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drawdowns Analysis: Statistical analysis of the Drawdowns in mayor indices.
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As for the previous trading day, June 11, 2025, the U.S. Government Bond market displayed notable trends across various maturities, reflecting broader economic conditions and investor sentiment. The 1-month yield stood at 4.3%, while the 3-month and 6-month yields were at 4.39% and 4.45%, respectively. The 1-year yield was 4.31%, and the 2-year yield was 4.08%. Longer maturities, such as the 10-year and 30-year bonds, yielded 4.93% and 4.91%, respectively.
Analyzing the historical yield data, we observe that short-term yields have shown a slight upward trend, particularly in the 1-month to 6-month range, indicating expectations of tighter monetary policy in the near term. Conversely, the 2-year yield has been relatively stable, suggesting market anticipation of a potential stabilization in interest rate hikes. The 10-year and 30-year yields have remained elevated, reflecting concerns about long-term inflation and economic growth prospects.
Currently, the 10-year bond offers the highest yield at 4.93%, while the 2-year bond has the lowest yield at 4.08%. This yield configuration suggests a preference for longer-duration bonds, possibly due to expectations of future economic stabilization or a decline in inflationary pressures. The long-term trend indicates a generally rising yield environment, consistent with market expectations of persistent inflation and a cautious Federal Reserve stance.
Turning to the yield curve slope analysis, the 2-Year to 10-Year yield spread is 0.85% (4.93% - 4.08%), indicating a positive slope. This positive spread suggests a normal yield curve, typically associated with expectations of economic growth and moderate inflation. The 3-Month to 10-Year yield spread is 0.54% (4.93% - 4.39%), also positive, reinforcing the view of a stable economic outlook. Historically, these spreads have been widening, suggesting increased confidence in long-term economic prospects.
From a bond price sensitivity perspective, longer-duration bonds like the 10-year and 30-year are more sensitive to interest rate changes, exhibiting greater price volatility. In a rising rate environment, shorter-duration bonds are preferable to minimize price risk. Conversely, in a declining rate environment, longer-duration bonds offer better capital appreciation potential due to their higher sensitivity to rate changes.
Given the current yield dynamics, investors might consider a balanced approach, incorporating both short and long-duration bonds to manage risk and capture yield opportunities. In light of potential Federal Reserve actions, maintaining flexibility in bond allocations can help navigate interest rate volatility.
Looking ahead, the macroeconomic outlook suggests a cautious approach, with potential shifts in monetary policy depending on inflation trends and economic data. If the yield curve remains positively sloped, it may signal continued economic expansion, albeit with vigilance for any signs of overheating. Investors should remain attentive to changes in yield spreads as indicators of shifting economic conditions.
To enhance understanding of these dynamics, additional resources such as yield curve charts and historical data analysis could provide valuable insights into the evolving fixed-income landscape. 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.
As for the previous trading day, global stock markets exhibited varied performance across different continents, reflecting a mix of economic conditions and investor sentiment. Here’s a detailed analysis of both Year-to-Date (YTD) and daily performance, grouped by continent, to provide insights into current market dynamics and potential investment opportunities.
YTD Performance Analysis
Oceania: - New Zealand has shown modest YTD growth at 0.79%, while Australia has performed better with an 11.25% increase. The stronger performance in Australia could be attributed to its robust commodity sector and economic resilience.
Asia: - South Korea leads with a remarkable 31.04% YTD growth, followed by China at 21.38% and Taiwan at 8.75%. Japan also shows solid performance with a 9.94% increase. The strong performance in South Korea and China may be driven by technology sector gains and economic recovery post-pandemic. - India shows moderate growth at 3.61%, while Saudi Arabia underperforms with a -6.10% decline, possibly due to fluctuating oil prices impacting its economy.
Europe: - Spain and Italy are standout performers with YTD gains of 40.44% and 34.82%, respectively. Germany also shows strong growth at 33.34%. These gains may be supported by economic recovery and fiscal stimulus measures. - France and Netherlands also perform well with over 21% growth, while the United Kingdom shows a solid 19.49% increase.
Middle East: - Qatar shows a positive YTD return of 5.98%, contrasting with Saudi Arabia’s negative performance. This divergence could be due to differing economic structures and external trade dependencies.
North America: - Canada has a strong YTD performance of 13.16%, while the United States shows a modest 3.17% increase. The US market’s slower growth may reflect concerns over interest rates and inflation.
South America: - Chile and Brazil show robust growth with 31.37% and 24.26% increases, respectively. Mexico also performs well with a 29.00% gain. These performances may be driven by commodity exports and economic stabilization.
Daily Performance Analysis
Oceania: - New Zealand saw a daily increase of 0.24%, while Australia experienced a slight decline of -0.41%. This mixed performance may reflect short-term market adjustments.
Asia: - South Korea led daily gains with a 1.25% increase, while China and India also saw positive movements. Japan experienced a slight decline of -0.28%. The daily gains in South Korea could be linked to positive earnings reports or economic data.
Europe: - United Kingdom showed a daily increase of 0.25%, while most other European markets, including Germany and France, experienced slight declines. This could indicate short-term profit-taking or geopolitical concerns.
Middle East: - Qatar had a small daily gain of 0.21%, while Saudi Arabia declined by -0.67%. This may reflect ongoing volatility in oil markets.
North America: - Canada saw a daily increase of 0.51%, while the United States declined by -0.29%. The US market’s decline could be due to investor caution ahead of economic data releases.
South America: - Chile and Brazil experienced significant daily gains of 2.26% and 1.80%, respectively, possibly driven by positive commodity price movements.
Regional Insights and Strategic Recommendations
Opportunities: - Asia, particularly South Korea and China, offers strong growth potential, driven by technology and economic recovery. Investors may consider growth-focused strategies in these markets. - Europe, with standout performances in Spain and Italy, presents opportunities for investors seeking exposure to economic recovery and fiscal stimulus benefits.
Risks: - Saudi Arabia’s negative YTD performance suggests caution, potentially favoring defensive strategies due to oil market volatility. - United States’s modest growth highlights potential risks from inflation and interest rate concerns, suggesting a balanced approach.
