Core Viewpoint - The recent decline in U.S. tech stocks has created a buying opportunity for investors, according to JPMorgan's market intel team [1][2]. Group 1: Market Conditions - Investors should closely monitor two key variables that could reverse bullish sentiment: potential "stagflation signals" from upcoming weak PMI data and worsening unemployment figures, as well as hawkish comments from Fed Chair Powell at the Jackson Hole meeting [2][15]. - The upcoming Nvidia earnings report is seen as a critical catalyst that could reignite interest in AI investments [3][16]. - The recent sell-off in tech stocks is primarily driven by a wave of selling in large-cap tech and AI stocks, attributed to high valuations, crowded positions, and risk-off behavior ahead of Nvidia's earnings [8]. Group 2: Technical Analysis - The momentum factor has retraced approximately 7%, which is within the historical normal range compared to past retracements averaging 8.3% [8]. - The S&P 500 index experienced its most severe single-day drop in nearly three weeks, while the Nasdaq is heading towards its largest two-day decline since April [5]. Group 3: Jackson Hole Meeting - The upcoming Jackson Hole global central bank meeting is not expected to yield significant new information, leading to a lack of high expectations from the market [9][11]. - The meeting will take place on August 21, with Powell's speech scheduled for August 22 [10]. Group 4: Investment Strategy - JPMorgan suggests viewing the recent market pullback as a buying opportunity, contingent on the absence of stagflation evidence [14][15]. - A strong earnings report from Nvidia could potentially reignite market enthusiasm for AI themes, leading to a rebound in tech stocks and the overall market [16].

Group 1: Report Industry Investment Rating - No relevant content provided Group 2: Report's Core View - The commodity market shows different trends in various sectors. The bearish proportion has slightly increased this week, with significant changes in the black and agricultural sectors. The overall market signals are mainly bearish, with some exceptions like the iron ore market turning neutral [1]. Group 3: Summary by Related Content Commodity Market Sector Analysis - The agricultural sector's momentum is rising, while the energy sector is relatively weak. In the black sector, the momentum factor has decreased marginally, and the term - structure differentiation has narrowed. In the non - ferrous sector, the position - holding factor has decreased marginally, and the cross - sectional differentiation has widened. In the energy - chemical sector, there is cross - sectional momentum differentiation. In the agricultural sector, the position - holding of oilseeds and meals has increased, and the short - cycle momentum of palm oil has rebounded [1]. Performance of Different Commodities Methanol - Last week, the supply factor strengthened by 0.64%, the inventory factor declined by 0.66%, and the comprehensive signal this week is bearish. Fundamentally, the supply side remains bearish, the demand side is neutral to bearish, the inventory side turns bearish, and the spread side is neutral to bearish [1]. Float Glass - Last week, the inventory factor increased by 2.47%, the spread factor weakened by 0.17%, the profit factor decreased by 0.20%, and the synthetic factor declined by 0.13%, with a bearish comprehensive signal this week. Fundamentally, the supply side is neutral, the demand side is neutral to bearish, the inventory side is bearish, and the profit side is neutral to bullish [1]. Iron Ore - Last week, the supply factor strengthened by 0.38%, the synthetic factor increased by 0.08%, and the comprehensive signal this week turns neutral. Fundamentally, the supply side's bearish feedback weakens to neutral, the demand side turns to bullish feedback but remains neutral, the inventory side turns bearish, and the spread side turns bullish [3][4].

