Core Viewpoint - The article discusses the RSR (Relative Strength Ratio) research, emphasizing the need for a more accurate calculation method that considers both upward movements and pullbacks, rather than solely focusing on price increases [1]. Individual Stock RSR Indicator Setup - The first step involves setting up the basic formulas, SSV and RSL, which are essential for calculating the RSR [2]. - The second step requires creating extended data to compute the two basic formulas, ensuring that the sequence numbers align correctly [2][3]. - The final step is to create the "RSR Individual Stock" sub-graph indicator by copying specific code into the formula manager, which calculates the average of SSV and RSL [7][8]. Industry RSR Indicator Setup - The setup process for the industry RSR is similar to that of individual stocks, starting with selecting two empty data rows for SSV and RSL [9]. - The second step involves creating the "RSR Industry" sub-graph indicator using a similar code structure as the individual stock setup [14]. - Custom sector settings can be created by accessing the custom sector management interface within the software [15][16]. Updates and Changes - The latest update distinguishes itself by using SSV and RSL as the foundational calculation formulas, focusing on cost deviation, while RSV is based on the relative proportion of price increases and decreases [19].

Core Viewpoint - The article discusses the challenges and complexities of using quantitative methods in stock selection, particularly focusing on the difficulties of translating chart patterns into formulas and the advantages of using indicators for more effective modeling [1][3][4]. Group 1: Challenges of Chart Patterns - Many investors start their quantitative journey by trying to convert chart patterns into formulas, believing that certain patterns have high success rates [1]. - Describing chart patterns with formulas is difficult and often leads to complex conditions that do not yield the desired results, highlighting the subjective nature of pattern interpretation [3]. - The majority of stock selection formulas in the market rely on a combination of chart patterns and moving averages, reflecting a common understanding among investors [3]. Group 2: Advantages of Indicators - Indicators are seen as a more advanced method of describing stock characteristics, as they extract specific features from raw data, providing a more abstract and statistical perspective [3][4]. - The effectiveness of quantitative modeling lies in its ability to combine multiple indicators to create a coherent model, which is more efficient than relying solely on chart patterns [4]. - Successful quantitative modeling requires a clear understanding of the underlying logic and the appropriate characteristics to describe, emphasizing a structured approach to building models [4].

Core Insights - The article emphasizes the importance of selecting the right stock trading app in the digital investment era, highlighting that the monthly active users of Chinese securities apps have surpassed 166 million, with a penetration rate of 15.46% [1] Group 1: Key Features of Leading Stock Trading Apps - Sina Finance App is recognized for its comprehensive capabilities, integrating real-time data, intelligent analysis, rapid trading, and social insights, making it a preferred choice for professional investors [2] - The app covers over 40 global markets, including A-shares, Hong Kong stocks, US stocks, futures, foreign exchange, and precious metals, with a data refresh speed of 0.03 seconds and exclusive access to Nasdaq Level 2 data [3] - The built-in "Xina AI Assistant" can condense a 5,000-word annual report into a 300-word summary, highlighting risk and opportunity points with color coding [3] - The app supports a distributed trading gateway capable of handling 120,000 concurrent transactions per second, maintaining zero lag during market turbulence [3] - The integration of social media insights from Weibo finance influencers creates a dynamic loop of information, analysis, and trading, with 82% of community-certified analysts filtering out 99% of noise [3] Group 2: Comparative Analysis of Other Stock Trading Apps - Tonghuashun is favored for cross-platform trading, covering 90% of brokers, and features a natural language search for stock selection [4] - Dongfang Caifu aims to build an intelligent internet wealth management ecosystem, offering comprehensive services from market data to community engagement [5] - Futu NiuNiu is a licensed brokerage platform that provides free Level 2 US stock data and supports pre-market and after-hours trading, making it a tool for cross-border investors [6] - Xueqiu has evolved into a successful investment community, offering user-generated content and a transparent display of real trading strategies [8] - Dazhihui specializes in high-frequency trading with a millisecond response time, suitable for A-share traders [9] - Tongdaxin focuses on technical analysis, providing a rich library of indicators and supporting Python strategy backtesting [10] Group 3: Recommendations Based on User Needs - For users seeking a single app, the Sina Finance App is recommended for its global monitoring, intelligent tools, and social validation, serving as an efficient navigation tool through market complexities [12] - For cross-border investors, Futu NiuNiu is highlighted as a strong choice for Hong Kong and US stock investments, particularly for Chinese investors [14] - Technical analysis enthusiasts may find Tongdaxin and Dazhihui suitable due to their extensive indicator offerings [14] - For community engagement, Xueqiu and Dongfang Caifu provide substantial user-generated content, although caution is advised regarding information verification [14] - Institutional and professional investors may prefer Wind Stock for its comprehensive data, despite its high cost [14]

Core Viewpoint - The article discusses the development and implementation of the RSR (Relative Strength Ratio) indicator, emphasizing the importance of a comprehensive strength calculation that considers both upward movements and pullbacks, rather than just price increases [1]. Individual Stock RSR Indicator Setup - The first step involves setting up the basic formulas for RSV and VWAP, which are essential for calculating the RSR [2]. - The second step requires creating extended data to compute the basic formulas, ensuring that the sequence numbers align correctly [3]. - The third step is to create the "RSR Individual Stock" sub-indicator, which averages the extended data from RSV and SSV, and must be named precisely to avoid errors [7][10]. Industry RSR Indicator Setup - The industry RSR has been modified to only use SSV data for stability in trend investment, discarding the RSV data due to its high sensitivity in industry rankings [11]. - The setup process for the industry RSR involves creating two extended data outputs, ensuring they do not conflict with existing formulas [11][12]. - The final step is to create the "RSR Industry" sub-indicator, which directly uses SSV1 output without averaging, focusing on stability during bullish market conditions [14][15]. Custom Sector Setup - Instructions are provided for setting up custom sectors within the trading software, allowing users to create identifiable folders for their analysis [16]. - The article outlines how to display sector data and manage custom sectors effectively, including importing data into newly created folders [18][19]. System Settings - The article mentions the need to adjust system settings to facilitate the research of industry classifications, ensuring that the necessary data is displayed correctly [20].

Core Viewpoint - The article discusses the construction of a true cost price curve using cumulative transaction amount divided by cumulative transaction volume, emphasizing its accuracy compared to traditional methods [1]. Group 1: Volume-Weighted Average Price (VWAP) - The article introduces a new formula for calculating VWAP using cumulative transaction amount (AMO) and price (C), which is expressed as SUM(AMO*C,N)/SUM(AMO,N) [1]. - This VWAP formula is designed to be more sensitive and reliable than traditional volume-weighted methods, especially when accounting for stock splits and other corporate actions [1]. Group 2: Standardized Strength Calculation - A new standardized strength formula is proposed, replacing the arithmetic mean price with the volume-weighted price, resulting in VWAP and standard deviation (STDD) calculations [1]. - Two output methods are provided: one using the weighted price as the divisor for deviation and another using standard deviation for normalization [1]. Group 3: Relative Strength (RS) Calculation - The article extends the VWAP concept to calculate a relative strength line (RSLine), which is claimed to be more reasonable than popular moving average methods [4]. - The RS calculation is defined as CLOSE/INDEXC, with a volume-weighted RS (VWRS) formula introduced for enhanced accuracy [4]. Group 4: Output Comparison - The article notes that the output from the new calculations is consistent and stable when configured as a Relative Strength Ratio (RSR) [2]. - It highlights the effectiveness of using volume-weighted prices in producing reliable output compared to traditional methods [2].