Macroeconomic factors such as inflation, interest rates, and geopolitical tensions continue to influence market dynamics. Investors should remain vigilant and consider these factors when making strategic decisions.
Additional reference data, including charts and historical data, are available to further support the insights presented in this analysis. 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.
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 | 3.29% | −0.30% | 1.06% | −0.54% | −0.54% |
Real Estate | VNQI | Vanguard Global ex-U.S. Real Estate ETF | 14.69% | 11.37% | 2.01% | −0.02% | −0.02% |
Real Estate | REZ | iShares Residential and Multisector Real Estate ETF | 3.75% | −4.15% | −0.85% | −0.65% | −0.65% |
Commodity | |||||||
Commodity | USO | United States Oil Fund LP | −2.74% | −3.25% | 11.42% | 4.50% | 4.50% |
Commodity | GLD | SPDR Gold Shares | 25.65% | 7.02% | 1.57% | 0.54% | 0.54% |
Commodity | SLV | iShares Silver Trust | 22.35% | 6.32% | 9.83% | −0.84% | −0.84% |
Commodity | DBA | Invesco DB Agriculture Fund | 1.62% | 2.70% | 1.31% | −0.07% | −0.07% |
Commodity | DBC | Invesco DB Commodity Index Tracking Fund | 1.76% | −2.36% | 5.22% | 1.62% | 1.62% |
Commodity | CPER | United States Copper Index Fund | 18.56% | −5.00% | 2.25% | −2.21% | −2.21% |
Commodity | UNG | United States Natural Gas Fund LP | −6.23% | −26.19% | 1.53% | −0.68% | −0.68% |
Fixed Income | |||||||
Fixed Income | BIL | SPDR Bloomberg 1-3 Month T-Bill ETF | 1.81% | 0.82% | 0.12% | 0.00% | 0.00% |
Fixed Income | SHY | iShares 1-3 Year Treasury Bond ETF | 2.18% | 0.58% | 0.03% | 0.16% | 0.16% |
Fixed Income | IEF | iShares 7-10 Year Treasury Bond ETF | 3.49% | −0.23% | −0.03% | 0.42% | 0.42% |
Fixed Income | TIP | iShares TIPS Bond ETF | 3.04% | −1.02% | −0.52% | 0.17% | 0.17% |
Fixed Income | TLT | iShares 20+ Year Treasury Bond ETF | 0.12% | −4.33% | 0.21% | 0.30% | 0.30% |
Fixed Income | BND | Vanguard Total Bond Market ETF | 2.67% | −0.06% | 0.22% | 0.32% | 0.32% |
Equity | |||||||
Equity | SPY | SPDR S&P 500 ETF Trust | 3.17% | 7.50% | 2.03% | −0.29% | −0.29% |
Equity | QQQ | Invesco QQQ Trust | 4.50% | 13.54% | 2.56% | −0.34% | −0.34% |
Equity | DIA | SPDR Dow Jones ETF Trust | 1.88% | 2.44% | 1.60% | −0.00% | −0.00% |
Equity | IWM | iShares Russell 2000 ETF | −3.18% | 7.09% | 4.17% | −0.41% | −0.41% |
By: 2025-06-11 |
As for the previous trading day, the financial markets presented a varied landscape, with distinct performance metrics across key sectors. In the Equities sector, the SPDR S&P 500 ETF Trust (SPY) experienced a slight daily decline of 0.29%, reflecting broader market caution. Over the week, SPY has seen a modest decrease of 0.29%, but it maintains a positive monthly return of 2.03% and a quarterly gain of 7.50%, with a year-to-date increase of 3.17%. The Invesco QQQ Trust (QQQ), representing the technology-heavy Nasdaq, also faced a daily decline of 0.34%. Despite this, QQQ has achieved a weekly decline of 0.34%, a monthly gain of 2.56%, and a significant year-to-date return of 4.50%, highlighting the resilience of tech stocks. The SPDR Dow Jones ETF Trust (DIA) remained relatively stable with a negligible daily decline, showing a weekly decrease of 0.002%, a monthly gain of 1.60%, and a year-to-date return of 1.88%. The iShares Russell 2000 ETF (IWM) faced a more pronounced daily decline of 0.41%, with a weekly drop of 0.41%, but it has shown a robust monthly gain of 4.17%, despite a year-to-date decline of 3.18%.
In the Fixed Income sector, the SPDR Bloomberg 1-3 Month T-Bill ETF (BIL) remained stable with no daily change, reflecting its role as a safe haven. The iShares 1-3 Year Treasury Bond ETF (SHY) showed a modest daily gain of 0.16%, with a slight weekly increase of 0.16%, and a year-to-date return of 2.18%. The iShares 7-10 Year Treasury Bond ETF (IEF) posted a daily gain of 0.42%, but faced challenges over the month with a negative return of 0.03%, highlighting the impact of rising interest rates. The iShares TIPS Bond ETF (TIP) also showed a daily gain of 0.17%, but faced a monthly decline of 0.52%, reflecting inflationary pressures. The iShares 20+ Year Treasury Bond ETF (TLT) showed a daily return of 0.30%, but a significant monthly decline of 4.33%, reflecting long-duration bond sensitivity to interest rate changes. The Vanguard Total Bond Market ETF (BND) showed a daily gain of 0.32%, with a monthly return of 0.22%, and a year-to-date gain of 2.67%.
Commodities presented a mixed picture, with the United States Oil Fund LP (USO) experiencing a strong daily gain of 4.50% and a substantial monthly increase of 11.42%, indicating volatility in energy markets. Conversely, SPDR Gold Shares (GLD) showed resilience with a daily gain of 0.54%, a monthly return of 1.57%, and a significant year-to-date gain of 25.65%, driven by safe-haven demand amid geopolitical tensions. The iShares Silver Trust (SLV) faced a daily decline of 0.84%, but has achieved a monthly gain of 9.83% and a year-to-date return of 22.35%. The United States Natural Gas Fund LP (UNG) faced significant challenges, with a daily decline of 0.68% and a staggering year-to-date loss of 6.23%, reflecting oversupply and demand fluctuations.
