Group 1: Current State of the US Real Estate Market - The US real estate market is primarily driven by existing home sales, with new home sales accounting for less than 20% of total transactions. Since 2023, home sales have been sluggish due to high interest rates, with existing home sales dropping to levels not seen since the 2009 financial crisis, and new home sales returning to pre-pandemic levels [2][8] - Existing home inventory is low, while new home inventory faces significant liquidation pressure. The "rate lock effect" has suppressed market liquidity, leading to low demand and high prices in the existing home market, while the new home market is characterized by low sales and high inventory, resulting in extended liquidation periods [2][7] - Housing investment's contribution to GDP has decreased to around 4%, while housing services consumption accounts for 12% of GDP, indicating its critical role in driving economic activity [2][15] Group 2: Housing Prices and Affordability - Post-pandemic, US housing prices have increased significantly, outpacing household income and rent growth by 19 percentage points and 17 percentage points, respectively, leading to higher mortgage costs and increased rental attractiveness [3][19] - The proportion of household income spent on housing has risen from approximately 15% to around 25%, significantly constraining consumer spending power [3][21] - The average mortgage repayment period has extended from 65 months to about 77 months since 2021, reflecting decreased affordability for homebuyers [3][22] Group 3: Mortgage Rates and Influencing Factors - High mortgage rates are primarily driven by elevated 10-year Treasury yields and MBS spreads that cannot decline further. Despite the Federal Reserve's rate cuts, the 30-year mortgage rate remains high at 6.01% due to persistent high Treasury yields and low refinancing activity [4][47] - The MBS yield is closely tied to the 10-year Treasury yield, with a correlation of 98%. Factors affecting MBS spreads include credit risk premiums and the Federal Reserve's MBS purchasing activities [4][32] Group 4: Impact of Trump's New Policies - The housing purchase power index has dropped to a historical low due to rising home prices and mortgage rates, which have significantly increased housing costs relative to income [5][50] - Trump's administration aims to implement targeted real estate policies to improve housing affordability and gain support from middle and low-income groups ahead of the midterm elections. However, the effectiveness of these policies remains uncertain [5][58] - Key proposals include allowing transferable mortgages, limiting large institutional purchases of homes, and purchasing $200 billion in MBS to lower mortgage rates. However, only the MBS purchase plan has been officially implemented, while other proposals face feasibility challenges [5][54][58]

Quantitative Models and Construction Methods Model Name: Net Liquidity - **Construction Idea**: Net liquidity is derived from the Federal Reserve's balance sheet, focusing on the core components of cash in circulation and bank reserves[2] - **Construction Process**: - Calculate net liquidity as total assets minus Treasury General Account (TGA) and reverse repos - Formula: $ \text{Net Liquidity} = \text{Total Assets} - \text{TGA} - \text{Reverse Repos} $ - This represents the base money supply under the money multiplier effect, directly determining the amount of money available for transactions and credit activities in the market[2][21] - **Evaluation**: Net liquidity effectively reflects the real available funds in the market, providing a clearer signal than total assets[31] Model Name: Federal Reserve Credit Support - **Construction Idea**: Federal Reserve credit support is based on the quality of collateral purchased by the Fed, aiming to enhance credit by buying lower-grade collateral[2] - **Construction Process**: - Construct the credit support indicator as the ratio of long-term government bonds, federal agency bonds, and mortgage-backed securities (MBS) to cash in circulation, reserves, and reverse repos - Formula: $ \text{Credit Support} = \frac{\text{Long-term Government Bonds} + \text{Federal Agency Bonds} + \text{MBS}}{\text{Cash in Circulation} + \text{Reserves} + \text{Reverse Repos}} $ - This indicator is smoothed and compared year-over-year to identify the direction of credit support changes[2][42] - **Evaluation**: The credit support indicator is significantly negatively correlated with credit spreads, indicating its effectiveness in reducing default risk in the economy[42] Model Name: Fed Sentiment Index - **Construction Idea**: The Fed Sentiment Index captures the sentiment of Federal Reserve officials' public statements to predict policy tendencies[3] - **Construction Process**: - Use Natural Language Processing (NLP) to analyze the sentiment of Fed officials' speeches, interviews, tweets, etc. - Assign scores ranging from extremely dovish to extremely hawkish - Calculate the total sentiment score daily to provide timely and comprehensive interpretations of Fed communication[57][59] - **Evaluation**: The Fed Sentiment Index improves the accuracy of predicting federal funds rates and bond yields, offering better differentiation for the S&P 500 compared to low-frequency document signals[59] Model Name: Market Implied Rate - **Construction Idea**: The market implied rate tracks the market's expectations of future interest rate changes based on federal funds rate futures contracts[3] - **Construction Process**: - Calculate the implied rate as $ 100 - \text{futures price} $ - Focus on the price difference between futures contracts maturing in the next month and those maturing in the month of the upcoming FOMC meeting - Smooth the quarterly differences to identify marginal changes in market expectations[68][72] - **Evaluation**: The market implied