Quant investing or algo investing has really picked up investors’ interest over the last couple of quarters. Simply defined, it is a systematic rule based approach to select stocks. The rules should clearly define the entry, exit points and also the size of each investment.
For Example, you rank all stocks based on their last 12 month returns. You select top 10 stocks having the highest returns and then you give them equal weights.
The first step in the development of quant based models is selecting your universe of stocks. It could be Nifty 50 for those who just want to focus on large cap stocks or could be BSE500 for those who are looking to construct multicap portfolios.
Next step is to backtest the investment hypothesis. One hypothesis could be that the stocks that are in momentum, tend to stay in momentum. You rank stocks on the basis of momentum over the past few months or weeks and then select the stocks which are high on momentum.
Next step will be to give these stocks weights. One of the simplistic ways to do this is to give them equal weights, so if you have selected 10 stocks, you give 10% weight to each. Another way is to give them weights in proportion to the momentum scores, or you try to optimize the risk adjusted returns for these 10 stocks.
Systematic investing is an investment approach that uses a rule-based approach for portfolio creation. It uses data-driven insights and advanced computer modelling techniques, in an automated way, that offers many advantages over the traditional approach.
The factors on the basis of which you select stocks are the driving force behind the returns of your strategy.
These factors could be macro-economic factors like GDP growth, interest rates, inflation or value of currency relative to USD. Other factors which are popular are style factors like value, momentum, quality, low vol etc.
Drawbacks of traditional investing
In traditional funds, your fund manager and his team does fundamental research on companies and sectors, and then constructs a portfolio.
It involves looking at qualitative factors like management capability, the strength of a company/sector vis a vis its competitors as well as quantitative factors like financial ratios of a company and price.
But at the end of the day, the decision to invest in a company or not is much more based on subjective factors. Though it has its own advantages, there are some obvious drawbacks in this approach.
Let’s look at some of those drawbacks.
The limited capacity of fund managers: One problem with discretionary investing is the limited capacity of a human being. In such an investment approach, starting from searching for investment avenues, to constructing your portfolio, to delivering returns, all tasks are of your fund manager.
But we all understand that if we can quantify the factors on which we are basing our decisions, then computers can do a much better job than humans.
- Subject to Human bias: Human involvement often brings along human judgement and bias. What is worthless for one person can be of immeasurable worth to others.
Similarly, a stock or fund valuable to you might be ignored by your fund manager because of subjective bias. Every investment decision can significantly impact your portfolio performance, and the fund manager’s incorrect judgement can be a reason for lower-than-expected returns.
- Returns depend on the fund manager’s skill and knowledge: One of the biggest problems with the discretionary investing approach is that your returns are highly dependent on the decision-making as well as research skills, knowledge of financial markets, and experience of fund managers. After all, he is the one who will take your investment decisions. If he lacks proper knowledge, skills, and experience in the market, your portfolio may see a big hit.
How does Factor Investing overcome these problems?
- Not dependent on one fund manager: With a systematic approach, you are not dependent on the skills, knowledge, and experience of one fund manager. Rather, a team of professional managers works on research to make the best out of your portfolio. As more fund managers work together to construct portfolios and bring their skills and expertise to the table, your portfolio is likely to be constructed in a better way,offering amplified returns.
- Scientific Approach: The systematic investing approach significantly differs from the old-schools approaches to investing. It believes that market prices don’t move in a random way, rather their movements are statistically measurable and predictable. Systematic investing involves high-quality big data, data science, data mining, and scientific testing of investment ideas to make an investment decision.
For instance, before making any of your investment decisions, historical price data may get tested keeping out some markets and periods. Then, the test may be conducted again including those markets and periods which were previously excluded. This way, it helps in minimizing the risks related to an investment decision.
- Decisions: When the Discretionary investing approach believes in suggesting fundamentally sound investment ideas, systematic investing goes a step above. It involves qualifying sound investment ideas using advanced modelling techniques, and filtering out others. This approach does not ignore human decisions, rather it amplifies them. Moreover, it makes sure that your portfolio is free from human bias
- Scalability: Systematic investing saves you from concentration risk by constructing well-diversified portfolios including varieties of securities. Automated and quick processing of new information with keeping risk elements in check allows for better implementation of investment strategies.
- Better targeted outcome: With the help of systematic investing, investors can have a much better control over the performance of their portfolio. These rule-based strategies can help investors optimize portfolios for better risk-return tradeoff. For example, an investor looking to reduce volatility in his portfolio can consider investing in low-volatility stocks.
Advantages of Estee’s Multi-factor approach
One look at the historical factor based indices tells us that they have been able to outperform the index and that too with lower volatility.
Diversifying across these factors helps us to deliver better risk adjusted returns in the long run. Let’s understand in detail. Momentum, one of the best performing factors across geographies, tends to do well when the markets are trending but when they are range-bound it will keep giving noisy signals.
An factors like quality and low vol tend to do well during bear markets and factors like size and growth tend to do well during bull markets.
We use the cyclicity of factors across different market conditions to create a diversified portfolio much the same way as an index is created. Like in an index, if a stock is not performing well, it gets booted out and a better performing one gets included in the index. In the same way, the factors that are performing well and also likely to perform well in the current market conditions are included and the factors that are not suitable are excluded.
This helps us generate stable returns across market cycles.
As we can see below, since October 2021 markets have been selling off, and are still down about 5% from peak, but due to the effective shift to efficient factors, our portfolios have been able to generate positive 12% returns.
Even during the bull markets, from our launch in May 2020 to Oct 21, we generate consistent alpha.
One can read a detailed blog about our performance here.
Investors have been open to investing in many such rule-based strategies, like factors based ETFs and curated baskets of stocks. There has been tremendous advances in awareness about these systematic strategies and their benefits in all market conditions.
This bodes well for the future of the investment industry. Investors should ideally allocate a part of their funds to the systematic strategies as then they will be able to take advantage of the scientific rule-based approach and diversify away from the traditional funds.