Group 1: Real Estate Market Trends - The current new home prices have not yet reached the bottom, with second-hand home prices generally 25% to 40% lower than new homes, and continuing to decline. In April, first-tier cities saw a 0.2% month-on-month decrease in second-hand home prices, while second and third-tier cities experienced a 0.4% decline [1][3] - Concerns about a prolonged downturn similar to Japan's are unfounded, as China's real estate market is currently in an adjustment phase following rapid growth from 2015 to 2017. This adjustment does not equate to a market collapse, as cyclical recovery is expected [3] Group 2: Stock Market Insights - Both the stock and real estate markets exhibit cyclical behavior, with bull markets often emerging during periods of market despair. Despite recent index declines, underlying support mechanisms remain [4] - The presence of institutional investors in stocks does not guarantee profitability for retail investors, as institutional strategies may shift with market conditions. The focus should be on the trading behavior of institutions rather than mere participation [6] Group 3: Understanding Institutional Trading - Institutional trading is characterized by large volumes and discreet operations, making it essential to utilize quantitative analysis to uncover their true actions, such as accumulation or distribution of shares [8] - Indicators such as the density of orange bars (indicating active institutional trading) and blue circles (indicating potential washout tactics) can provide insights into institutional strategies. For instance, repeated downward movements may signal preparation for a significant upward movement [10][13] Group 4: Identifying Market Signals - To determine the end of a washout phase, it is crucial to analyze two sets of data: a shift from blue candlesticks to blue bars indicates a return of previously sold funds, while dense orange bars suggest concentrated institutional holdings [13] - Retail investors often face losses due to a lack of understanding of institutional trading behaviors. By interpreting data accurately, investors can avoid being shaken out of positions during volatile periods [15]