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Technology has transformed everyone’s life in a way or another; it is almost inevitable to be not affected by the revolution. Investment techniques are also changing rapidly with the help of Quantitative techniques, and Asset management is also not free from these changes. Here we are going to discuss how these changes are taking place and how these techniques are changing the basics of investment. These techniques are becoming more and more essential for every investor, which once was used by only big investors.

Data plays a central role in all these techniques. With technological advancement, data available for taking any decision has increased enormously. Whether it is analyzing the buying behavior of customers with the help of credit card data, analyzing the use of cars with the help of GPS trackers, almost each and every thing can be analyzed with the help of data available around. This available data offers a big opportunity for asset managers for investment, however, it all depends on how you use this available data. Alternative data refers to a data set used to analyze an investment opportunity.

Some of the Quantitative Techniques used for the Investment purpose are:

In past industry trends, insights were hard to get, it was only restricted to a handful of analyst firms who used to publish these trends and very few had access to these. But these days industry insight is available in great depth, with various parameters like demographic, age, income and various others.

Monitoring:

Alternative data can help in getting the insight and get the signals for a trend reversal in the market, especially when trends are analyzed considering all the correlated factors.

Segmentation Analysis:

This technique helps in data mining. Here we study the impact of an event on the different types of firms. (e.g. Scarcity of raw material, winners and losers.)

Risk Analysis:

This technique helps in identifying the risk related to stock before picking the same. Which otherwise is difficult to analyze.

Using Quantitative Techniques for Data Management

Combining quantitative techniques with fundamentals for investment should be done mindfully as it’s not easy. It just can’t be done in any other way, with such a huge data available for any problem; solutions finding could be very difficult as well. We need to have some grasp of the data and how it can be used. Some industry data can be very technical in nature requiring the technical expertise to understand that data. There are various factors involved in each data set; fundamental analysis by a domain expert can only help to find which factors need to be used for the solution of a given problem. Managers having a strong understanding of their industry can have an edge over others in using these quantitative techniques for gaps underlying in the related industry. While using these techniques, they have the answer to gaps and how they are going to fill these gaps using the available data.
Due to fast development in the field of technology, there has been a lot of advancement in this field. But regulatory setup has been slow in catching up with the pace of the development. Nevertheless, the new regulatory setup is setting a new era for alternate data, as this data has increased many folds due to various technologies and was in intense need to be regulated as lots of data is being generated by various industries and can be misused. For example, tech giants like Google Inc.  Apple are changing the way how and what data of users they are storing. Being cautious about the use of this enormous data has become the need of the hour for everyone using this data effectively and efficiently.
Adding quantitative techniques with fundamental techniques can work wonders for any asset management company, however, it takes a lot of effort in aligning both for better results. Fundamental analysis requires strong domain knowledge, helps in the analysis of the trend of industry, whereas quantitative techniques help in managing big data, doing statistical analysis promptly. Using both techniques can garner good results, but will require a lot of changes to be done in an organization. Strong cross-functional teams will be required for this which is aligned with each other. Starting will small steps and taking leaps after getting some tangible results will be a better strategy to start with.

About Author

Dr. Shikha

I’m having an MBA (Marketing and Finance), an M.Sc (Mathematics) and a qualified UGC-NET with more than 9 years of experience in education. I have worked with DIMS, Aryabhatt and the IAMR groups of institutions. Currently associated with a prestigious institution i.e. IPEM group of institution.

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I'm having an MBA (Marketing and Finance), an M.Sc (Mathematics) and a qualified UGC-NET with more than 9 years of experience in education. I have worked with DIMS, Aryabhatt and the IAMR groups of institutions. Currently associated with a prestigious institution i.e. IPEM group of institution.

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