Group 1: Weekly Index Enhanced Portfolio Performance - The CSI 300 index enhanced portfolio achieved an excess return of 0.93% this week and 12.11% year-to-date [1][6] - The CSI 500 index enhanced portfolio recorded an excess return of -0.58% this week and 10.97% year-to-date [1][6] - The CSI 1000 index enhanced portfolio had an excess return of -1.56% this week and 14.33% year-to-date [1][6] - The CSI A500 index enhanced portfolio saw an excess return of -0.15% this week and 11.56% year-to-date [1][6] Group 2: Stock Selection Factor Performance Tracking - In the CSI 300 component stocks, factors such as single-season ROA, standardized expected external income, and standardized expected external profit performed well [1][9] - In the CSI 500 component stocks, factors like one-year momentum, single-season surprise magnitude, and standardized expected external profit showed strong performance [1][9] - For the CSI 1000 component stocks, one-year momentum, EPTTM one-year percentile, and standardized expected external profit were notable [1][9] - In the CSI A500 index component stocks, DELTAROA, standardized expected external income, and DELTAROE performed well [1][9] - Among public fund heavy stocks, one-year momentum, DELTAROA, and single-season revenue year-on-year growth were strong [1][9] Group 3: Public Fund Index Enhanced Product Performance Tracking - The CSI 300 index enhanced products had a maximum excess return of 1.91%, a minimum of -1.41%, and a median of -0.09% this week [1][20] - The CSI 500 index enhanced products recorded a maximum excess return of 0.52%, a minimum of -2.05%, and a median of -0.51% this week [1][21] - The CSI 1000 index enhanced products achieved a maximum excess return of 0.94%, a minimum of -1.70%, and a median of -0.53% this week [1][22] - The CSI A500 index enhanced products had a maximum excess return of 0.71%, a minimum of -1.10%, and a median of -0.25% this week [1][25]

Quantitative Models and Construction Methods 1. Model Name: Diffusion Index Model - **Model Construction Idea**: The model is used to monitor the critical points of trend changes in the micro-cap stock index by analyzing the distribution of stock price movements over a specific time window[6][38]. - **Model Construction Process**: The model calculates the diffusion index based on the relative price changes of all constituent stocks in the micro-cap stock index over a given time window. For example, if the horizontal axis is 0.95 and the vertical axis is 15 days, the value of 0.51 indicates that after 5 days (review period from T=20 to T=15), if all stocks in the micro-cap index drop by 5%, the diffusion index value is 0.51[38]. - Current diffusion index value: 0.87 (horizontal axis = 20, vertical axis = 1.00)[38]. - **Model Evaluation**: The model shows that the current distribution is relatively uniform, indicating that the time window has little impact, and the main influence comes from the spatial distribution[38]. 2. Model Name: First Threshold Method (Left-Side Trading) - **Model Construction Idea**: This method triggers a sell signal when the diffusion index reaches a predefined threshold[6][42]. - **Model Construction Process**: - On May 8, 2025, the model triggered a sell signal when the diffusion index reached 0.9850[42]. 3. Model Name: Delayed Threshold Method (Right-Side Trading) - **Model Construction Idea**: Similar to the first threshold method but with a delayed response to confirm the trend[6][44]. - **Model Construction Process**: - On May 15, 2025, the model triggered a sell signal when the diffusion index reached 0.8975[46]. 4. Model Name: Dual Moving Average Method (Adaptive Trading) - **Model Construction Idea**: This method uses two moving averages to adaptively identify trading signals based on the diffusion index[6][47]. - **Model Construction Process**: - On August 4, 2025, the model issued a sell signal based on the dual moving average strategy[47]. --- Model Backtesting Results 1. Diffusion Index Model - Current diffusion index value: 0.87[38]. 2. First Threshold Method - Triggered sell signal at diffusion index value: 0.9850[42]. 3. Delayed Threshold Method - Triggered sell signal at diffusion index value: 0.8975[46]. 4. Dual Moving Average Method - Triggered sell signal on August 4, 2025[47]. --- Quantitative Factors and Construction Methods 1. Factor Name: Momentum Factor - **Factor Construction Idea**: Measures the tendency of stocks to continue their past performance[5][33]. - **Factor Construction Process**: - Weekly rank IC: 0.224 - Historical average rank IC: -0.005[5][33]. 2. Factor Name: Beta Factor - **Factor Construction Idea**: Captures the sensitivity of stock returns to market movements[5][33]. - **Factor Construction Process**: - Weekly rank IC: 0.146 - Historical average rank IC: 0.006[5][33]. 3. Factor Name: Illiquidity Factor - **Factor Construction Idea**: Measures the impact of trading volume on stock price changes[5][33]. - **Factor Construction Process**: - Weekly rank IC: 0.14 - Historical average rank IC: 0.041[5][33]. 4. Factor Name: Unadjusted Stock Price Factor - **Factor Construction Idea**: Reflects the raw stock price without adjustments for splits or dividends[5][33]. - **Factor Construction Process**: - Weekly rank IC: 0.131 - Historical average rank IC: -0.015[5][33]. 5. Factor Name: PE_TTM Reciprocal Factor - **Factor Construction Idea**: Represents the inverse of the price-to-earnings ratio based on trailing twelve months[5][33]. - **Factor Construction Process**: - Weekly rank IC: 0.125 - Historical average rank IC: 0.017[5][33]. --- Factor Backtesting Results 1. Momentum Factor - Weekly rank IC: 0.224 - Historical average rank IC: -0.005[5][33]. 2. Beta Factor - Weekly rank IC: 0.146 - Historical average rank IC: 0.006[5][33]. 3. Illiquidity Factor - Weekly rank IC: 0.14 - Historical average rank IC: 0.041[5][33]. 4. Unadjusted Stock Price Factor - Weekly rank IC: 0.131 - Historical average rank IC: -0.015[5][33]. 5. PE_TTM Reciprocal Factor - Weekly rank IC: 0.125 - Historical average rank IC: 0.017[5][33].

