Sara, a 50-year-old working professional, was in a car accident. She suffered some serious injuries and submitted a claim for permanent partial disability benefits with her insurance company. Her personal physician had already provided detailed documentation. But her insurance company requested her to attend an examination with another doctor, provided by them. This doctor, they said, is an "insurance doctor." Now, this was something new to Sara. But is it a new concept? Let us find out. Who Is an Insurance Doctor? Insurance doctors play a critical role in the insurance sector, which is quite underrated and misunderstood. Most of us assume that they actually replace the role of our treating physicians, but that is not the case. Our physicians treat us in case of any mishap, but they do not assess or evaluate our level of injury or disability. But then, who actually does it? This work is done by Insurance doctors, which, in turn, impacts or affects our insurance benefits. Th...
Investing our hard-earned money into profitable assets or opportunities ensures that our funds grow well and on time to meet our financial goals. However since many of us do not have the required time or expertise to handle this, we prefer to seek the help of responsible and experienced fund managers who understand the market better.
But what if your investment opportunities turn out to be:
- Computer-based models?
- Use statistical data and advanced algorithms to invest in funds?
- Non-traditional in nature?
- Generate excess returns or Alpha, and most importantly,
- No human intervention?
Here comes the Quantitative funds, or "Quant funds", as they are typically called, that represent a highly advanced level of finance, merging market expertise with technology and mathematics to redefine the traditional methods of investment.
So, what are actually Quant funds?
These funds do not depend on human judgment or intuition, which are often subjective. Rather they follow both real-time and historical data and employ advanced automated and quantitative algorithms for financial decisions.
It is interesting to note that these funds are quite secretive about their method of operation, following back-tested techniques, making them reliable enough to be able to identify market inefficiencies and patterns to earn considerable profits from a trade.
The global effort towards automation of tasks, supported by the availability of a huge quantity of data is fuelling the effort toward more sophisticated market, time horizon, and scenario analysis, and this is the point from which quant funds draw their inspiration.
What is the result?
Where traditional fund managers are struggling to meet, leave alone cross the market benchmark, quant funds are looking forward to Alpha, or a return that crosses the benchmark. These funds have been attracting a large number of market participants due to their ability to generate very good levels of returns, over the years.
The speed and consistency of trade execution, and diversifying funds over multiple asset classes, within an acceptable risk level, are turning these sophisticated financial models designed by using software programs, into very effective tools that can forecast future investment opportunities.
How are these models designed?
However, designing such top-class statistical models requires professionals who have a very high level of technical experience along with sharp mathematical and programming skills. But how do they create these programs?
- Input - They input data related to company financials, the market, GDP, inflation, interest rates, etc. At this stage, stocks that have low earning potential are eliminated, leaving behind only the high-performing ones that have good future prospects.
- Forecasting - In this stage, stocks are evaluated and future estimations regarding price, risk, and returns are generated.
- Creation of portfolio - Here the most efficient and optimum portfolio is constructed, where each stock is assigned a weight, that will give considerable profits at very low risk.
Even though they are neutral funds, eliminating bias and prejudice, controlled risk, least room for errors, and fast decision-making, their over-reliance on historical data and continuous backtesting complicates them. The funds work on many assumptions without factoring in unforeseen contingencies. Combined with Artificial Intelligence, these assumptions reduce their flexibility in financial markets.
Conclusion:
Finally, investment decisions are based on individual goals, risk appetite, and time horizon. Professional advice is extremely important while making such decisions. Therefore, be it a quant fund or any other investment option, it is always desirable to do proper research and understand the process before making an investment.
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