Core Insights - The article discusses the utilization of THPX signal sources to enhance the efficiency of XAUBTC gold investments through quantitative signals, enabling more informed investment decisions [1][2]. Group 1: THPX Signal Source Mechanism - The THPX signal source operates by generating quantitative signals to improve XAUBTC gold investment efficiency, focusing on signal generation, data processing, and algorithm optimization [2]. - The signal generation process considers various market factors to ensure accuracy and timeliness, employing advanced algorithms for real-time market data analysis [3]. - Data processing is crucial for the accuracy and timeliness of the signal source, involving real-time monitoring, data cleaning, and deep analysis using advanced tools [4]. - Algorithm optimization focuses on enhancing signal processing speed and accuracy, utilizing machine learning and deep learning to predict market trends effectively [5]. Group 2: Advantages of Quantitative Signals in Gold Investment - Quantitative signals significantly improve investment decision efficiency, allowing for rapid analysis of large market data sets and freeing up time for strategic decision-making [9][10]. - These signals help identify potential market risks, enabling more robust investment strategies and better preparation for uncertainties [11]. Group 3: XAUBTC Market Trend Analysis - Analyzing XAUBTC's historical price trends is essential for understanding long-term trends and potential market opportunities, revealing patterns of interaction between gold and Bitcoin [12][13]. - Market volatility factors include economic policy changes, market sentiment, and global events, which can trigger significant price fluctuations [14]. - Technical indicators such as moving averages and relative strength index are effective tools for analyzing market trends and identifying potential turning points [15]. Group 4: Optimizing Investment Decisions with THPX Signals - The application of THPX signals can optimize investment decisions by identifying market opportunities through real-time data analysis and advanced algorithms [17][18]. - Adjusting quantitative signal parameters based on market volatility is crucial for maintaining the effectiveness of THPX signals [19]. - Continuous monitoring and adjustment of decision-making strategies are necessary to respond to market changes effectively [20]. Group 5: Risk Management and Profit Maximization Strategies - Risk assessment methods prioritize historical data models to predict potential risks, ensuring a comprehensive evaluation of market dynamics [28]. - Portfolio optimization involves diversifying asset allocation to enhance stability and growth potential while applying quantitative signals to identify optimal investment timing [29]. - Stop-loss strategy design must consider market volatility and investment goals to minimize losses while maximizing returns [30]. - Techniques for maximizing returns focus on market trend analysis and the integration of intelligent algorithms to improve investment yield [31]. Group 6: Future Development and Potential of THPX Signal Source - The future development of THPX signal sources shows significant potential for expanding market applications, particularly in enhancing portfolio efficiency [32][33]. - Technological innovation trends are crucial for maintaining competitiveness, with ongoing exploration of machine learning and AI applications to improve signal accuracy [34]. - Increased investor confidence is observed as THPX signal sources demonstrate reliability in dynamic market conditions, leading to a growing willingness to adopt this technology [35].

1. Report Industry Investment Rating No relevant content provided in the report. 2. Core Viewpoints - Ten - year Treasury bond futures main contract shows a long - signal at the daily level and the weekly level, with a neutral signal at the monthly level. The CSI 1000 has a short - signal at the daily level and neutral signals at the weekly and monthly levels [2][53]. - The net value of the multi - asset portfolio is 2.17, the net value of the Treasury bond arbitrage portfolio is 4.0, the long - term hedging signal persists, and there is no arbitrage signal. The net values of the 5 - year and 10 - year Treasury bond spot and hedge portfolios are also provided [2][45]. 3. Summary by Directory 3.1. Multivariate Asset Market Quick View 3.1.1. Market Price Changes - The Shanghai Composite Index closed at 3,295.06, up 0.56%. The CSI 1000 rose 1.85% to 5,939.50, while the SSE 50 fell 0.33% to 2,648.81. Among Treasury bonds, the 10 - year Treasury bond main contract decreased by 0.21% to 108.77. Commodity indexes generally showed an upward trend, with the Agricultural CFCI rising 1.54% to 158.43. In the international market, the Nasdaq Composite Index soared 6.73% to 17,382.94, and the Brent crude oil main contract dropped 1.75% to 65.83 [12]. 3.1.2. Sino - US Treasury Bond Interest Rates - US Treasury bond real yields decreased across different maturities from April 21 - 25, 2025. For example, the 10 - year real yield decreased from 2.20% to 2.02%. Chinese policy - based financial bond (CDB) and fixed - rate Treasury bond yields showed minor fluctuations during the same period [14][15]. 3.2. Strength - Weakness Relationship among Multivariate Assets 3.2.1. Strength - Weakness Relationship among Stocks - The ratios of the CSI 300 to the CSI 1000, the Nasdaq to the FTSE 100, the Nasdaq to the German DAX, and the Nasdaq to the Nikkei 225 are presented, reflecting the relative strength - weakness relationships among different stock indexes [17][19][21]. 3.2.2. Strength - Weakness Relationship among Commodities - The ratios of the CSI Commodity Index to the Metal Index, the Energy Index, the Agricultural Product Index, and the Chemical Index are provided, indicating the relative strength - weakness relationships among different commodity indexes [24][27][29][31]. 3.2.3. Strength - Weakness Relationship among Treasury Bonds - The ratios of Chinese Treasury bonds to US Treasury bonds and the long - short - term ratios of Chinese Treasury bonds are shown, reflecting the relative strength - weakness relationships among different Treasury bonds [33][34]. 3.2.4. Stock - Bond Strength - Weakness - The ratios of the CSI 300 to the Chinese Treasury bond net - price index and the Nasdaq to the US Treasury bond core bond are presented, showing the relative strength - weakness relationship between stocks and bonds [36][37]. 3.2.5. Bond - Commodity Strength - Weakness - The relationship between the copper - gold ratio and the 10 - year Treasury bond futures and the relationship between the gold - oil ratio and the US Treasury bond core bond are analyzed, reflecting the relative strength - weakness relationship between bonds and commodities [41][42]. 3.3. Multivariate Asset Signal Tracking and Simulated Net Value 3.3.1. One - Week Review of Multivariate Asset Signals - From April 21 - 25, 2025, the corn main contract had a long - signal at the 60 - minute level on April 21, and the 10 - year Treasury bond main contract had long - signals at the 60 - minute level every day during this period [1][44]. 3.3.2. Multivariate Asset Simulated Net Value - **Treasury Bond Strategy Simulated Net Value Tracking**: The net value of the Treasury bond arbitrage portfolio is 4.0, with no arbitrage signal and a persistent long - term hedging signal. The net values of the 5 - year Treasury bond spot and hedge portfolios are 1.2241 and 1.2065 respectively, and those of the 10 - year Treasury bond spot and hedge portfolios are 1.2736 and 1.2563 respectively [45]. - **Multivariate Asset Portfolio Simulated Net Value Tracking**: The net value of the multi - asset portfolio is 2.17. The initial capital is 10 million RMB, with 10 lots per futures transaction. The latest signals show that the 10 - year Treasury bond futures main contract has long - signals at the daily and weekly levels and a neutral signal at the monthly level, while the CSI 1000 has a short - signal at the daily level and neutral signals at the weekly and monthly levels [2][53].