Value
Bitcoin's market cap is now nearly 2x TeslaThis chart caught my attention. I had to write about it. I am not sure what it means, but in terms of market risk, tech, and what assets have the mainstream's attention, I did not expect Tesla to underperform as much as it has.
Both Bitcoin and Tesla are remarkable assets in their own right, yet the recent divergence in their valuations is striking.
This divergence raises intriguing questions about how the market is pricing specific assets or favoriting for the long run. Will Bitcoin continue to outpace traditional high-growth stocks like Tesla? Are growth stocks now value stocks? Has Bitcoin become the new large cap player?
I'll be watching these two closely, but specifically Tesla, as it does strike me as a potential dip buy.
Cisco Systems (CSCO) 31% margin of safety NOW!!!Cisco Systems Inc. (NASDAQ: CSCO) is a global technology leader that designs, manufactures, and sells networking equipment, software, and services. The company operates in four primary segments: Infrastructure Platforms, Applications, Security, and Other.
Price Analysis
Based on a 5.5% discount rate and a 10-year average growth rate of 3.83%, our DCF model suggests that Cisco Systems Inc. (NASDAQ: CSCO) has an intrinsic value of approximately $70.25. With the current market price of $48.06, there appears to be a 31% margin of safety, indicating that the stock may be undervalued.
It appears that Cisco's Earnings Yield, which is a measure of how much profit a company is generating relative to its stock price, is currently 6.84%. This is higher than the current US Dollar fixed deposit rate of 5.5%. This indicates that, from a relative perspective, Cisco is offering a higher return on investment compared to a fixed deposit in US Dollars.
Quality Analysis
Cisco's operating margin of 27.25% (black line) is indeed significantly higher than the average operating margin of its competitors, which stands at 13.74% (red line). This indicates that Cisco is more efficient in generating profits from its operations compared to its competitors, which could be a positive sign for potential investors.
Cisco's ROE of 29.99% (black line) is indeed higher than the average ROE of its competitors, which stands at 23.86% (red line). This indicates that Cisco is generating a higher return on shareholders' equity compared to its competitors.
Cisco Systems Inc. (NASDAQ: CSCO) exhibits a Free Cash Flow Margin of 33.40% (black line), which surpasses the average Free Cash Flow Margin of its competitors, standing at 15.49% (red line). This distinction underscores Cisco's superior ability to convert its revenue into free cash flow, signifying operational efficiency and robust cash generation relative to its peers.
Free Cash Flow Margin, a pivotal metric, delineates a company's capability to produce cash from its operations after accounting for capital expenditures. Cisco's notable performance in this area suggests a prudent allocation of resources, efficient management of working capital, and a focus on capital expenditure optimization.
Competitive Landscape
Cisco faces competition from both traditional networking players and newer entrants in the market. However, Cisco's strong brand reputation, extensive product portfolio, and global reach give it a competitive advantage in the market.
The stock appears to be undervalued based on current market prices and offers a higher return on investment compared to fixed deposit rates. However, investors should carefully consider the risks before making any investment decisions.
Remember Expensify!? I remember when this company had a Super Bowl commercial. I remember its IPO. I am also familiar with its platform, which I still use to this day and was surprised to see how far its fallen.
Can it ever make a come back?
A few things stand out to me:
The company has cleared its debt, a significant move that shifts its financial landscape from leveraged to liquidity-rich. With its balance sheet now boasting only cash, earning steady interest from 5% treasuries and CDs. Furthermore, the company still has an active $41 million stock buyback program that has not used. What are they waiting for?
Financially, Expensify projects a free cash flow (FCF) of $10-12 million this year. When you consider the current market price, the stock is trading at roughly 10 times its FCF, significantly lower than the industry standard for tech companies, which often hovers around 30 times FCF.
Decisions, decisions!
Always do your own research. Some of my trades are great, others are bad! This one has my attention.
Analyzing the FaZe-Gamesquare Merger: A Potential OpportunityIn the dynamic world of stock trading, the recent discussion of a merger between FaZe Holdings and Gamesquare has stirred considerable interest. As of now, FaZe's current trading price stands at a modest $0.18, while Gamesquare boasts a more robust $1.52.
This valuation difference opens the door to intriguing possibilities for FaZe Holdings investors. The considerable gap in trading prices suggests potential room for movement in FaZe's stock. Savvy traders might see this as an opportunity to capitalize on potential future developments arising from the merger.
However, it's essential for investors to approach this with caution, considering various factors such as market trends, the impact of the merger on FaZe's business model, and broader industry dynamics. While the price differential is noteworthy, thorough analysis and a comprehensive understanding of the market landscape will be key in making informed investment decisions.
