The year 2021 saw the peak in issuance of residential mortgage backed securities (MBS), at *** trillion U.S. dollars. Since then, MBS issuance has slowed, reaching *** trillion U.S. dollars in 2023. What are mortgage backed securities? A mortgage backed security is a financial instrument in which mortgages are bundled together and sold to investors. The idea is that the risk of these individual mortgages is pooled when they are packaged together. This is a sound investment policy, unless the foreclosure rate increases significantly in a short amount of time. Mortgage risk Since mortgages are loans backed by an asset, the house, the risk is often considered relatively low. However, the loan maturities are very long, sometimes decades, meaning lenders must factor in the risk of a shift in the economic climate. As such, interest rates on longer mortgages tend to be higher than on shorter loans. The ten-year treasury yield influences these rates, since it is a long-term rate that most investors accept as risk-free. Additionally, a decline in the value of homeowner equity could lead to a situation where the debtor is “underwater” and owes more than the home is worth.

Graph and download economic data for Treasury and Agency Securities: Mortgage-Backed Securities (MBS), All Commercial Banks (TMBACBW027NBOG) from 2009-07-01 to 2025-07-02 about mortgage-backed, agency, securities, Treasury, banks, depository institutions, and USA.

Mortgage Backed Security Market Outlook

The global mortgage-backed security (MBS) market size was valued at approximately $2.1 trillion in 2023 and is projected to reach $3.5 trillion by 2032, growing at a CAGR of 5.5%. A key driver of this growth is the increasing demand for mortgage-backed securities due to their ability to provide liquidity and diversify investment portfolios. The growth is further stimulated by favorable government policies and increased homeownership rates, which collectively bolster the issuance of new MBS.

One of the primary growth factors for the MBS market is the low-interest-rate environment, which has persisted over recent years. This scenario has encouraged borrowing and refinancing activities, leading to a higher number of mortgages that can be securitized. Moreover, the stability and relatively lower risk associated with MBS compared to other investment vehicles make them an attractive option for institutional investors. Additionally, advancements in financial technology have streamlined the process of bundling and selling these securities, increasing market efficiency.

Another significant factor contributing to the expansion of the MBS market is the role of government-sponsored enterprises (GSEs) such as Fannie Mae, Freddie Mac, and Ginnie Mae. These GSEs guarantee a significant portion of the residential MBS, providing a safety net that minimizes risk for investors. The support from these entities ensures a continuous and reliable flow of investment into the housing sector, which in turn stimulates further securitization of mortgages. Moreover, government policies aimed at bolstering housing finance systems in emerging markets are expected to create additional opportunities for growth.

The diversification of mortgage products, including the rise in demand for commercial mortgage-backed securities (CMBS), is another driving force for the market. Commercial real estate has shown robust growth, and investors are increasingly looking towards CMBS as a way to gain exposure to this sector. The structured nature of these securities, offering tranches with varying risk and return profiles, allows investors to tailor their investment strategies according to their risk tolerance.

In the context of the MBS market, Lenders Mortgage Insurance (LMI) plays a crucial role in facilitating homeownership, especially for borrowers who are unable to provide a substantial down payment. LMI is a type of insurance that protects lenders against the risk of borrower default, allowing them to offer loans with lower down payment requirements. This insurance is particularly significant in markets where home prices are high, and saving for a large deposit is challenging for many potential homeowners. By mitigating the risk for lenders, LMI enables more individuals to enter the housing market, thereby supporting the overall growth of mortgage-backed securities. As a result, LMI not only aids in increasing homeownership rates but also contributes to the liquidity and stability of the housing finance system.

Type Analysis

The mortgage-backed security market is bifurcated into Residential MBS and Commercial MBS. Residential MBS (RMBS) dominate the market due to the larger volume of residential mortgages compared to commercial ones. RMBS are typically backed by residential loans, including home mortgages, and are considered less risky. They offer a steady income stream to investors through mortgage payments made by homeowners. The demand for RMBS is bolstered by the high rate of homeownership and the continuous flow of new mortgages.

On the other hand, Commercial MBS (CMBS) are seeing increased traction due to their attractive yields and the growth of the commercial real estate sector. CMBS are backed by loans on commercial properties such as office buildings, retail centers, and hotels. They offer investors exposure to the commercial property market, which is often less correlated with the residential real estate market, providing an additional layer of diversification. The complexity and higher risk associated with CMBS attract sophisticated investors looking for higher returns.

