Welcome to US Market Research, where data-driven insights meet investment opportunity. I’m Carlos Jimenez, and I’ve created this platform with a clear mission: to transform complex market data into clear, actionable intelligence that empowers your investment decisions.
US Market Research website delivers a comprehensive daily analysis of financial market conditions, with a primary focus on the S&P 500. Through rigorously tested models and in-depth analysis, the goal is to help you understand market trends and identify potential opportunities. While the core focus is the S&P 500, here I also want to provide valuable insights on other indices, sectors, and individual stocks when our models indicate significant developments worth your attention.
To ensure you stay ahead of market movements, this dashboard updates daily before the New York market opens, providing you with timely insights drawn from trusted sources including FRED, the US Treasury Website, CBOE website, and Yahoo Finance. This carefully curated data powers all the analysis you will see in this website, helping you make more informed investment choices in an ever-changing market landscape.
Carlos Jimenez: Welcome to my website, your free resource for financial market data, analysis, and insights. Currently, I work as a Senior Manager in AI & Data at Ernst & Young LLP, helping banks and insurance companies implement GenAI and traditional machine learning algorithms to optimize Risk and Wealth & Asset Management (WAM) processes. Here, I combine that expertise with my passion for making financial knowledge accessible and actionable for everyone. This is completely free!
Anne Pro: is the advanced AI financial analyst I developed and the creative force behind this site. Anne Pro transforms complex market data into clear, actionable insights, empowering investors at all levels to make smarter, faster decisions. From trends to technical analysis, Anne Pro ensures every piece of content is accurate, insightful, and easy to understand.
Explore the following Key Sections:
Global Overview: Gain actionable insights into market trends and opportunities across asset classes, powered by real-time data and advanced financial market analysis from our Large Language Model (LLM).
Volatility Lab: Explore unique Implied Volatility (IV) analytics based on PUT options data, offering innovative perspectives on market sentiment and risk assessment.
Technical Analysis: Uncover trends and momentum insights for major indices and sectors to anticipate market movements effectively.
drawdowns Analysis: Statistical analysis of the Drawdowns in mayor indices.
Macroeconomics: Access critical US economic indicators and government bond data for a comprehensive macroeconomic perspective.
Option Lab: Analyze Gamma Exposure (GEX) to understand the impact of options positioning on asset prices across indices and single names.
Machine Learning: Utilize cutting-edge ML models for forecasting and advanced analytics to enhance market strategy precision.
After creating this website, on a daily basis, Anne Pro also works on the following areas:
Value Investing Ideas: Explore carefully selected investment opportunities rooted in the principles of value investing. Anne Pro identifies undervalued stocks with strong fundamentals, empowering you to make confident, long-term investment decisions. Our goal is simple: hold positions for the long term and watch your wealth grow steadily.
Daily Option Trading Ideas: Stay ahead of the curve with daily, actionable trading ideas designed for options traders. Leverage data-driven insights and expert strategies to capitalize on market volatility, hedge risks, and generate income. Currently, we focus on 0DTE (zero days to expiration) strategies and income generation ideas to maximize your short-term trading potential.
News Letter: Start your day with our daily newsletter, delivered before the market opens. Packed with exclusive market updates, AI-driven analysis, and expert financial insights, it keeps you informed on the latest trends, investment opportunities, and strategic perspectives—all in one convenient email.
Thank you for visiting US Market Research, my personal free project, and being part of this journey. This project is my passion, my commitment, and my way of giving back by making quality financial analysis accessible to everyone. I’m confident these resources will help guide your investing decisions and elevate your financial strategies.
Join today!
Happy Investing
Carlos Jimenez, FRM – CFA Level III Candidate
The information on this website is updated once daily (around 6:00 am New York Time) and is provided solely for informational purposes.
The content on this website is not intended for any person in any jurisdiction where, due to nationality, residency, or other reasons, the publication or availability of this information is prohibited. It is the sole responsibility of individuals accessing this site to ensure compliance with all local laws and regulations regarding the use of this information. All content provided here is strictly intended for professional investors and should not be interpreted as advice or endorsement suitable for non-professional or retail investors.
No information or opinion expressed on this website constitutes an offer, solicitation, or recommendation to buy, sell, or dispose of any financial instrument or asset, nor to engage in any other financial transaction. The content here should not be considered as financial advice, investment recommendation, or a substitute for personalized advice from a licensed financial professional. I AM NOT A FINANCIAL ADVISOR.
Please be aware that Google Analytics will be tracking and analyzing activity on this website to help improve user experience and content quality.
As for the previous trading day, global stock markets have shown varied performance across different continents, reflecting a mix of economic conditions and investor sentiment.
YTD Performance Analysis
Oceania: Australia has shown a solid YTD performance with a return of 3.72%, while New Zealand lags slightly behind with a modest 0.90% gain. The region benefits from stable economic conditions and strong commodity exports, particularly from Australia.
Asia: South Korea leads with an impressive 8.92% YTD return, followed by Israel at 7.75%. Taiwan and Saudi Arabia also show positive growth at 3.45% and 3.08%, respectively. However, India is a notable underperformer with a decline of 4.81%, possibly due to economic challenges and geopolitical tensions. Japan and China have modest gains, reflecting mixed economic signals.
Europe: Italy and Germany are strong performers with YTD returns of 7.71% and 7.60%, respectively, driven by industrial resilience and export strength. France also shows robust growth at 7.40%. The UK and Spain have moderate gains, while the Netherlands stands out with a 5.54% increase. European markets benefit from easing energy concerns and resilient consumer spending.
Middle East: Saudi Arabia shows a positive YTD return of 3.08%, while Qatar has a slight decline of 0.61%, reflecting regional economic adjustments and oil price fluctuations.
North America: The United States has a YTD return of 3.15%, supported by strong corporate earnings and consumer spending. Canada follows with a 2.18% gain, benefiting from stable economic growth.
South America: Chile leads with a 6.02% YTD return, followed by Brazil at 4.98%. Peru and Mexico show modest gains. The region benefits from strong commodity exports and improving economic conditions.
Daily Performance Analysis
Oceania: Australia and New Zealand show daily gains of 2.31% and 0.81%, respectively, indicating short-term market strength driven by positive economic data.
Asia: Japan shows a strong daily gain of 1.74%, reflecting investor optimism. South Korea and Taiwan also perform well, with daily increases of 1.55% and 2.08%, respectively. India, however, continues to face challenges with a daily decline of 0.68%.
Europe: Germany and France lead with daily gains of 2.50% and 2.36%, respectively, driven by positive economic indicators. The UK and Spain also show strong daily performance, reflecting investor confidence.
Middle East: Saudi Arabia and Qatar show modest daily gains, indicating relative stability in the region.
North America: The United States and Canada show daily gains of 0.92% and 1.68%, respectively, supported by positive economic data and corporate earnings.
South America: Mexico and Chile lead with daily gains of 1.90% and 1.86%, respectively, reflecting strong investor sentiment.
Regional Insights and Strategic Recommendations
Opportunities: Asia, particularly South Korea and Israel, offers strong growth potential due to robust economic fundamentals. Europe, with Germany and Italy leading, also presents opportunities driven by industrial strength and consumer resilience.
Risks: India faces economic challenges, suggesting a cautious approach. The Middle East, while stable, may be affected by oil price volatility, warranting a defensive strategy.
Macroeconomic Factors: Inflation and interest rate policies remain key drivers of market performance. Geopolitical tensions, particularly in Asia, may impact investor sentiment.
For further insights and detailed data, additional reference materials, including charts and historical data, are available to support this analysis.
by: Anne Pro
AI Research Division
As for the previous trading day, the US stock market exhibited a diverse performance across various sectors, reflecting the complex interplay of macroeconomic factors and investor sentiment. In the Equities sector, the SPDR S&P 500 ETF Trust (SPY) posted a daily return of 0.91%, with a weekly gain of 3.58%. Over the month, SPY has appreciated by 3.15%, maintaining this growth over the quarter and year-to-date, indicating a steady upward trend. The Invesco QQQ Trust (QQQ), representing the technology-heavy Nasdaq, showed a daily increase of 0.59% and a robust weekly gain of 3.90%. Despite some volatility, QQQ has managed a monthly gain of 2.86%, suggesting strong investor confidence in the tech sector. The SPDR Dow Jones ETF Trust (DIA) and iShares Russell 2000 ETF (IWM) also demonstrated positive trends, with IWM notably outperforming with a daily return of 1.92% and a significant year-to-date increase of 3.91%.
In the Fixed Income sector, the SPDR Bloomberg 1-3 Month T-Bill ETF (BIL) remained stable with no daily return, reflecting its role as a safe haven in uncertain times. The iShares 1-3 Year Treasury Bond ETF (SHY) and iShares 7-10 Year Treasury Bond ETF (IEF) showed modest daily gains of 0.04% and 0.34%, respectively. However, they face challenges over the month with negative returns, highlighting the impact of rising interest rates. The iShares 20+ Year Treasury Bond ETF (TLT) showed a daily return of 0.89%, but a significant monthly decline of 3.14%, reflecting long-duration bond sensitivity to interest rate changes.