XAUUSD, Short Term Investment, DowTheoryGold continues to exhibit a bearish trend in the short and mid-term timeframes while maintaining a neutral stance in the long term. The Dow Theory is continuing its trajectory. Relative Strength Index (RSI) readings indicate overbought conditions in the short and mid periods. Bearish sentiment prevails in the market. Bearish Engulfing encountered on 1H & 4H. Dollar on other end shows more Hawkish tune last week than expected. Our recommendation entails identifying four trading opportunities suitable for scalpers and day traders, emphasizing a bearish outlook.
NXU & Lynx: Could we see a merge/acquisition in the future?Nxu's Strategic Partnership with Lynx Motors
Nxu, Inc. (NASDAQ: NXU), a company specializing in innovative EV charging and energy storage solutions, has announced a strategic partnership and investment in Lynx Motors. This partnership is outlined in a letter of intent (LOI) and represents a significant step in Nxu's commitment to electrification and the future of electric vehicles (EVs).
Key Details of the Partnership
Strategic Investment: Nxu's investment in Lynx Motors is structured as a share exchange, with $3 million in Nxu shares being exchanged for $3 million in Lynx shares. This investment will be reflected as an asset on Nxu's balance sheet.
Board Representation: As part of the transaction, Nxu will receive a seat on Lynx's Board of Directors, indicating a deep level of involvement and influence in Lynx's strategic direction.
Collaborative Development: Nxu aims to assist Lynx in leveraging its vehicle and charging technology to expedite the development of electrified products. Lynx Motors is known for reimagining classic vehicles with modern amenities and powertrains, blending tradition with innovation.
Financial Support: Lynx will issue an interest-free promissory note of $250,000 to Nxu in exchange for a $250,000 bridge loan, further solidifying the financial collaboration between the two companies.
Professional Analysis
Complementary Strengths: This partnership leverages Nxu's expertise in EV charging and energy storage with Lynx's focus on electrifying classic vehicles. It's a strategic alignment that combines technological innovation with a unique market niche.
Market Positioning: Lynx's approach to electrifying popular classic cars, coupled with its robust reservation list, suggests strong market demand. Nxu's involvement could accelerate Lynx's path to significant revenue and profitability.
Impact on Nxu's Market Compliance: The partnership is a step towards Nxu's compliance with Nasdaq's listing standards, potentially increasing shareholder equity and market confidence.
Future Prospects: The collaboration between Nxu and Lynx, especially in the realm of EVs, aligns with the broader trend towards electrification in the automotive industry. This partnership could position both companies favorably in a rapidly evolving market.
Conclusion
The strategic partnership between Nxu and Lynx Motors represents a synergistic collaboration that could enhance both companies' positions in the EV market. By combining Nxu's charging technology with Lynx's innovative approach to vehicle electrification, this partnership holds the potential for significant advancements in the EV sector, offering promising prospects for both companies and their stakeholders.
BOIL is starting to get hot ( 3X Natural Gas ETF)as shown on the 15 minute chart is rising in an ascending parallel channel and is suitable
for a long buy entry when the indicators are triggered. The onslaught of winter cold, the
sanctions against Russian gas exports and inflationary pressure on commodities all bode well
for the trend up for natural gas on forex and equities markets. See also my idea linked below
for a view of the chart from the 4H time frame.
Bitcoin's upper price limit will exceed $190K in 2025.In my long-term strategy, I have deeply explored the key factors influencing the price of Bitcoin. By precisely calculating the correlation between these factors and the price of Bitcoin, I found that they are closely linked to the value of Bitcoin. To more effectively predict the fair price of Bitcoin, I have built a predictive model .
Based on historical experience, the limit value of price deviation has been determined, and the upper and lower limits of the price have been calculated. Observing the price of Bitcoin and the price upper and lower limits can guide trading. According to current data, calculate the upper limit of Bitcoin price in 2025.
Historical simulations prove that, the prediction results of this model correspond quite high with actual values, fully demonstrating its reliability in predicting price fluctuations.
When the future is uncertain and the outlook is unclear, people often choose to hold back and avoid risks, or even abandon their original plans. However, the prediction of Bitcoin is full of challenges, but I have taken the first step in exploring.
📖 Table of contents:
🏃 Step 1: Identify the factors that have the greatest impact on Bitcoin price
🏃 Step 2: Build a Bitcoin price prediction model
🏃 Step 3: Find indicators for warning of bear market bottoms and bull market tops
🏃 Step 4: Predict Bitcoin Price in 2025
🏃 Step 5: Verify the performance of indicators for warning
🏃 Step 1: Identify the factors that have the greatest impact on Bitcoin price
📖 Correlation Coefficient: A mathematical concept for measuring influence
In order to predict the price trend of Bitcoin, we need to delve into the factors that have the greatest impact on its price. These factors or variables can be expressed in mathematical or statistical correlation coefficients. The correlation coefficient is an indicator of the degree of association between two variables, ranging from -1 to 1. A value of 1 indicates a perfect positive correlation, while a value of -1 indicates a perfect negative correlation.