In Real Estate, the Vanguard Real Estate ETF (VNQ) showed a daily decline of 0.54%, with a monthly return of 1.06%, indicating investor caution in the sector. The Vanguard Global ex-U.S. Real Estate ETF (VNQI) remained relatively stable with a negligible daily decline, showing a monthly gain of 2.01% and a year-to-date return of 14.69%. The iShares Residential and Multisector Real Estate ETF (REZ) faced a daily decline of 0.65%, with a monthly decline of 0.85%, reflecting challenges in the residential sector.
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 QQQ is recommended, capitalizing on broad market exposure and tech sector resilience. 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 offering a hedge against inflation, while energy investments require careful consideration due to volatility. In Real Estate, VNQI 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.
For additional reference data, please consult the table accompanying this analysis.
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 13.7987% on June 12, 2025, it has steadily increased to 17.8743% by June 18, 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 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.
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 gradual upward trend over the past two years. Starting from 14.48% on June 13, 2025, it has increased to 16.52% 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.
As for the previous trading day, the performance of the major U.S. indices, namely the SP500, Nasdaq, and Dow Jones, reflects a complex market environment. The SP500 has shown a mixed performance with periods of gains and subsequent declines, indicating volatility and uncertainty in the market. The Nasdaq, heavily weighted towards technology stocks, has experienced more pronounced fluctuations, suggesting heightened sensitivity to changes in market sentiment and economic indicators. Meanwhile, the Dow Jones, with its composition of more established companies, has demonstrated relative stability but still faces challenges.
In analyzing the SP500, sector performance provides valuable insights. The top-performing companies, although not explicitly listed in the provided data, can be inferred from the sectors that have shown resilience. For instance, sectors such as Consumer Discretionary and Information Technology have companies like Deckers Brands and Enphase Energy, respectively, which have faced significant declines. This suggests that while these sectors may have potential for growth, they are currently under pressure, possibly due to shifts in consumer behavior and technological disruptions.
Conversely, the bottom-performing companies, as highlighted, include those from Health Care and Utilities, with UnitedHealth Group and Edison International experiencing notable declines. These sectors may be grappling with regulatory challenges, cost pressures, or changes in demand dynamics. The underperformance of these sectors could weigh on the SP500’s overall returns, especially if these companies hold significant weight within the index.
Sector rotation trends indicate a potential shift towards more defensive sectors. The presence of Consumer Staples companies like Target Corporation and Clorox among the bottom performers suggests that even traditionally stable sectors are not immune to current market challenges. However, the broader market cycle appears to be in a contraction phase, with investors possibly seeking refuge in sectors that offer stability and consistent returns.
Strategically, it may be prudent to consider overweight positions in sectors that have shown resilience or are poised for recovery. For instance, while Information Technology has faced setbacks, its long-term growth prospects remain strong, making it a candidate for strategic investment. Conversely, sectors like Health Care, despite current underperformance, may offer value opportunities as they navigate through regulatory and operational challenges.
Risk management strategies should focus on diversification across sectors to mitigate potential downturns. Additionally, considering the current market cycle, investors might benefit from focusing on dividend-paying stocks in stable sectors, providing a buffer against volatility. Monitoring macroeconomic factors such as inflation, interest rate changes, and geopolitical risks will be crucial in assessing sector performance and making informed investment decisions.
For a deeper understanding of market trends, additional resources such as sector breakdowns, performance charts, and economic forecasts could provide valuable context and support strategic decision-making.
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 2025-06-11 | ||||||
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%) | −1.69% |
Historical ES (95%) | −2.86% |
Modified VaR (95%) | −1.56% |
Modified ES (95%) | −1.56% |
Updated: 2025-06-11 |
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 2025-06-11 | ||||||
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 |
2024-12-17 | 2025-04-08 | NA | −24.3% | 121 | 76 | NA |
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 | 0.90% |
Loss Deviation | 1.02% |
Downside Deviation (MAR=210%) | 1.37% |
Downside Deviation (Rf=0%) | 0.90% |
Downside Deviation (0%) | 0.90% |
Maximum Drawdown | 77.93% |
Historical VaR (95%) | −2.02% |
Historical ES (95%) | −3.12% |
Modified VaR (95%) | −1.83% |
Modified ES (95%) | −2.73% |
Updated: 2025-06-11 |
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 2025-06-11 | ||||||
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 | 0.79% |
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%) | −2.61% |
Modified VaR (95%) | −1.54% |
Modified ES (95%) | −1.81% |
Updated: 2025-06-11 |
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, the SP500’s Gamma Exposure (GEX) analysis reveals critical insights into market dynamics and potential strategies. The key levels of interest include the put wall, call wall, and gamma flip, which are essential for understanding the current market environment.
The put wall is identified at a strike price of 5217, representing the level where the highest concentration of negative gamma is present. This level acts as a significant downside support, suggesting that if the SP500 approaches this level, market makers might need to adjust their hedging strategies, potentially increasing volatility. The call wall, on the other hand, is located at a strike price of 6236, indicating the area with the highest positive gamma concentration. This level serves as a resistance point, potentially capping upside movements.
The gamma flip, a crucial level where the total gamma exposure switches from negative to positive, is at 5965. The SP500’s closing price should be compared to this level to assess the current gamma territory. If the SP500 is trading below the gamma flip, it indicates negative gamma territory, where market makers may exacerbate price movements, leading to increased volatility. Conversely, trading above the gamma flip suggests positive gamma territory, where market makers’ hedging activities tend to dampen volatility.
In the current scenario, the SP500’s closing price is at 6012, which is above the gamma flip level of 5965. This places the market in positive gamma territory, suggesting a more stable environment with reduced volatility. The proximity of the closing price to the call wall at 6236 indicates potential resistance, while the distance from the put wall at 5217 suggests a buffer against immediate downside risk.