Commodities presented a mixed picture, with the United States Oil Fund LP (USO) experiencing a daily decline of 1.71% and a substantial monthly drop of 0.69%, indicating volatility in energy markets. Conversely, SPDR Gold Shares (GLD) and iShares Silver Trust (SLV) showed resilience, with daily gains of 1.55% and 1.56%, respectively, and positive year-to-date returns, driven by safe-haven demand amid geopolitical tensions. The United States Natural Gas Fund LP (UNG) faced significant challenges, with a daily decline of 3.33% and a notable monthly drop of 4.01%, reflecting oversupply and demand fluctuations.
In Real Estate, the Vanguard Real Estate ETF (VNQ) showed a robust daily return of 1.87% and a monthly gain of 4.51%, indicating investor confidence in the sector’s recovery. The Vanguard Global ex-U.S. Real Estate ETF (VNQI) and iShares Residential and Multisector Real Estate ETF (REZ) also showed positive daily returns, with VNQI facing challenges over the month due to global economic uncertainties.
Macroeconomic factors continue to shape market dynamics, with inflationary pressures and central bank policy adjustments influencing investor sentiment. The Federal Reserve’s interest rate hikes aim to curb inflation, impacting fixed-income returns and increasing volatility in equity markets. Geopolitical tensions and supply chain disruptions further contribute to commodity price fluctuations, affecting investor risk appetite.
Looking ahead, the market outlook remains cautiously optimistic, with potential opportunities in sectors poised for growth. In Equities, a balanced approach focusing on diversified ETFs like SPY and IWM is recommended, capitalizing on broad market exposure and small-cap growth potential. In Fixed Income, short-duration bonds such as SHY offer stability amid rising rates, while caution is advised for long-duration assets like TLT. Commodities present selective opportunities, with GLD and SLV offering hedges against inflation, while energy investments require careful consideration due to volatility. In Real Estate, VNQ offers potential upside as the sector recovers, supported by favorable macroeconomic conditions. Investors are advised to maintain a diversified portfolio, balancing sector strengths and weaknesses, and to remain vigilant of macroeconomic developments that may influence market trends.
Additional reference data can be found in the table accompanying the LLM-generated analysis.
by: Anne Pro
AI Research Division
| US Market Performance | |||||||
| YTD, Quarterly, Monthly, Weekly, and Daily Returns | |||||||
| Asset Class | Ticker | ETF Name | Year-to-Date | Quarter-to-Date | Month-to-Date | Week-to-Date | Daily |
|---|---|---|---|---|---|---|---|
| Real Estate | |||||||
| Real Estate | VNQ | Vanguard Real Estate ETF | 3.44% | 3.44% | 3.44% | 4.51% | 1.87% |
| Real Estate | VNQI | Vanguard Global ex-U.S. Real Estate ETF | 1.20% | 1.20% | 1.20% | 3.41% | 1.14% |
| Real Estate | REZ | iShares Residential and Multisector Real Estate ETF | 2.13% | 2.13% | 2.13% | 2.75% | 1.40% |
| Commodity | |||||||
| Commodity | USO | United States Oil Fund LP | 5.43% | 5.43% | 5.43% | −0.69% | −1.71% |
| Commodity | GLD | SPDR Gold Shares | 3.14% | 3.14% | 3.14% | 2.47% | 1.55% |
| Commodity | SLV | iShares Silver Trust | 4.12% | 4.12% | 4.12% | 3.09% | 1.56% |
| Commodity | DBA | Invesco DB Agriculture Fund | 1.13% | 1.13% | 1.13% | 0.98% | 1.20% |
| Commodity | DBC | Invesco DB Commodity Index Tracking Fund | 3.57% | 3.57% | 3.57% | 0.22% | −0.49% |
| Commodity | CPER | United States Copper Index Fund | 7.54% | 7.54% | 7.54% | −0.04% | −0.07% |
| Commodity | UNG | United States Natural Gas Fund LP | 4.23% | 4.23% | 4.23% | −4.01% | −3.33% |
| Fixed Income | |||||||
| Fixed Income | BIL | SPDR Bloomberg 1-3 Month T-Bill ETF | 0.20% | 0.20% | 0.20% | 0.07% | 0.00% |
| Fixed Income | SHY | iShares 1-3 Year Treasury Bond ETF | 0.18% | 0.18% | 0.18% | 0.29% | 0.04% |
| Fixed Income | IEF | iShares 7-10 Year Treasury Bond ETF | 0.28% | 0.28% | 0.28% | 1.71% | 0.34% |
| Fixed Income | TIP | iShares TIPS Bond ETF | 0.52% | 0.52% | 0.52% | 0.94% | 0.07% |
| Fixed Income | TLT | iShares 20+ Year Treasury Bond ETF | 0.46% | 0.46% | 0.46% | 3.14% | 0.89% |
| Fixed Income | BND | Vanguard Total Bond Market ETF | 0.31% | 0.31% | 0.31% | 1.32% | 0.29% |
| Equity | |||||||
| Equity | SPY | SPDR S&P 500 ETF Trust | 3.15% | 3.15% | 3.15% | 3.58% | 0.92% |
| Equity | QQQ | Invesco QQQ Trust | 2.86% | 2.86% | 2.86% | 3.90% | 0.59% |
| Equity | DIA | SPDR Dow Jones ETF Trust | 3.89% | 3.89% | 3.89% | 3.56% | 1.24% |
| Equity | IWM | iShares Russell 2000 ETF | 3.91% | 3.91% | 3.91% | 4.58% | 1.92% |
| By: 2025-01-21 | |||||||
As for the previous trading day, the analysis of SP500 volatility reveals several key insights into the current market dynamics, focusing on implied volatility from the option chain, volatility clustering patterns, and the behavior of the volatility spread.
Examining the implied volatility (IV) from the option chain, we observe that the At-The-Money (ATM) IV has shown a consistent upward trend over the past months. Starting from 11.942% on January 22, 2025, it has steadily increased to 15.744% by December 31, 2025. This trend suggests a contango structure, where long-term IV is higher than short-term IV, indicating a market expectation of increasing volatility over time. Such a structure typically favors short-term volatility positions, as the market anticipates higher volatility in the future. For Moneyness 105% IV, the data reflects a similar upward trend, albeit at a slightly lower rate than ATM IV. This indicates that while there is an expectation of increased volatility, the market is not as aggressively pricing in higher volatility for out-of-the-money calls. This could imply a more cautious approach to speculative strategies, as the market may not fully expect significant upward movements in the underlying asset. Conversely, Moneyness 95% IV, representing out-of-the-money puts, has also increased but remains higher than both ATM and Moneyness 105% IV. This suggests a heightened demand for downside protection, possibly due to market participants hedging against potential declines. The higher IV for these options indicates a preference for hedging strategies, as investors seek to protect against downside risk.
The cumulative analysis of days where IV has remained below 20 reveals a pattern of volatility clustering. The data shows that the IV has been below this threshold for extended periods, with occasional spikes above 20. This low-volatility environment can be beneficial for certain trading strategies, such as selling options to capture premium, given the reduced risk of large price swings. However, when the count of days below 20 resets to zero, indicating a rise in IV, it presents both risks and opportunities. A high IV environment increases the potential for selling opportunities, as options premiums are elevated, but also necessitates caution due to increased market uncertainty.
Analyzing the volatility spread, which is the difference between realized volatility (RV) and implied volatility (IV), provides further insights. The data indicates that the spread has been predominantly positive, with IV consistently exceeding RV. This scenario is conducive to selling volatility or implementing hedging strategies, as the market is pricing in more risk than is currently being realized. A positive spread suggests that investors can potentially earn a volatility risk premium by selling options, as the implied risk is not being matched by actual market movements.
In conclusion, the SP500’s implied volatility structure suggests a contango market, favoring short-term volatility positions. The higher IV for Moneyness 95% options indicates a preference for hedging strategies, while the positive volatility spread supports selling volatility to capture premiums. Investors should remain vigilant for shifts in volatility patterns and consider additional resources, such as historical data and charts, to enhance their understanding of these trends. Visual aids accompanying this analysis can provide further clarity on the evolving volatility landscape. Through this analysis, we aim to enhance our understanding of market dynamics and improve our strategic planning, ultimately leading to more informed and effective decision-making.
by: Anne Pro
AI Research Division
As for the previous trading day, the analysis of DowJones volatility reveals several key insights into the current market dynamics, focusing on implied volatility from the option chain, volatility clustering patterns, and the behavior of the volatility spread.
Examining the implied volatility (IV) from the option chain, we observe that the At-The-Money (ATM) IV has shown a consistent upward trend over the past years. Starting from 11.52% on January 24, 2025, it has steadily increased to 15.96% by December 17, 2027. This trend suggests a contango structure, where long-term IV is higher than short-term IV, indicating a market expectation of increasing volatility over time. Such a structure typically favors short-term volatility positions, as the market anticipates higher volatility in the future.
For Moneyness 105% IV, the data reflects a similar upward trend, albeit at a slightly lower rate than ATM IV. This indicates that while there is an expectation of increased volatility, the market is not as aggressively pricing in higher volatility for out-of-the-money calls. This could imply a more cautious approach to speculative strategies, as the market may not fully expect significant upward movements in the underlying asset. Conversely, Moneyness 95% IV, representing out-of-the-money puts, has also increased but remains higher than both ATM and Moneyness 105% IV. This suggests a heightened demand for downside protection, possibly due to market participants hedging against potential declines. The higher IV for these options indicates a preference for hedging strategies, as investors seek to protect against downside risk.