- The report tracks the performance of style factors, including momentum, beta, and liquidity factors, which showed strong long positions, while leverage, market capitalization, and valuation factors exhibited strong short positions[3][16] - The report includes the performance of fundamental factors across different stock pools, such as the CSI 300, CSI 500, and CSI 1000, highlighting that low valuation and high growth stocks were generally strong[5][6][7][20][22][25] - Technical factors' performance was mostly positive, with high volatility and long-term momentum stocks performing well, except for the 20-day momentum factor which showed negative performance[4][18][23][26] - The GRU factors' performance was weak overall, with the close1d model showing strong performance, while other models like open1d and barra1d experienced drawdowns[4][5][6][7][18][20][23][26] - The report details the construction and recent performance of the GRU long-only portfolios, noting that the barra1d model outperformed the CSI 1000 index by 0.38%, while the open1d and close1d models underperformed by 0.40%-0.53%[8][31][32] Factor Construction and Performance - **Barra Style Factors**: The report lists several style factors such as Beta, Market Cap, Momentum, Volatility, Non-linear Size, Valuation, Liquidity, Profitability, Growth, and Leverage, with detailed formulas for each[14][15] - **Fundamental Factors**: The report tracks various fundamental factors, including unexpected growth and growth-related financial factors, with mixed performance across different stock pools[4][5][6][7][18][20][22][25] - **Technical Factors**: The report includes several technical factors, such as 20-day momentum, 60-day momentum, 120-day momentum, and various volatility measures, with detailed performance metrics[4][18][23][26] Factor Performance Metrics - **Fundamental Factors**: - Operating Turnover: -1.14% (1 week), 4.19% (1 month), -11.23% (6 months), -11.52% (YTD), -1.86% (3-year annualized), 3.31% (5-year annualized)[19] - ROC: -0.68% (1 week), 0.89% (1 month), -10.51% (6 months), -10.59% (YTD), -13.06% (3-year annualized), -11.85% (5-year annualized)[19] - ROE Growth: 0.36% (1 week), 2.01% (1 month), 10.43% (6 months), 2.27% (YTD), 0.38% (3-year annualized), 2.61% (5-year annualized)[19] - **Technical Factors**: - 20-day Momentum: -0.73% (1 week), 0.66% (1 month), -8.17% (6 months), -12.18% (YTD), -13.19% (3-year annualized), -13.77% (5-year annualized)[19] - Median Deviation: -0.38% (1 week), -3.25% (1 month), -5.83% (6 months), -4.72% (YTD), -15.12% (3-year annualized), -15.62% (5-year annualized)[19] - 60-day Momentum: 0.35% (1 week), -3.31% (1 month), 2.64% (6 months), 5.08% (YTD), -12.82% (3-year annualized), -16.17% (5-year annualized)[19] GRU Model Performance - **GRU Long-Only Portfolios**: - open1d: -0.40% (1 week), -0.20% (1 month), 2.37% (3 months), 6.32% (6 months), 7.16% (YTD)[32] - close1d: -0.53% (1 week), -0.83% (1 month), 4.38% (3 months), 6.80% (6 months), 6.59% (YTD)[32] - barra1d: 0.38% (1 week), -0.25% (1 month), 0.85% (3 months), 2.85% (6 months), 3.78% (YTD)[32] - barra5d: 0.00% (1 week), -0.36% (1 month), 3.59% (3 months), 7.41% (6 months), 8.37% (YTD)[32] - Multi-Factor: -0.38% (1 week), -0.30% (1 month), 1.62% (3 months), 2.54% (6 months), 2.54% (YTD)[32]

Core Viewpoint - The report highlights the performance of various market factors and investment strategies, indicating positive returns in several areas while noting the mixed performance of different factors across industries [4][5][6]. Group 1: Market Factor Performance - The momentum factor achieved a positive return of 0.70%, indicating a momentum effect in the market; profitability and Beta factors also showed positive returns of 0.34% and 0.28% respectively, while the market capitalization factor had a negative return of -0.58%, reflecting a small-cap style [4]. - In the CSI 300 stock pool, the best-performing factors included quarterly operating profit growth rate (1.25%), quarterly ROE (1.07%), and early session return factor (0.95%), while the worst performers were the standard deviation of 6-day trading volume (-0.91%), standardized unexpected income (-0.89%), and quarterly EPS (-0.83%) [5]. - In the CSI 500 stock pool, the top factors were post-early session return factor (1.24%), standard