The analysis of gamma exposure across different strikes shows significant clustering around the gamma flip level, with notable positive gamma values above this level. This clustering indicates that as long as the SP500 remains above the gamma flip, market volatility is likely to be contained, favoring range-bound trading strategies.
Given the SP500’s position relative to these key levels, several strategies can be recommended. Since the market is in positive gamma territory, range-bound strategies such as selling options or implementing iron condors could be effective, as they capitalize on reduced volatility. If the SP500 approaches the call wall, strategies that involve selling calls or taking advantage of limited upside potential may be prudent. Conversely, if the SP500 were to move closer to the put wall, protective hedging strategies would become more relevant to guard against potential downside risks.
For readers seeking additional insights, charts and visual aids accompanying this analysis can provide a more comprehensive view of Gamma Exposure trends. These resources, available for SPX, SPY, and XSP, can enhance understanding and support strategic planning, ultimately leading to more informed decision-making.
As for the previous trading day, the Consumer Price Index (CPI) data reveals several important trends and implications for the economy and financial markets.
1. Component Contribution Analysis
Recent data indicates that housing and services have been significant contributors to the CPI, with consistent increases over the past months. Housing costs, in particular, have shown a steady upward trend, reflecting ongoing supply constraints and high demand. Services also continue to rise, driven by increased labor costs and demand for various service-related activities.
On the other hand, apparel and commodities have shown minimal impact on the overall CPI. Apparel prices have been relatively stable, while commodities have experienced some fluctuations but have not significantly influenced the overall index. Notably, transportation costs have shown some volatility, with occasional spikes likely due to fluctuating fuel prices and supply chain disruptions.
Overall, the component-level trends suggest that while some areas like housing and services are experiencing rising costs, others like apparel and commodities are more stable. These trends are consistent with ongoing supply chain challenges and shifts in consumer demand patterns.
2. Month-over-Month (MoM) Change and Volatility
The MoM analysis shows that the CPI has experienced moderate volatility over the past year. Recent months have seen some fluctuations, with notable increases in January and August, suggesting temporary inflationary pressures. These spikes could be attributed to seasonal factors or short-term supply disruptions.
However, the overall trend indicates a gradual stabilization, with MoM changes becoming less pronounced in recent months. This suggests that while inflationary pressures persist, they may be moderating as supply chains adjust and demand stabilizes.
3. Year-over-Year (YoY) Change and Volatility
The YoY analysis reveals that the CPI remains above the 2% target, with core CPI consistently above this threshold. While there has been a slight downward trend in recent months, the CPI is still elevated, indicating persistent inflationary pressures.
This elevated CPI suggests that central banks may continue to consider interest rate hikes to curb inflation. However, the recent moderation in YoY changes could signal that inflation is beginning to stabilize, potentially reducing the urgency for aggressive rate hikes.
4. Strategic Implications and Macroeconomic Insights
Given the current CPI trends, there is a likelihood of continued interest rate hikes in the near term, although the pace may slow if inflation continues to moderate. The persistent inflationary pressures increase the risk of a recession, as higher interest rates could dampen economic growth.
For the stock market, sectors sensitive to inflation, such as consumer staples and utilities, may benefit from the current environment. Conversely, sectors like technology and discretionary spending could face headwinds due to higher borrowing costs and reduced consumer spending.
Globally, economic scenarios such as geopolitical tensions or policy shifts could further impact CPI trends. For instance, any resolution to supply chain disruptions or changes in trade policies could influence inflation dynamics and market performance.
In summary, while CPI trends indicate persistent inflationary pressures, there are signs of moderation. This complex environment requires careful monitoring of economic indicators and strategic adjustments to navigate potential risks and opportunities in the financial markets.
YoY CPI Component Changes | ||||||||||||
Core | All Items | Apparel | Medical Care | Housing | Food and Beverage | Commodities | Services | Transport | Education | Education and Comms | Recreation | |
---|---|---|---|---|---|---|---|---|---|---|---|---|
May 2025 | 2.767% | 2.376% | -0.923% | 2.481% | 3.972% | 2.814% | 0.026% | 3.695% | -1.231% | 3.645% | 0.319% | 1.803% |
Apr 2025 | 2.782% | 2.334% | -0.713% | 2.738% | 3.971% | 2.687% | -0.126% | 3.716% | -1.401% | 3.751% | 0.233% | 1.590% |