For example, if the price of corn rises, the price of live pigs usually rises accordingly, because corn is the main feed source for pig breeding. In this case, the correlation coefficient between corn and live pig prices is approximately 0.3. This means that corn is a factor affecting the price of live pigs. On the other hand, if a shooter's performance improves while another shooter's performance deteriorates due to increased psychological pressure, we can say that the former is a factor affecting the latter's performance.
Therefore, in order to identify the factors that have the greatest impact on the price of Bitcoin, we need to find the factors with the highest correlation coefficients with the price of Bitcoin. If, through the analysis of the correlation between the price of Bitcoin and the data on the chain, we find that a certain data factor on the chain has the highest correlation coefficient with the price of Bitcoin, then this data factor on the chain can be identified as the factor that has the greatest impact on the price of Bitcoin. Through calculation, we found that the 🔵 number of Bitcoin blocks is one of the factors that has the greatest impact on the price of Bitcoin. From historical data, it can be clearly seen that the growth rate of the 🔵 number of Bitcoin blocks is basically consistent with the movement direction of the price of Bitcoin. By analyzing the past ten years of data, we obtained a daily correlation coefficient of 0.93 between the number of Bitcoin blocks and the price of Bitcoin.
🏃 Step 2: Build a Bitcoin price prediction model
📖 Predictive Model: What formula is used to predict the price of Bitcoin?
Among various prediction models, the linear function is the preferred model due to its high accuracy. Take the standard weight as an example, its linear function graph is a straight line, which is why we choose the linear function model. However, the growth rate of the price of Bitcoin and the number of blocks is extremely fast, which does not conform to the characteristics of the linear function. Therefore, in order to make them more in line with the characteristics of the linear function, we first take the logarithm of both. By observing the logarithmic graph of the price of Bitcoin and the number of blocks, we can find that after the logarithm transformation, the two are more in line with the characteristics of the linear function. Based on this feature, we choose the linear regression model to establish the prediction model.
From the graph below, we can see that the actual red and green K-line fluctuates around the predicted blue and 🟢 green line. These predicted values are based on fundamental factors of Bitcoin, which support its value and reflect its reasonable value. This picture is consistent with the theory proposed by Karl Marx in "Capital" that "prices fluctuate around values."
The predicted logarithm of the market cap of Bitcoin is calculated through the model. The specific calculation formula of the Bitcoin price prediction value is as follows:
btc_predicted_marketcap = math.exp(btc_predicted_marketcap_log)
btc_predicted_price = btc_predicted_marketcap / btc_supply
🏃 Step 3: Find indicators for early warning of bear market bottoms and bull market tops
📖 Warning Indicator: How to Determine Whether the Bitcoin Price has Reached the Bear Market Bottom or the Bull Market Top?
By observing the Bitcoin price logarithmic prediction chart mentioned above, we notice that the actual price often falls below the predicted value at the bottom of a bear market; during the peak of a bull market, the actual price exceeds the predicted price. This pattern indicates that the deviation between the actual price and the predicted price can serve as an early warning signal. When the 🟠 Bitcoin price deviation is very low, as shown by the chart with 🟩 green background, it usually means that we are at the bottom of the bear market; Conversely, when the 🟠 Bitcoin price deviation is very high, the chart with a 🟥 red background indicates that we are at the peak of the bull market.
This pattern has been validated through six bull and bear markets, and the deviation value indeed serves as an early warning signal, which can be used as an important reference for us to judge market trends.
The calculation formula for the price deviation of Bitcoin is as follows:
btc_price_bias = btc_marketcap_log - btc_predicted_marketcap_log
Specifically, we can find the rule by watching the Bitcoin price log and the Bitcoin price deviation chart. For example, on August 25, 2015, the 🔴Bitcoin price deviation was at its lowest value of -1.11; on December 17, 2017, the
🔴Bitcoin price deviation was at its highest value at the time, 1.69; on March 16, 2020, the
🔴Bitcoin price deviation was at its lowest value at the time, -0.91; on March 13, 2021, the
🔴Bitcoin price deviation was at its highest value at the time, 1.1; on December 31, 2022, the
🔴Bitcoin price deviation was at its lowest value at the time, -1.
For conservative reasons, we set the lower limit value of the Bitcoin price deviation warning indicator to the larger of the three lowest values, -0.9, and the upper limit value to the smaller of the two highest values, 1.