Within RMBS, the market is further segmented into agency RMBS and non-agency RMBS. Agency RMBS are guaranteed by GSEs, making them more secure and attractive to risk-averse investors. Non-agency RMBS, though not backed by GSEs, offer higher yields and are appealing to investors with a higher risk appetite. The interplay betw

Graph and download economic data for Treasury and Agency Securities: Mortgage-Backed Securities (MBS), All Commercial Banks (H8B1301NCBCQG) from Q4 2009 to Q2 2025 about mortgage-backed, agency, securities, Treasury, banks, depository institutions, and USA.

Rambus reported $0 in Loan Capital for its fiscal quarter ending in March of 2025. Data for Rambus | RMBS - Loan Capital including historical, tables and charts were last updated by Trading Economics this last July in 2025.

MBS Market Outlook

The global mortgage-backed securities (MBS) market size was valued at approximately $2.5 trillion in 2023 and is projected to reach around $3.8 trillion by 2032, growing at a compound annual growth rate (CAGR) of 4.5%. This growth is driven by factors such as increasing demand for diversified investment products, the stability of real estate markets in key regions, and the rising involvement of government-sponsored entities in the securitization process.

One of the primary growth factors of the MBS market is the increasing demand for investment diversification. Investors are continually on the lookout for stable yet lucrative investment opportunities, and MBS provides a unique avenue by offering a relatively safer investment backed by real estate assets. The combination of regular income streams and the potential for capital appreciation makes MBS an attractive option for both institutional and retail investors. Furthermore, the growing sophistication of financial markets globally ensures better transparency and understanding of MBS products, thereby boosting investor confidence.

Another significant growth factor is the stability and growth of the real estate market, particularly in developed regions such as North America and Europe. As the real estate market continues to show robust growth, the underlying assets backing these securities become more valuable and stable, thus enhancing the attractiveness of MBS. Additionally, favorable regulatory frameworks in these regions have facilitated the smooth functioning and growth of the MBS market. Government regulations often play a pivotal role in providing the necessary safeguards and ensuring market stability, which in turn attracts more investors.

The increasing involvement of government-sponsored entities such as Fannie Mae, Freddie Mac, and Ginnie Mae in the United States has also significantly contributed to the growth of the MBS market. These entities not only provide a level of security and credibility but also ensure a steady supply of MBS products in the market. Their active participation helps in maintaining market liquidity and provides a safety net for investors, making the MBS market more resilient to economic downturns. Additionally, similar government-backed initiatives in other regions are expected to drive the market further in the coming years.

From a regional perspective, North America remains the largest market for MBS, driven primarily by the well-established real estate and financial markets in the United States. The presence of major market players and a favorable regulatory environment further solidify its leading position. Europe follows closely, with increasing investments in real estate and government initiatives to boost the financial markets. The Asia Pacific region is expected to witness the highest growth rate, owing to rapid urbanization, increasing disposable incomes, and favorable government policies aimed at boosting the housing sector. Latin America and the Middle East & Africa regions are also expected to show steady growth, driven by improving economic conditions and increasing investment activities.

Type Analysis

The MBS market can be segmented by type into Residential MBS (RMBS) and Commercial MBS (CMBS). Residential Mortgage-Backed Securities (RMBS) are typically backed by residential real estate properties. These securities are attractive to investors due to the low default rates associated with residential properties. The demand for RMBS is particularly high in regions with stable and growing residential real estate markets, such as North America and Europe. The growing trend of homeownership, along with favorable mortgage rates, has significantly contributed to the growth of the RMBS segment. Additionally, the increasing availability of data and analytics has improved the risk assessment associated with RMBS, making it a more attractive investment option.

Commercial Mortgage-Backed Securities (CMBS) are backed by commercial real estate properties, such as office buildings, shopping malls, and hotels. The performance of CMBS is closely tied to the health of the commercial real estate market. With the recovery of the global economy post the COVID-19 pandemic, the commercial real estate market has shown significant signs of recovery, thereby boosting the demand for CMBS. Investors are increasingly looking at CMBS as a means to diversify their portfolios, given the attractive yields and potential for capital appreciation. Moreover, the increasing trend of mixed-use developments and smart cities is expected to drive the demand for CMBS in the coming years.&

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

RMBS Stock: A Bright Investment or a Bubble Waiting to Burst?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Rambus (RMBS) Ready to Ram Through Resistance?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Rambus reported $29.19M in Debt for its fiscal quarter ending in March of 2025. Data for Rambus | RMBS - Debt including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Graph and download economic data for 66) Over the Past Three Months, How Have the Terms Under Which Non-Agency Rmbs Are Funded Changed?| A. Terms for Average Clients | 4. Collateral Spreads over Relevant Benchmark (Effective Financing Rates). | Answer Type: Tightened Considerably (ALLQ66A4TCNR) from Q4 2011 to Q1 2025 about collateral, change, funds, financing, spread, 3-month, average, rate, and USA.