Mar 2025 | 2.809% | 2.406% | 0.346% | 2.644% | 3.710% | 2.889% | 0.083% | 3.707% | -0.826% | 3.911% | 0.559% | 1.848% |
Feb 2025 | 3.144% | 2.814% | 0.547% | 2.887% | 3.845% | 2.519% | 0.555% | 4.075% | 1.583% | 3.654% | 0.334% | 1.777% |
Jan 2025 | 3.292% | 2.999% | 0.468% | 2.635% | 3.847% | 2.408% | 0.776% | 4.237% | 3.064% | 3.831% | 0.491% | 1.625% |
Dec 2024 | 3.214% | 2.872% | 1.318% | 2.816% | 4.097% | 2.391% | 0.239% | 4.393% | 1.586% | 3.953% | 0.611% | 1.090% |
Nov 2024 | 3.280% | 2.714% | 1.246% | 3.066% | 4.129% | 2.324% | -0.329% | 4.492% | 0.302% | 4.151% | 0.716% | 1.479% |
Oct 2024 | 3.293% | 2.571% | 0.342% | 3.290% | 4.188% | 2.116% | -1.078% | 4.735% | -0.320% | 3.764% | 0.765% | 1.006% |
Sep 2024 | 3.290% | 2.433% | 1.782% | 3.256% | 4.091% | 2.228% | -1.343% | 4.696% | -1.124% | 3.576% | 0.877% | 0.716% |
Aug 2024 | 3.292% | 2.611% | 0.238% | 3.015% | 4.349% | 2.057% | -1.093% | 4.848% | -0.630% | 3.100% | 1.000% | 1.546% |
Jul 2024 | 3.228% | 2.938% | 0.139% | 3.209% | 4.342% | 2.181% | -0.285% | 4.881% | 1.148% | 2.833% | 0.885% | 1.373% |
Jun 2024 | 3.261% | 2.970% | 0.644% | 3.253% | 4.392% | 2.222% | -0.343% | 4.989% | 1.187% | 2.778% | 0.714% | 1.331% |
May 2024 | 3.391% | 3.239% | 0.751% | 3.066% | 4.556% | 2.125% | 0.086% | 5.177% | 2.665% | 2.717% | 0.538% | 1.368% |
Apr 2024 | 3.624% | 3.354% | 1.274% | 2.628% | 4.515% | 2.230% | 0.346% | 5.222% | 3.461% | 2.470% | 0.422% | 1.513% |
Mar 2024 | 3.815% | 3.469% | 0.398% | 2.217% | 4.638% | 2.256% | 0.591% | 5.253% | 3.999% | 2.441% | 0.246% | 1.856% |
Feb 2024 | 3.768% | 3.166% | -0.016% | 1.417% | 4.535% | 2.241% | 0.296% | 4.968% | 2.799% | 2.724% | 0.391% | 2.081% |
Jan 2024 | 3.867% | 3.108% | 0.108% | 1.031% | 4.646% | 2.537% | 0.134% | 4.982% | 1.807% | 2.457% | 0.026% | 2.773% |
Dec 2023 | 3.914% | 3.322% | 1.227% | 0.426% | 4.831% | 2.710% | 0.716% | 4.959% | 2.707% | 2.390% | -0.066% | 2.721% |
Nov 2023 | 4.015% | 3.140% | 1.407% | 0.150% | 5.221% | 2.939% | -0.064% | 5.190% | 0.832% | 2.400% | -0.044% | 2.492% |
Oct 2023 | 4.026% | 3.247% | 2.737% | -0.781% | 5.257% | 3.326% | 0.426% | 5.063% | 0.749% | 2.665% | 0.928% | 3.178% |
Sep 2023 | 4.135% | 3.695% | 2.230% | -1.423% | 5.560% | 3.709% | 1.414% | 5.159% | 2.409% | 2.868% | 1.038% | 3.886% |
Aug 2023 | 4.405% | 3.719% | 2.961% | -0.938% | 5.709% | 4.222% | 1.123% | 5.398% | 1.634% | 2.865% | 1.013% | 3.551% |
Jul 2023 | 4.703% | 3.280% | 3.079% | -0.475% | 6.195% | 4.811% | -0.406% | 5.702% | -2.654% | 3.237% | 1.208% | 4.037% |
Jun 2023 | 4.858% | 3.059% | 2.892% | 0.118% | 6.322% | 5.680% | -0.979% | 5.746% | -4.779% | 3.144% | 1.088% | 4.290% |
May 2023 | 5.336% | 4.125% | 3.401% | 0.723% | 6.797% | 6.593% | 0.821% | 6.302% | -1.679% | 3.396% | 1.463% | 4.542% |
Apr 2023 | 5.514% | 4.947% | 3.554% | 1.051% | 7.428% | 7.472% | 2.141% | 6.789% | 0.274% | 3.574% | 1.554% | 5.004% |
Mar 2023 | 5.563% | 4.931% | 3.153% | 1.499% | 7.783% | 8.239% | 1.461% | 7.231% | -1.114% | 3.546% | 1.398% | 4.867% |
Feb 2023 | 5.495% | 5.958% | 3.263% | 2.361% | 8.201% | 9.166% | 3.460% | 7.597% | 2.369% | 3.330% | 1.041% | 4.967% |
Jan 2023 | 5.539% | 6.340% | 3.069% | 3.037% | 8.229% | 9.827% | 4.379% | 7.619% | 3.655% | 3.388% | 1.016% | 4.790% |
Dec 2022 | 5.684% | 6.411% | 3.045% | 3.936% | 8.042% | 10.136% | 4.746% | 7.488% | 3.608% | 3.337% | 0.766% | 5.153% |
Nov 2022 | 5.965% | 7.131% | 3.855% | 4.131% | 7.802% | 10.323% | 7.011% | 7.210% | 7.854% | 3.127% | 0.717% | 4.782% |
Oct 2022 | 6.296% | 7.757% | 4.275% | 5.000% | 7.880% | 10.559% | 8.587% | 7.231% | 11.215% | 3.022% | 0.032% | 4.087% |
Sep 2022 | 6.633% | 8.206% | 5.439% | 5.991% | 8.034% | 10.751% | 9.529% | 7.374% | 12.624% | 3.099% | 0.146% | 4.072% |
Aug 2022 | 6.294% | 8.216% | 4.873% | 5.383% | 7.861% | 10.919% | 10.420% | 6.835% | 13.295% | 3.090% | 0.416% | 4.110% |
Jul 2022 | 5.900% | 8.448% | 4.967% | 4.880% | 7.407% | 10.480% | 11.898% | 6.292% | 16.182% | 2.616% | 0.494% | 4.351% |
Jun 2022 | 5.908% | 8.999% | 5.037% | 4.535% | 7.368% | 10.027% | 13.407% | 6.247% | 19.670% | 2.706% | 0.821% | 4.623% |
May 2022 | 6.020% | 8.530% | 4.907% | 3.738% | 6.922% | 9.742% | 13.034% | 5.752% | 19.339% | 2.499% | 0.793% | 4.459% |
Apr 2022 | 6.157% | 8.235% | 5.410% | 3.234% | 6.498% | 9.016% | 12.904% | 5.379% | 19.881% | 2.508% | 1.042% | 4.276% |
Mar 2022 | 6.480% | 8.541% | 6.731% | 2.869% | 6.329% | 8.472% | 14.189% | 5.097% | 22.506% | 2.515% | 1.570% | 4.749% |
Feb 2022 | 6.456% | 7.949% | 6.530% | 2.451% | 5.927% | 7.613% | 13.176% | 4.777% | 21.239% | 2.143% | 1.578% | 4.938% |
Jan 2022 | 6.058% | 7.578% | 5.307% | 2.468% | 5.644% | 6.686% | 12.587% | 4.545% | 21.051% | 2.148% | 1.643% | 4.766% |
Dec 2021 | 5.504% | 7.159% | 5.866% | 2.150% | 5.085% | 6.014% | 12.344% | 4.036% | 21.501% | 2.007% | 1.627% | 3.276% |
Nov 2021 | 4.974% | 6.866% | 5.288% | 1.722% | 4.791% | 5.803% | 12.020% | 3.793% | 21.228% | 2.107% | 1.664% | 3.214% |
Oct 2021 | 4.583% | 6.227% | 4.578% | 1.295% | 4.518% | 5.100% | 10.538% | 3.653% | 18.650% | 2.049% | 1.771% | 3.853% |
Sep 2021 | 4.014% | 5.364% | 3.386% | 0.411% | 3.885% | 4.437% | 9.006% | 3.192% | 16.495% | 1.950% | 1.716% | 3.472% |
Aug 2021 | 3.949% | 5.181% | 3.988% | 0.356% | 3.499% | 3.650% | 8.798% | 3.034% | 17.473% | 1.379% | 1.202% | 3.410% |
