Group 1 - The core viewpoint of the article is that despite recent declines in risk assets, the VIX index has not shown a true "clearing signal," indicating that market panic has not fully materialized. A VIX level around 40 is considered a buy signal for investors [1][4]. - The article emphasizes that the Federal Reserve's rationale for interest rate cuts is diminishing due to persistent inflation, with Fed Chair Powell stating that rate cuts will not occur without visible progress on inflation [1][6]. - The article highlights that the current state of the stock market may still have downward potential, advising investors to remain cautious and avoid blind buying [5]. Group 2 - The article discusses the negative outlook on the Federal Reserve's monetary policy, suggesting that the optimistic inflation forecasts may be unrealistic, with inflation likely to remain above 3% if commodity prices, especially energy, stay high [6]. - There is a strong interest in gold and commodities, with the article suggesting that current levels present a good buying opportunity, despite previous reductions in gold positions [7]. - A significant warning is issued regarding the private credit market, likening its current state to the chaotic environment of the 1830s American West, with alarming data indicating serious asset quality issues and rising credit spreads in CCC-rated loans [10].

Core Viewpoint - The article emphasizes the significance of the CBOE Volatility Index (VIX) as a key indicator of market sentiment and risk, suggesting that changes in VIX levels can signal shifts in market dynamics and investor behavior [2][10][15]. Group 1: VIX as a Market Sentiment Indicator - The VIX, known as the "fear index," reflects market expectations of volatility in the S&P 500 over the next 30 days, serving as a thermometer for market sentiment [2][4]. - A low VIX indicates stable market conditions and a willingness among investors to take risks, while a high VIX suggests rising systemic risks and panic [2][5]. - Historical data shows that when VIX is below 15, the market is in a high-risk appetite phase, while levels above 40 indicate extreme fear and potential market bottoms [5][11]. Group 2: Recent Changes in VIX Behavior - In recent years, the VIX has shown a structural change, with its average level gradually rising from a low volatility environment (10-15) to a higher range (18-24) [7][8]. - This shift indicates a decrease in risk appetite among investors, who are increasingly purchasing hedging options even during market uptrends [9][10]. - The rising VIX suggests that while the market may be increasing, investor confidence in a low-risk environment is waning, leading to heightened sensitivity to negative news [9][12]. Group 3: Implications of Rising VIX Levels - A higher VIX typically results in reduced leverage among institutions, as increased volatility raises the perceived risk of losses, leading to lower market liquidity [11]. - There is an acceleration in sector rotation, with funds moving from high-growth stocks to defensive assets, reflecting a shift from aggressive to conservative investment strategies [11]. - The risk of market crashes increases in high-volatility environments, as seen in past events where rising VIX levels preceded significant downturns [11][12]. Group 4: Strategic Recommendations - Investors are advised to monitor VIX trends closely, as rising volatility can indicate underlying market weaknesses even when indices are climbing [15][16]. - The article suggests that maintaining lower leverage and increasing cash reserves may be prudent strategies in response to rising VIX levels [15][16].

Core Insights - Short-term and medium-term U.S. Treasury bonds experienced slight increases, while long-term bonds remained stable amid risk-off sentiment impacting the stock market [1][4] - The VIX index surged, enhancing demand for short-term Treasuries as many commodities erased gains [1][4] - A $44 billion 7-year Treasury auction attracted demand close to expectations [1][4] Treasury Yield Summary - As of 3:47 PM New York time, the 2-year Treasury yield was reported at 3.557% [5] - The 5-year Treasury yield was reported at 3.8123% [6] - The 10-year Treasury yield was reported at 4.2313% [7] - The 30-year Treasury yield was reported at 4.853% [8] - The yield spread between the 2-year and 10-year Treasuries was 67.228 basis points [8] - The yield spread between the 5-year and 30-year Treasuries was 103.888 basis points [9] Auction Details - The 7-year Treasury auction had a high yield of 0.4 basis points above pre-issue trading levels, with minimal market impact [1][4] - Primary dealers received 10.9% of the auction, above the recent average of 10.2% [1][4] - Direct bidders received 22.2%, below the average of 28% from the previous six auctions, while indirect bidders received 66.9%, above the average of 61.8% from the previous six auctions [1][4]

