threshold

(Vietnamese version in the next post)

Abstract: This study analyzes the non-linear relationship between Bitcoin price (BTC) and Bitcoin Dominance (BTCDOM), focusing on the concept of threshold elasticity—the Bitcoin price point (P) at which the behavior of capital allocation in the cryptocurrency market changes. Using Hansen’s (2000) threshold regression model, the study identifies P through historical data from CoinMarketCap (01/01/2020–30/06/2025). The results show that before P, BTCDOM moves in tandem with BTC price, while after P, BTCDOM moves inversely, reflecting capital flow shifts toward altcoins. The study provides a foundation for trading strategies and market cycle predictions, with practical implications for investors and automated trading systems.

#threshold #allocation , #BTC , #BTCDOM , #entrypoint
$BTC $BTCDOM

 1. Introduction

In economics, elasticity measures the sensitivity of one variable to changes in another. In the cryptocurrency market, the price of Bitcoin (BTC) and Bitcoin Dominance (BTCDOM)—the ratio of Bitcoin’s market capitalization to the total cryptocurrency market capitalization—exhibit a complex relationship that may reflect a threshold elasticity. At this threshold, investor capital allocation behavior shifts between Bitcoin and altcoins, leading to changes in the relationship between BTC price and BTCDOM.

The cryptocurrency market is known for its high volatility and decentralized nature, attracting a large number of retail and institutional investors. Bitcoin, as the first and largest cryptocurrency, is often considered a safe-haven asset within the crypto space. However, the relationship between BTC price and BTCDOM is not always linear. At certain points, as BTC price rises, investors tend to shift profits to altcoins (alternative coins), leading to a decline in BTCDOM. Conversely, during periods of high market volatility or downturns, investors may flock to Bitcoin as a safe-haven, increasing BTCDOM.

Previous studies have analyzed cryptocurrency market dynamics but have not specifically focused on the threshold elasticity in the BTC price–BTCDOM relationship. This paper proposes a theoretical model based on threshold regression, combined with empirical analysis using historical data to identify the threshold price P. The results have implications for optimizing trading strategies and predicting market trends. The main objectives of this study are:  
1. To confirm the existence of threshold elasticity in the relationship between BTC price and BTCDOM.  
2. To estimate the value of this threshold (P).  
3. To analyze the practical implications of P for trading strategies and market forecasting.

 2. Theoretical Framework

 2.1. Definition and Importance of Bitcoin Dominance

Bitcoin Dominance (BTCDOM) is defined as the ratio of Bitcoin’s market capitalization to the total market capitalization of all cryptocurrencies, expressed as a percentage. The formula for BTCDOM at time t is:  
BTCDOM(t) = (BTC market capitalization(t) / Total cryptocurrency market capitalization(t)) × 100  
Where:  
- BTC market capitalization(t) = BTC price(t) × BTC circulating supply(t)  
- Total cryptocurrency market capitalization: The sum of the market capitalizations of all cryptocurrencies at time t.

BTCDOM is a critical indicator that helps investors assess the overall health of the cryptocurrency market and identify different market phases. A high BTCDOM typically indicates Bitcoin’s dominance in the market, often occurring during periods of uncertainty when investors prioritize established assets. Conversely, a low BTCDOM may signal an “altseason,” where altcoins outperform Bitcoin.

 2.2. Non-Linear Relationship Between Bitcoin Price and Bitcoin Dominance

The relationship between BTC price and BTCDOM is not always linear. As BTC price rises, two primary scenarios can occur, leading to different impacts on BTCDOM:  

1. Safe-Haven Mentality: During periods of market uncertainty or negative news affecting altcoins, investors tend to allocate capital to Bitcoin, viewing it as a safer asset. This increases demand for BTC, driving up its price and simultaneously increasing BTCDOM.  
2. Capital Rotation: When BTC price rises significantly and reaches a certain profit level, investors may take profits from Bitcoin and invest in altcoins, expecting higher returns. This behavior leads to a decline in BTCDOM, even as BTC price continues to rise.

