A：Well, quantification is a very mature asset management tool overseas. The quantitative strategy system is divided into two main lines: quantification on the asset allocation side and quantification on the equity side. On the asset allocation side, from the mean variance model to the bridge water all-weather strategy to the AQR risk evaluation model, the risk-return characteristics of different asset classes are described by quantitative methods, and the optimization algorithm is used to solve the optimal allocation weight to solve the cross-asset allocation problem. The quantitative strategy on the equity side, initially the CAPM model, evolved into multi-factor models, ML, and the introduction of alternative data, with the core objective of selecting stocks with excess returns.

A：Quantitative models play a key role in asset allocation decisions, allocating funds among various types of assets such as stocks, bonds, gold, and commodities based on practical factors such as investors' investment objectives, risk appetite, and maturity. Quantitative asset allocation takes advantage of the differences and correlations of the return risk characteristics of different assets to combine investments to effectively diversify unsystematic risks and smooth investment fluctuations to achieve the best balance between return and risk. At the same time, quantification will also widely apply risk evaluation models to ensure that each asset contributes equally to the overall risk of the portfolio, further enhancing the resilience of the portfolio in different market environments.

A：As market effectiveness increases, it becomes more difficult to actively invest in excess returns (alpha). The asset allocation strategy is gradually becoming the first choice of investors because of its stable income characteristics in the volatile market environment. Especially in fixed income plus products, through the introduction of quantitative investment strategies, including the setting of asset allocation dimensions, the adjustment of stock ratios, the quantitative index increase or quantitative stock selection of full-end investment, etc., it can better adapt to the needs of customers with medium and low risk preferences, and optimize asset allocation strategies through historical backtracking to prevent potential risks and operate portfolios stably and steadily.

A：The quantitative index enhancement strategy is based on tracking the benchmark index, using a multi-factor model for stock selection, and strives to consistently outperform the benchmark index while controlling tracking error and deviation. Specifically, the strategy needs to do two things: first, lock in beta risk to ensure that the market risk taken is clearly revealed, and second, use a multi-factor model to obtain excess returns (alpha), which reflects the core ability of quantitative investment. In the process of building a multi-factor model, we will focus on a wide range of data sources, including fundamental data, quantitative data, and alternative data (e. g., supply chain, public opinion, patent data, etc.), while continuously mining and testing new factors, and rigorously testing and monitoring existing factors to ensure their validity and economic logic.

A：We will use a linear model and a nonlinear model. Linear models are easy to understand because of their simplicity and transparency, while nonlinear models are better at capturing nonlinear relationships in high-dimensional data and often use complex models such as digital models and ML neural networks to make predictions.

A：The multi-factor model combines static wind control and dynamic factor allocation strategies to coordinate inter-factor correlations to synthesize stable alpha states through the predictive power of different dimensions (e. g., time dimension, industry sector strength). Static wind control is extremely deviated, and dynamic factor configuration provides active resilience in style and industry changes.

A：Quantitative investing strictly follows models and algorithms to avoid subjective emotional interference and better control risk. As market effectiveness increases, quantitative models can reduce the need for high-frequency subjective decisions and improve decision wins. Active investment wind control focuses on investment industry policy compliance and other requirements, while quantitative enhancement strategies are based on multiple constraint model testing, maximizing returns with minimal risk, and adjusting models and investment targets in a timely manner according to market conditions to reduce overall volatility and risk.

A：Quantitative fixed income plus product transparency is high, so that customers can understand the beta volatility characteristics and risk-return characteristics of the underlying strategy, according to their own needs to choose the opportunity to open positions or take profit. At the same time, quantitative fixed income plus products help customers achieve a better stable income profit experience by clearly demonstrating the income risk characteristics.

A：We adhere to the principle of prioritizing risk management over return thickening, and achieve balance through asset allocation philosophy and five dimensions of risk management. Among them, equity position management is a key part, according to the macroeconomic trend of dynamic adjustment of fixed income asset allocation ratio, including the strategic long-term stock bond allocation ratio pivot determination, but also includes the short-and medium-term market research under the tactical trading management.