Core Viewpoint - The current financial market is characterized by a paradox where low VIX levels suggest calmness, while rising gold prices indicate underlying systemic risks [1][3][12]. Group 1: VIX Index and Market Dynamics - The VIX index has dropped to 13.6, a five-year low, indicating a seemingly stable market and high investor confidence [3][5]. - However, this low VIX does not reflect a lack of risk; rather, it suggests that risks are being artificially suppressed by institutions engaging in strategies like shorting volatility and high-frequency trading [7][9]. - The market's apparent calmness is fragile, as historical precedents show that low VIX levels can quickly lead to significant volatility spikes [9][11]. Group 2: Gold Prices and Systemic Risks - Gold prices have surged to over $4,500, reflecting skepticism towards the VIX and signaling growing systemic risks in the financial system [12][14]. - Key indicators, such as the rising interest payments on U.S. debt and the expansion of the Federal Reserve's balance sheet, suggest that systemic risks are accumulating [14][16]. - The demand for gold, including ETFs and physical gold, has increased among central banks and investors, indicating a shift towards tangible assets as a hedge against financial instability [18][20]. Group 3: Future Outlook and Market Sentiment - The outlook for 2026 suggests a facade of geopolitical stability, but real risks lie within the financial system, including potential AI bubble bursts and unsustainable debt levels [22][24]. - The divergence between the narratives of a tech-driven market and the reality of unsustainable debt is becoming more pronounced, with investors increasingly favoring the latter perspective [20][24]. - The current market conditions may not lead to an immediate crisis, but they are likely to prompt a reevaluation of risks and investment strategies as the underlying vulnerabilities become more apparent [26].

Quantitative Models and Construction Methods 1. Model Name: Continuous Hedging Strategy - **Model Construction Idea**: This strategy is based on the analysis of basis convergence factors and optimization strategies, as detailed in the Cinda derivatives research report series. Adjustments are made to the settings for continuous hedging[44] - **Model Construction Process**: - **Backtesting Period**: From July 22, 2022, to December 19, 2025[45] - **Spot Side**: Holding the total return index of the corresponding benchmark index[45] - **Futures Side**: - 70% of the funds are allocated to the spot side - The remaining 30% is used for shorting futures contracts of the same nominal principal (e.g., CSI 500, CSI 300, SSE 50, CSI 1000 index futures)[45] - After each rebalancing, the quantities of the spot and futures sides are recalculated based on the product's net value[45] - **Rebalancing Rules**: - Continuously hold quarterly/monthly contracts until the remaining time to maturity is less than two days - Close the position at the closing price on that day and simultaneously short the next quarterly/monthly contract at the closing price[45] - **Assumptions**: Equal principal allocation between the spot and futures sides, excluding transaction fees, impact costs, and the indivisibility of futures contracts[45] 2. Model Name: Minimum Basis Strategy - **Model Construction Idea**: This strategy selects contracts with the smallest annualized basis discount for hedging, as described in the Cinda derivatives research report series[46] - **Model Construction Process**: - **Backtesting Period**: From July 22, 2022, to December 19, 2025[46] - **Spot Side**: Holding the total return index of the corresponding benchmark index[46] - **Futures Side**: - 70% of the funds are allocated to the spot side - The remaining 30% is used for shorting futures contracts of the same nominal principal (e.g., CSI 500, CSI 300, SSE 50, CSI 1000 index futures)[46] - After each rebalancing, the quantities of the spot and futures sides are recalculated based on the product's net value[46] - **Rebalancing Rules**: - Calculate the annualized basis for all tradable futures contracts on the day of rebalancing - Select the contract with the smallest basis