deviation of 5-day trading volume (1.05%), and standard deviation of 6-day trading volume (0.82%), with the weakest factors being ROE stability (-0.96%), 5-minute return skewness (-0.84%), and ROA stability (-0.83%) [5]. Group 2: Industry Factor Performance - Fundamental factors showed varied performance across industries, with net asset growth rate, net profit growth rate, earnings per share, and TTM operating profit factors yielding consistent positive returns in the utilities and leisure services sectors [6]. - Valuation factors, particularly the BP factor, demonstrated significant positive returns in the construction materials, banking, and media sectors, while the EP factor showed notable positive returns in the coal industry [6]. - Residual volatility and liquidity factors yielded consistent positive returns in the defense, oil and petrochemical, and automotive industries, with a significant large-cap style observed in the coal and banking sectors [6]. Group 3: Investment Strategy Performance - The PB-ROE-50 combination achieved positive excess returns in the overall market stock pool, with a negative excess return of -0.40% in the CSI 500 stock pool and a positive excess return of 0.44% in the CSI 800 stock pool [7]. - Public fund research stock selection strategy and private fund research tracking strategy both achieved positive excess returns, with the public fund strategy outperforming the CSI 800 by 3.21% and the private fund strategy by 0.16% [8]. - The block trading combination achieved a positive excess return of 3.61% relative to the CSI All Index [9]. - The targeted issuance combination also achieved a positive excess return of 0.77% relative to the CSI All Index [10].

Group 1: Overall Market Conditions - The proportion of short positions in commodities increased this week, mainly due to the decline in the factor strength of the energy and chemical sector. Currently, the relatively strong sectors in the cross - section are precious metals and agricultural products, while the relatively weak sector is the energy sector [3]. - In the precious metals sector, the sequential momentum of gold has marginally recovered, and the differentiation within the sector has narrowed. In the non - ferrous sector, the position factor has continued to decline slightly, and the cross - sectional differentiation has expanded, with copper and zinc being on the weaker end [3]. - In the black sector, the short - term momentum factor has marginally decreased, but the long - term factor has gradually stabilized, and the term structure differentiation has narrowed. In the energy and chemical sector, the cross - sectional momentum has declined overall, and PTA, soda ash, and glass are on the weaker end of the sector's cross - section [3]. - In the agricultural products sector, the positions of oilseeds and meals have both decreased slightly, and the differentiation has narrowed [3]. Group 2: Factor Returns - Last week's returns and monthly returns for different factors: supply factor had a last - week return of 1.64% and a monthly return of 0.00%; demand factor had a last - week return of 1.51% and a monthly return of 0.00%; inventory factor had a last - week return of 1.20% and a monthly return of - 2.28%; spread factor had a last - week return of 3.90% and a monthly return of 2.50%; profit factor had a last - week return of 0.00% and a monthly return of 0.00%; the cumulative return of major categories last week was 1.64% and this month was - 0.04% [7]. Group 3: Methanol Analysis - In terms of strategy net value, last week, the supply factor strengthened by 0.21%, the demand factor increased by 0.13%, the inventory factor weakened by 0.19%, the spread factor increased by 0.09%, and the composite factor increased by 0.16%. This week, the comprehensive signal for short positions continues. On the fundamental factor side, the capacity utilization rate of domestic methanol plants has increased, and the import arrival volume has increased slightly, indicating a short position on the supply side; the operating rates of formaldehyde and chloride plants have increased, but the capacity utilization rates of acetic acid and MTBE plants have decreased, making the demand side neutral; the inventory of domestic methanol manufacturers has decreased, indicating