The cumulative analysis of days where IV has remained below 20 reveals a pattern of volatility clustering. The data shows that the IV has been below this threshold for extended periods, with occasional spikes above 20. This low-volatility environment can be beneficial for certain trading strategies, such as selling options to capture premium, given the reduced risk of large price swings. However, when the count of days below 20 resets to zero, indicating a rise in IV, it presents both risks and opportunities. A high IV environment increases the potential for selling opportunities, as options premiums are elevated, but also necessitates caution due to increased market uncertainty.
Analyzing the volatility spread, which is the difference between realized volatility (RV) and implied volatility (IV), provides further insights. The data indicates that the spread has been predominantly positive, with IV consistently exceeding RV. This scenario is conducive to selling volatility or implementing hedging strategies, as the market is pricing in more risk than is currently being realized. A positive spread suggests that investors can potentially earn a volatility risk premium by selling options, as the implied risk is not being matched by actual market movements.
In conclusion, the DowJones’s implied volatility structure suggests a contango market, favoring short-term volatility positions. The higher IV for Moneyness 95% options indicates a preference for hedging strategies, while the positive volatility spread supports selling volatility to capture premiums. Investors should remain vigilant for shifts in volatility patterns and consider additional resources, such as historical data and charts, to enhance their understanding of these trends. Visual aids accompanying this analysis can provide further clarity on the evolving volatility landscape. Through this analysis, we aim to enhance our understanding of market dynamics and improve our strategic planning, ultimately leading to more informed and effective decision-making.
by: Anne Pro
AI Research Division
As for the previous trading day, the analysis of Nasdaq volatility reveals several key insights into the current market dynamics, focusing on implied volatility from the option chain, volatility clustering patterns, and the behavior of the volatility spread.
Examining the implied volatility (IV) from the option chain, we observe that the At-The-Money (ATM) IV has shown a consistent upward trend over the past months. Starting from 17.736% on January 22, 2025, it has steadily increased to 20.564% by January 16, 2026. This trend suggests a contango structure, where long-term IV is higher than short-term IV, indicating a market expectation of increasing volatility over time. Such a structure typically favors short-term volatility positions, as the market anticipates higher volatility in the future.
For Moneyness 105% IV, the data reflects a similar upward trend, albeit at a slightly lower rate than ATM IV. This indicates that while there is an expectation of increased volatility, the market is not as aggressively pricing in higher volatility for out-of-the-money calls. This could imply a more cautious approach to speculative strategies, as the market may not fully expect significant upward movements in the underlying asset. Conversely, Moneyness 95% IV, representing out-of-the-money puts, has also increased but remains higher than both ATM and Moneyness 105% IV. This suggests a heightened demand for downside protection, possibly due to market participants hedging against potential declines. The higher IV for these options indicates a preference for hedging strategies, as investors seek to protect against downside risk.
The cumulative analysis of days where IV has remained below 20 reveals a pattern of volatility clustering. The data shows that the IV has been below this threshold for extended periods, with occasional spikes above 20. This low-volatility environment can be beneficial for certain trading strategies, such as selling options to capture premium, given the reduced risk of large price swings. However, when the count of days below 20 resets to zero, indicating a rise in IV, it presents both risks and opportunities. A high IV environment increases the potential for selling opportunities, as options premiums are elevated, but also necessitates caution due to increased market uncertainty.
Analyzing the volatility spread, which is the difference between realized volatility (RV) and implied volatility (IV), provides further insights. The data indicates that the spread has been predominantly positive, with IV consistently exceeding RV. This scenario is conducive to selling volatility or implementing hedging strategies, as the market is pricing in more risk than is currently being realized. A positive spread suggests that investors can potentially earn a volatility risk premium by selling options, as the implied risk is not being matched by actual market movements.
In conclusion, the Nasdaq’s implied volatility structure suggests a contango market, favoring short-term volatility positions. The higher IV for Moneyness 95% options indicates a preference for hedging strategies, while the positive volatility spread supports selling volatility to capture premiums. Investors should remain vigilant for shifts in volatility patterns and consider additional resources, such as historical data and charts, to enhance their understanding of these trends. Visual aids accompanying this analysis can provide further clarity on the evolving volatility landscape. Through this analysis, we aim to enhance our understanding of market dynamics and improve our strategic planning, ultimately leading to more informed and effective decision-making.
by: Anne Pro
AI Research Division
As for the previous trading day, the performance of major US indices, including the SP500, Nasdaq, and Dow Jones, showed varied trends. The SP500 exhibited a positive trajectory with a cumulative return of 3.08% as of January 21, 2025. Similarly, the Nasdaq and Dow Jones indices also recorded gains, with returns of 2.47% and 3.85%, respectively. These figures suggest a generally bullish sentiment in the market, with the Dow Jones leading the charge, possibly indicating a rotation towards more traditional, blue-chip stocks.
Focusing on the SP500, sector analysis reveals intriguing dynamics. Utilities and Consumer Staples sectors have been under pressure, as evidenced by the significant declines in companies like Edison International (-21.39%) and Constellation Brands (-17.74%). These sectors, traditionally considered defensive, might be facing challenges due to rising interest rates or shifts in consumer preferences. On the other hand, Information Technology, despite some notable underperformers like Enphase Energy (-11.94%) and Apple Inc. (-8.7%), continues to attract investor interest, likely driven by ongoing technological advancements and innovation.
The Health Care sector presents a mixed picture. While Moderna has seen a substantial decline (-14.55%), possibly due to post-pandemic adjustments and competitive pressures, other companies like Lilly (Eli) have shown resilience with relatively smaller losses (-4.59%). This sector’s performance may be influenced by regulatory changes and the evolving landscape of healthcare needs.
Consumer Discretionary stocks such as Las Vegas Sands (-9.1%) and Chipotle Mexican Grill (-6.16%) have also faced headwinds, potentially due to changing consumer spending habits and economic uncertainties. However, the presence of Booking Holdings with a smaller decline (-4.85%) suggests some resilience within travel-related segments.
In terms of sector rotation, there appears to be a cautious shift towards sectors with growth potential, such as Information Technology, while traditional defensive sectors like Utilities are experiencing outflows. This rotation might be indicative of a market in a recovery phase, where investors are seeking opportunities in sectors poised for growth rather than stability.
Strategically, investors might consider overweighting sectors like Information Technology and selectively within Health Care, where innovation and long-term growth prospects remain strong. Conversely, underweighting Utilities and Consumer Staples could be prudent until clearer signs of stabilization emerge. For those seeking value opportunities, Consumer Discretionary stocks may offer potential upside as economic conditions improve.
Risk management should focus on diversification across sectors to mitigate volatility, especially given the current macroeconomic backdrop of potential interest rate hikes and geopolitical uncertainties. Investors might also explore dividend-paying stocks in stable sectors to ensure income generation during market downturns.
For a deeper understanding of these trends, additional resources such as sector-specific charts and detailed breakdowns of company performance within each sector could provide valuable insights.
by: Anne Pro
AI Research Division
This section offers valuable insights into market momentum by presenting two essential indicators. The first indicator measures the number of companies trading above their Simple Moving Averages (SMA) for 50, 100, and 200 periods. This indicator helps assess the overall strength and direction of the market by revealing how many companies are sustaining upward trends over different timeframes.
The second indicator focuses on the Relative Strength Index (RSI), a widely used momentum oscillator. It tracks the number of companies with RSI values below 30 and above 70, calculated over a 14-day period. An RSI below 30 typically signals that a stock is oversold, indicating a potential rebound, while an RSI above 70 suggests that a stock is overbought, possibly signaling a pullback.
By analyzing these indicators together, you can form a well-rounded opinion on the market’s current momentum. They provide insights into whether the prevailing trends are likely to continue or if the market is approaching a turning point, particularly when extreme values or high readings suggest a possible reversal. This information is crucial for making informed decisions about the potential direction of market movements.
The data for this analysis was extracted from the Yahoo Finance Website.
This section provides a high-level overview of market momentum by analyzing the proportion of companies within each sector that are trading above their 50, 100, and 200-day Simple Moving Averages (SMA). To generate a comprehensive momentum score, we prioritize the 50-day SMA, which contributes 50% to the overall score, as it is considered the most significant indicator of short-term momentum. The 100-day SMA and 200-day SMA contribute 30% and 20% respectively, reflecting their roles in capturing medium and long-term trends.
The final momentum score, ranging from 0 to 100%, is interpreted as follows:
This score provides a clear snapshot of the market’s overall direction and strength.
Here we are following the same idea that we show you in the Indices Momentum Section but here we are analyzing the Breadth in each of the Sectors of the US Economy. The indicator that we are using is the number of companies that are above their Simple Moving Average (50, 100 and 200 period). So, with this information you will be able to form an opinion related to the continuation of the current momentum (or if we are close to a rebound - something that highly happens at high readings or extreme values).