discount for opening a position - Hold the same contract for eight trading days or until the remaining time to maturity is less than eight days, then select a new contract[46] - **Assumptions**: Equal principal allocation between the spot and futures sides, excluding transaction fees, impact costs, and the indivisibility of futures contracts[46] --- Model Backtesting Results 1. Continuous Hedging Strategy - **CSI 500 Index Futures**: - Annualized Return: -3.42% (monthly), -2.58% (quarterly)[48] - Volatility: 3.79% (monthly), 4.69% (quarterly)[48] - Maximum Drawdown: -11.27% (monthly), -8.74% (quarterly)[48] - Net Value: 0.8886 (monthly), 0.9149 (quarterly)[48] - Annual Turnover: 12 (monthly), 4 (quarterly)[48] - 2025 YTD Return: -6.60% (monthly), -3.91% (quarterly)[48] - **CSI 300 Index Futures**: - Annualized Return: 0.33% (monthly), 0.69% (quarterly)[53] - Volatility: 2.89% (monthly), 3.23% (quarterly)[53] - Maximum Drawdown: -3.95% (monthly), -4.03% (quarterly)[53] - Net Value: 1.0112 (monthly), 1.0236 (quarterly)[53] - Annual Turnover: 12 (monthly), 4 (quarterly)[53] - 2025 YTD Return: -1.21% (monthly), 0.37% (quarterly)[53] - **SSE 50 Index Futures**: - Annualized Return: 1.02% (monthly), 1.95% (quarterly)[57] - Volatility: 2.96% (monthly), 3.36% (quarterly)[57] - Maximum Drawdown: -4.22% (monthly), -3.75% (quarterly)[57] - Net Value: 1.0350 (monthly), 1.0679 (quarterly)[57] - Annual Turnover: 12 (monthly), 4 (quarterly)[57] - 2025 YTD Return: 0.42% (monthly), 1.85% (quarterly)[57] - **CSI 1000 Index Futures**: - Annualized Return: -6.48% (monthly), -4.82% (quarterly)[61] - Volatility: 4.73% (monthly), 5.75% (quarterly)[61] - Maximum Drawdown: -14.00% (monthly), -12.63% (quarterly)[61] - Net Value: 0.8319 (monthly), 0.8498 (quarterly)[61] - Annual Turnover: 12 (monthly), 4 (quarterly)[61] - 2025 YTD Return: -12.98% (monthly), -7.87% (quarterly)[61] 2. Minimum Basis Strategy - **CSI 500 Index Futures**: - Annualized Return: -1.93%[48] - Volatility: 4.49%[48] - Maximum Drawdown: -8.75%[48] - Net Value: 0.9361[48] - Annual Turnover: 16.78[48] - 2025 YTD Return: -4.27%[48] - **CSI 300 Index Futures**: - Annualized Return: 1.09%[53] - Volatility: 3.00%[53] - Maximum Drawdown: -4.06%[53] - Net Value: 1.0376[53] - Annual Turnover: 15.01[53] - 2025 YTD Return: 0.40%[53] - **SSE 50 Index Futures**: - Annualized Return: 1.58%[57] - Volatility: 2.97%[57] - Maximum Drawdown: -3.91%[57] - Net Value: 1.0548[57] - Annual Turnover: 15.60[57] - 2025 YTD Return: 1.36%[57] - **CSI 1000 Index Futures**: - Annualized Return: -4.42%[61] - Volatility: 5.50%[61] - Maximum Drawdown: -11.11%[61] - Net Value: 0.8693[61] - Annual Turnover: 15.73[61] - 2025 YTD Return: -8.19%[61] --- Quantitative Factors and Construction Methods 1. Factor Name: Cinda-VIX - **Factor Construction Idea**: Reflects investors' expectations of future volatility in the options market, with a term structure to capture different time horizons[63] - **Factor Construction Process**: - Based on overseas methodologies, adjusted for China's on-exchange options market[63] - Captures implied volatility from options pricing to reflect market sentiment[63] - **Factor Values** (as of December 19, 2025): - SSE 50 VIX: 15.85 - CSI 300 VIX: 17.10 - CSI 500 VIX: 26.35 - CSI 1000 VIX: 19.91[63] 2. Factor Name: Cinda-SKEW - **Factor Construction Idea**: Measures the skewness of implied volatility across different strike prices, capturing market concerns about tail risks[70] - **Factor Construction Process**: - Analyzes the slope of implied volatility curves for options with different strike prices[70] - Higher SKEW values indicate increased demand for out-of-the-money options, reflecting heightened tail risk concerns[70] - **Factor Values** (as of December 19, 2025): - SSE 50 SKEW: 101.20 - CSI 300 SKEW: 101.08 - CSI 500 SKEW: 102.87 - CSI 1000 SKE

Quantitative Models and Construction - **Model Name**: Volume Model **Construction Idea**: This model evaluates market trends based on trading volume dynamics[8][12][66] **Construction Process**: The model uses trading volume as a key input to assess the market's short-term sentiment. It categorizes all broad-based indices as neutral in the current week[12][66] - **Model Name**: Feature Volume Model **Construction Idea**: This model focuses on specific volume-related features to predict market trends[12][66] **Construction Process**: The model applies feature engineering on volume data to derive signals. For this week, it indicates a bearish outlook for A-share indices[12][66] - **Model Name**: Feature