a long position on the inventory side; the closing price of the main methanol futures contract and the 9 - 1 spread on the futures market have both released short - position signals, and the spread side has turned to a short position [4]. Group 4: Glass Analysis - In terms of strategy net value, last week, the inventory factor decreased by 2.28%, the spread factor increased by 2.50%, and the composite factor weakened by 0.04%. This week, the comprehensive signal is a short position. On the fundamental factor side, the capacity utilization rate of float glass has remained flat month - on - month, keeping the supply side neutral; the number of commercial housing transactions in 30 large - and medium - sized Chinese cities has increased slightly, making the demand side neutral; float glass enterprises have continued to reduce inventory, indicating a long position on the inventory side; the spot prices of the float glass markets in Central China, North China, and South China have all released short - position signals, indicating a short position on the spread side; the pre - tax gross profit of float glass made from steam coal has declined, indicating a short position on the profit side [7]. Group 5: Iron Ore Analysis - In terms of strategy net value, last week, each factor remained unchanged, and this week, the comprehensive signal remains neutral. The arrival volume at Qingdao Port has increased significantly, and the shipping volumes of BHP and Rio Tinto have increased, turning the supply side into a short - position feedback, but the overall signal remains neutral. The consumption of iron ore powder for sintering in steel mills and the proportion of sintered ore in the furnace have decreased, and the strength of the long - position feedback on the demand side has decreased slightly, but the signal is still neutral. The iron ore concentrate at ports and the domestic sintering iron ore powder in steel mills have both reduced inventory slightly, weakening the short - position feedback on the inventory side. The price center of PB powder has shifted down, further weakening the strength of the long - position feedback on the spread side [7]. Group 6: Lead Analysis - In terms of strategy net value, last week, the supply factor strengthened by 0.52%, the demand factor decreased by 0.51%, the spread factor increased by 0.46%, and the composite factor strengthened by 0.15%. This week, the comprehensive signal has changed from a short position to neutral. The price of domestic lead concentrates from SMM has decreased, and the profit of tax - free recycled lead has decreased, turning the supply - side signal to neutral. The LME lead inventory and registered warrants have increased, turning the inventory side into a short - position feedback, but the overall signal remains neutral. The spread between the near and far months of LME lead has widened, strengthening the short - position feedback on the spread side [7].

Quantitative Models and Construction Methods 1. Model Name: "Day and Night Convergence" New Momentum Factor - **Model Construction Idea**: The model improves traditional momentum factors by incorporating the price-volume relationship during intraday and overnight trading sessions, leveraging the distinct characteristics of these two periods to enhance signal strength and stability [7][6] - **Model Construction Process**: 1. The trading period is divided into intraday and overnight sessions [7] 2. Price-volume relationships are separately analyzed for each session to identify unique patterns and characteristics [7] 3. The insights from these analyses are combined to construct a new momentum factor, referred to as the "Day and Night Convergence" factor [7] - **Model Evaluation**: The model demonstrates significant improvement in stability and performance compared to traditional momentum factors, effectively addressing the instability issues observed in the A-share market [6][7] --- Model Backtesting Results 1. "Day and Night Convergence" New Momentum Factor - **Annualized Return**: 18.08% [14] - **Annualized Volatility**: 8.75% [14] - **Information Ratio (IR)**: 2.07 [14] - **Monthly Win Rate**: 77.54% [14] - **Maximum Drawdown**: 9.07% [14]