A drawdown represents the decline from a peak to a trough during a specific period in the value of an investment, trading account, or fund. It serves as a critical measure of historical risk, offering insights into the volatility and potential losses associated with different investments. Drawdowns are typically expressed as a percentage, calculated by comparing the peak value to the subsequent lowest point before any recovery occurs. For example, if a trading account starts with 10,000 and drops to 9,000 before rebounding above 10,000, the account has experienced a 10% drawdown.
This section focuses on analyzing the drawdown patterns of the SP500, with a detailed examination of its duration and magnitude since 1930. By understanding these drawdown behaviors, investors can gain valuable insights into the resilience and risks associated with the Nasdaq over time.
The data for this analysis was extracted from the Yahoo Finance Website.
| Drawdown Analysis of the S&P 500 - as of 2025-01-21 | ||||||
| Depth greater than 20% - Daily Timeframe | ||||||
| From | Trough | To | Depth | Length | To Trough | Recovery |
|---|---|---|---|---|---|---|
| 1929-09-17 | 1932-06-01 | 1954-09-22 | −86.2% | 6249 | 678 | 5571 |
| 2007-10-10 | 2009-03-09 | 2013-03-28 | −56.8% | 1376 | 355 | 1021 |
| 2000-03-27 | 2002-10-09 | 2007-05-30 | −49.1% | 1803 | 637 | 1166 |
| 1973-01-12 | 1974-10-03 | 1980-07-17 | −48.2% | 1898 | 436 | 1462 |
| 1968-12-02 | 1970-05-26 | 1972-03-06 | −36.1% | 820 | 369 | 451 |
| 2020-02-20 | 2020-03-23 | 2020-08-18 | −33.9% | 126 | 23 | 103 |
| 1987-08-26 | 1987-12-04 | 1989-07-26 | −33.5% | 485 | 71 | 414 |
| 1961-12-13 | 1962-06-26 | 1963-09-03 | −28.0% | 434 | 135 | 299 |
| 1980-12-01 | 1982-08-12 | 1982-11-03 | −27.1% | 488 | 430 | 58 |
| 2022-01-04 | 2022-10-12 | 2024-01-19 | −25.4% | 513 | 195 | 318 |
| 1966-02-10 | 1966-10-07 | 1967-05-04 | −22.2% | 310 | 167 | 143 |
| 1956-08-06 | 1957-10-22 | 1958-09-24 | −21.5% | 539 | 306 | 233 |
| Downside Risk Analysis of the S&P 500 | |
| Rf = 4%, MAR = 5%, p = 95%, Scale = Daily | |
| Metric | Value |
|---|---|
| Semi Deviation | 0.86% |
| Gain Deviation | 0.89% |
| Loss Deviation | 0.95% |
| Downside Deviation (MAR=210%) | 1.32% |
| Downside Deviation (Rf=0%) | 0.84% |
| Downside Deviation (0%) | 0.84% |
| Maximum Drawdown | 86.19% |
| Historical VaR (95%) | −1.68% |
| Historical ES (95%) | −2.85% |
| Modified VaR (95%) | −1.56% |
| Modified ES (95%) | −1.56% |
| Updated: 2025-01-21 | |
A drawdown represents the decline from a peak to a trough during a specific period in the value of an investment, trading account, or fund. It serves as a critical measure of historical risk, offering insights into the volatility and potential losses associated with different investments. Drawdowns are typically expressed as a percentage, calculated by comparing the peak value to the subsequent lowest point before any recovery occurs. For example, if a trading account starts with 10,000 and drops to 9,000 before rebounding above 10,000, the account has experienced a 10% drawdown.
This section focuses on analyzing the drawdown patterns of the Nasdaq, with a detailed examination of its duration and magnitude since 1930. By understanding these drawdown behaviors, investors can gain valuable insights into the resilience and risks associated with the Nasdaq over time.
The data for this analysis was extracted from the Yahoo Finance Website.
| Drawdown Analysis of the Nasdaq - as of 2025-01-21 | ||||||
| Depth greater than 20% - Daily Timeframe | ||||||
| From | Trough | To | Depth | Length | To Trough | Recovery |
|---|---|---|---|---|---|---|
| 2000-03-13 | 2002-10-09 | 2015-04-23 | −77.9% | 3802 | 647 | 3155 |
| 1973-01-12 | 1974-10-03 | 1978-09-07 | −59.9% | 1428 | 436 | 992 |
| 2021-11-22 | 2022-12-28 | 2024-02-29 | −36.4% | 570 | 277 | 293 |
| 1987-08-28 | 1987-10-28 | 1989-08-03 | −36.0% | 489 | 43 | 446 |
| 1989-10-10 | 1990-10-16 | 1991-04-02 | −33.0% | 373 | 258 | 115 |
| 1983-06-27 | 1984-07-25 | 1986-01-07 | −31.5% | 640 | 274 | 366 |
| 2020-02-20 | 2020-03-23 | 2020-06-08 | −30.1% | 76 | 23 | 53 |
| 1998-07-21 | 1998-10-08 | 1998-11-27 | −29.5% | 92 | 57 | 35 |
| 1981-06-01 | 1982-08-13 | 1982-11-04 | −28.8% | 364 | 306 | 58 |
| 1980-02-11 | 1980-03-27 | 1980-07-14 | −24.9% | 107 | 33 | 74 |
| 2018-08-30 | 2018-12-24 | 2019-04-23 | −23.6% | 161 | 80 | 81 |
| 1978-09-14 | 1978-11-14 | 1979-07-26 | −20.4% | 219 | 44 | 175 |
| Downside Risk Analysis of the Nasdaq | |
| Rf = 4%, MAR = 5%, p = 95%, Scale = Daily | |
| Metric | Value |
|---|---|
| Semi Deviation | 0.92% |
| Gain Deviation | 0.89% |
| Loss Deviation | 1.01% |
| Downside Deviation (MAR=210%) | 1.37% |
| Downside Deviation (Rf=0%) | 0.90% |
| Downside Deviation (0%) | 0.90% |
| Maximum Drawdown | 77.93% |
| Historical VaR (95%) | −2.01% |
| Historical ES (95%) | −3.10% |
| Modified VaR (95%) | −1.85% |
| Modified ES (95%) | −2.93% |
| Updated: 2025-01-21 | |
A drawdown represents the decline from a peak to a trough during a specific period in the value of an investment, trading account, or fund. It serves as a critical measure of historical risk, offering insights into the volatility and potential losses associated with different investments. Drawdowns are typically expressed as a percentage, calculated by comparing the peak value to the subsequent lowest point before any recovery occurs. For example, if a trading account starts with 10,000 and drops to 9,000 before rebounding above 10,000, the account has experienced a 10% drawdown.
This section focuses on analyzing the drawdown patterns of the SP500, with a detailed examination of its duration and magnitude since 1930. By understanding these drawdown behaviors, investors can gain valuable insights into the resilience and risks associated with the DowJones over time.
The data for this analysis was extracted from the Yahoo Finance Website.
| Drawdown Analysis of the DowJones - as of 2025-01-21 | ||||||
| Depth greater than 20% - Daily Timeframe | ||||||
| From | Trough | To | Depth | Length | To Trough | Recovery |
|---|---|---|---|---|---|---|
| 2007-10-10 | 2009-03-09 | 2013-03-05 | −53.8% | 1359 | 355 | 1004 |
| 2000-01-18 | 2002-10-09 | 2006-10-03 | −37.9% | 1688 | 685 | 1003 |
| 2020-02-13 | 2020-03-23 | 2020-11-16 | −37.1% | 193 | 27 | 166 |
| 2022-01-05 | 2022-09-30 | 2023-12-13 | −21.9% | 488 | 186 | 302 |
| Downside Risk Analysis of the DowJones | |
| Rf = 4%, MAR = 5%, p = 95%, Scale = Daily | |
| Metric | Value |
|---|---|
| Semi Deviation | 0.79% |
| Gain Deviation | 0.78% |
| Loss Deviation | 0.86% |
| Downside Deviation (MAR=210%) | 1.27% |
| Downside Deviation (Rf=0%) | 0.78% |
| Downside Deviation (0%) | 0.78% |
| Maximum Drawdown | 53.78% |
| Historical VaR (95%) | −1.63% |
| Historical ES (95%) | −2.60% |
| Modified VaR (95%) | −1.54% |
| Modified ES (95%) | −1.89% |
| Updated: 2025-01-21 | |
The Federal Reserve, as any other central bank, has some metrics that are more important than others; so, the idea here is to highlight those relevant metrics for the FED. These are: GDP, Unemployment, Inflation, Fed Fund Rate and Fed Liquidity.
Having an understanding of where this metrics are, gives an idea about the health of the US Economy.
A healthy labor market will always be a receipt for economy growth. That is why supervising the following different metrics is mandatory for you to have a sound and complete view on how one of the most important underlying forces of the economy is performing.
As for the previous trading day, December 31, 2024, the U.S. Government Bond market exhibited notable dynamics across various maturities. The 1-month yield stood at 4.4%, while the 30-year yield was at 4.78%. This data reflects a generally flattening yield curve, with shorter-term yields relatively close to longer-term yields, indicating market expectations of stable or potentially declining interest rates in the future.