Institutional Model **Construction Idea**: This model leverages institutional trading patterns to assess market sentiment[12][66] **Construction Process**: It analyzes institutional activity from the "Dragon and Tiger" list. The model remains neutral for this week[12][66] - **Model Name**: Intelligent Algorithm Model **Construction Idea**: This model uses machine learning algorithms to predict market trends[12][66] **Construction Process**: The model provides a bullish signal for the CSI 300 and CSI 500 indices this week, indicating potential upward momentum[12][66] - **Model Name**: Limit-Up/Down Model **Construction Idea**: This model evaluates market sentiment based on the frequency of limit-up and limit-down events[13] **Construction Process**: It remains neutral for all broad-based indices in the medium term[13] - **Model Name**: Up-Down Return Difference Model **Construction Idea**: This model calculates the difference between upward and downward returns to gauge market direction[13][16] **Construction Process**: It signals a bullish outlook for all broad-based indices in the medium term[13][16] - **Model Name**: Calendar Effect Model **Construction Idea**: This model incorporates seasonal and calendar-based effects to predict market trends[13] **Construction Process**: It remains neutral for the medium term this week[13] - **Model Name**: Long-Term Momentum Model **Construction Idea**: This model evaluates long-term price momentum to predict market trends[14] **Construction Process**: It signals a bullish outlook for the long term this week[14] - **Model Name**: A-Share Comprehensive Weapon V3 Model **Construction Idea**: This composite model integrates multiple signals to provide a comprehensive market outlook[15] **Construction Process**: It indicates a bearish outlook for A-shares this week[15] - **Model Name**: A-Share Comprehensive Guozheng 2000 Model **Construction Idea**: This composite model focuses on the Guozheng 2000 index to provide a market outlook[15] **Construction Process**: It signals a bearish outlook for the Guozheng 2000 index this week[15] - **Model Name**: Turnover-Amplitude Model (Hong Kong Market) **Construction Idea**: This model evaluates the relationship between turnover and amplitude to predict market trends[16] **Construction Process**: It provides a bullish signal for the medium term in the Hong Kong market[16] - **Model Name**: Up-Down Return Difference Model (Hong Kong Market) **Construction Idea**: This model calculates the difference between upward and downward returns for the Hong Kong market[16] **Construction Process**: It remains neutral for the medium term this week[16] Model Backtesting Results - **Volume Model**: Neutral for all broad-based indices[12][66] - **Feature Volume Model**: Bearish for A-share indices[12][66] - **Feature Institutional Model**: Neutral for A-share indices[12][66] - **Intelligent Algorithm Model**: Bullish for CSI 300 and CSI 500 indices[12][66] - **Limit-Up/Down Model**: Neutral for all broad-based indices[13] - **Up-Down Return Difference Model**: Bullish for all broad-based indices[13][16] - **Calendar Effect Model**: Neutral for all broad-based indices[13] - **Long-Term Momentum Model**: Bullish for all broad-based indices[14] - **A-Share Comprehensive Weapon V3 Model**: Bearish for A-shares[15] - **A-Share Comprehensive Guozheng 2000 Model**: Bearish for Guozheng 2000 index[15] - **Turnover-Amplitude Model (Hong Kong Market)**: Bullish for the medium term[16] - **Up-Down Return Difference Model (Hong Kong Market)**: Neutral for the medium term[16]

- The report discusses multiple quantitative models for A-share and Hong Kong stock markets, including short-term, medium-term, and long-term models. These models are constructed based on price-volume, momentum, acceleration, and trend perspectives, among others. The report emphasizes the importance of combining signals from different models and periods to achieve a balanced strategy[9][12][13] - For A-shares, the short-term models include the "Volume Model" (neutral for all broad-based indices), "Feature Institutional Model" (bearish), "Feature Volume Model" (bearish), and "Smart Algorithm Models" (neutral for CSI 300, bullish for CSI 500)[12][71] - Medium-term A-share models include the "Limit-Up and Limit-Down Model" (neutral), "Up-Down Return Difference Model" (bullish for all broad-based indices), and "Calendar Effect Model" (neutral)[13][72] - The long-term A-share model, "Long-Term Momentum Model," is bullish[14][73] - Comprehensive A-share models, such as "A-Share