rate indicator leads actual policy rate adjustments, providing early signals of policy shifts[72] Model Name: Announcement Surprise - **Construction Idea**: Announcement surprise captures the unexpected impact of FOMC meeting decisions on market expectations[3] - **Construction Process**: - Use the price changes of federal funds rate futures contracts maturing three months after the meeting to calculate the difference between actual and implied rate changes - Sample high-frequency data 10 minutes before and 20 minutes after the meeting to precisely capture the policy expectation gap[74][75] - **Evaluation**: Announcement surprise effectively identifies the unexpected tightening or easing of Fed policies, with significant impacts on bond yields[74] Model Backtest Results Net Liquidity - **Annualized Excess Return**: 5.1% relative to S&P 500 equal-weight benchmark[92] - **Annualized Excess Return**: 7.2% relative to Nasdaq 100 equal-weight benchmark[92] - **Maximum Drawdown Reduction**: 15% for S&P 500, 31% for Nasdaq 100[92] Federal Reserve Credit Support - **Annualized Sharpe Ratio**: Enhanced for most assets during periods of increased credit support[48] Fed Sentiment Index - **Annualized Excess Return**: Significant differentiation for S&P 500 returns in hawkish vs. dovish sentiment periods[61] Market Implied Rate - **Annualized Excess Return**: Effective in predicting policy shifts, leading actual rate adjustments[72] Announcement Surprise - **Bond Yield Impact**: Higher future bond yields in unexpected easing scenarios compared to unexpected tightening scenarios[76] Quantitative Factors and Construction Methods Factor Name: Net Liquidity - **Construction Idea**: Derived from the Federal Reserve's balance sheet, focusing on cash in circulation and bank reserves[2] - **Construction Process**: - Calculate net liquidity as total assets minus TGA and reverse repos - Formula: $ \text{Net Liquidity} = \text{Total Assets} - \text{TGA} - \text{Reverse Repos} $ - This represents the base money supply under the money multiplier effect, directly determining the amount of money available for transactions and credit activities in the market[2][21] - **Evaluation**: Net liquidity effectively reflects the real available funds in the market, providing a clearer signal than total assets[31] Factor Name: Federal Reserve Credit Support - **Construction Idea**: Based on the quality of collateral purchased by the Fed, aiming to enhance credit by buying lower-grade collateral[2] - **Construction Process**: - Construct the credit support indicator as the ratio of long-term government bonds, federal agency bonds, and MBS to cash in circulation, reserves, and reverse repos - Formula: $ \text{Credit Support} = \frac{\text{Long-term Government Bonds} + \text{Federal Agency Bonds} + \text{MBS}}{\text{Cash in Circulation} + \text{Reserves} + \text{Reverse Repos}} $ - This indicator is smoothed and compared year-over-year to identify the direction of credit support changes[2][42] - **Evaluation**: The credit support indicator is significantly negatively correlated with credit spreads, indicating its effectiveness in reducing default risk in the economy[42] Factor Name: Fed Sentiment Index - **Construction Idea**: Captures the sentiment of Federal Reserve officials' public statements to predict policy tendencies[3] - **Construction Process**: - Use NLP to analyze the sentiment of Fed officials' speeches, interviews, tweets, etc. - Assign scores ranging from extremely dovish to extremely hawkish - Calculate the total sentiment score daily to provide timely and comprehensive interpretations of Fed communication[57][59] - **Evaluation**: Improves the accuracy of predicting federal funds rates and bond yields, offering better differentiation for the S&P 500 compared to low-frequency document signals[59] Factor Name: Market Implied Rate - **Construction Idea**: Tracks the market's expectations of future interest rate changes based on federal funds rate futures contracts[3] - **Construction Process**: - Calculate the implied rate as $ 100 - \text{futures price} $ - Focus on the price difference between futures contracts maturing in the next month and those maturing in the month of the upcoming FOMC meeting - Smooth the quarterly differences to identify marginal changes in market expectations[68][72] - **Evaluation**: Leads actual policy rate adjustments, providing early signals of policy shifts[72] Factor Name: Announcement Surprise - **Construction Idea**: Captures the unexpected impact of FOMC meeting decisions on market expectations[3] - **Construction Process**: - Use the price changes of federal funds rate futures contracts maturing three months after the meeting to calculate the difference between actual and implied rate changes - Sample high-frequency data 10 minutes before and 20 minutes after the meeting to precisely capture the policy expectation gap[74][75] - **Evaluation**: Effectively identifies the unexpected tightening or easing of Fed policies, with significant impacts on bond yields[74] Factor Backtest Results Net Liquidity - **Annualized Excess Return**: 5.1% relative to S&P 500 equal-weight benchmark[92] - **Annualized Excess Return**: 7.2% relative to Nasdaq 100 equal-weight benchmark[92] - **Maximum Drawdown Reduction**: 15% for S&P 500, 31% for Nasdaq 100[92] Federal Reserve Credit Support - **Annualized Sharpe Ratio**: Enhanced for most assets during periods of increased credit support[48] Fed Sentiment Index - **Annualized Excess Return**: Significant differentiation for S&P 500 returns in hawkish vs. dovish sentiment periods[61] Market Implied Rate - **Annualized Excess Return**: Effective in predicting policy shifts, leading actual rate adjustments[72] Announcement Surprise - **Bond Yield Impact**: Higher future bond yields in unexpected easing scenarios compared to unexpected tightening scenarios[76]