Bitcoin and Crypto Market Updates (May 15th)
BTC Weekly Chart (CME) — Resistance in the 29k — 32k zone — Support in the 24k — 25k zone. Looking at the weekly here we are tapping the 200MA. For me, this is a pretty simple/clean chart because we have a clean bullish invalidation scenario if we fall below the support zone. This would cause the MACD to roll and cross + we would lose the 200MA. CHARTS ARE STILL BULLISH unless we lose this zone.
BTC Daily — Short-term resistance above and longer-term support below. Pretty clean H+S pattern here and I really would like to see us back above the neckline and then move through that tricky resistance zone — This resistance zone could easily see a rejection as we rise into the 25/50 MA cross + high volume VPVR zone. It’s currently bouncing off the 100MA and attempting to break back above the neckline.
SUMMARY — Tricky stuff here, we need to see some repairs in the chart over the next few sessions this week.
BTC.D — Still managing to hold this range high zone. What we really want to see here is DOM falling while BTC rises or remains stable. Things start to look pretty grim if BTC cant push higher and this starts to break out.
USDT.D — Clean zone below that if we break under should provide some upside for crypto. If we start to find support around these levels I’m concerned we push for the 5th wave. Eyes on what happens here this week because that break below support would be some validation to go long magic internet money.
Going to review the legacy side of markets this morning and will post some charts in the Discord!
1 Million Bitcoin Addresses now own 1 BTC or more
One million Bitcoin addresses now own 1 BTC or more, thanks to last year’s Bitcoin price plunge. According to data from Glassnode, the number of addresses with full BTC status increased considerably at the end of February last year when Bitcoin was halfway through correcting after its record high. Holding one BTC is now roughly equivalent to half the median US salary, making it easier for people to jump on the Bitcoin bandwagon or continue stacking sats. However, it’s worth noting that one BTC address doesn’t necessarily represent one person, and some addresses may belong to institutions or groups of people.
Coinbase Lost $2.6 Billion Last Year Executives Made Millions
Despite a rough year for the crypto market in 2022, Coinbase executives managed to take home more money than the year before. CEO Brian Armstrong made a total of $7.4 million, with $6.3 million of that going to personal security costs. Emilie Choi, chief operating officer and president, received $23.4 million in total compensation, while chief financial officer Alesia Haas made $11.9 million. Although Coinbase lost $2.6 billion in 2022, the company posted smaller net losses in the first quarter of 2023. This comes after the crypto sector was hit by a series of events, including the de-pegging of the algorithmic stablecoin Terra and the bankruptcies of several crypto lenders.
Binance, Paxos and DYDX Withdraw from Canada
Binance, one of the world’s largest cryptocurrency exchanges, has announced its withdrawal from the Canadian market due to the country’s new stablecoin guidance and investor limits. The regulatory environment forced Binance to join other major crypto businesses that have left the Canadian market. Failure to register with the Canadian Securities Administrators by March 23 meant crypto trading firms had to cease operations, leading Binance to conclude that the market was no longer tenable. Although confident it will return, Binance customers in Canada will receive an email with information on how this will impact their accounts going forward.
Jump Trading Class Action Lawsuit for Allegedly Making $1.3 Billion on Terra Collapse
A class action lawsuit has been filed against Jump Trading accusing the firm of manipulating the value of algorithmic stablecoin UST, leading to investor losses of at least $40 billion. The lawsuit alleges that Jump Trading purchased substantial quantities of UST to manipulate its value towards $1, which misled investors about the token’s true price and risks. Jump Trading is also accused of conspiring to artificially inflate the prices of UST and aUST, a token used on Terra’s lending platform, by covertly purchasing large quantities of UST. The lawsuit claims Jump Trading made a profit of more than $1.28 billion through the scheme.
US Defense Department Explore Crypto Use Cases
The US Department of Defense has completed a contract with San Francisco-based blockchain startup Constellation, marking a significant milestone as one of the first completed blockchain Phase II contracts within the government sector. The contract aims to modernize the cybersecurity of the Defense Transportation System’s commercial airlift partners and evaluate the commercial potential of the platform. The prototype is “defence-approved,” and Constellation is currently exploring other crypto use cases with the DOD, including payments and settlement layers in federal procurement workflows, real-time micropayments for licensing microservices, and gated identity systems unlocked with NFTs. Constellation’s ultimate goal is to focus on the largest benefit of using blockchain networks: crypto as “true utilities.”
ALGO TRADING — Utilizing AI for Efficient Trading Strategies
In today’s dynamic financial markets, algorithmic trading has emerged as a compelling approach for traders and investors. By harnessing the power of artificial intelligence (AI), algo trading enables individuals to create sophisticated trading algorithms that can automate decision-making and execution processes. In this article, we will delve into the concept of algo trading, highlighting its benefits, and providing valuable tips on creating effective trading algorithms using AI.
