Group 1 - The core viewpoint is that the asset pricing paradigm is undergoing a profound transformation, shifting from a static world based on certainty to a dynamic ecosystem based on uncertainty [1][2] - The financial market is transitioning from a Newtonian mechanical worldview to a quantum characteristic market, where asset prices exhibit both "particle" (real value based on cash flow) and "wave" (narrative value based on consensus) properties [2][3] - The new pricing paradigm emphasizes the importance of technology, new productivity, and collective consensus as key factors in asset valuation [12][16] Group 2 - The three pillars of asset pricing are changing: the curvature of pricing in time and space has been altered, the definition of value is expanding from "atomic value" to "bit value," and the traditional risk-return equation is being rewritten [2][3][10] - Investors need to transition from being "valuation accountants" to "paradigm geographers," utilizing tools beyond financial statements and discount models to include technology roadmaps and narrative networks [4][5] - Traditional valuation models like DCF and DDM are losing their explanatory power due to high uncertainty and sensitivity to assumptions, making them less applicable to high-growth or volatile companies [6][7][8] Group 3 - The classic economic cycle models, such as the Merrill Lynch Clock, have become ineffective due to structural changes in the macroeconomic environment, requiring a shift in asset allocation strategies [8][9] - The concept of "safe assets" is diminishing as traditional safe havens like government bonds face challenges from fiscal credit erosion and the politicization of monetary policy [10][11] - The definition of safety is evolving from unconditional trust in sovereign credit to seeking systemic resilience in extreme situations, with gold and cryptocurrencies emerging as new forms of value storage [10][12] Group 4 - The new asset pricing paradigm should focus on the sources of value creation in the digital economy, including technological advancements, new productivity, and collective consensus [12][13][14] - The A-share market is becoming a battleground for new productivity and valuation reassessment, moving away from traditional macroeconomic cycles towards sectors aligned with national strategic intentions [16] - The U.S. stock market is evolving into a core pricing arena for global technological innovation, with tech giants being valued not just on current cash flows but also on their potential as platform-based options for future infrastructure [16][17] Group 5 - Gold's role is shifting from a simple inflation hedge to a decentralized consensus vehicle, reflecting global capital's distrust in fiat currency systems [17] - Cryptocurrencies represent an extreme experiment in asset pricing, relying on technology architecture and global consensus rather than traditional fundamentals [18] - The asset allocation strategy must evolve from passive tracking of economic cycles to proactive identification of key sectors representing technological progress and new productivity [18][19]

Core Viewpoint - The article emphasizes the need for a paradigm shift in asset pricing and investment management, moving from traditional models to a more dynamic and adaptive approach that considers the non-linear relationships between assets and their roles within a portfolio [4][11][18]. Group 1: Asset Pricing Theory - Traditional asset pricing theories, such as the Capital Asset Pricing Model (CAPM), are based on strict assumptions of market efficiency and rational investors, which fail to explain market anomalies like momentum and value effects [4][12]. - The article argues that asset prices are influenced not only by their expected returns and risks but also by their roles in the overall investment portfolio and the dynamic relationships with other assets [4][11]. Group 2: Investment Strategy - The new investment philosophy focuses on systematically and proactively enhancing the risk-adjusted returns of investment portfolios rather than merely seeking absolute returns [4][11]. - The investment framework proposed is not about finding the "true value" of assets but about creating an adaptive system that can achieve stable growth across different market environments [7][16]. Group 3: Multi-Asset Allocation - The article discusses the importance of low correlation among assets in a multi-asset allocation strategy, which can significantly reduce the probability of negative monthly returns [22][23]. - A two-stage strategy combining CPPI (Constant Proportion Portfolio Insurance) and risk budgeting is suggested to enhance traditional methodologies and improve risk-adjusted returns [17][23]. Group 4: Market Dynamics - The article highlights that the correlation between assets is dynamic and can change with market conditions, which poses risks to traditional asset allocation frameworks that rely on historical data [12][15]. - The concept of "free lunch" in asset allocation, derived from low correlation, may diminish as market environments evolve, necessitating a deeper understanding of the underlying factors driving asset correlations [15][18]. Group 5: Future of Asset Pricing - The future of asset pricing is seen as a transition from a focus on historical data to an understanding of technological trends, industry changes, and collective human behavior [34]. - The new asset pricing framework is described as a three-dimensional investment model centered around technological advancement, new productive forces, and consensus-driven narratives [18][28].

Core Insights - The investment landscape is undergoing profound changes driven by "technological advancement, new productive forces, and collective consensus" as the new paradigm for asset pricing [2][3] - The traditional valuation models are becoming less effective, necessitating a shift towards quantitative discipline to translate qualitative insights into actionable investment strategies [2][3] Group 1: Investment Philosophy - The investment approach emphasizes the balance between rational calculation and human insight, seeking optimal solutions through a dynamic equilibrium [1][2] - A strategic direction is established through qualitative research, which serves as a guiding compass for investment decisions [2] Group 2: Quantitative Tools - A precise navigation system is essential for executing investment strategies, consisting of two main components: CPPI technology for dynamic risk control and a risk budgeting model for resource allocation [3] - The CPPI technology includes mechanisms for dynamic adjustment of risk exposure based on net value performance and automatic asset allocation during market fluctuations [3] Group 3: Balancing Act - The essence of investment management lies in finding a delicate balance across multiple dimensions, including short-term versus long-term coordination and maintaining flexibility while adhering to core strategies [4][7] - The investment model aims to filter out short-term noise while capturing long-term signals, ensuring that the strategy remains robust against market volatility [6] Group 4: Communication and Adaptation - Clear communication with investors is prioritized, with regular reports to explain performance and investment rationale, helping to set rational expectations [8] - The investment process involves a step-by-step adjustment strategy to minimize market impact while ensuring that asset selection aligns with emerging productive forces [8] Group 5: Continuous Improvement - The investment methodology focuses on building a self-evolving system that withstands the test of time, with quantitative tools playing a crucial role in achieving investment objectives [9] - Each analysis, model optimization, and allocation adjustment is part of a continuous search for better solutions, emphasizing a sustainable approach over chasing short-term trends [9]