation for breaching any of the aforementioned resistance lines, let alone the supply zone itself.
In summary, a scalping strategy within the supply zone from the upper trendline to the lower boundary, as depicted in the short position on the chart, could be considered. If the bearish trend persists, other strategies may extend this short position beyond the resistance zone, potentially reaching the EMA 200 at around $25,000, where Bitcoin could encounter an underlying demand zone and various support trendlines.
It's essential to remember that trading decisions should not be solely based on price forecasts. The cryptocurrency market is influenced by various factors, and price is just one of them. This is not intended as investment advice. I encourage you to conduct your research and take full responsibility for your funds. Past performance does not guarantee future results.
In conclusion, understanding the stages of a downtrend is vital for any investor seeking to navigate the complexities of financial markets. Additionally, the integration of AI analysis can provide valuable insights, enhancing our ability to make informed decisions in the ever-evolving world of finance. Remember that no prediction is foolproof, and prudent risk management remains essential in the world of investment.
Warm regards,
Ely
Comment:
Although I wrote a tutorial what chart patterns predicted short-term bullish outcomes, I hold my view about BTC's possible bearish future. I believe that these two patterns indicated a local rally:
However, none of them invalidate the indications of this particular chart.
Comment:
Look at the chart! BTC dumped into the short trade on the chart right after placing that position. People always talk about entry prices and target prices, but don't forget to add entry times, target times, and timeouts to your strategy. These are equally important characteristics of a trade.
Comment:
Look at where BTC's standing. The rally happened to halt at the predicted resistance trendline in the estimated supply zone. Could a pullback or bearish reversal being formulated?
Comment:
The bearish pullback from the previous bullish trend has been playing out as AI expected. See the last update about the retracement alert. But how did AI expect this signal? I used a technique called boosting, where I create a vector of AI bots, and every following vector member processes the estimation of the previous one. The bots themselves operate with random forests. You can find public Python libraries for all these algorithms. I used the 3.12 version. If you don't feel bored already, I could contribute with more details.
Comment:
The retracement might be nearing its end. You could ask the question of whether it's a bearish retracement in a bullish trend or a new bearish trend. If it's a new bearish trend, the price would have the potential for further downside. I, however, haven't confirmed the existence of bearish trend signals.
Comment:
It might be prudent to secure short-term profits now and evaluate the likelihood of a sustained bullish trend. While bearish scenarios remain plausible, the current price may not be the most favorable entry point for a short position. Instead of accepting a less favorable risk-reward ratio, consider waiting for a bullish move and revisiting the "short position" near the purple dotted resistance level.