Understanding Algo Trading:
Algo trading refers to the practice of using computer programs and algorithms to execute trades based on predefined rules and conditions. These algorithms are designed to analyze market data, identify patterns, and execute trades with precision and speed. By leveraging AI technologies, such as machine learning and natural language processing, algo trading algorithms can process vast amounts of data and make data-driven decisions.
Why Consider Using Algo Trading?
These are some of the advantages that using algorithms and AI for trading would have:
- Speed and Efficiency: Algo trading algorithms operate at lightning-fast speeds, enabling traders to capitalize on even the smallest market inefficiencies. With automated execution and near-instantaneous response times, algo trading eliminates the delays associated with manual trading, maximizing efficiency and reducing the impact of human emotions on decision-making.
- Data Analysis and Pattern Recognition: The power of AI allows algo trading algorithms to process enormous volumes of data from various sources. By analyzing historical and real-time data, these algorithms can identify patterns, correlations, and market trends that may not be immediately apparent to human traders. This data-driven approach enhances decision-making and increases the likelihood of profitable trades.
- Risk Management and Consistency: Algo trading algorithms can incorporate sophisticated risk management techniques into their strategies. These algorithms can automatically implement predefined risk parameters, such as stop-loss orders and position sizing rules, to manage potential losses. By maintaining discipline and consistency in risk management, algo trading offers the potential for long-term profitability and risk mitigation.
- Reduced Emotional Bias: Emotions can often cloud judgment and lead to suboptimal trading decisions. Algo trading algorithms eliminate emotional biases by relying on predefined rules and data-driven analysis. This approach helps traders maintain objectivity and consistency in their trading strategies, ultimately leading to more rational decision-making.
- Accessibility and Availability: Algo trading is not limited to institutional investors or experienced traders. With advancements in technology and the availability of user-friendly platforms, individuals with varying levels of trading expertise can engage in algo trading. This accessibility allows traders to explore new opportunities and diversify their investment strategies.
As you can see algo trading, empowered by AI, is revolutionizing the way traders and investors approach financial markets. By leveraging the speed, efficiency, and data analysis capabilities of algo trading algorithms, individuals can enhance their trading strategies and decision-making processes. While embarking on the algo trading journey, it is essential to define clear objectives, gather quality data, choose appropriate AI techniques, conduct thorough testing, and prioritize risk management. By continuously monitoring and improving the algorithm, traders can adapt to changing market conditions and potentially achieve better trading outcomes.
On the other hand, while algo trading offers numerous advantages, it is essential to be aware of the potential challenges and problems associated with this approach. It is crucial to address these issues to ensure the effectiveness and long-term success of your algo trading strategies.
What are the risks of using Algos?
Let’s explore some of the potential problems of trading using algorithms:
- Over-Optimization: When designing trading algorithms, there is a risk of curve-fitting. This occurs when an algorithm is excessively tuned to fit historical data, resulting in a strategy that performs exceptionally well on past data but fails to adapt to future market conditions. This can lead to poor performance and financial losses when applied to real-time trading.
- Technical Glitches and System Failures: Algo trading relies heavily on technology and computer systems. Despite rigorous testing, technical glitches and system failures can occur. Network outages, software bugs, or data feed errors can disrupt the execution of trades or lead to unintended consequences. It is crucial to have backup systems in place and be prepared to handle unexpected technical issues.
- Data Quality and Accuracy: The accuracy and quality of data used by algo trading algorithms are paramount. If the data is incomplete, inaccurate, or delayed, it can significantly impact the performance of the algorithms. Traders must ensure they have reliable data sources and implement robust data cleansing and validation processes.
- Market Volatility and Black Swan Events: Algo trading algorithms are designed based on historical data and predefined rules. However, unexpected market volatility or black swan events that deviate significantly from historical patterns can pose challenges for algorithms. Rapid price movements, sudden shifts in market sentiment, or unforeseen events can result in significant losses or trigger a cascade of automated trades.
- Regulatory and Compliance Risks: Algorithmic trading is subject to regulations aimed at maintaining fair and orderly markets. Traders must be familiar with and adhere to regulatory requirements, such as market manipulation rules and position limits. Failure to comply with regulations can lead to legal consequences and reputational damage.
- Lack of Human Intuition: While algo trading algorithms excel at processing vast amounts of data and executing trades with speed and precision, they lack the human intuition and qualitative assessment that experienced traders bring to the table. Algo trading algorithms may struggle to interpret complex market dynamics or adjust to unexpected events that require subjective judgment.
Algo trading presents exciting opportunities for traders and investors, leveraging AI to automate and optimize trading strategies. However, it is important to recognize and address the potential problems that may arise. Guarding against over-optimization, preparing for technical glitches, ensuring data quality, accounting for market volatility, complying with regulations, and acknowledging the limitations of algorithms are essential steps to mitigate risks. By striking a balance between technological advancements and human expertise, traders can harness the benefits of algo trading while navigating the challenges to achieve successful and sustainable trading outcomes.
If you would like to get some tips to help you start building your own trading algorithm subscribe and come back next Monday!