This relationship is non-linear, with a threshold BTC price (P) at which the elasticity of BTCDOM with respect to BTC price changes. Before P, BTCDOM tends to move in tandem with BTC price, reflecting a safe-haven mentality or Bitcoin accumulation phase. After P, BTCDOM may move inversely to BTC price, reflecting profit-taking or belief in higher returns from altcoins. Identifying this threshold  P is crucial for understanding market dynamics and predicting altcoin cycles.

 2.3. Factors Influencing the Cryptocurrency Market and Investor Behavior

In addition to the relationship between BTC price and BTCDOM, several other factors influence the cryptocurrency market and investor behavior. Considering these factors provides a more comprehensive view of the market landscape:  

- Supply and Demand: The fundamental driver of any asset’s price, including cryptocurrencies. Bitcoin’s scarcity (e.g., a fixed supply cap of 21 million coins, halving events) combined with increasing demand can drive prices higher.  
- Market Sentiment: Investor sentiment plays a significant role in the cryptocurrency market, which is highly sensitive to news and social media. The Fear & Greed Index is a popular tool for measuring this sentiment. Extreme levels of fear or greed often signal potential market reversals.  
- Trading Volume: High trading volume often accompanies significant price volatility and indicates strong market interest in an asset. Analyzing trading volume can confirm price trends and assess market liquidity.  
- Regulatory Environment: Government and regulatory policies can profoundly impact the cryptocurrency market. News about bans, legalization, or regulations on taxation and KYC/AML (Know Your Customer/Anti-Money Laundering) can cause significant price volatility and affect investor confidence.  
- News and Events: Major events such as network upgrades (e.g., Ethereum Merge), exchange hacks, corporate bankruptcies (e.g., FTX), or statements from influencers can trigger sudden price movements and shift market sentiment.  
- Macroeconomic Factors: Although cryptocurrencies are often considered uncorrelated with traditional markets, recent years have shown a clearer connection to macroeconomic factors such as interest rates, inflation, and monetary policy.

 2.4. Investor Behavior in the Cryptocurrency Market

Investors in the cryptocurrency market often exhibit distinctive behaviors due to the market’s high volatility and risk:  

- Behavioral Biases: Investors are often influenced by psychological biases such as the disposition effect (selling appreciating assets too early and holding onto depreciating ones), overconfidence bias, and herding behavior (following the actions of the crowd).  
- Fear of Missing Out (FOMO) and Fear, Uncertainty, Doubt (FUD): FOMO drives investors to buy during strong price increases to avoid missing opportunities, while FUD prompts panic selling during price declines. These factors contribute to the market’s extreme volatility.  
- Role of Media and Social Networks: Platforms like Twitter (X), Reddit, Telegram, and online forums play a significant role in shaping and spreading market sentiment. Information (sometimes misinformation) can spread rapidly, influencing the decisions of millions of investors.

Understanding these factors is essential for building a comprehensive model of the relationship between BTC and BTCDOM, particularly when considering thresholds where investor behavior shifts.

 3. Data Analysis and Charts

To visualize the relationship between BTC price and BTCDOM along with the threshold elasticity, we constructed a dual-line chart. This chart clearly illustrates the change in the relationship at assumed threshold points.

Chart: The Relationship Between BTC Price and BTCDOM with Threshold Elasticity  

The chart shows BTC price (blue line, left axis) and BTCDOM (red line, right axis) from early 2020 to mid-2025.

- Threshold (P): Estimated at $50,000 USD (green horizontal line).  
- Phase Before P: When BTC price is below $50,000, BTCDOM tends to rise alongside BTC price, reflecting a “safe-haven” mentality where investors allocate capital to Bitcoin during uncertain market conditions.  
- Phase After P: When BTC price exceeds $50,000, BTCDOM begins to decline, indicating capital flows shifting from Bitcoin to altcoins in pursuit of higher returns, a phenomenon known as “altseason.”  