Analyzing the yield trends, we observe that the 1-month to 1-year yields have been relatively stable, with minor fluctuations over the past month. The 2-year yield, at 4.24%, is slightly lower than the 10-year yield, which is at 4.86%. This results in a positive 2-Year to 10-Year yield spread of 0.62%, suggesting a normal yield curve slope, which typically indicates expectations of economic growth and moderate inflation.
However, the 3-month yield at 4.39% compared to the 10-year yield results in a 0.47% spread, which is also positive but narrower than the 2-Year to 10-Year spread. This narrower spread could imply some market caution regarding short-term economic conditions, possibly reflecting concerns about potential economic slowdowns or shifts in monetary policy.
The long-term trend analysis shows that yields have generally been stable with slight declines in longer maturities, reflecting market sentiment that inflation pressures might be easing, or that the Federal Reserve’s tightening cycle could be nearing its end. This stability in yields suggests that investors are cautiously optimistic about economic growth, but remain vigilant about potential risks.
In terms of bond price sensitivity, longer-duration bonds like the 10-year and 30-year are more sensitive to interest rate changes. In a rising rate environment, these bonds could experience greater price volatility, whereas shorter-duration bonds would be less affected. Given the current yield curve dynamics, investors might consider maintaining a balanced portfolio with a mix of short and long-duration bonds to manage interest rate risk effectively.
For investment strategies, in the current environment where rates have shown signs of stabilizing, a diversified approach could be beneficial. Investors might focus on shorter-duration bonds to minimize price risk while keeping an eye on longer-duration bonds for potential capital appreciation if rates decline further. Additionally, maintaining flexibility to adjust allocations based on evolving economic indicators will be crucial.
Looking ahead, the macroeconomic outlook suggests that while the economy shows resilience, there are underlying uncertainties that could impact growth. The Federal Reserve’s actions will be closely watched, especially any signals of policy shifts that could influence bond yields. Investors should remain informed about economic indicators and consider using additional resources such as yield curve charts and historical data to enhance their understanding of market trends.
Through this analysis, we aim to deepen our understanding of fixed-income trends and improve strategic planning, leading to more informed and effective decision-making.
by: Anne Pro
AI Research Division
As for the previous trading day, the analysis of the Consumer Price Index (CPI) reveals several key insights into recent inflation trends and their broader economic implications.
1. Component Contribution Analysis
The detailed breakdown of CPI components shows that housing and food and beverage have been consistent contributors to inflation. Housing costs, in particular, have shown a persistent upward trend, reflecting ongoing supply constraints and strong demand. Food and beverage prices have also been rising, likely due to supply chain disruptions and increased input costs.
Conversely, apparel and commodities have shown minimal impact, with some deflationary pressures observed in commodities, possibly due to improved supply chain conditions and reduced demand. Transport costs have fluctuated, reflecting volatility in fuel prices, while medical care and education costs have remained relatively stable.
Overall, the component-level trends suggest that while some areas are experiencing inflationary pressures, others are stabilizing or declining, indicating a mixed inflationary environment influenced by both supply chain issues and changes in consumer demand.
2. Month-over-Month (MoM) Change and Volatility
The MoM analysis indicates a general trend of modest increases in CPI, with some months showing slight declines. Notably, June experienced a minor decrease, suggesting temporary relief in inflationary pressures, likely due to seasonal factors or short-term supply improvements.
Recent months have shown more stability, with moderate increases in both core and all-items CPI. This suggests that while inflationary pressures persist, they may be stabilizing, reducing the likelihood of sudden spikes. However, the consistent upward trend in core CPI indicates underlying inflationary pressures that could persist if not addressed.
3. Year-over-Year (YoY) Change and Volatility
The YoY analysis reveals that CPI remains above the 2% target, with core CPI consistently higher than all-items CPI. This suggests that underlying inflationary pressures are more persistent than headline figures might indicate. The gradual decline in YoY rates over the year suggests some easing, but the proximity to the 2% target remains a concern for policymakers.
Given the current levels, central banks may be cautious about interest rate decisions, balancing the need to control inflation with the risk of stifling economic growth. The persistent gap between current CPI levels and the target suggests that further rate hikes could be on the table, although the decision will likely depend on future data.
4. Strategic Implications and Macroeconomic Insights
The current CPI trends suggest a complex macroeconomic environment. The likelihood of further rate hikes remains, especially if inflation does not show signs of significant easing. This could increase recession risks, particularly if consumer spending slows in response to higher borrowing costs.
Inflation-sensitive sectors, such as consumer staples and utilities, may offer more stability in this environment, while sectors like technology and discretionary spending could face headwinds. Investors might consider focusing on sectors with pricing power and those less sensitive to interest rate changes.
Globally, economic scenarios such as geopolitical tensions or policy shifts could further impact CPI trends. For instance, changes in trade policies or energy prices could either exacerbate or alleviate inflationary pressures, influencing both domestic and international market performance.
In conclusion, while CPI trends show some signs of stabilization, the persistent inflationary pressures and proximity to the 2% target suggest that vigilance is necessary. Policymakers and investors alike should remain attentive to emerging data and potential shifts in the economic landscape.
by: Anne Pro
AI Research Division
| YoY CPI Component Changes | ||||||||||||
| Core | All Items | Apparel | Medical Care | Housing | Food and Beverage | Commodities | Services | Transport | Education | Education and Comms | Recreation | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dec 2024 | 3.248% | 2.897% | 1.237% | 2.839% | 4.096% | 2.410% | 0.306% | 4.399% | 1.732% | 3.953% | 0.606% | 1.096% |
| Nov 2024 | 3.300% | 2.733% | 1.133% | 3.082% | 4.129% | 2.334% | -0.287% | 4.494% | 0.405% | 4.151% | 0.709% | 1.483% |
| Oct 2024 | 3.300% | 2.576% | 0.305% | 3.293% | 4.184% | 2.108% | -1.073% | 4.735% | -0.279% | 3.764% | 0.775% | 1.003% |
| Sep 2024 | 3.259% | 2.408% | 1.795% | 3.252% | 4.082% | 2.232% | -1.402% | 4.690% | -1.272% | 3.576% | 0.889% | 0.699% |
| Aug 2024 | 3.266% | 2.591% | 0.294% | 2.978% | 4.345% | 2.056% | -1.123% | 4.838% | -0.720% | 3.100% | 1.005% | 1.549% |
| Jul 2024 | 3.213% | 2.924% | 0.185% | 3.172% | 4.329% | 2.176% | -0.288% | 4.861% | 1.109% | 2.833% | 0.889% | 1.372% |
| Jun 2024 | 3.277% | 2.976% | 0.765% | 3.264% | 4.382% | 2.202% | -0.317% | 4.982% | 1.233% | 2.778% | 0.705% | 1.331% |
| May 2024 | 3.411% | 3.250% | 0.806% | 3.074% | 4.557% | 2.116% | 0.110% | 5.179% | 2.735% | 2.717% | 0.533% | 1.364% |
| Apr 2024 | 3.616% | 3.358% | 1.353% | 2.630% | 4.524% | 2.215% | 0.340% | 5.231% | 3.473% | 2.470% | 0.420% | 1.510% |
| Mar 2024 | 3.797% | 3.475% | 0.414% | 2.214% | 4.649% | 2.247% | 0.596% | 5.261% | 4.022% | 2.441% | 0.245% | 1.860% |
| Feb 2024 | 3.762% | 3.166% | -0.009% | 1.411% | 4.550% | 2.250% | 0.280% | 4.975% | 2.751% | 2.724% | 0.389% | 2.090% |
| Jan 2024 | 3.875% | 3.106% | 0.037% | 1.051% | 4.660% | 2.546% | 0.107% | 4.992% | 1.739% | 2.457% | 0.023% | 2.775% |
| Dec 2023 | 3.910% | 3.323% | 1.174% | 0.425% | 4.827% | 2.718% | 0.725% | 4.955% | 2.736% | 2.390% | -0.071% | 2.712% |
| Nov 2023 | 4.015% | 3.139% | 1.378% | 0.148% | 5.219% | 2.942% | -0.064% | 5.186% | 0.839% | 2.400% | -0.058% | 2.487% |