Jul 2021 | 4.207% | 5.269% | 4.068% | 0.325% | 3.359% | 3.368% | 9.013% | 3.057% | 19.027% | 1.165% | 1.129% | 3.514% |
Jun 2021 | 4.423% | 5.317% | 4.760% | 0.432% | 3.143% | 2.358% | 8.879% | 3.207% | 21.265% | 1.176% | 2.086% | 2.353% |
May 2021 | 3.785% | 4.926% | 5.574% | 0.921% | 2.895% | 2.123% | 8.121% | 3.047% | 19.710% | 1.045% | 1.904% | 1.601% |
Apr 2021 | 2.965% | 4.137% | 2.076% | 1.475% | 2.617% | 2.364% | 6.715% | 2.621% | 14.737% | 0.822% | 1.694% | 2.128% |
Mar 2021 | 1.647% | 2.624% | -2.531% | 1.787% | 2.111% | 3.372% | 4.096% | 1.747% | 5.871% | 0.783% | 1.500% | 1.067% |
Feb 2021 | 1.274% | 1.668% | -3.704% | 2.045% | 1.765% | 3.529% | 2.202% | 1.345% | 0.636% | 1.180% | 1.741% | 0.786% |
Jan 2021 | 1.387% | 1.355% | -2.649% | 1.938% | 1.760% | 3.706% | 1.428% | 1.309% | -1.360% | 1.264% | 1.744% | 0.144% |
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 of factors shaping the current and future market environment. The analysis of recent trends in the Fed’s liquidity provisions, particularly focusing on the repo market and other balance sheet components, provides valuable insights into market behavior and potential outcomes.
Liquidity Trends and Analysis
The Federal Reserve’s liquidity position is influenced by several key metrics, including total assets, liabilities, net liquidity, and liquidity facilities. As of June 4, 2025, the data indicates a net liquidity position of approximately 6.127 billion USD, with primary credit facilities showing minimal utilization. This suggests a relatively stable liquidity environment, with the Fed maintaining a cautious stance on credit provisions.
The overnight repo market, a critical component of the Fed’s liquidity operations, has shown significant activity. On June 11, 2025, the overnight repo volume reached 204.625 billion USD, marking a notable increase from previous days. This upward trend in repo volumes indicates heightened demand for short-term funding, reflecting financial institutions’ need for liquidity to meet their obligations.
Impact on Market Dynamics and Strategic Insights
The current liquidity environment, characterized by stable net liquidity and increasing repo activity, suggests a supportive backdrop for financial markets. The rise in repo volumes points to robust short-term funding conditions, which can enhance financial stability and reduce market volatility. However, it also signals potential stress points if liquidity demand continues to outpace supply.
In terms of market positioning, the increased liquidity provisions could foster risk-on conditions, encouraging investors to seek higher returns in equity markets. Conversely, any contraction in liquidity, particularly in the repo market, could trigger risk-off sentiment, leading to increased volatility and potential market corrections.
Broader macroeconomic factors, such as inflation and interest rate expectations, play a crucial role in shaping the Fed’s liquidity decisions. With inflationary pressures and potential rate hikes on the horizon, the Fed may adjust its liquidity stance to balance economic growth and price stability.
REPO Market Analytics
Recent trends in the repo market highlight the critical role of overnight repo operations in meeting liquidity demands. The increase in repo volumes from 135.841 billion USD on June 2, 2025, to 204.625 billion USD on June 11, 2025, underscores the growing need for short-term funding. This trend correlates with increased liquidity demand from financial institutions, reflecting the Fed’s ability to influence short-term funding conditions effectively.
Repo market activities significantly impact the Fed’s net liquidity stance. The current increase in repo volumes supports overall liquidity levels, indicating looser funding conditions. Historically, increased repo activity has often corresponded with bullish trends in the stock market, suggesting potential for short-term market gains.
However, the risk associated with current repo market activities should not be underestimated. A sudden decrease in repo volumes could lead to tighter funding conditions, posing risks to financial stability. Monitoring repo activities closely is essential to identify potential stress points and mitigate market disruptions.
Observations and Recommendations
In summary, the Fed’s liquidity provisions have shown stability, with increased repo activity supporting market liquidity. This environment presents growth opportunities in equity markets, although caution is warranted given potential liquidity contractions. Investors should consider positioning strategies that capitalize on increased liquidity while remaining vigilant to shifts in repo volumes and net liquidity.
Potential scenarios include continued repo volume growth, supporting market stability, or a contraction in liquidity, leading to increased volatility. Monitoring these trends will be crucial for navigating market dynamics effectively.
Additional data, including detailed metrics and historical trends, is available to support this analysis and provide further insights into the Fed’s liquidity measures and their implications for financial markets.
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 17.0158% on June 12, 2025, it has steadily increased to 22.1805% by June 18, 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.