Following the drastic increase directly after the COVID-19 pandemic, the delinquency rate started to gradually decline, falling below *** percent in the second quarter of 2023. In the second half of 2023, the delinquency rate picked up, but remained stable throughout 2024. In the first quarter of 2025, **** percent of mortgage loans were delinquent. That was significantly lower than the **** percent during the onset of the COVID-19 pandemic in 2020 or the peak of *** percent during the subprime mortgage crisis of 2007-2010. What does the mortgage delinquency rate tell us? The mortgage delinquency rate is the share of the total number of mortgaged home loans in the U.S. where payment is overdue by 30 days or more. Many borrowers eventually manage to service their loan, though, as indicated by the markedly lower foreclosure rates. Total home mortgage debt in the U.S. stood at almost ** trillion U.S. dollars in 2024. Not all mortgage loans are made equal ‘Subprime’ loans, being targeted at high-risk borrowers and generally coupled with higher interest rates to compensate for the risk. These loans have far higher delinquency rates than conventional loans. Defaulting on such loans was one of the triggers for the 2007-2010 financial crisis, with subprime delinquency rates reaching almost ** percent around this time. These higher delinquency rates translate into higher foreclosure rates, which peaked at just under ** percent of all subprime mortgages in 2011.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Is Rambus (RMBS) Stock a Good Investment?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Rambus reported $6.97B in Market Capitalization this July of 2025, considering the latest stock price and the number of outstanding shares.Data for Rambus | RMBS - Market Capitalization including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Graph and download economic data for 62) Over the Past Three Months, How Have the Terms Under Which Agency Rmbs Are Funded Changed?| A. Terms for Average Clients | 4. Collateral Spreads over Relevant Benchmark (Effective Financing Rates). | Answer Type: Remained Basically Unchanged (ALLQ62A4RBUNR) from Q4 2011 to Q1 2025 about collateral, change, funds, agency, financing, spread, 3-month, average, rate, and USA.

Rambus reported $719.46M in Current Assets for its fiscal quarter ending in March of 2025. Data for Rambus | RMBS - Current Assets including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Rambus reported $60.3M in Net Income for its fiscal quarter ending in March of 2025. Data for Rambus | RMBS - Net Income including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Bankrate is the market leading online aggregator and publisher of market rates, including mortgage rates, in the U.S. markets.

description: Treasury plans to sell up to $10 billion of securities per month, subject to market conditions. This is in addition to principal paydowns (currently ranging between $2 and $4 billion per month). If the sales proceeded at the full $10 billion per month, the portfolio would be unwound in whole over approximately one year, depending on future rates of prepayments. If market conditions change and Treasury slows asset sales, it is possible that the unwind will take a longer period of time. Dealer scorecard shows a ranking of buyers of MBS securities by amount purchased monthly and overall.; abstract: Treasury plans to sell up to $10 billion of securities per month, subject to market conditions. This is in addition to principal paydowns (currently ranging between $2 and $4 billion per month). If the sales proceeded at the full $10 billion per month, the portfolio would be unwound in whole over approximately one year, depending on future rates of prepayments. If market conditions change and Treasury slows asset sales, it is possible that the unwind will take a longer period of time. Dealer scorecard shows a ranking of buyers of MBS securities by amount purchased monthly and overall.

Rambus reported $103.46M in Operating Expenses for its fiscal quarter ending in March of 2025. Data for Rambus | RMBS - Operating Expenses including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Graph and download economic data for 62) Over the Past Three Months, How Have the Terms Under Which Agency RMBS Are Funded Changed?| A. Terms for Average Clients | 4. Collateral Spreads Over Relevant Benchmark (Effective Financing Rates). | Answer Type: Tightened Considerably (SFQ62A4TCNR) from Q4 2011 to Q2 2025 about collateral, change, funds, agency, financing, spread, 3-month, average, rate, and USA.