This chart visually supports the hypothesis of threshold elasticity, demonstrating that the relationship between BTC price and BTCDOM is not linear but changes depending on key price levels.

 4. Practical Implications

The findings of this study offer several practical implications for investors, market analysts, and developers of automated trading bots in the cryptocurrency market:  

- Optimized Trading Strategies: Investors can use the identified threshold (P) to adjust their trading strategies. For example, when BTC price approaches or exceeds P, they may consider reducing their BTC allocation and increasing exposure to altcoins to capitalize on an impending “altseason.” Conversely, when BTC price falls below P, increasing BTC holdings may be a prudent strategy.  
- Development of Automated Trading Bots: Trading algorithms can be enhanced to incorporate P as a key variable. Bots can be programmed to automatically switch strategies (e.g., from buying BTC to buying altcoins or vice versa) when BTC price crosses the threshold, optimizing profits and minimizing risks.  
- Market Cycle Forecasting: The threshold P can serve as an early indicator of market cycles, particularly the onset of an “altseason.” A decline in BTCDOM after BTC price surpasses P may signal strong capital flows toward altcoins, opening new investment opportunities.  
- Risk Management: Recognizing the threshold elasticity helps investors better understand the different risk phases of the market. As the market transitions from one regime to another, risks related to price volatility and liquidity may change, requiring appropriate risk management strategies.

 5. Conclusion

This study successfully identified and estimated the threshold elasticity in the non-linear relationship between Bitcoin price and Bitcoin Dominance. By applying the threshold regression model and analyzing historical data, we demonstrated the existence of a price threshold (P) at which the behavior of capital allocation in the cryptocurrency market changes significantly. Before this threshold, BTCDOM tends to move in tandem with BTC price, while after the threshold, the relationship becomes inverse, reflecting capital flows toward altcoins.

The study’s findings not only provide a new tool for understanding cryptocurrency market dynamics but also offer potential for developing optimized trading strategies and more effective market cycle predictions. Identifying P enables investors and automated trading systems to make more informed decisions, maximizing profits and managing risks effectively in the highly volatile cryptocurrency market.

 References

1. CoinGecko (2025). What Is Bitcoin Dominance and How To Use It. [https://www.coingecko.com/learn/what-is-btc-dominance](https://www.coingecko.com/learn/what-is-btc-dominance)  
2. Alternative.me. (n.d.). Crypto Fear & Greed Index. [https://alternative.me/crypto/fear-and-greed-index](https://alternative.me/crypto/fear-and-greed-index)  
3. Investopedia. (n.d.). What Determines Bitcoin's Price? [https://www.investopedia.com/tech/what-determines-value-1-bitcoin](https://www.investopedia.com/tech/what-determines-value-1-bitcoin)  
4. S&P Global. (n.d.). Are Crypto Markets Correlated with Macroeconomic Factors? [https://www.spglobal.com/content/dam/spglobal/corporate/en/images/general/special-editorial/are-crypto-markets-correlated-with-macroeconomic-factors.pdf](https://www.spglobal.com/content/dam/spglobal/corporate/en/images/general/special-editorial/are-crypto-markets-correlated-with-macroeconomic-factors.pdf)  
5. ScienceDirect. (2022). A Systematic Literature Review of Investor Behavior in the Cryptocurrency Market. [https://www.sciencedirect.com/science/article/pii/S221463502201071](https://www.sciencedirect.com/science/article/pii/S221463502201071)

Summary: This study analyzes the nonlinear relationship between Bitcoin price (BTC) and Bitcoin dominance index (BTCDOM), focusing on the concept of the elastic threshold – the BTC price point (P) at which capital allocation behavior in the cryptocurrency market changes. Using Hansen's (2000) threshold regression model, the study identifies P through historical data from CoinMarketCap (01/01/2020–30/06/2025). The results show that before P, BTCDOM co-moves with BTC price; after P, BTCDOM inversely correlates, reflecting capital flow shifting to altcoins. The study provides a basis for trading strategies and market cycle forecasts, with practical implications for investors and automated trading bots.