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 a nuanced picture of market positioning and critical levels across major indices and sectors. The SPX, with a gamma flip point at 6012, is currently trading below this level, indicating a negative gamma regime. This suggests potential for accelerated downside moves unless the index can reclaim the 6012 level. The put wall at 5965 provides a significant support level, while the call wall at 6236 marks a resistance zone. The NDX is similarly positioned below its gamma flip point of 21824, with support at 21005 and resistance at 22342, indicating a wide trading range.
In the technology sector, AAPL’s current price is near its gamma flip point of 199, suggesting a pivotal moment. With support at 196 and resistance at 225, AAPL is in a tight range, indicating potential for a breakout or breakdown. MSFT, trading below its gamma flip at 472, faces support at 413 and resistance at 484, highlighting a wider range and potential volatility. NVDA is also below its gamma flip of 143, with support at 126 and resistance at 151, suggesting a cautious approach as it navigates these levels.
The financial sector, represented by JPM and BAC, shows JPM trading below its gamma flip of 268, with support at 246 and resistance at 276. BAC is similarly positioned below its gamma flip of 45, with support at 43 and resistance at 46, indicating a narrow trading range and potential for swift moves.
In healthcare, JNJ is trading near its gamma flip of 156, with support at 152 and resistance at 164, suggesting a potential pivot point. UNH, below its gamma flip of 309, finds support at 286 and resistance at 370, indicating a broader range and potential for significant moves.
The major indices, SPX, NDX, and DJX, are key indicators of overall market sentiment. The DJX, trading below its gamma flip of 428, has support at 362 and resistance at 432, suggesting a potential for volatility as it approaches these critical levels.
From a trading perspective, the proximity of current prices to gamma flip points and support/resistance levels provides actionable insights. For instance, AAPL’s tight range suggests monitoring for a breakout above 199 or a breakdown below 196. Similarly, SPX’s position below its gamma flip indicates caution, with potential support at 5965 as a bounce zone.
Risk management is crucial near these key levels. Traders should consider stop-loss orders near support levels and profit-taking strategies near resistance zones. The potential for breakout or breakdown scenarios necessitates a flexible approach, ready to adapt to rapid market changes.
In conclusion, the current market positioning, with several stocks and indices near critical gamma levels, suggests heightened attention to potential volatility. Additional reference data can be found in the table accompanying this analysis, providing further context for strategic decision-making.
Gamma Exposure for the Most Active Tickets | |||||
Critical Levels to Consider | |||||
Symbol | Name | Price | Gamma Flip | Put Wall | Call Wall |
---|---|---|---|---|---|
Stocks | |||||
AAPL | APPLE INC | 198.84 | 196.14 | 179.30 | 225.13 |
MSFT | MICROSOFT CORP | 472.32 | 413.38 | 377.86 | 483.53 |
AMZN | AMAZON.COM INC | 213.37 | 194.52 | 170.70 | 224.22 |
NVDA | NVIDIA CORP | 142.66 | 126.37 | 114.13 | 150.89 |
GOOGL | ALPHABET INC CL A | 177.86 | 161.53 | 142.29 | 185.70 |
TSLA | TESLA INC | 324.58 | 292.10 | 259.66 | 389.50 |
GOOG | ALPHABET INC CL C | 179.19 | 161.77 | 144.57 | 188.30 |
META | META PLATFORMS INC CLASS A | 693.92 | 590.39 | 555.14 | 724.50 |
XOM | EXXON MOBIL CORP | 108.81 | 102.60 | 95.16 | 113.61 |
LLY | ELI LILLY + CO | 807.16 | 731.78 | 651.20 | 891.99 |
UNH | UNITEDHEALTH GROUP INC | 308.62 | 285.76 | 257.36 | 370.34 |
JPM | JPMORGAN CHASE + CO | 268.03 | 245.71 | 214.42 | 276.21 |
JNJ | JOHNSON + JOHNSON W/D | 156.25 | 151.89 | 141.94 | 164.19 |
V | VISA INC CLASS A SHARES | 372.23 | 339.83 | 302.83 | 376.01 |
PG | PROCTER + GAMBLE CO/THE | 162.31 | 159.84 | 150.76 | 177.17 |
AVGO | BROADCOM INC | 252.41 | 216.95 | 201.93 | 268.67 |
MA | MASTERCARD INC A | 591.02 | 567.16 | 520.90 | 605.04 |
HD | HOME DEPOT INC | 360.38 | 361.39 | 334.73 | 393.36 |
CVX | CHEVRON CORP | 144.61 | 137.50 | 124.51 | 169.61 |
MRK | MERCK + CO. INC. | 80.21 | 78.45 | 70.69 | 96.25 |
ABBV | ABBVIE INC | 192.25 | 177.52 | 157.71 | 208.54 |
ADBE | ADOBE INC | 413.19 | 418.70 | 347.36 | 495.82 |
COST | COSTCO WHOLESALE CORP | 995.78 | 1,000.82 | 924.89 | 1,080.17 |
PEP | PEPSICO INC | 129.95 | 127.20 | 121.58 | 138.32 |
WMT | WALMART INC | 95.53 | 95.60 | 79.01 | 104.27 |
CSCO | CISCO SYSTEMS INC | 64.18 | 58.93 | 51.34 | 66.57 |
KO | COCA COLA CO/THE | 71.95 | 68.84 | 64.39 | 74.64 |
CRM | SALESFORCE INC | 266.46 | 262.58 | 236.65 | 312.53 |
MCD | MCDONALD S CORP | 302.08 | 303.16 | 288.77 | 323.58 |
BAC | BANK OF AMERICA CORP | 44.66 | 42.95 | 37.85 | 46.33 |
ACN | ACCENTURE PLC CL A | 318.05 | 315.98 | 276.00 | 373.03 |
TMO | THERMO FISHER SCIENTIFIC INC | 416.76 | 425.26 | 381.44 | 500.11 |
PFE | PFIZER INC | 24.39 | 23.62 | 21.66 | 28.60 |
CMCSA | COMCAST CORP CLASS A | 35.62 | 33.33 | 31.40 | 37.92 |
LIN | LINDE PLC | 476.00 | 450.57 | 413.07 | 484.07 |
ABT | ABBOTT LABORATORIES | 134.62 | 126.10 | 109.52 | 137.81 |
NFLX | NETFLIX INC | 1,218.00 | 1,204.50 | 1,147.81 | 1,288.19 |
ORCL | ORACLE CORP | 177.10 | 154.17 | 141.68 | 198.11 |
AMD | ADVANCED MICRO DEVICES | 120.90 | 108.44 | 96.72 | 131.97 |
Nasdaq | |||||
NDX | Nasdaq-100 Index | 21,823.91 | 21,004.89 | 19,234.63 | 22,341.76 |
QQQ | Invesco QQQ Trust | 531.62 | 524.05 | 475.75 | 547.84 |
DowJones | |||||
DJX | 1/100 Dow Jones Industrial Average Index | 428.04 | 362.36 | 342.43 | 432.39 |
DIA | SPDR Dow Jones Industrial Average ETF Trust | 429.06 | 425.75 | 401.43 | 439.24 |
SP500 | |||||
SPX | Standard & Poor's 500 Index | 6,012.24 | 5,965.24 | 5,217.40 | 6,236.43 |
XSP | Mini Standard & Poor's 500 Index | 601.22 | 614.81 | 558.42 | 664.40 |
SPY | SPDR S&P 500 ETF Trust | 600.38 | 599.11 | 549.50 | 622.77 |
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.