Comprehensive Weapon V3 Model" and "A-Share Comprehensive Guozheng 2000 Model," are bearish[15][74] - For Hong Kong stocks, the medium-term models include the "Turnover to Volatility Model" (bearish) and "Hang Seng Index Up-Down Return Difference Model" (neutral)[16][74] - The report highlights that the quantitative models are designed to provide market timing signals and are based on historical data, emphasizing simplicity and universality in their construction[9][12] - The backtesting results for the "Double Bottom Pattern" and "Cup and Handle Pattern" show that the double bottom pattern outperformed the Shanghai Composite Index by 1.93% this week, while the cup and handle pattern outperformed by 2.5%[44][50] - The cumulative performance of the double bottom pattern since December 31, 2020, is 13.99%, outperforming the Shanghai Composite Index by 2.02%. However, the cup and handle pattern underperformed the Shanghai Composite Index by -1.14% over the same period[44][50]

1. Report Industry Investment Rating There is no information provided regarding the industry investment rating in the report. 2. Core Viewpoints of the Report - This week, although the index showed a weakening trend, the derivatives market demonstrated a relatively restrained emotional response. The VIX increased overall but did not experience an extreme upward movement. The SKEW continued to rise, but most varieties except the Shanghai - Shenzhen 50 remained below the extreme threshold, indicating that investors' concerns about tail - risks were relatively rational. More positively, the futures index market increased its positions by over 70,000 contracts this week, and the basis of small - and medium - cap futures improved significantly, with the IM basis narrowing by nearly 100 points, suggesting that funds were making structural layouts during the market adjustment, presenting a market characteristic of index pressure but non - extreme expectations [2]. 3. Summary by Relevant Catalogs 3.1. Estimation of Dividends during the Lifespan of Stock Index Futures Contracts and Basis Correction - **Dividend Estimation**: On November 21, 2025, the estimated dividend points for the CSI 500, SSE 50, CSI 1000, and Shanghai - Shenzhen 300 indexes in the next year were 80.73, 63.63, 63.40, and 80.42 respectively. The estimated dividend points during the lifespan of different contracts for each index were also provided [4][9]. - **Basis Correction**: The basis of a stock index futures contract is the difference between the contract's closing price and the closing price of the underlying index. When analyzing the contract basis, the impact of dividends needs to be removed. This week, the adjusted annualized basis of the current - quarter IC contract increased, while those of the IF, IH, and IM contracts decreased. The trading and holding levels of IC, IF, IH, and IM contracts increased compared to the previous week [19][20][26]. 3.2. Back - testing and Tracking of Spot - Futures Hedging Strategies - **Strategy Introduction**: The strategy is based on the analysis of basis convergence factors and optimization strategies in the relevant research report. Two strategies, continuous hedging and minimum basis strategy, are used for back - testing, with specific parameter settings provided [45][46]. - **Performance of Different Strategies**: For different indexes (CSI 500, Shanghai - Shenzhen 300, SSE 50, and CSI 1000), the back - testing results of different strategies (continuous hedging and minimum basis strategy) from July 22, 2022, to November 21, 2025, are presented, including indicators such as annualized return, volatility, maximum drawdown, net value, and annual turnover times. This week, the IC and IM hedging strategies had drawdowns, while the IF and IH hedging strategies performed stably [48][50][55]. 3.3. Cinda Options Series Indexes - **Cinda Volatility Index Cinda - VIX**: Cinda - VIX can reflect investors' expectations of the future volatility of the underlying asset. As of November 21, 2025, the 30 - day VIX values for the SSE 50, Shanghai - Shenzhen 300, CSI 500, and CSI 1000 were 19.95, 21.49, 32.21, and 26.91 respectively [63]. - **Cinda Volatility Index Cinda - SKEW**: The SKEW index measures the degree of volatility skew. When the SKEW index exceeds 100, it usually means that investors are more worried about the risk of a significant market decline. As of November 21, 2025, the SKEW values for the SSE 50, Shanghai - Shenzhen 300, CSI 500, and CSI 1000 were 104.78, 104.75, 104.79, and 106.83 respectively [71][72].

