Core Viewpoint - Incrementum AG's annual report indicates that despite the surge in gold prices to a record $3,500 per ounce, the long-term bull market for gold is still in its early stages, with expectations of higher price increases in the latter half of this decade [1] Group 1: Price Predictions - The research team led by Ronald-Peter Stferle and Mark Valek forecasts that gold could reach $4,800 per ounce by 2030, with a potential "bull market scenario" pushing prices up to $8,900 due to rising inflation threats [1] - Since the initial prediction in 2020, gold prices have increased by 92%, yet its allocation in overall investment portfolios remains around 1% [1] Group 2: Market Dynamics - The report emphasizes that the current phase of the bull market is characterized by increasing media optimism, which could lead to a "mania phase" [1] - Although gold prices have performed well this year, they remain moderate compared to historical bull markets, with 22 new highs recorded as of April 30, compared to 43 last year [1] Group 3: Demand Drivers - Incrementum anticipates that investment demand will become a new driving force for gold prices, as investors seek to hedge against inflation and geopolitical uncertainties, despite current inflows into gold ETFs lagging behind stocks and bonds [1] - Central bank demand is highlighted as a significant support for gold prices, but the report suggests that the influx of Western financial investors is still awaited [1] Group 4: Economic Context - The report critiques the U.S. government's tightening policies, suggesting they may push the economy towards recession, which could ultimately benefit gold as the Federal Reserve is likely to lower interest rates in response to economic slowdowns [1] - Analysts warn that a weak dollar policy could undermine currency credibility and deter essential capital inflows, potentially leading to inflation and reduced purchasing power [2]

- The report introduces the "Caixin JinGong Three-Dimensional Sentiment Model," which is based on the Dow Theory's triple movement principle. It constructs a signal system from three dimensions: sentiment temperature, sentiment expectation, and sentiment concentration, corresponding to different market frequencies: high-frequency (days to weeks), medium-frequency (weeks to months), and low-frequency (months to years) [6][7][9] - The sentiment expectation dimension uses the futures basis rate and the inverse of the option's PCR (Put-Call Ratio) to reflect short-term market sentiment. The sentiment temperature dimension quantifies market fund activity using the main force buying rate. The sentiment concentration dimension measures the correlation of multiple assets in the A-share market using the first principal component variance contribution rate of the CITIC Level-3 industry index [7][8] - The model's application scenarios are diverse: it can serve as a risk warning tool, a risk preference indicator, or a guide for A-share equity position operations. High positions indicate low market risk, while low positions suggest high risk. The model helps investors control drawdowns in bear and volatile markets and optimize asset allocation [6][9] - The long-term performance of the Caixin JinGong Three-Dimensional Sentiment Strategy shows significant advantages over the HS300 holding strategy. From 2010 to 2025, the strategy achieved an annualized return of 6.0%, a maximum drawdown of 26.93%, and a Sharpe ratio of 0.3969, compared to the HS300's 0.69% annualized return, 46.50% maximum drawdown, and 0.1288 Sharpe ratio [6][12][14] - The strategy's performance in specific years (2011, 2013, 2015, 2018, 2022, 2023, and 2024) consistently shows strong risk control and return potential. For example, in 2011, the strategy's maximum drawdown was 13.45% compared to HS300's 31.19%, and its annualized return was -3.32% compared to HS300's -26.41% [17][20][23][27][31][35][39] - The model's core logic is to dynamically adjust asset positions based on market sentiment changes, effectively controlling drawdowns in bear and volatile markets. It is designed for risk warning rather than actively creating alpha returns, making it perform better than the benchmark in bear and volatile markets but often underperform in bull markets due to conservative position adjustments [6][15][40]