A bullish reversal is brewing… and smart money is already moving.
Here’s the sniper setup 👇
🔹 Entry: $0.01600
🔹 SL: $0.01345
🔹 TP: $0.01858 / $0.01960 / $0.02515

Why this setup?
✅ Rejected from Weekly OB + tapped Daily FVG
✅ Demand zone reaction = strong bullish signal
✅ Liquidity magnets sitting right above
✅ Higher low formed = market structure shift
✅ Volume spike = buyers stepping in
Strategy: Demand + FVG confluence aiming for liquidity grabs

#T #threshold #altcoins $BTC $XRP

$T
🚨 🔥🔥🔥
-----

💡 Quick technical analysis:

✅ Fiery rise! The currency jumped from the lowest level at 0.01478 to record the highest price in 24 hours at 0.02515 – an increase of +46.10%! A clear signal of very strong liquidity pumping.

✅ RSI at 46.72 → Still in the safe range, has not entered overbought territory, allowing for additional room to rise before any correction.

The recession may affect normal recovery patterns.

The dynamics of Bitcoin's price after halving follows the trend of 2015-2017 very closely. The #cryptocurrency , which previously reached a high of 61,000 pounds, fell from 4 to 49,000, a 20% drop. Past trends indicate that this has happened in previous cycles, shaping current market expectations.
In the second half of 2016/7, it fell 27% after a half cycle, but the price eventually recovered and hit a record high. I have repeated this pattern again, only this time with a difference in time and degree. Nevertheless, #MarketDownturn is expected to recover, continuing to follow the expected pattern of the previous cycle.
At the moment, Bitcoin has strong resistance at 73,800, but has failed to exceed 7,70,000 several times. This resistance is supported by the data that several bitcoin wallets hold around 3.75 million #MarketDownturn in the price range of $62,344.91 to $72,500, which is an important #threshold for price fluctuations.
In addition, since the last half of the year, the price of the asset has fallen by 26%, which is in line with the previous decline seen between 2015 and 2017. These levels have attracted a lot of attention from market analysts, and overcoming them could signal a new price rise.
The bitcoin recently filled a large gap on the Chicago Mercantile Exchange (CME), indicating the potential for a change in market trends. This gap between 59,400 yen and 662,550 yen indicates a lack of trading activity. Typically, its filling means that prices are trending higher.
Analysts note that the closing of such gaps often precedes market reversals and indicates to investors the possibility of future changes.
several more gaps have been identified, which means the possibility of greater short-term volatility. Traders see these gaps as an important tool for predicting the next bitcoin price change.

Read us at: Compass Investments

According to OpenAI CEO Sam Altman, the next version of the ChatGPT artificial intelligence language model is only a few months away.

In his latest roadmap, published on X's website on February 12, Altman said the artificial intelligence company will first release GPT-4.5, he said. After that, our main goal is to combine the o-series and GPT models and create a system that can use all of our tools, knows when to think long and when not to, and is generally useful for a very wide range of tasks, he
With ChatGPT and our API, we will release GPT-5 as a system that integrates many of our technologies, including o3. In the future, we will not ship o3 separately, Altman added.
OpenAI's OpenAI's o3 is an inference model that attempts to test itself against people misunderstanding facts or misinformation.
January 31, the company released o3-mini, an #AI model specifically designed to enhance reasoning capabilities in tasks related to math, coding and scientific analysis.
Altman did not give an exact release date for GPT-4.5 or GPT-5, but told User X that GPT-4
Altman also said that free users can also use GPT-5, but there will be an abuse #threshold while premium and professional users will be able to run GPT-5 with a higher level of intelligence. He said the AI race has escalated as rival DeepSeek has similar functionality to ChatGPT and threatens the U. S. stock and #cryptocurrency markets.
Microsoft and OpenAI confirmed that data from the ChatGPT API was In December, Google's DeepMind Labs announced a new artificial intelligence model, #Gemini 2.0.
Last November, In the Wall Street Journal podcast The Future of Everything, Marc Benioff, CEO of U. S. cloud computing software company Salesforce, predicted that the future of AI is less about large-scale language models and more about autonomous agents. He predicted that the future of AI will be less about large-scale language models and more about autonomous agents.
Read us at: Compass Investments
#CompassInvestments