Summary of Key Points from the Conference Call Industry Overview - The conference call discusses the current state of global equity markets, with a focus on the US market, including specific references to sectors such as technology and real estate in China. Core Insights and Arguments 1. **Market Performance**: The week’s market action was mixed, with notable performances from NVDA in the US, property stocks in China, and the FTSE in the UK [1][2] 2. **Economic Expectations**: The market is revising economic growth expectations upward while simultaneously lowering expectations for the Fed Funds rate [3] 3. **Technical Indicators**: Local seasonal factors are strong, and capital flows are supportive, primarily from systematic investors [3] 4. **Investment Strategy**: Despite current unattractiveness for adding risk, there is a belief that US large-cap stocks still have potential for growth [4] 5. **S&P 500 Forecast**: The US portfolio strategy has upgraded its outlook, predicting the S&P 500 will reach 6900 (+10%) in 12 months, assuming no change in earnings expectations [5][6] 6. **Market Breadth**: The breadth of the market is considered narrow, but there is an expectation for improvement within large-cap stocks, while small-cap stocks are expected to underperform [7][8] 7. **Momentum Factor Issues**: The momentum factor has faced challenges, with a significant decline noted in recent weeks [9][10] 8. **Investor Sentiment**: Various sentiment measures indicate a somewhat optimistic outlook, but positioning has not kept pace with this sentiment [13][14] 9. **Earnings Season**: The upcoming earnings season is anticipated to show a 4% growth in EPS for Q2, which is lower than previous expectations, making it harder for companies to beat estimates [15][16] 10. **Tariff Impacts**: Asian equities have remained stable despite tariff increases, and the market expects framework deals with the EU and India soon [17][18] 11. **AI Capital Expenditure**: A podcast discussion highlighted the potential for high AI capital expenditure while maintaining low displacement of knowledge workers [19][20] 12. **Regional Bank Outlook**: Recent regulatory announcements may lead to increased loan growth and M&A activity in US regional banks [21] 13. **Japanese Market Activity**: Foreign investment in Japan has been strong, with the Nikkei index nearing 40,000 [22] 14. **Chinese Market Skepticism**: Despite skepticism, the Shanghai Composite Index has rebounded to levels not seen since early 2022 [23] 15. **European Earnings Trends**: Earnings estimates for European equities are trending down, contrasting with the stabilization seen in US equities [24] 16. **Bitcoin Surge**: Bitcoin has seen a significant increase, rising sevenfold since late 2022 [25] Other Important Insights - The "high retail sentiment basket" has broken out, surpassing previous highs from 2021 [10] - The overall bullish narrative for US equities is supported by rising growth expectations [27] - A snapshot of recent capital flows indicates varying trends across regions, with significant implications for investment strategies [33][34] This summary encapsulates the key points discussed in the conference call, providing insights into market dynamics, sector performances, and future expectations.

Quantitative Factors and Construction Methods 1. Factor Name: **bp** - **Factor Construction Idea**: Measures the valuation level of a stock based on its book-to-price ratio [13] - **Factor Construction Process**: Calculated as the current net asset divided by the current total market value $ bp = \frac{\text{Current Net Asset}}{\text{Current Total Market Value}} $ [13] 2. Factor Name: **bp Three-Year Percentile** - **Factor Construction Idea**: Evaluates the relative valuation of a stock over the past three years [13] - **Factor Construction Process**: Represents the percentile rank of the current bp value within the stock's bp distribution over the last three years [13] 3. Factor Name: **Quarterly EP** - **Factor Construction Idea**: Reflects the profitability of a stock relative to its equity [13] - **Factor Construction Process**: Calculated as the quarterly net profit divided by the net asset $ \text{Quarterly EP} = \frac{\text{Quarterly Net Profit}}{\text{Net Asset}} $ [13] 4. Factor Name: **Quarterly EP One-Year Percentile** - **Factor Construction Idea**: Measures the relative profitability