A：In the strategy of quantitative finger increase, industry dispersion is its own characteristic. Quantitative investments are based on the industry distribution of financial indices and are usually more dispersed. Through the multi-factor model, moderate small deviations are allowed in the industry allocation, aiming to maximize alpha returns. Therefore, the emergence of industry ultra-low allocation at the portfolio level is more a result of stock selection than an active increase in industry concentration.

A：Style equilibrium is an important dimension when building a stock portfolio with quantitative investment. By adopting stable alpha factors and avoiding excessive concentration of a single investment style, quantitative models can cover a wide range of fundamental, emotional, financial, technical and other factors, thus capturing investment opportunities at different stages of the market and reducing the volatility and risks associated with exposure to a single style.

A：Diversification of positions means that the portfolio will choose more targets to reduce exposure to a small number of stocks. Even high-quality companies may be exposed to operational or financial risks, and diversification of positions can effectively reduce the impact of individual stock risk on the portfolio and enhance the overall stability of the portfolio.

A：By monitoring changes in market style in real time and applying a dynamic adjustment mechanism, when a certain type of risk indicator exceeds a preset threshold, measures can be taken quickly to adjust the position ratio. For example, when the risk of liquidity depletion arises, small-cap strategies are reduced to adapt to changing market conditions and risk conditions.

A：The product's return and withdrawal targets are first outlined based on customer needs and the applicable equity investment strategy is evaluated based on positioning (e. g., fixed income, medium wave, small cap, etc.). Through historical back-testing, adjusting asset allocation strategies and wind control strategies to ensure close to earnings withdrawal targets, especially in extreme market conditions for stress testing and tail risk avoidance. If there is still a gap, overlay hard stop loss target retracement management to deal with extremes.

A：Quantitative fixed income plus products mainly use quantitative index increase strategy, so that investors have a clear and transparent understanding of equity positions. After long-term research precipitation, portfolio management is simplified to volatility management, I .e. small position management. Due to the transparency and interpretability of the strategy, investors and managers can work together to smooth out earnings fluctuations, and through the effective separation of beta and alpha, fund managers can focus more on intraday beta volatility management, while having mature position management strategies, such as fixing long-term position pivots and constraining the float range.

A：In the management of Anhua's fixed income plus products, the equity strategy has a high beta transparency, allowing investors to design investment strategies based on their own return risk appetite. For example, the impact of equity market volatility can be reduced through fixed investment, and for stock price products or other complex fixed investment strategies, it is possible to invest at a constant rate during the upswing of the beta, double the investment during the downswing of the beta or adopt a grid timing strategy to optimize the investment effect. Investors can also calculate the ratio and estimate the product position by calculating the change in the net value of the product and the daily return of the underlying equity benchmark, so as to better grasp the product performance.

A：For specific products, we target exposures based on product strategies and return recovery targets, and are generally actively exposed to low volatility and value styles, as these strategies are resilient and have strong absolute return properties when the portfolio is pulled back. In the face of drastic changes in market style, it is mainly dealt with by adjusting position management, such as adopting a more active management approach when liquidity in small-cap stocks dries up. In addition, extreme style reversals are hedged through relatively ultra-low matching, such as a low-wave strategy that overmatches near the bottom of the market.

A：In the face of similar problems, in addition to the temporal analysis, it will also be considered from a cross-sectional perspective, I .e., grouping according to stock characteristics and then assigning factor weights to different subsets, rather than using the traditional market-wide uniform weighting approach. This allows for decentralization at the factor level, so that when a factor fails in one sub-domain, it may still be valid in another sub-domain, thus achieving a relatively stable configuration effect.

A：At present, the portfolio I manage mainly applies additional quantitative fixed income plus strategies on different product types such as zero allocation flexible allocation and partial debt mixed secondary stations. The strategy covers a number of aspects such as growing broad-based value. Among them, Imagination may be more familiar, in the company's secondary debt products have been operating for more than two and a half years.

A：HTC products are based on the CITIC Growth Style Index as the basis of quantitative stock selection strategy, which is characterized by the selection of stocks from CITIC's three-tier industry classification and allocation according to the five styles of growth cycle, consumption, finance and stability, defining growth in the industry dimension. In addition, the product uses a volatile but low-correlation or even negative-correlation investment strategy on both ends of the stock and bond, and emphasizes the risk pricing strategy of tail risk, thus achieving a high daily positive yield and high Karma effect over the past year.

A：Anrong products have adopted the standard CSI dividend enhancement strategy. In the past year, except for the first month, Anrong products have basically achieved the effect of outperforming the benchmark every month, with an average monthly outperforming the CSI dividend index by about 1 point. At the same time, through the standard AY index increase and CSI 500, CSI 1000 mid-cap stock pool for stock selection, the formation of a strategy to adapt to the growth plus cycle rotation market, and in the alpha tail risk and position management to find a balance point.

A：Ruifeng product is a market-wide stock selection to enhance the operation of the CSI all-index secondary debt products, the goal is through the stock part of the alpha stability, in the long-term continued to outperform the secondary debt index. The product operation emphasizes the quality of cash flow, selects companies with good cash flow for stock selection, and extends the product line to diversified asset allocation, including stocks, bonds, convertible bonds, Hong Kong stock ETF funds, etc., aiming to provide medium and low wave fixed income plus products with transparent strategy, income withdrawal ratio and volatility characteristics.

A：Penghua Imagination is a fixed-income plus product for customers with weak risk tolerance, focusing on investing in the board to share the progress of domestic high-end manufacturing and hard technology companies. The product is 100% invested in the internal standard of the Science and Technology Innovation Board, and is optimistic about the development potential of its six major high-tech and strategic emerging industries. In terms of asset allocation, it mainly focuses on the rapid adjustment and rebound characteristics of the board, emphasizing target withdrawal management, and focusing more on controlling equity positions than other products to mitigate the impact of market volatility on earnings.

A：The CSI 300 Index was chosen as the benchmark because of its high weighting in the field of modern new technology, which can better reflect the number of mid-cap listed companies and the stage of market capitalization development, and is representative.

A：Quantitative fixed income plus products are suitable for investors who have a high demand for risk control and income robustness, especially those who have a certain understanding and recognition of the quantitative investment philosophy, or who wish to allocate to specific theme style equity assets (such as science and technology, small and medium-sized cap, dividend or brokerage, etc.). Through these products, investors can earn returns that exceed their benchmarks, while enjoying the robustness of fixed income investments and the discipline of quantitative investing.

A：In July, our current bullish style is still the small-cap growth style. From the model level, the size of the disk dimension, whether it is the macro environment or market sentiment and market state, are relatively optimistic about the small cap. The growth style has returned to the view of small plate dominance since June. In addition, in the growth value dimension, changes in some indicators of market sentiment and market conditions, such as the China Wave Index, the decline in fund raising, and the decline in the number of new investors, all point to a favorable growth style. June recommended communications, building materials, computers and other industries, July the latest bullish banking, computers, building materials, consumer services, telecommunications and home appliances industry.

A：The industry rotation model is adjusted according to the speed of market industry rotation, and the main driving information includes price information, research information, momentum reversal information and liquidity information. In the current fast-rotating market environment, this information has a stronger ability to predict industry rotation.

A：We feel that stocks are better than commodities than bonds. For equity assets, it is recommended to do a good job of asset allocation, moderate allocation of equity, can be quantified through fixed income plus products to take into account income enhancement and withdrawal control. In the specific configuration, we need to pay attention to macro liquidity and market style indicators, dynamic adjustment of the portfolio.