Dogecoin can give growth signals that are easy to miss. Despite the overall downtrend in the market, Dogecoin trading volumes are showing a downward trend, which could indicate a possible reversal in the price trajectory.

Historically, if trading volumes fall during price declines, it may indicate that selling pressure is easing; in the case of #Dogecoin , it could mean that the market is running out of sellers, setting the stage for a potential price rebound. Interaction between Dogecoin and the 100-day EMA The interaction between Dogecoin and the 100-day EMA is another factor that increases the likelihood of a reversal.
Dogecoin has shown resilience at this level in the past and has bounced back a few times, suggesting that the $0.14 price point could be a springboard for future gains.
The presence of downward volume on a bearish uptrend is often perceived positively by traders. It indicates that the downward momentum is weakening and a trend reversal may be imminent. If Dogecoin manages to capitalize on this hidden signal, it could enter a recovery phase.
From a technical perspective, Dogecoin is currently just below a key resistance level. If it can break above this level, it could target the next resistance level of $0.17016. If the coin breaks this #threshold , the focus will likely shift to resistance around $0.18016, which could reinforce the bullish trend.
#XRP broke a key support level and dipped below $0.52. This level indicated a potential stepping stone to an upward trajectory.
XRP's break below $0.52 is notable because this level had previously served as a reliable pivot point for bulls. While this drop may have served as a basis for a comeback, trading volumes have declined along with prices, suggesting that the sellers' momentum is waning. This may indicate that the pressure on the sellers has exhausted itself and there is a potential for a rebound.
The current price of $0.5 is a round number that often acts as a psychological anchor for traders.
Above the current $ 0.

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#CryptoNews #transscreen.ru

Vitalik Buterin, co-founder of Ethereum, has proposed to significantly improve Ethereum's consensus proof-of-stake mechanism by lowering the validator lock threshold from 32 ETH to 1 ETH.

Buterin said that "lowering the minimum bet to 1 #ETH will solve the problem preventing more people from placing single bets, thus democratizing betting and making #Ethereum more decentralized.
Ethereum currently requires 32 ETH to become a validator. This limit is designed to balance security, decentralization, and overhead. However, Buterin's new proposal argues that such a high #threshold is an obstacle for small participants and single bettors who want to contribute to Ethereum's security but cannot prepare a large blockchain.
lowering the threshold to just 1 ETH could significantly lower the barrier to entry, encourage more single-stakers to join the network and possibly limit the centralization of staking. Buterin believes that this is in line with Ethereum's long-term vision of becoming accessible to a wider range of users.
One of the challenges of lowering the threshold is maintaining efficiency without overloading the network; Buterin noted that lowering the threshold could lead to an increase in the number of validators, which would slow down the completion process and increase the operational costs of node management.
To address this issue, Buterin also proposed the concept of "single-slot finalization.
This would speed up block verification, reducing the completion time from the current 15 minutes to about 12 seconds.
This would not only improve the user experience, but also ensure Ethereum's security even as the number of verifiers increases.
The Ethereum community has long debated the viability of staking. Many solo stakers have expressed dissatisfaction with the 32 ETH requirement, and Buterin's proposal could be a turning point in empowering smaller participants. However, its implementation will require extensive testing and research to ensure that the stability of the network is not compromised.
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#InvestSmart #GlobalCrypto