The main idea of this algorithm is to generate a possible future scenario for several asset classes.
The algorithm runs 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
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The data for this analysis was extracted from the Yahoo Finance Website
📈 Stocks with Positive Trend | ||||||
Report Date: 2025-06-12 | ||||||
Ticker Symbol | Trend Change Date | Price at Trend Change | Days Since Trend Change | Latest Friday Close | return | Return Since Trend Change |
---|---|---|---|---|---|---|
T | 2023-10-27 | $13.64 | 593 | $28.34 | 107.83% | 107.8% |
GLD | 2025-01-24 | $255.65 | 138 | $308.37 | 20.62% | 20.6% |
SLV | 2025-03-07 | $29.59 | 96 | $32.95 | 11.36% | 11.4% |
MSFT | 2025-05-30 | $460.36 | 12 | $472.62 | 2.66% | 2.7% |
PLTR | 2024-07-12 | $28.07 | 334 | $136.39 | 385.89% | 385.9% |
KO | 2025-02-28 | $70.69 | 103 | $72.07 | 1.95% | 1.9% |
BABA | 2025-02-21 | $143.75 | 110 | $120.33 | -16.29% | −16.3% |
📉 Stocks with Negative Trend | ||||||
Report Date: 2025-06-12 | ||||||
Ticker Symbol | Trend Change Date | Price at Trend Change | Days Since Trend Change | Latest Friday Close | return | Return Since Trend Change |
---|---|---|---|---|---|---|
QQQ | 2025-03-21 | $480.12 | 82 | $532.41 | 10.89% | 10.9% |
SPY | 2025-03-21 | $563.98 | 82 | $601.36 | 6.63% | 6.6% |
DIA | 2025-03-28 | $415.10 | 75 | $429.60 | 3.49% | 3.5% |
IWM | 2025-02-07 | $225.49 | 124 | $213.63 | -5.26% | −5.3% |
AAPL | 2025-03-07 | $238.76 | 96 | $198.78 | -16.74% | −16.7% |
NVDA | 2025-02-07 | $129.83 | 124 | $142.83 | 10.01% | 10.0% |
TSLA | 2025-03-14 | $249.98 | 89 | $326.43 | 30.58% | 30.6% |
GOOG | 2025-03-28 | $155.87 | 75 | $178.79 | 14.70% | 14.7% |
AMZN | 2025-03-28 | $192.72 | 75 | $213.20 | 10.63% | 10.6% |
META | 2025-04-25 | $547.27 | 47 | $694.14 | 26.84% | 26.8% |
ACN | 2025-03-21 | $303.81 | 82 | $319.22 | 5.07% | 5.1% |
WMT | 2025-04-11 | $92.58 | 61 | $95.80 | 3.48% | 3.5% |
PANW | 2025-02-14 | $200.03 | 117 | $194.39 | -2.82% | −2.8% |
SMH | 2025-03-14 | $226.57 | 89 | $261.88 | 15.58% | 15.6% |
VST | 2025-03-28 | $119.05 | 75 | $166.79 | 40.10% | 40.1% |
ORCL | 2025-01-31 | $169.45 | 131 | $176.38 | 4.09% | 4.1% |
DELL | 2025-01-24 | $113.01 | 138 | $111.24 | -1.56% | −1.6% |
CSCO | 2025-05-02 | $59.33 | 40 | $64.19 | 8.19% | 8.2% |
SNOW | 2025-04-04 | $130.53 | 68 | $208.61 | 59.82% | 59.8% |
MDB | 2025-01-17 | $253.11 | 145 | $210.60 | -16.80% | −16.8% |
INTC | 2025-05-30 | $19.55 | 12 | $20.68 | 5.78% | 5.8% |
MMM | 2025-05-23 | $147.62 | 19 | $147.18 | -0.30% | −0.3% |
AMD | 2024-12-13 | $126.91 | 180 | $121.14 | -4.55% | −4.5% |
QCOM | 2025-04-11 | $138.42 | 61 | $159.48 | 15.22% | 15.2% |
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⚙️ How the Strategy Works - Index Momentum Analysis: Every day, my system scans all the constituents of a chosen index, assessing price action and trend alignment to detect underlying momentum shifts. - Signal Clarity: Based on a proprietary scoring algorithm, the strategy determines whether to go long or hold a position; eliminating emotional bias from decision-making. Build position when you see a Yellow Dot and increase the bet when you see a Dark Dot (statistically speaking it is when the positive trend starts). - Quantitative Edge: The model pulls historical and real-time data from Yahoo Finance, transforming raw numbers into actionable insights using a disciplined, repeatable process.
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The data for this analysis was extracted from the Yahoo Finance Website