of a stock over the past year [13] - **Factor Construction Process**: Represents the percentile rank of the current quarterly EP value within the stock's EP distribution over the last year [13] 5. Factor Name: **Quarterly SP** - **Factor Construction Idea**: Indicates the revenue generation efficiency of a stock relative to its equity [13] - **Factor Construction Process**: Calculated as the quarterly operating revenue divided by the net asset $ \text{Quarterly SP} = \frac{\text{Quarterly Operating Revenue}}{\text{Net Asset}} $ [13] 6. Factor Name: **Quarterly SP One-Year Percentile** - **Factor Construction Idea**: Evaluates the relative revenue efficiency of a stock over the past year [13] - **Factor Construction Process**: Represents the percentile rank of the current quarterly SP value within the stock's SP distribution over the last year [13] 7. Factor Name: **Fama-French Three-Factor One-Month Residual Volatility** - **Factor Construction Idea**: Measures the idiosyncratic risk of a stock based on its residual volatility after regressing against the Fama-French three-factor model [13] - **Factor Construction Process**: Calculated as the standard deviation of the residuals from the regression of daily returns over the past 20 trading days on the Fama-French three factors $ \text{Residual Volatility} = \sqrt{\frac{\sum (\text{Actual Return} - \text{Predicted Return})^2}{n}} $ where "Predicted Return" is derived from the Fama-French three-factor model [13] 8. Factor Name: **One-Month Excess Return Volatility** - **Factor Construction Idea**: Captures the volatility of a stock's excess return over the past month [13] - **Factor Construction Process**: Calculated as the standard deviation of the excess returns over the past 20 trading days $ \text{Excess Return Volatility} = \sqrt{\frac{\sum (\text{Excess Return} - \text{Mean Excess Return})^2}{n}} $ [13] --- Factor Backtesting Results IC Performance - **bp**: Weekly IC = 9.73%, Monthly IC = 2.21%, Yearly IC = 1.64%, Historical IC = 2.27% [9] - **bp Three-Year Percentile**: Weekly IC = 14.75%, Monthly IC = 3.36%, Yearly IC = 2.85%, Historical IC = 1.69% [9] - **Quarterly EP**: Weekly IC = -4.31%, Monthly IC = 0.38%, Yearly IC = -0.58%, Historical IC = 1.13% [9] - **Quarterly EP One-Year Percentile**: Weekly IC = 7.25%, Monthly IC = 3.57%, Yearly IC = 0.94%, Historical IC = 1.73% [9] - **Quarterly SP**: Weekly IC = -0.92%, Monthly IC = 0.38%, Yearly IC = 0.23%, Historical IC = 0.71% [9] - **Quarterly SP One-Year Percentile**: Weekly IC = 11.79%, Monthly IC = 4.40%, Yearly IC = 3.08%, Historical IC = 1.86% [9] - **Fama-French Three-Factor One-Month Residual Volatility**: Weekly IC = 14.50%, Monthly IC = 5.11%, Yearly IC = 3.29%, Historical IC = 2.54% [9] - **One-Month Excess Return Volatility**: Weekly IC = 14.87%, Monthly IC = 5.14%, Yearly IC = 3.26%, Historical IC = 2.22% [9] Long-Only Portfolio Excess Returns - **bp**: Weekly Excess Return = 0.52%, Monthly Excess Return = -0.36%, Yearly Excess Return = 1.57%, Historical Cumulative Excess Return = 30.39% [11] - **bp Three-Year Percentile**: Weekly Excess Return = 0.75%, Monthly Excess Return = -0.59%, Yearly Excess Return = 3.19%, Historical Cumulative Excess Return = -1.63% [11] - **Quarterly EP**: Weekly Excess Return = 0.13%, Monthly Excess Return = 1.56%, Yearly Excess Return = 1.05%, Historical Cumulative Excess Return = 30.66% [11] - **Quarterly EP One-Year Percentile**: Weekly Excess Return = 0.81%, Monthly Excess Return = 0.32%, Yearly Excess Return = 3.53%, Historical Cumulative Excess Return = 33.78% [11] - **Quarterly SP**: Weekly Excess Return = -0.30%, Monthly Excess Return = 0.33%, Yearly Excess Return = 0.34%, Historical Cumulative Excess Return = -2.98% [11] - **Quarterly SP One-Year Percentile**: Weekly Excess Return = 0.56%, Monthly Excess Return = 1.09%, Yearly Excess Return = 9.91%, Historical Cumulative Excess Return = 1.99% [11] - **Fama-French Three-Factor One-Month Residual Volatility**: Weekly Excess Return = 1.33%, Monthly Excess Return = 1.68%, Yearly Excess Return = 8.97%, Historical Cumulative Excess Return = 19.84% [11] - **One-Month Excess Return Volatility**: Weekly Excess Return = 1.34%, Monthly Excess Return = 1.55%, Yearly Excess Return = 10.29%, Historical Cumulative Excess Return = 11.42% [11]