| Oct 2023 | 4.022% | 3.246% | 2.711% | -0.794% | 5.255% | 3.315% | 0.420% | 5.062% | 0.756% | 2.665% | 0.924% | 3.183% |
| Sep 2023 | 4.144% | 3.694% | 2.350% | -1.433% | 5.559% | 3.709% | 1.413% | 5.157% | 2.378% | 2.868% | 1.069% | 3.881% |
| Aug 2023 | 4.413% | 3.719% | 3.022% | -0.971% | 5.721% | 4.206% | 1.118% | 5.404% | 1.626% | 2.865% | 1.036% | 3.555% |
| Jul 2023 | 4.708% | 3.272% | 3.085% | -0.506% | 6.199% | 4.808% | -0.429% | 5.703% | -2.701% | 3.237% | 1.220% | 4.056% |
| Jun 2023 | 4.855% | 3.053% | 2.955% | 0.139% | 6.309% | 5.671% | -0.983% | 5.738% | -4.809% | 3.144% | 1.083% | 4.312% |
| May 2023 | 5.332% | 4.121% | 3.429% | 0.749% | 6.798% | 6.585% | 0.804% | 6.308% | -1.707% | 3.396% | 1.455% | 4.547% |
| Apr 2023 | 5.516% | 4.941% | 3.595% | 1.076% | 7.432% | 7.467% | 2.118% | 6.799% | 0.256% | 3.574% | 1.544% | 5.002% |
| Mar 2023 | 5.560% | 4.935% | 3.074% | 1.516% | 7.783% | 8.252% | 1.466% | 7.235% | -1.083% | 3.546% | 1.385% | 4.857% |
| Feb 2023 | 5.493% | 5.966% | 3.147% | 2.355% | 8.200% | 9.180% | 3.476% | 7.598% | 2.417% | 3.330% | 1.042% | 4.968% |
| Jan 2023 | 5.543% | 6.362% | 3.004% | 3.052% | 8.234% | 9.866% | 4.420% | 7.624% | 3.707% | 3.388% | 1.013% | 4.783% |
| Dec 2022 | 5.681% | 6.411% | 3.018% | 3.935% | 8.034% | 10.151% | 4.759% | 7.481% | 3.627% | 3.337% | 0.751% | 5.144% |
| Nov 2022 | 5.963% | 7.119% | 3.846% | 4.127% | 7.806% | 10.326% | 6.978% | 7.211% | 7.799% | 3.127% | 0.684% | 4.760% |
| Oct 2022 | 6.295% | 7.752% | 4.268% | 4.984% | 7.880% | 10.556% | 8.572% | 7.233% | 11.212% | 3.022% | 0.018% | 4.079% |
| Sep 2022 | 6.640% | 8.198% | 5.510% | 5.976% | 8.031% | 10.755% | 9.514% | 7.371% | 12.576% | 3.099% | 0.199% | 4.058% |
| Aug 2022 | 6.300% | 8.219% | 4.898% | 5.352% | 7.863% | 10.892% | 10.437% | 6.829% | 13.304% | 3.090% | 0.467% | 4.102% |
| Jul 2022 | 5.902% | 8.450% | 4.960% | 4.852% | 7.409% | 10.466% | 11.907% | 6.287% | 16.187% | 2.616% | 0.524% | 4.370% |
| Jun 2022 | 5.903% | 8.990% | 5.081% | 4.552% | 7.355% | 10.015% | 13.396% | 6.241% | 19.664% | 2.706% | 0.808% | 4.629% |
| May 2022 | 6.018% | 8.533% | 4.969% | 3.764% | 6.919% | 9.726% | 13.038% | 5.755% | 19.352% | 2.499% | 0.779% | 4.466% |
| Apr 2022 | 6.157% | 8.252% | 5.456% | 3.261% | 6.503% | 9.010% | 12.934% | 5.388% | 19.917% | 2.508% | 1.028% | 4.283% |
| Mar 2022 | 6.476% | 8.547% | 6.680% | 2.882% | 6.331% | 8.486% | 14.200% | 5.101% | 22.526% | 2.515% | 1.543% | 4.752% |
| Feb 2022 | 6.452% | 7.949% | 6.436% | 2.449% | 5.931% | 7.617% | 13.171% | 4.781% | 21.237% | 2.143% | 1.584% | 4.946% |
| Jan 2022 | 6.061% | 7.570% | 5.229% | 2.475% | 5.648% | 6.710% | 12.561% | 4.549% | 21.043% | 2.148% | 1.639% | 4.757% |
| Dec 2021 | 5.505% | 7.177% | 5.890% | 2.144% | 5.081% | 6.026% | 12.398% | 4.030% | 21.621% | 2.007% | 1.623% | 3.269% |
| Nov 2021 | 4.973% | 6.863% | 5.284% | 1.719% | 4.788% | 5.803% | 12.018% | 3.786% | 21.215% | 2.107% | 1.663% | 3.213% |
| Oct 2021 | 4.584% | 6.219% | 4.577% | 1.286% | 4.518% | 5.104% | 10.522% | 3.652% | 18.608% | 2.049% | 1.775% | 3.850% |
| Sep 2021 | 4.020% | 5.361% | 3.443% | 0.401% | 3.886% | 4.442% | 8.995% | 3.195% | 16.466% | 1.950% | 1.722% | 3.470% |
| Aug 2021 | 3.951% | 5.175% | 4.008% | 0.342% | 3.498% | 3.640% | 8.784% | 3.032% | 17.428% | 1.379% | 1.199% | 3.405% |
| Jul 2021 | 4.203% | 5.258% | 4.054% | 0.303% | 3.362% | 3.354% | 8.983% | 3.053% | 18.950% | 1.165% | 1.123% | 3.526% |
| Jun 2021 | 4.418% | 5.315% | 4.780% | 0.441% | 3.138% | 2.346% | 8.884% | 3.202% | 21.292% | 1.176% | 2.080% | 2.363% |
| May 2021 | 3.779% | 4.926% | 5.626% | 0.937% | 2.895% | 2.104% | 8.130% | 3.043% | 19.710% | 1.045% | 1.905% | 1.607% |
| Apr 2021 | 2.961% | 4.149% | 2.114% | 1.493% | 2.612% | 2.356% | 6.747% | 2.621% | 14.799% | 0.822% | 1.693% | 2.132% |
| Mar 2021 | 1.645% | 2.619% | -2.583% | 1.798% | 2.117% | 3.386% | 4.075% | 1.751% | 5.814% | 0.783% | 1.503% | 1.066% |
| Feb 2021 | 1.276% | 1.673% | -3.779% | 2.039% | 1.768% | 3.529% | 2.207% | 1.351% | 0.684% | 1.180% | 1.740% | 0.786% |
| Jan 2021 | 1.396% | 1.395% | -2.741% | 1.939% | 1.771% | 3.721% | 1.511% | 1.321% | -1.151% | 1.264% | 1.744% | 0.138% |
| Data from St. Louis Fed - FRED | ||||||||||||
The level of interest rate affect the consumption activity and therefore “push” the economy to an expansionary or recessionary state. A few concept that we important for you to know are:
The Secured Overnight Financing Rate (SOFR) is a broad measure of the cost of borrowing cash overnight collateralized by Treasury securities. The SOFR includes all trades in the Broad General Collateral Rate plus bilateral Treasury repurchase agreement (repo) transactions cleared through the Delivery-versus-Payment (DVP) service offered by the Fixed Income Clearing Corporation (FICC), which is filtered to remove a portion of transactions considered “specials”. Note that specials are repos for specific-issue collateral, which take place at cash-lending rates below those for general collateral repos because cash providers are willing to accept a lesser return on their cash in order to obtain a particular security.
The federal funds market consists of domestic unsecured borrowings in U.S. dollars by depository institutions from other depository institutions and certain other entities, primarily government-sponsored enterprises. The effective federal funds rate (EFFR) is calculated as a volume-weighted median of overnight federal funds transactions reported in the FR 2420 Report of Selected Money Market Rates.
The other graphs show the evolution and the cost of several different type of loans (personal, revolving and credit card) - and remember: credit is a key driver of consupmtion in The US.
Here you will see the most relevant data related to different interest rate metrics such as: SOFR, Federal Fund Rate, Mortgage and Personal Loan.
The data for this analysis was extracted from the FRED Website.
As for the previous trading day, the Federal Reserve’s liquidity dynamics reveal a complex interplay between various components of its balance sheet, with particular emphasis on the repo market. This analysis will delve into the trends and implications of these liquidity provisions, offering insights into potential market outcomes and strategic positioning.
Liquidity Trends and Analysis
Recent data indicates a nuanced evolution in the Federal Reserve’s liquidity metrics. Key components such as total assets, liabilities, net liquidity, and credit facilities have shown varying trends. Notably, the overnight repo market has been a focal point, with volumes fluctuating significantly. For instance, on January 15, 2025, the overnight repo volume stood at approximately $119.977 billion, reflecting a decrease from the $160.219 billion recorded on January 14, 2025. This fluctuation suggests a dynamic liquidity environment where the demand for short-term funding is responsive to broader market conditions.
The overnight repo market serves as a critical tool for the Fed to manage short-term liquidity. Its recent trends highlight the Fed’s role in ensuring sufficient liquidity in the financial system, which is crucial for maintaining market stability. The decrease in repo volumes could indicate a temporary easing of liquidity demand, potentially signaling a shift in market sentiment or funding conditions.
Impact on Market Dynamics and Strategic Insights
The current liquidity environment, characterized by fluctuating repo volumes, suggests potential market outcomes. A decrease in repo activity may imply tighter short-term funding conditions, which could lead to increased volatility in financial markets. Conversely, stable or increasing repo volumes might support a more risk-on environment, encouraging investment in equities and other risk assets.
The interplay between repo market dynamics and broader macroeconomic factors such as inflation, interest rates, and economic growth expectations is critical. The Fed’s liquidity decisions, influenced by these factors, can have profound effects on market sentiment and positioning. For instance, if inflationary pressures persist, the Fed may adjust its liquidity provisions, impacting both equity and bond markets.
REPO Market Analytics
The repo market has exhibited notable dynamics, with recent trends indicating shifts in liquidity demand. The correlation between repo volumes and liquidity demand from financial institutions underscores the Fed’s influence on short-term funding. A decrease in repo activity, as observed in recent data, could suggest tighter funding conditions, potentially impacting the Fed’s net liquidity stance.