When we add the upper and lower limit values of the Bitcoin price deviation to the forecast price, we obtain the 🟠 upper limit and 🟤 lower limit of the price. This can intuitively guide trading. When the Bitcoin price is below the price lower limit, buy. When the Bitcoin price is above the price upper limit, sell.
The calculation formula for the upper and lower limits of the price is as follows:
btc_price_upper_limit = math.exp(btc_predicted_price_log + btc_price_bias_upper_limit)
btc_price_lower_limit = math.exp(btc_predicted_price_log + btc_price_bias_lower_limit)
🏃 Step 4: Predict Bitcoin Price in 2025
According to the data calculated on February 25, 2024, the upper limit of the Bitcoin price is $194,287, which is the price ceiling of this bull market. The peak of the last bull market was on November 9, 2021, at $68,664. The bull-bear market cycle is 4 years, so the highest point of this bull market is expected in 2025, and the upper limit of the Bitcoin price will exceed $190,000. The closing price of Bitcoin on February 25, 2024, was $51,729, with an expected increase of 2.7 times.
🏃 Step 5: Verify the performance of indicators for warning
📖 Model accuracy validation: How to judge the accuracy of the Bitcoin price model?
The accuracy of the model is represented by the coefficient of determination R square, which reflects the degree of match between the predicted value and the actual value. I divided all the historical data from August 18, 2015 into two groups, and used the data from August 18, 2011 to August 18, 2015 as training data to generate the model. The calculation result shows that the coefficient of determination R squared during the 2011-2015 training period is as high as 0.81, which shows that the accuracy of this model is quite high. From the Bitcoin price logarithmic prediction chart in the figure below, we can see that the deviation between the predicted value and the actual value is not far, which means that most of the predicted values can explain the actual value well.
The calculation formula for the coefficient of determination R square is as follows:
residual = btc_close_log - btc_predicted_price_log
residual_square = residual * residual
train_residual_square_sum = math.sum(residual_square, train_days)
train_mse = train_residual_square_sum / train_days
train_r2 = 1 - train_mse / ta.variance(btc_close_log, train_days)
📖 Model reliability verification: How to affirm the reliability of the Bitcoin price model when new data is available?
Model reliability is achieved through model verification. I set the last day of the training period to February 2, 2024 as the "verification group" and used it as verification data to verify the reliability of the model. This means that after generating the model if there is new data, I will use these new data together with the model for prediction, and then evaluate the accuracy of the model. If the coefficient of determination when using verification data is close to the previous training one and both remain at a high level, then we can consider this model as reliable. The coefficient of determination calculated from the validation period data and model prediction results is as high as 0.83, which is close to the previous 0.81, further proving the reliability of this model.
📖 Strategy: When to buy or sell, and how many to choose?
We introduce the Bitcoin 5A strategy. This strategy requires us to generate trading signals based on the critical values of the warning indicators, simulate the trades, and collect performance data for evaluation. In the Bitcoin 5A strategy, there are three key parameters: buying warning indicator, batch trading days, and selling warning indicator. Batch trading days are set to ensure that we can make purchases in batches after the trading signal is sent, thus buying at a lower price, selling at a higher price, and reducing the trading impact cost.
In order to find the optimal warning indicator critical value and batch trading days, we need to adjust these parameters repeatedly and perform backtesting. Backtesting is a method established by observing historical data, which can help us better understand market trends and trading opportunities.
When the warning indicator Bitcoin price deviation is below -0.9, that is, when the Bitcoin price is lower than the lower price limit, buy. When it is higher than 1, that is, when the Bitcoin price is higher than the upper price limit, sell.
In addition, we set the batch trading days as 25 days to implement a strategy that averages purchases and sales. Within these 25 days, we will invest all funds into the market evenly, buying once a day. At the same time, we also sell positions at the same pace, selling once a day.
📖 Adjusting the threshold: a key step to optimizing trading strategy
Adjusting the threshold is an indispensable step for better performance. Here are some suggestions for adjusting the batch trading days and critical values of warning indicators:
- Batch trading days: Try different days like 25 to see how it affects overall performance.
- Buy and sell critical values for warning indicators: iteratively fine-tune the buy threshold value of -0.9 and the sell threshold value of 1 exhaustively to find the best combination of threshold values.
Through such careful adjustments, we may find an optimized approach with a lower maximum drawdown rate (e.g., 11%) and a higher cumulative return rate for closed trades (e.g., 474 times). The chart below is a backtest optimization chart for the Bitcoin 5A strategy, providing an intuitive display of strategy adjustments and optimizations.
In this way, we can better grasp market trends and trading opportunities, thereby achieving a more robust and efficient trading strategy.
📖 Performance evaluation: How to accurately evaluate historical backtesting results?
