金 金融工程点评 [Table_Title] 房地产相对指数趋势跟踪模型效果点评 [Table_Author] 证券分析师：刘晓锋 电话：13401163428 E-MAIL：liuxf@tpyzq.com 执业资格证书编码：S1190522090001 研究助理：孙弋轩 电话：18910596766 E-MAIL：sunyixuan@tpyzq.com 一般证券业务登记编码：S1190123080008 模型概述 结果评估： 区间年化收益：2.22% 波动率（年化）：23.52% 夏普率：0.09 最大回撤：17.24% 指数期间总回报率：-26.63% [Table_Message]2025-06-05 太 平 洋 证 券 股 份 有 限 公 司 证 券 研 究 报 告 ◼ 模型策略适用情况总结：在 2023 年 3 月 7 日至 2023 年 6 月 2 日及 2023 年 7 月 19 日至 2023 年 11 月 10 日期间，模型表现良好，模型整体呈现上升趋势， 模型处于正收益通道；2024 年 4 月 25 日至 2024 年 9 月 13 日，模型净值整 体处于下降趋势，无法取得累计收益。跟踪 ...

金 金融工程点评 汽车指数趋势跟踪模型效果点评 [Table_Author] 证券分析师：刘晓锋 电话：13401163428 E-MAIL：liuxf@tpyzq.com 执业资格证书编码：S1190522090001 研究助理：孙弋轩 电话：18910596766 E-MAIL：sunyixuan@tpyzq.com 一般证券业务登记编码：S1190123080008 模型概述 结果评估： [Table_Message]2025-05-19 区间年化收益：6.26% 波动率（年化）：25.15% 夏普率：0.25 最大回撤：32.95% 指数期间总回报率：30.17% 太 平 洋 证 券 股 份 有 限 公 司 证 券 研 究 [Table_Title] [Table_Summary] 融 工 程 点 评 报 告 ◼ 设计原理：模型假定标的价格走势具有很好的局部延续性，标的价格永远处 于某一趋势中，出现反转行情的持续时间明显小于趋势延续的时间，若出现 窄幅盘整的情况，亦假设其延续之前的趋势。当处于大级别的趋势之中时， 给定较短时间的观察窗口，走势将延续观察窗口内的局部趋势。而当趋势发 生反转时，在观察窗口 ...

- Model Name: Electricity Equipment Index Trend Tracking Model[2] - Model Construction Idea: The model assumes that the price trend of the target has good local continuity, and the target price is always in a certain trend. The duration of the reversal trend is significantly shorter than the trend continuation time. If there is a narrow range consolidation, it is assumed to continue the previous trend[3] - Model Construction Process: - Calculate the difference (del) between the closing price on day T and the closing price on day T-20 - Calculate the volatility (Vol) from day T-20 to day T (excluding) - If the absolute value of del is greater than N times Vol, it is considered that the current price has deviated from the original oscillation range and formed a trend. The trend direction corresponds to the positive or negative of del. If it is less than or equal to N times Vol, it is considered that the current trend continues, and the trend direction is the same as day T-1 - Considering the more intense fluctuations in the stock market compared to the bond market, small wave opportunities are more frequent, so N=1 is used for tracking - The return of both long and short directions of electricity equipment is considered, and the combined result is used as the final evaluation basis[3] - Model Evaluation: The model is not suitable for direct use on the Shenwan First-Level Electricity Equipment Index due to long periods of drawdown and inability to achieve good cumulative returns during certain periods[4] Model Backtest Results - Annualized Return: 13.52%[3] - Annualized Volatility: 29.91%[3] - Sharpe Ratio: 0.45[3] - Maximum Drawdown: 27.32%[3] - Total Return Rate of the Index During the Period: -22.56%[3]

- The model is named "Building Decoration Index Trend Tracking Model" and is designed based on the assumption that the price trend of the target has strong local continuity, with reversal periods being significantly shorter than trend continuation periods. It assumes that narrow-range consolidation will continue the previous trend. When a major trend is present, a short observation window will reflect the local trend, and reversals will show price changes exceeding the range of random fluctuations, thus filtering out random noise[2][3] - The model targets the SW First-Level Building Decoration Index, with raw data retained for preprocessing. It operates on a long-short signal dimension[3] - The specific algorithm involves calculating the difference between the closing price on day T and day T-20 ($del$), as well as the volatility ($Vol$) from day T-20 to day T (excluding T). If the absolute value of $del$ exceeds $N$ times $Vol$, it indicates a trend breakout, with the trend direction determined by the sign of $del$. Otherwise, the trend direction follows that of day T-1. For this model, $N$ is set to 1 to capture smaller opportunities in the more volatile stock market. The model evaluates combined long-short returns as the final performance metric[3] - The model's backtesting period spans from March 7, 2023, to March 18, 2025[3] - The model's performance evaluation indicates that it achieved its highest net value during the period from March 7, 2023, to January 22, 2024. However, from January 22, 2024, to September 26, 2024, the net value declined due to market conditions. Subsequently, the net value returned to near its historical high but entered a period of oscillation. The model demonstrates relatively low annualized returns and prolonged drawdowns in the later stages, making it unsuitable for direct application to the SW First-Level Building Decoration Index[4] - The model's backtesting results include the following metrics: annualized return of 4.39%, annualized volatility of 23.96%, Sharpe ratio of 0.18, maximum drawdown of 22.47%, and total return of -12.25% during the evaluation period[3]

金 金融工程点评 [Table_Title] 综合指数趋势跟踪模型效果点评 [Table_Author] 证券分析师：刘晓锋 电话：13401163428 E-MAIL：liuxf@tpyzq.com 执业资格证书编码：S1190522090001 研究助理：孙弋轩 电话：18910596766 E-MAIL：sunyixuan@tpyzq.com 一般证券业务登记编码：S1190123080008 模型概述 结果评估： 区间年化收益：13.05% 波动率（年化）：26.25% 夏普率：0.50 最大回撤：27.97% 指数期间总回报率：-6.43% [Table_Summary] 融 工 程 点 评 ◼ 设计原理：模型假定标的价格走势具有很好的局部延续性，标的价格永远处 于某一趋势中，出现反转行情的持续时间明显小于趋势延续的时间，若出现 窄幅盘整的情况，亦假设其延续之前的趋势。当处于大级别的趋势之中时， 给定较短时间的观察窗口，走势将延续观察窗口内的局部趋势。而当趋势发 生反转时，在观察窗口始末位置的价格变动方向会明显超出随机波动造成的 趋势背离范围，从而排除随机波动的影响。虽然指数本身在实际中进行双向 操 ...