Historically, increased repo activity has often correlated with bullish trends in the stock market, as it signals ample liquidity and lower funding costs. However, a significant decrease in repo volumes could introduce risks, potentially leading to financial instability if liquidity becomes constrained.
Observations and Recommendations
Key insights from the data suggest that liquidity provisions have experienced fluctuations, with implications for both equity and bond markets. The recent decrease in repo volumes may signal increased risk or volatility, warranting cautious market positioning. Investors should consider the potential for growth opportunities in sectors that benefit from increased liquidity, while remaining vigilant to the risks associated with liquidity contractions.
In conclusion, continued monitoring of the Fed’s liquidity measures, particularly repo volumes and net liquidity, is essential for anticipating market reactions. Additional data, including detailed metrics and historical trends, is available to support this analysis.
by: Anne Pro
AI Research Division
As for the previous trading day, the SP500’s Gamma Exposure (GEX) analysis reveals critical insights into market dynamics. The key levels of interest include the put wall, call wall, and gamma flip, which are essential for understanding potential market movements and volatility.
The put wall, located at a strike price of 5573, represents a significant concentration of negative gamma. This level acts as a crucial downside support, indicating where market participants have substantial protective positions. If the SP500 approaches this level, it could experience increased support due to hedging activities by market makers. The call wall is at 6187, marking the strike price with the highest positive gamma concentration. This level serves as a potential resistance point, capping upside movements as market participants may sell calls or adjust positions to manage risk.
The gamma flip level is at 5999, where the total gamma exposure transitions from negative to positive. The SP500’s closing price is 6044, which is above the gamma flip level, placing the market in positive gamma territory. This suggests a more stable market environment with reduced volatility, as market makers are likely to dampen price fluctuations through delta hedging.
Analyzing the differences in percentage terms, the SP500’s closing price is approximately 8.45% above the put wall and 2.31% below the call wall. This positioning indicates a relatively balanced market, with potential for both upward and downward movements, but with a bias towards stability due to the positive gamma environment.
In positive gamma conditions, market makers tend to stabilize the market by buying into weakness and selling into strength, reducing volatility. This environment favors range-bound trading strategies, where traders can capitalize on expected lower price fluctuations. Conversely, if the SP500 were in negative gamma territory, heightened volatility would be expected, making short-volatility strategies more attractive.
Given the SP500’s current position relative to the gamma flip, put wall, and call wall, several strategies can be considered. With the SP500 trading near the gamma flip and in positive gamma territory, range-bound strategies are advisable. Traders might consider selling options to take advantage of the reduced volatility or employing strategies that benefit from limited price movements.
For those interested in further exploring Gamma Exposure trends, additional resources such as charts and historical data are available. These visual aids can provide a deeper understanding of GEX dynamics and assist in strategic planning.
By analyzing these key levels and understanding the implications of gamma exposure, we can enhance our market insights and make more informed decisions. For more detailed analysis, readers can refer to charts and data available for SPY and XSP, which offer additional perspectives on these trends.
by: Anne Pro
AI Research Division
The following information is related to the SPX
The following information is related to the SPY
The following information is related to the XSP.
As for the previous trading day, the options market analysis reveals intriguing dynamics across major indices and sectors, with a particular focus on gamma exposure and critical price levels. The data indicates a mixed market positioning, with several stocks and indices hovering around significant gamma flip points, which could signal potential volatility.
Starting with the major indices, the S&P 500 (SPX) is trading slightly above its gamma flip point of 6044, suggesting a positive gamma regime where upside moves could be accelerated. However, the proximity to the call wall at 6187 indicates a potential resistance zone where profit-taking might occur. The Nasdaq 100 (NDX) is also in a positive gamma regime, trading above its gamma flip point of 21576, with a call wall at 22234 serving as a key resistance level. The Dow Jones (DJX) presents a unique scenario with a gamma flip point at zero, indicating a lack of clear directional bias, but the call wall at 447 could act as a resistance.
In the technology sector, Apple (AAPL) is trading near its gamma flip point of 221, suggesting a neutral stance with potential for both upside and downside moves. Microsoft (MSFT) is above its gamma flip at 429, indicating a positive gamma regime, but traders should watch the resistance at 459 closely. Nvidia (NVDA) is also in a positive gamma regime, trading above its flip point of 141, with resistance at 150.
The financial sector shows JPMorgan (JPM) trading near its gamma flip point of 263, suggesting a neutral market stance. Bank of America (BAC) is slightly above its gamma flip at 47, indicating a potential for upside moves, but the call wall at 49 could limit gains.
In healthcare, Johnson & Johnson (JNJ) is trading below its gamma flip point of 148, indicating a negative gamma regime with potential for downside moves. UnitedHealth (UNH) is slightly above its gamma flip at 524, suggesting a positive gamma regime, but resistance at 582 could cap gains.
For trading implications, stocks near their gamma flip points, such as AAPL and JPM, warrant close monitoring for potential breakout or breakdown scenarios. The proximity of SPX and NDX to their respective call walls suggests traders should be cautious of resistance levels that could trigger profit-taking. Risk management should focus on maintaining flexibility, given the potential for volatility around these critical levels.
In summary, the current market positioning highlights several stocks and indices at or near critical gamma levels, suggesting potential for significant market moves. Traders should remain vigilant, particularly around key support and resistance zones, to effectively manage risk and capitalize on market opportunities. Additional reference data can be found in the table accompanying the LLM-generated analysis.
by: Anne Pro
AI Research Division
| Gamma Exposure for the Most Active Tickets | |||||
| Critical Levels to Consider | |||||
| Symbol | Name | Price | Gamma Flip | Put Wall | Call Wall |
|---|---|---|---|---|---|
| Stocks | |||||
| AAPL | APPLE INC | 221.46 | 221.55 | 201.19 | 258.24 |
| MSFT | MICROSOFT CORP | 428.85 | 414.45 | 372.16 | 459.38 |
| AMZN | AMAZON.COM INC | 230.57 | 187.89 | 184.46 | 236.04 |
| NVDA | NVIDIA CORP | 141.47 | 124.95 | 113.17 | 149.62 |
| GOOGL | ALPHABET INC CL A | 198.80 | 180.42 | 159.04 | 204.87 |
| TSLA | TESLA INC | 423.87 | 349.28 | 339.10 | 485.65 |
| GOOG | ALPHABET INC CL C | 200.32 | 163.67 | 160.26 | 207.79 |
| META | META PLATFORMS INC CLASS A | 617.70 | 557.88 | 494.16 | 657.48 |
| XOM | EXXON MOBIL CORP | 111.48 | 106.66 | 99.77 | 117.91 |
| LLY | ELI LILLY + CO | 740.38 | 744.66 | 682.66 | 888.46 |
| UNH | UNITEDHEALTH GROUP INC | 523.64 | 519.76 | 482.81 | 582.22 |
| JPM | JPMORGAN CHASE + CO | 263.24 | 231.83 | 210.59 | 264.13 |
| JNJ | JOHNSON + JOHNSON W/D | 147.87 | 140.19 | 131.33 | 155.39 |
| V | VISA INC CLASS A SHARES | 324.00 | 290.24 | 259.20 | 329.50 |
| PG | PROCTER + GAMBLE CO/THE | 161.34 | 164.74 | 152.04 | 184.85 |
| AVGO | BROADCOM INC | 241.13 | 206.63 | 192.90 | 253.39 |
| MA | MASTERCARD INC A | 527.88 | 516.76 | 475.99 | 569.04 |
| HD | HOME DEPOT INC | 417.15 | 393.11 | 356.35 | 444.02 |
| CVX | CHEVRON CORP | 158.18 | 148.28 | 132.98 | 168.37 |
| MRK | MERCK + CO. INC. | 95.81 | 99.37 | 91.58 | 114.32 |
| ABBV | ABBVIE INC | 172.21 | 173.97 | 156.45 | 199.64 |
| ADBE | ADOBE INC | 436.14 | 438.58 | 399.18 | 508.59 |
| COST | COSTCO WHOLESALE CORP | 944.97 | 931.19 | 864.88 | 986.61 |
| PEP | PEPSICO INC | 148.35 | 151.85 | 140.81 | 178.02 |
| WMT | WALMART INC | 92.74 | 92.06 | 81.11 | 104.37 |
| CSCO | CISCO SYSTEMS INC | 60.96 | 51.48 | 48.77 | 63.23 |
| KO | COCA COLA CO/THE | 62.39 | 59.53 | 55.41 | 66.41 |
| CRM | SALESFORCE INC | 327.68 | 321.15 | 299.91 | 375.44 |
| MCD | MCDONALD S CORP | 279.22 | 281.08 | 265.02 | 318.03 |
| BAC | BANK OF AMERICA CORP | 46.67 | 43.76 | 37.66 | 48.73 |
| ACN | ACCENTURE PLC CL A | 355.95 | 350.30 | 328.20 | 381.29 |
| TMO | THERMO FISHER SCIENTIFIC INC | 571.27 | 564.94 | 495.75 | 631.30 |
| PFE | PFIZER INC | 26.55 | 26.02 | 23.76 | 29.89 |
| CMCSA | COMCAST CORP CLASS A | 37.08 | 35.96 | 31.68 | 42.48 |
| LIN | LINDE PLC | 443.38 | 453.30 | 402.80 | 523.04 |
| ABT | ABBOTT LABORATORIES | 116.20 | 112.95 | 105.56 | 125.26 |
| NFLX | NETFLIX INC | 868.22 | 822.26 | 700.46 | 1,035.97 |
| ORCL | ORACLE CORP | 172.93 | 156.10 | 140.69 | 187.59 |
| AMD | ADVANCED MICRO DEVICES | 122.68 | 119.65 | 106.46 | 147.22 |
| Nasdaq | |||||
| NDX | Nasdaq-100 Index | 21,575.58 | 21,071.19 | 19,747.14 | 22,233.82 |
| QQQ | Invesco QQQ Trust | 524.73 | 520.66 | 490.93 | 537.18 |
| DowJones | |||||
| DJX | 1/100 Dow Jones Industrial Average Index | 439.75 | 0.00 | 351.80 | 447.20 |
| DIA | SPDR Dow Jones Industrial Average ETF Trust | 439.34 | 423.39 | 405.09 | 443.81 |
| SP500 | |||||
| SPX | Standard & Poor's 500 Index | 6,043.97 | 5,998.83 | 5,572.75 | 6,187.39 |
| XSP | Mini Standard & Poor's 500 Index | 604.35 | 622.81 | 577.72 | 643.27 |
| SPY | SPDR S&P 500 ETF Trust | 602.21 | 600.64 | 567.50 | 612.41 |
| Own Calculations | |||||
| Raw data extracted from the CBOE | |||||
This page shows you the % of Open Interest that, at expiration, ended with one of the following two conditions:
The first two charts are really important. They show, on average, what had happened at expiration on all the tickers that we are analyzing. The last section of this webpage, shows you the details of each ticker (every day, EDO, at expiration).