After detailed strategy testing, to ensure the accuracy and reliability of the results, we need to carry out a detailed performance evaluation on the backtest results. The key evaluation indices include:
- Net value curve: As shown in the rose line, it intuitively reflects the growth of the account net value. By observing the net value curve, we can understand the overall performance and profitability of the strategy.
The basic attributes of this strategy are as follows:
Trading range: 2015-8-19—2024-2-18, backtest range: 2011-8-18—2024-2-18
Initial capital: 1000USD, order size: 1 contract, pyramid: 50 orders, commission rate: 0.2%, slippage: 20 markers.
In the strategy tester overview chart, we also obtained the following key data:
- Net profit rate of closed trades: as high as 474 times, far exceeding the benchmark, as shown in the strategy tester performance summary chart, Bitcoin buys and holds 210 times.
- Number of closed trades and winning percentage: 100 trades were all profitable, showing the stability and reliability of the strategy.
- Drawdown rate & win-loose ratio: The maximum drawdown rate is only 11%, far lower than Bitcoin's 78%. Profit factor, or win-loose ratio, reached 500, further proving the advantage of the strategy.
Through these detailed evaluations, we can see clearly the excellent balance between risk and return of the Bitcoin 5A strategy.
CleanSpark Major Potential CleanSpark Inc - NASDAQ:CLSK
This is a unique mid tier BTC miner that is edging ahead of Cipher Mining in terms of size, production and reserves held (See below for the pecking order of 4 BTC miners).
The CLSK Trade
- Ideal entry would be bounce off 200 DSMA
- Risk/Reward from here is 5.55 which is not bad
- Stop Loss placement at 200 DSMA or POC
Chart Positives
- High Volume is ideal signifying increased interest
,float and momentum
- Price above POC
- Price above 200 DSMA
- Pennant price congestion reaching its decision
point
The Pecking Order for BTC Miners covered to date
1. Marathon Digital NASDAQ:MARA have 156,600 rigs & mined 825 BTC in Mar 2023 (12,964 BTC Reserves)
2. Riot Platforms NASDAQ:RIOT have 95,904 rigs and mined 592 Bitcoin in June 2023 (6,696 BTC reserves)
2. Clearspark NASDAQ:CLSK have 87,936 rigs and mined 575 Bitcoin in July 2023 (1,061 BTC reserves)
3. Cipher Mining NASDAQ:CIFR have 70,000 rigs and mined 493 bitcoin in May 2023 (518 BTC reserves)
Clearspark has earned its place above Cipher mining however both companies have been investing much of their Bitcoin into expanding their production lines this year which is why they have lower reserves than the likes of the well established RIOT.
We will need to keep a close eye on both going forward as they both fully intend to continue to expand. I am already invested in NASDAQ:CIFR with a small initial position (previously shared a chart on this).
I'll be looking for NASDAQ:CLSK exposure between here and the 200 DSMA. The risk reward is reasonable and the chart is attractive.
PUKA
Ride the Wave: Long-Term BTC Investment StrategyUnlock the potential of BTC with a long-term investment strategy backed by four years of market impact. As a seasoned finance advisor and wealth account manager, I'll guide you through the dynamics of this evolving landscape, including the introduction of the new BTC ETF. DM me to seize the opportunities ahead! 📈💼 #BTC #ETF #Investing #Finance
tv 18 : strong weekly chartThe stock as can be seen i s in a strong uptrend
stock is alreay above key averages and is trading above multiweek highs
the counter completed the retracement and now its likely to show continuation towards 77-80 mark followed by 87-89 areas on the upside
the supports are placed at 60-58 area and only below this stock may turn bearish from current strong bullish trend
HOW-TO use Bitcoin 5A Strategy@LilibtcIn our long-term strategy, we have deeply explored the key factors influencing the price of Bitcoin. By precisely calculating the correlation between these factors and the price of Bitcoin, we found that they are closely linked to the value of Bitcoin. To more effectively predict the fair price of Bitcoin, we have built a predictive model and adjusted our investment strategy accordingly based on this model. In practice, the prediction results of this model correspond quite high with actual values, fully demonstrating its reliability in predicting price fluctuations.
When the future is uncertain and the outlook is unclear, people often choose to hold back and avoid risks, or even abandon their original plans. However, the prediction of Bitcoin is full of challenges, but we have taken the first step in exploring.
Table of contents:
Guide
Step 1: Identify the factors that have the greatest impact on Bitcoin price
Step 2: Build a Bitcoin price prediction model
Step 3: Find indicators for warning of bear market bottoms and bull market tops
Step 4: Develop a Bitcoin 5A strategy
Step 5: Verify the performance of the Bitcoin 5A strategy
Opportunities
Usage Restrictions
Guide:
1. On the main interface, modify the code, find the BTCUSD trading pair, and select the BITSTAMP exchange for trading.
2. Set the time period to the daily chart.
3. Select a logarithmic chart in the chart type to better identify price trends.
4. In the strategy settings, adjust the options according to personal needs, including language, display indicators, display strategies, display performance, display optimizations, sell alerts, buy prompts, opening days, backtesting start year, backtesting start month, and backtesting start date.
Step 1: Identify the factors that have the greatest impact on Bitcoin price
Correlation Coefficient: A mathematical concept for measuring influence
In order to predict the price trend of Bitcoin, we need to delve into the factors that have the greatest impact on its price.
These factors or variables can be expressed in mathematical or statistical correlation coefficients. The correlation coefficient is an indicator of the degree of association between two variables, ranging from -1 to 1. A value of 1 indicates a perfect positive correlation, while a value of -1 indicates a perfect negative correlation.
For example, if the price of corn rises, the price of live pigs usually rises accordingly, because corn is the main feed source for pig breeding. In this case, the correlation coefficient between corn and live pig prices is approximately 0.3. This means that corn is a factor affecting the price of live pigs. On the other hand, if a shooter's performance improves while another shooter's performance deteriorates due to increased psychological pressure, we can say that the former is a factor affecting the latter's performance.
Therefore, in order to identify the factors that have the greatest impact on the price of Bitcoin, we need to find the factors with the highest correlation coefficients with the price of Bitcoin. If, through the analysis of the correlation between the price of Bitcoin and the data on the chain, we find that a certain data factor on the chain has the highest correlation coefficient with the price of Bitcoin, then this data factor on the chain can be identified as the factor that has the greatest impact on the price of Bitcoin. Through calculation, we found that the 🔵number of Bitcoin blocks is one of the factors that has the greatest impact on the price of Bitcoin. From historical data, it can be clearly seen that the growth rate of the 🔵number of Bitcoin blocks is basically consistent with the movement direction of the price of Bitcoin. By analyzing the past ten years of data, we obtained a daily correlation coefficient of 0.93 between the number of Bitcoin blocks and the price of Bitcoin.
Step 2: Build a Bitcoin price prediction model
Predictive Model: What formula is used to predict the price of Bitcoin?
Among various prediction models, the linear function is the preferred model due to its high accuracy. Take the standard weight as an example, its linear function graph is a straight line, which is why we choose the linear function model.
However, the growth rate of the price of Bitcoin and the number of blocks is extremely fast, which does not conform to the characteristics of the linear function. Therefore, in order to make them more in line with the characteristics of the linear function, we first take the logarithm of both. By observing the logarithmic graph of the price of Bitcoin and the number of blocks, we can find that after the logarithm transformation, the two are more in line with the characteristics of the linear function. Based on this feature, we choose the linear regression model to establish the prediction model.
From the graph below, we can see that the actual red and green K-line fluctuates around the predicted blue and 🟢green line. These predicted values are based on fundamental factors of Bitcoin, which support its value and reflect its reasonable value. This picture is consistent with the theory proposed by Marx in "Das Kapital" that "prices fluctuate around values."
The predicted logarithm of the market cap of Bitcoin is calculated through the model. The specific calculation formula of the Bitcoin price prediction value is as follows:
btc_predicted_marketcap = math.exp(btc_predicted_marketcap_log)
btc_predicted_price = btc_predicted_marketcap / btc_supply
Step 3: Find indicators for early warning of bear market bottoms and bull market tops
Warning Indicator: How to Determine Whether the Bitcoin Price has Reached the Bear Market Bottom or the Bull Market Top?
By observing the Bitcoin price logarithmic prediction chart mentioned above, we notice that the actual price often falls below the predicted value at the bottom of a bear market; during the peak of a bull market, the actual price exceeds the predicted price. This pattern indicates that the deviation between the actual price and the predicted price can serve as an early warning signal. When the 🟠Bitcoin price deviation is very low, as shown by the chart with 🟩green background, it usually means that we are at the bottom of the bear market;
Conversely, when the 🟠Bitcoin price deviation is very high, the chart with a 🟥red background indicates that we are at the peak of the bull market.
This pattern has been validated through six bull and bear markets, and the deviation value indeed serves as an early warning signal, which can be used as an important reference for us to judge market trends.
Step 4: Bitcoin 5A Strategy Formulation
Strategy: When to buy or sell, and how many to choose?
We introduce the Bitcoin 5A strategy. This strategy requires us to generate trading signals based on the critical values of the warning indicators, simulate the trades, and collect performance data for evaluation. In the Bitcoin 5A strategy, there are three key parameters: buying warning indicator, batch trading days, and selling warning indicator. Batch trading days are set to ensure that we can make purchases in batches after the trading signal is sent, thus buying at a lower price, selling at a higher price, and reducing the trading impact cost.
In order to find the optimal warning indicator critical value and batch trading days, we need to adjust these parameters repeatedly and perform backtesting. Backtesting is a method established by observing historical data, which can help us better understand market trends and trading opportunities.
Specifically, we can find the key trading points by watching the Bitcoin price log and the Bitcoin price deviation chart.
For example, on August 25, 2015, the 🟠Bitcoin price deviation was at its lowest value of -1.11; on December 17, 2017, the 🟠Bitcoin price deviation was at its highest value at the time, 1.69; on March 16, 2020, the 🟠Bitcoin price deviation was at its lowest value at the time, -0.91; on March 13, 2021, the 🟠Bitcoin price deviation was at its highest value at the time, 1.1; on December 31, 2022, the 🟠Bitcoin price deviation was at its lowest value at the time, -1.
To ensure that all five key trading points generate trading signals, we set the warning indicator Bitcoin price deviation to the larger of the three lowest values, -0.9, and the smallest of the two highest values, 1. Then, we buy when the warning indicator Bitcoin price deviation is below -0.9, and sell when it is above 1.
In addition, we set the batch trading days as 25 days to implement a strategy that averages purchases and sales. Within these 25 days, we will invest all funds into the market evenly, buying once a day. At the same time, we also sell positions at the same pace, selling once a day.
Adjusting the threshold: a key step to optimizing trading strategy
Adjusting the threshold is an indispensable step for better performance. Here are some suggestions for adjusting the batch trading days and critical values of warning indicators:
• Batch trading days: Try different days like 25 to see how it affects overall performance.
• Buy and sell critical values for warning indicators: iteratively fine-tune the buy threshold value of -0.9 and the sell threshold value of 1 exhaustively to find the best combination of threshold values.
Through such careful adjustments, we may find an optimized approach with a lower maximum drawdown rate (e.g., 11%) and a higher cumulative return rate for closed trades (e.g., 474 times). The chart below is a backtest optimization chart for the Bitcoin 5A strategy, providing an intuitive display of strategy adjustments and optimizations.
In this way, we can better grasp market trends and trading opportunities, thereby achieving a more robust and efficient trading strategy.
Step 5: Validating the performance of the Bitcoin 5A Strategy
Model accuracy validation: How to judge the accuracy of the Bitcoin price model?
The accuracy of the model is represented by the coefficient of determination R square, which reflects the degree of match between the predicted value and the actual value. I divided all the historical data from August 18, 2015 into two groups, and used the data from August 18, 2011 to August 18, 2015 as training data to generate the model. The calculation result shows that the coefficient of determination R squared during the 2011-2015 training period is as high as 0.81, which shows that the accuracy of this model is quite high. From the Bitcoin price logarithmic prediction chart in the figure below, we can see that the deviation between the predicted value and the actual value is not far, which means that most of the predicted values can explain the actual value well.
The calculation formula for the coefficient of determination R square is as follows:
residual = btc_close_log - btc_predicted_price_log
residual_square = residual * residual
train_residual_square_sum = math.sum(residual_square, train_days)
train_mse = train_residual_square_sum / train_days
train_r2 = 1 - train_mse / ta.variance(btc_close_log, train_days)
Model reliability verification: How to affirm the reliability of the Bitcoin price model when new data is available?
Model reliability is achieved through model verification. I set the last day of the training period to February 2, 2024 as the "verification group" and used it as verification data to verify the reliability of the model. This means that after generating the model if there is new data, I will use these new data together with the model for prediction, and then evaluate the accuracy of the model. If the coefficient of determination when using verification data is close to the previous training one and both remain at a high level, then we can consider this model as reliable. The coefficient of determination calculated from the validation period data and model prediction results is as high as 0.83, which is close to the previous 0.81, further proving the reliability of this model.
Performance evaluation: How to accurately evaluate historical backtesting results?
After detailed strategy testing, to ensure the accuracy and reliability of the results, we need to carry out a detailed performance evaluation on the backtest results. The key evaluation indices include:
• Net value curve: As shown in the rose line, it intuitively reflects the growth of the account net value. By observing the net value curve, we can understand the overall performance and profitability of the strategy.
The basic attributes of this strategy are as follows:
Trading range: 2015-8-19—2024-2-18, backtest range: 2011-8-18—2024-2-18
Initial capital: 1000USD, order size: 1 contract, pyramid: 50 orders, commission rate: 0.2%, slippage: 20 markers.
In the strategy tester overview chart, we also obtained the following key data:
• Net profit rate of closed trades: as high as 474 times, far exceeding the benchmark, as shown in the strategy tester performance summary chart, Bitcoin buys and holds 210 times.
• Number of closed trades and winning percentage: 100 trades were all profitable, showing the stability and reliability of the strategy.