Group 1: Monetary Policy and Economic Indicators - The Federal Reserve has lowered interest rates by 25 basis points to a range of 3.75%–4.00%, marking the second rate cut of the year, and plans to end balance sheet reduction by December 1, 2025, with all maturing U.S. Treasury securities being reinvested [1] - The breakeven inflation rate increased by 0.04% to 2.40%, while the U.S. September CPI rose by 3.02% year-on-year, up from 2.94%, indicating a rebound for five consecutive months [2] - The dollar index increased by 2.1% in October, influenced by hawkish statements from Fed Chairman Powell regarding future rate cuts [3] Group 2: Market Risks and Global Trends - The VIX index peaked in mid-October but significantly declined due to the easing of U.S.-China tariff risks, while geopolitical uncertainties remain high following the cancellation of a summit between Trump and Putin [3] - In 2024, global central banks have cumulatively purchased 1,044.63 tons of gold, marking the 17th consecutive quarter of net purchases, with a notable increase in global gold ETF holdings as of 2025 [3] Group 3: Gold and Silver Market Outlook - A new tax policy regarding gold transactions will take effect on November 1, 2025, which may initially pressure physical demand but could enhance the financial attributes of gold in the long term [4] - The short-term outlook for gold is cautiously bullish, with expectations of upward movement due to anticipated declines in real interest rates [5][6] - Silver prices are also expected to trend cautiously upward, sharing macroeconomic logic with gold amid expectations of lower future interest rates [7]

- The report mentions multiple quantitative models for market timing, including short-term, mid-term, and long-term models. Short-term models include the "Volume Model" (neutral for all broad-based indices), "Feature Volume Model" (bearish), "Feature Institutional Model" (bearish), and "Smart Algorithm Model" (bearish for CSI 300, neutral for CSI 500)[1][13][66]. Mid-term models include the "Limit-Up-Limit-Down Model" and "Calendar Effect Model," both neutral[14][67]. The long-term model is the "Long-Term Momentum Model," which is bullish[15][68]. Comprehensive models like "A-Share Comprehensive Weapon V3 Model" and "A-Share Comprehensive CSI 2000 Model" are bearish[16][69]. - The "Volume Model" is constructed based on trading volume trends, while the "Feature Volume Model" and "Feature Institutional Model" focus on specific volume characteristics and institutional trading patterns, respectively. The "Smart Algorithm Model" utilizes machine learning techniques to predict market movements[1][13][66]. The "Limit-Up-Limit-Down Model" analyzes price limits, and the "Calendar Effect Model" incorporates seasonal patterns[14][67]. The "Long-Term Momentum Model" evaluates price trends over extended periods[15][68]. - The "Comprehensive Weapon V3 Model" and "Comprehensive CSI 2000 Model" combine signals from multiple models across different timeframes to provide a holistic market outlook[16][69]. - The report evaluates these models qualitatively, noting that short-term models are generally neutral to bearish, mid-term models are neutral, and long-term models are bullish. Comprehensive models are bearish for A-shares[1][13][66][16][69]. - Testing results for the models are summarized as follows: Short-term models show mixed signals, with bearish predictions for specific indices like CSI 300 and CSI 2000. Mid-term models remain neutral, while the long-term momentum model indicates a bullish outlook. Comprehensive models suggest a bearish trend for A-shares[1][13][66][16][69]. - For Hong Kong stocks, the "Turnover Inverse Volatility Model" is bearish, indicating potential downward movement for the Hang Seng Index[16][70]. - The report also highlights shape-based models like the "Double Bottom Pattern" and "Cup-and-Handle Pattern." The "Double Bottom Pattern" portfolio outperformed the Shanghai Composite Index by 2.57% this week, with cumulative returns of 34.32% since December 31, 2020[43][48]. The "Cup-and-Handle Pattern" portfolio outperformed the Shanghai Composite Index by 1.28% this week, with cumulative returns of 70.89% since December 31, 2020[43][44]. - The report evaluates these shape-based models positively, noting their consistent outperformance compared to the benchmark index over time[43][44][48]. - Testing results for shape-based models: "Double Bottom Pattern" portfolio weekly return of 3.0%, cumulative return of 34.32% since December 31, 2020[43][48]. "Cup-and-Handle Pattern" portfolio weekly return of 1.71%, cumulative return of 70.89% since December 31, 2020[43][44].