Portfolio Management and What it Actually Means

Portfolio Management. You have probably heard this term before. But, have you ever wondered what this term actually means. Does it mean to just buy many stocks/ asset classes or just diversify and forget? Today, we are going to look at the actual meaning of portfolio management and the things that come into play while you are managing a portfolio. So, let’s dive in.

The concept of portfolio theory was laid out by Nobel laureate Harry Markowitz in 1952 in his classic paper Portfolio theory. This paper was so much influential that it changed the whole finance industry forever. After that, universities around the world started teaching this concept. In simple words, portfolio management is basically a concept that promotes the idea of diversification. You don’t want to have all the eggs in the same basket. Rather, you want to have a portfolio that consists of assets that have a low correlation with each other. I have something here which might help you to picture this concept:

I was just kidding, chill out! Many of you reading this might have difficulty understanding what is going on above. Essentially, what it is saying is that we want to think about risks and returns in terms of a portfolio rather than individual stocks/ assets. Our goal is to maximize our returns while simultaneously minimizing our risks. There is no free lunch in finance. You cannot completely eliminate risks. Risks can be only minimized. This can be done via transferring it to some other sources/parties or diversifying among many assets or using derivative products.

So a textbook example of a portfolio would be to imagine you have 2 stocks: stock A and stock B. A generated 10% return with volatility (as measured by standard deviation) of just 6% last year. On the other hand, B yielded a 15% return with a volatility of 13% last year. Also, let’s say you know that the correlation/covariance between these two stocks is 0.3. If you are faced with this kind of situation, how would you allocate your money between these two portfolios? 

Portfolio theory suggests that instead of putting all of your money in either A or B, you should rather make some form of allocation between the two. This process is called portfolio optimization. What would be the best allocation of the resources controlling for risks and returns? This is the holy grail of portfolio management. However, the simplest case would be to divide the capital equally between A and B and construct an equal-weighted portfolio. So, if you have Rs 1 lakh to invest, you are allocating Rs 50000 to each stock. If you do this, your portfolio’s return would be:

E(R_p)

= W_A (R_A) + W_B (R_B)

= 0.5 * 0.10 + 0.5 * 0.15

= 0.125 (or 12.5%)

Our hypothetical portfolio which has A and B equally weighted generated a 12.5% return last year. Now, you might think, so what? I could easily put all my money in stock B and get a 15% return which is obviously more than 12.5%. And, I would say you are absolutely right but you would also be taking a higher risk than the portfolio approach. I will demonstrate this effect to you here:

And, there you have it, my answer to the earlier question of yours as to why not just put all the money in stock B is that if you diversify your capital between A and B, your return will be 10% but also your risk is minimized to just 7.93%. If you had invested in B alone, you would have a volatility of 13%. The lower the volatility, the better for our portfolio.

You might be wondering who wants do all the math above, right? Well, you don’t have to actually do it by hand. Just a few clicks in Excel and ta-da, you will have your answer. The main goal of why I demonstrated to you the above calculation was that I wanted you to understand the fundamentals and the intuition behind it. You can find tons of video tutorials on YouTube if you are interested in this stuff. This is the simplest explanation I could come up with. I hope it was understandable.

Lastly, I want to leave you with an analysis I had done about the historical correlations among different sectors in NEPSE few months ago. Correlations are very integral in portfolio construction. Like we discussed above, we want portfolios that have a low correlation with each other. This helps balance our risk-return tradeoffs. Here is a table for you that might give some insights as to how much are sectors really correlated with each other:

The data used, leading up to this article, starts from 2011 to 2020. Readers are also notified that data of Microfinance and Insurance starts only from 2015 and (sorry, I could not manage further than that!)

A word of warning here: Correlation does not equal causation. This is a point raised in every introductory stat lecture and it is very important that people mustn’t misinterpret it. For example, we can see that the NEPSE total index has a very strong correlation of 0.94 (94%) with the Commercial Banking index. Similarly, we also see that Hotels are least correlated with Nepse. Does this mean that every time Nepse performs well, the impact on hotels would always be low? No! The 0.57 correlation implies just an association and from this number, we cannot deduce any kind of cause-effect relationship.

Obviously, I missed a lot of things that come into play in a portfolio management such as rebalancing, timing, optimization, asset allocation, etc. However, these topics require an article of their own because there are many dimensions to them. The portfolio theory covers my entire semester so, it did not surprise me that I could not fit all the topics in this article. But, I am looking forward to sharing more about these things in future.

A Side note: I am conducting an empirical research on size premium on NEPSE. Size effect has been known to persist all over the world and I want to test how do firms in NEPSE behave when small cap stocks are compared with the large cap stocks. So that is why, I am looking for collaborators. If anyone is interested in doing such studies, I would love to work with you. However, please note that I would expect the person to have at least a rudimentary understanding of concepts like EMH, Factor models, Market Anomalies etc. I look forward to having a conversation with you.

Bivek Neupane is a MSc. Finance and Economics student. He is also a CFA candidate. He is specializing in quantitative finance and research. His other interests include Factor modeling, Portfolio optimization, Behavioral finance, Alternative asset management, etc. Connect with him via LinkedIn or his blog.