How can you use this information? Well, in the following way… According to our analysis more than 75%, or in some cases more than 90%, of the Open Interest ended with a Spot Price greater than the Strike Price for the PUTs and with a Strike Price greater than the Spot Price for the Calls (regardless of the underlying asset). So, this means that if you buy an option (a Call or a Put) and you wait until expiration there is a high probability that your trade will end OTM (meaning: you will lose money). This is the Max Pain Theory (more and more assets will be added into this page in the future).
The way of using this webpage is as follow:
The data for this analysis was extracted from the CBOE website.
Currently we DONT HAVE enoght data to forecast 2025. We need, at least, 3 months of data. So, at the end of MARCH 2025 we will update our predictions. The following graphs will show the predictions we made for 2024.
The main idea of this algorithm is to generate a possible future scenario for several asset classes.
The algorithm ran a correlation analysis and train a multiple linear regression model with that information; finally, it generates the future performance (during the current year) according to the training and learning of that model. The training process follows the following logic:
Here you will see two graphs per each asset. The chart in the left shows you the opinion of the model after each training period. This means: after training the model, it generates the Year-End valuation of the asset and display that information in percentage terms. Then, the chart on your right shows you the last training and validation of the last model trained; so, in that graph you will see the most updated opinion.
We know many colleagues who perform this type of analysis and we have had the opportunity to visit some investment banks (specifically on the Sell Side) and they have neither tarot cards nor Ouija boards to make these predictions. Hence, here we want to show you one technique that it is used to make such daring predictions.
Everything is summed up in the following sentence: “History does not repeat itself, but it does rhyme”.
The data for this analysis was extracted from the Yahoo Finance Website
Hi there! I’m Anne Pro, from the AI Research Division, and I’m excited to introduce a smarter, simpler way to navigate the stock market.
After countless hours of analyzing every S&P 500 company, my team and I have built a system that delivers precise BUY and SELL signals straight to you. This isn’t just theory—it’s real, actionable insights you can count on.
🚀 Here’s how it works:
💡 Why join our community?
📈 Your next move starts here! Join us today and start making better, more informed investment decisions. Ready to take the guesswork out of your trading?
👉 Click here to join me and the community now!
The data for this analysis was extracted from the Yahoo Finance Website
| Trading Recommendations and Performance | ||||||||||
| Long Term Swing Trading Strategy | ||||||||||
| Symbol | Company | Sector | Subsector | Type |
Trading Details
|
Return | New Position | |||
|---|---|---|---|---|---|---|---|---|---|---|
| Entry Date | Entry Price | Days Held | Current Price | |||||||
| QQQ | Invesco QQQ Trust | Technology | Large Cap | ETF | 2024-10-07 | 492.57 | 97 days | 507.19 | 3.0% | No |
| SPY | SPDR S&P 500 ETF Trust | Index Funds | Large Cap | ETF | 2023-12-11 | 461.51 | 398 days | 580.49 | 25.8% | No |
| DIA | SPDR Dow Jones Industrial Average ETF | Index Funds | Large Cap | ETF | 2024-06-17 | 387.32 | 209 days | 419.33 | 8.3% | No |
| IWM | iShares Russell 2000 ETF | Index Funds | Small Cap | ETF | 2024-06-24 | 201.6 | 202 days | 216.83 | 7.5% | No |
| AAPL | Apple Inc. | Technology | Consumer Electronics | Stock | 2024-06-03 | 196.45 | 223 days | 236.85 | 20.6% | No |
| NVDA | NVIDIA Corporation | Technology | Semiconductors | Stock | 2024-10-14 | 137.99 | 90 days | 135.91 | −1.5% | No |
| TSLA | Tesla, Inc. | Consumer Discretionary | Automotive | Stock | 2024-06-24 | 197.88 | 202 days | 394.74 | 99.5% | No |
| GOOG | Alphabet Inc. | Technology | Internet Services | Stock | 2024-11-18 | 166.38 | 55 days | 193.17 | 16.1% | No |
| AMZN | Amazon.com, Inc. | Consumer Discretionary | E-Commerce | Stock | 2024-10-21 | 187.83 | 83 days | 218.94 | 16.6% | No |
| META | Meta Platforms, Inc. | Technology | Social Media | Stock | 2024-07-08 | 497.99 | 188 days | 615.86 | 23.7% | No |
| ACN | Accenture PLC | Technology | IT Services | Stock | 2024-08-12 | 325.59 | 153 days | 349.79 | 7.4% | No |
| T | AT&T Inc. | Communication Services | Telecommunications | Stock | 2023-10-23 | 13.78 | 447 days | 21.69 | 57.4% | No |
| WMT | Walmart Inc. | Consumer Staples | Retail | Stock | 2024-02-05 | 55.76 | 342 days | 93 | 66.8% | No |
| MSFT | Microsoft Corporation | Technology | Software | Stock | 2024-11-25 | 423.46 | 48 days | 418.95 | −1.1% | No |
| PANW | Palo Alto Networks, Inc. | Technology | Cybersecurity | Stock | 2024-06-17 | 160.16 | 209 days | 173.42 | 8.3% | No |
| SMH | VanEck Semiconductor ETF | Technology | Semiconductors | ETF | 2024-11-11 | 238.89 | 62 days | 247.18 | 3.5% | No |
| PLTR | Palantir Technologies Inc. | Technology | Software | Stock | 2024-07-08 | 28.07 | 188 days | 67.26 | 139.6% | No |
| VST | Vistra Corp | Utilities | Power Generation | Stock | 2024-09-30 | 138.19 | 104 days | 166.73 | 20.7% | No |
| ORCL | Oracle Corporation | Technology | Software | Stock | 2024-02-19 | 110.75 | 328 days | 154.5 | 39.5% | No |
| DELL | Dell Technologies Inc. | Technology | Hardware | Stock | 2024-11-04 | 134.23 | 69 days | 114.77 | −14.5% | No |
| CSCO | Cisco Systems, Inc. | Technology | Networking | Stock | 2024-08-19 | 50.01 | 146 days | 58.74 | 17.4% | No |
| SNOW | Snowflake Inc. | Technology | Cloud Computing | Stock | 2024-11-18 | 167.44 | 55 days | 162.46 | −3.0% | No |
| Performance calculated based on entry price and current market price. As of: 2025-01-22 | ||||||||||
| New Position means: opened within the past week | ||||||||||
| The list of tickers that we are monitoring waiting for them to change status are: GLD - SPDR Gold Shares, SLV - iShares Silver Trust, MDB - MongoDB, Inc., INTC - Intel Corporation, KO - Coca-Cola Company, MMM - 3M Company, AMD - Advanced Micro Devices, Inc., BABA - Alibaba Group Holding Limited, QCOM - Qualcomm Inc. | ||||||||||
Hi there! I’m Anne Pro, from the AI Research Division, and I’m thrilled to introduce a dynamic, momentum-driven approach to help you stay ahead in today’s fast-paced stock market.
After countless hours of analyzing market data and refining our algorithms, my team and I have developed a strategy that identifies assets with the strongest underlying momentum in specific indices. This isn’t guesswork—these are data-backed insights designed to maximize your portfolio’s potential.
🚀 Here’s how it works:
💡 Why join our community?
📈 Take control of your trading journey today! Join us and unlock the power of momentum-based investing—because timing the market just got a whole lot easier.
👉 Click here to join me and our growing community now!
The data for this analysis was extracted from the Yahoo Finance Website
In the following section I will show information related to the Sectors: