After experiencing the volatility of the A-share market in recent years, how to "absorb shocks" has become the voice of most investors.
Quantitative funds have become one of the solutions for more and more investors.
Especially in recent years, with the advent of new technologies such as machine learning, neural networks, and genetic algorithms, quantitative investment has made breakthroughs, and its performance has become more stable and the attention has been further increased.
Quantitative funds can be divided into index-enhanced quantitative funds, active quantitative funds and quantitative hedge funds according to different trading strategies.
Due to the obsession of A-share investors with yields, index-enhanced quantitative funds and active quantitative funds are currently the mainstream of the market.
However, to truly reduce the sensation of shock, quantitative hedge funds are the "magic weapon", and the products use stock index futures and other tools to hedge risks, and strive to strip off the overall volatility of the market and obtain absolute returns.
In terms of performance, quantitative hedge funds have been able to ride out almost every more extreme market environment.
Classification of quantitative funds
According to different trading strategies, public quantitative fund products can be roughly divided into three categories: index-enhanced quantitative funds, active quantitative funds and quantitative hedge funds.
The index-enhanced quantitative fund is to select stocks with a high probability of surpassing the benchmark index in the future to build a portfolio to obtain excess returns through quantitative methods, mainly capturing the α excess returns of index β return + quantitative model stock selection.
Active quantitative fund is a fund that relies on the ability of fund managers and uses quantitative strategies as the starting point for active management, mainly capturing the β returns of the stock market + the α excess returns of quantitative model stock selection.
Quantitative hedge funds use stock index futures and other tools to hedge risks while constructing stock portfolios through quantitative methods, striving to strip off the overall volatility of the market to obtain absolute returns, mainly capturing the net α returns of quantitative model stock selection.
Source: CICC Research Department, Classification of Public Offering Quantitative Products Based on Income Attributes
In terms of dependence on β returns in the stock market, index-enhanced quantitative funds are the highest, while quantitative hedge funds are the lowest.
To a certain extent, quantifying hedge funds can effectively reduce the impact of market systemic risk on product performance.
At present, the index enhanced quantitative fund with the most products and the largest scale in the public fund market is the index-enhanced quantitative fund, followed by the active quantitative fund, and the quantitative hedge fund is the least.
Therefore, everyone is relatively unfamiliar with quantitative hedge funds, especially how quantitative hedging hedges hedges risks.
Let's take a simple example, for example, a quantitative hedge fund buys stock index futures to "insure" the portfolio, and will buy stock index futures for risk hedging while allocating stock spots, if the market subsequently falls, the fund will obtain the profit of stock index futures to offset the loss of stock spot, and if the market rises subsequently, the loss of stock index futures will offset the profit of stock spot position to a certain extent.
Theoretically, the part of the stock spot position that earns/loses less than the stock index futures will be converted into the actual income of the product. Of course, in the specific operation of the fund, the return is also affected by the proportion of hedged positions and the basis of futures.
How effective are domestic quantitative hedge funds?
Source: iFinD, the type is hybrid-active hybrid-open-hedging strategy hybrid three-level classification
From the perspective of performance, domestic quantitative hedge funds as a whole have been able to ride out almost every more extreme market environment relatively smoothly.
According to iFinD data, in 2018, when the CSI 300 index fell by 25.31%, the quantitative hedge fund index fell by only 0.29%, and in 2022, when the CSI 300 index fell by 21.63%, the quantitative hedge fund index fell by only 4.15%.
Source: ifind
In a horizontal comparison, most types of equity products in the market failed to resist the sharp decline in the market last year, and only quantitative hedge funds basically resisted the pullback pressure, with a slight loss of 0.46%.
What are the excellent quantitative hedge funds in China?
At present, there are 24 quantitative hedge funds in the market, which are very scarce, and combined with the data of performance, scale and institutional holdings, the products of HFT Fund are worth paying attention to.
Note: The performance comparison benchmark of HFT Anyi Hedge Hybrid A in the past 1 year, the past 2 years and the last 3 years are 2.77%, 5.64% and 8.59%.
Data source: Haitong Securities, similar products are hybrid-active hybrid-open-hedging strategy hybrid three-level classification, as of 2023/12/29.
HFT Anyi Hedge Hybrid (Class A 008831/Class C 008830) is one of the representative products of HFT Fund's quantitative hedge fund, ranking among the top 5 in the class A share in the past 1 year and 3 years, and the class A share of the product will still achieve a positive return of 4.59% in 2023 when the market is volatile and adjusted.
Source: Fund Periodic Reports, Wind.
Compared with the previous two years, 2023 will undoubtedly be a year for the fund's performance to "go to the next level", showing a more "resistant" net value performance in the changing market environment. It is understood that in 2023, the quantitative team of HFT Fund will optimize and upgrade the quantitative strategy - using the advantages of AI in data processing, nonlinear information mining, self-learning ability, etc., to more comprehensively and efficiently explore high-quality companies with reasonable valuations and sustainable performance growth.
For this product, the hedging strategy is mainly to use a variety of tools such as CSI 1000 stock index futures to strip off the systemic risk of the stock market, in order to convert excess returns into absolute returns, supplemented by fixed income, convertible bonds and other strategies in order to increase returns and find a wider range of income sources.
Source: HFT Anyi Hedging Mixed 3rd Quarterly Report
As we all know, quantification has always been a very "volume" track, which tests the investment team's ability to develop strategies. And fund manager Zhu Binquan is good at this.
Zhu Binquan has 16 years of experience in the securities industry, including 5 years of fund investment experience, as early as April 2007 to join HFT Fund, from traders, analysts step by step growth, refinement, has accumulated a deep quantitative strategy research foundation, independently developed a number of stock quantitative models, index enhancement, quantitative hedging and other areas he is good at.
It is also worth noting that in addition to the good results of HFT Anyi Hedging Mix, the HFT Xinxiang Mixed A (fund code: 519229) managed by Zhu Bin also performed well, and the fund ranked 266/1855 in the past year, ranking in the top 15% of the industry, which also proved the effectiveness of this quantitative strategy upgrade.
Data source: Haitong Securities, similar products are hybrid-active hybrid-open-flexible strategy hybrid, as of 2023/12/29.
Source: Galaxy Securities, time: From the inception of the product to December 31, 2023, it is classified as a hedging strategy absolute return target fund (Class A).
Another representative quantitative hedge fund under HFT Fund is HFT Alpha Hedge Hybrid (Class A 519062/Class C 008795), which has been established for more than 9 years. According to data from Galaxy Securities, as of December 31, 2023, HFT Alpha Hedged Hybrid A is a quantitative hedge fund with the highest cumulative return in the market, and at the same time, it ranks second in annualized return.
The transformation of HFT's quantitative investment team
HFT Fund is one of the earliest fund companies to deploy quantitative investment, as early as 2014, has established a quantitative investment department, has more than 9 years of practical experience, not only complete product lines, net value has also reached new highs.
As mentioned above, in the past 2023, HFT's quantitative investment team upgraded its quantitative stock selection model and introduced artificial intelligence (AI) technology into the quantitative investment research system. With the advantages of AI in data processing, nonlinear information mining, deep learning, etc., it can learn from massive data, and at the same time, the training data contains several complete bull and bear cycles, which can adapt to a variety of different styles of market environments.
According to the quantitative investment team of HFT Fund, "In the past two years, we have been developing a deep learning stock selection model, but the early progress is relatively slow and has taken many detours. The emergence of ChatGPT has given us a lot of inspiration, and developers have adopted cutting-edge AI technology and made certain research results. In the second quarter of last year, AI models were launched on a small scale on some products, and their performance was better than traditional multi-factor models. Of course, the effectiveness of the model still needs to be tested for a longer time. ”
It is understood that HFT Fund strongly supports the development of the quantitative investment team, especially in order to further meet the needs of AI+ models, in 2023, it will upgrade the high-performance AI server and deploy more high-performance computers on all fronts of the quantitative investment department.
Note: According to the three-level classification of Galaxy Securities Fund, HFT Anyi Hedge Hybrid is classified as the absolute return target fund of hedging strategy. The net value growth rate of the Fund's Class A shares from 2020 to 2023 is 3.51%, 2.86%, -3.51% and 4.59% respectively, and the Class C shares are 3.10%, 2.44%, -3.89% and 4.16% respectively, and the benchmark returns for performance comparison are 2.60%, 2.75%, 2.75% and 2.75% respectively. Data source: Fund regular report, 2020 annual results are calculated from the effective date of the fund contract (2020/1/22). During this period, previous fund managers: Du Xiaohai (2020/1-2022/8), Zhu Binquan (2022/8-present).
Note: According to the three-level classification of Galaxy Securities Fund, HFT Alpha Hedge Hybrid is classified as the absolute return target fund of hedging strategy. From 2016 to 2023, the net value growth rate of HFT Alpha Hedged Hybrid Class A shares was 17.16%, 2.51%, 9.14%, 6.35%, 8.26%, 4.05%, 2.10%, -7.58% and -1.98%, respectively, and the benchmark rate of return was 3.37%, 2.76%, 2.75%, 2.75%, 2.75%, 2.76%, 2.75%, 2.75% and 2.75% respectively. The net value growth rate of HFT Alpha Hedge Class C shares from 2020 to 2023 is 2.95%, 1.67%, -7.94% and -2.37% respectively, and the benchmark rate of return is 2.59%, 2.75%, 2.75% and 2.75% respectively. The 2020 results are calculated from the effective date of the contract (January 22, 2020). Source: Periodic reports of the Fund. The previous fund managers of the Fund are: Chen Zhenpu (2014/11-2018/5), Zhu Binquan (2018/11-2022/8), Du Xiaohai (2018/4-present), Li Ziwu (2023/4-present).