• Drawdown rate & win-loose ratio: The maximum drawdown rate is only 11%, far lower than Bitcoin's 78%. Profit factor, or win-loose ratio, reached 500, further proving the advantage of the strategy.
Through these detailed evaluations, we can see clearly the excellent balance between risk and return of the Bitcoin 5A strategy.
Opportunity: Capturing factor changes
Changes in factors provide us with valuable trading opportunities. The 🟠orange line in the chart below represents the factor indicator when its value on February 20, 2024 is -0.32, which is greater than the threshold of -0.9. This could be a signal worth paying attention to. Opportunities like this do not come up often, so we need to stay alert and act fast.
Usage Restrictions: Strategy Application in Specific Situations
Please note that this strategy is designed specifically for Bitcoin and should not be applied to other assets or markets without authorization. In actual operations, we should make careful decisions according to our risk tolerance and investment goals.
XRP: Chris Larsen Wallet Hack... or STAGED Dump?📉Hi Traders, Investors and Speculators of Charts📈
Yesterday, news came out that a huge XRP wallet has been hacked, stealing $112 million worth of XRP. According to information currently available, the hack was as a result of compromised security keys. It turned out to be the wallet of none other than tech-giant Chris Larsen, Ripple Co-founder. (suspicious already?🤔 let's dive in...)
One of many strange incidents surrounding this hack is that it was discovered by a Twitter user and popular blockchain security expert ZachXBT. I imagined that one would notice if your personal accounting holding 9 digits of XRP worth $112 million got hacked, but apparently not. It took ZachXBT a public Twitter post to make the apparently unaware team at Ripple take action. This makes you wonder, if ZachXBT didn't pick it up... would this have gone unnoticed and been swept under the rug, or would Chris Larsen have come out and admitted it? I guess we'll never know. But with Ripple's dodgy actions in the past (ultimately leading to the SEC case), one can only guess.
Not too long ago, Jed McCaleb finally sold off the last of his enormous amount of XRP which he had been dumping monthly for years. One Twitter user voiced a very valid concern; "are all Ripple execs holding 9 digits of xrp, is there something in place to prevent them from dumping all at once on the market?"
It just seems like despite the markets best bullish trends, the constant overwhelming selling pressure is just too high for XRP to reach new highs. It's sad to see such a industry leader and once-promising project fall to new lows.
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Is ZM Finally Buyable?ZM longs have been absolutely eviscerated since 2020. One of the quintessential names of the 2020 exuberance, it has since seen a 90% drawdown from the 2020 high to the 2023 low late last year.
However, ZM has seen a trading range between 60 and 75 for almost a year now. This basing has clear analogs to Wyckoff accumulation, and the failed breakdown in October with low volume and no follow through could have finally put in a durable bottom. The 50SMA crossed above the 200SMA in January, providing a clue about the possibility for a shift in trend on this beaten down name.
If ZM sees markup and can break out of this accumulation range, it is possible we could see a gap fill of the August 2022 earning gap around 97.4.
As a trade, a tight stop at the recent low of 63.06 presents a very favorable setup, with a potential > 10:1 RR.
There was a time when ZM was a clear no-touch, and for good reason. But after the absolute destruction in value over the last few years, to finally allow price to re-align with more reasonable valuation levels, this name can finally be taken back out of the penalty box.
Doge1 was used to pay for NovaC,But it seems Doge is not onboardDoge-1 Coin was used to pay for NovaC project. NovaC is going to the Moon in less than half an hour, but right now, at the moment of launch time, a few personnel told that the DogeCoin itself is not loaded onboard for journey to the Moon...
Unveiling the Golden Opportunity: Why XAUUSD/Gold is My FavoriteJoin me on an immersive journey as I delve into the unparalleled allure of trading XAUUSD/Gold. In this comprehensive exploration, I'll unravel the intricacies of trading gold, from its status as a timeless safe-haven asset to its remarkable resilience in the face of market volatility. Delve deeper into the historical significance of gold, its correlation with global economic trends, and the unique opportunities it presents to traders. Through expert analysis and insightful commentary, I'll showcase why XAUUSD/Gold remains my preferred pair for unlocking consistent profits and navigating the ever-evolving landscape of financial markets. Buckle up and discover the golden secrets to trading success with me.
Doge bullish journey to the Moon + the watch link!Following the announcement of the launch of Doge to the Moon, the bulls have dominated the market and the supply ranges have been greatly reduced, and the price of Doge as well as the price of Bitcoin are getting higher, and it is expected that this trend will continue until the landing of Doge on the Moon's surface. Dogecoin is supposed to launch to the Moon from the launchpad in next several hours, by SpaceX's Falcon 9 rocket.
To watch the launch live, click on the following link:
www.youtube.com
or this:
www.youtube.com