Portfolio Theory
Every successful investor should have a high-quality portfolio. All that remains is to understand what it is
Regardless of experience, every investor has heard of portfolio, diversification, and their importance. These terms are integral and closely related to the investment environment. It is no secret that many investments involve risk. To minimize them, it is worth taking the time (and money) to build a quality investment portfolio. Moreover, such a portfolio should meet the individual needs of an investor.
These are obvious things that, ironically, many people stubbornly ignore. One way or another, we want to introduce our readers to the basic principles of building an investment portfolio. We hope you will find it enjoyable and valuable.
A Brief History of Investment Portfolios
The entire history of investment portfolios can be divided into three time periods: pre-1952, 1952, and 1991.
Before 1952, it was common in investment circles not to put all your eggs in one basket. This well-known expression does not mean what you think it implies. Not putting all your eggs in one basket meant investing in several of the same companies. In general, the main rule of this approach was not to put all your money in one place. It did not really matter where it was.
In 1952, a real revolution took place. The American economist Harry Markowitz published an article “Portfolio Selection” in the Journal of Finance, in which he established diversification in its modern sense. This was the birth of Modern Portfolio Theory (MPT), which is still used by most investors today. The impact of the theory on the world economy was so great that the author was awarded the Nobel Prize.
In 1991, this theory was modified by Brian M. Rom and Kathleen Ferguson, who considered it outdated. The result was the Post-Modern Portfolio Theory (PMPT). It is considered the second most important theory after the modern one.
Modern Portfolio Theory (MPT)
Despite its venerable age of more than 70 years, this theory is still a mainstream practice in the investment world. If you've heard anything about diversification, risk optimization, and so on, it's probably this beast. Modern Portfolio Theory has, without exaggeration, defined the world's investment strategy for decades.
The theory consists of several key features. First, high risk should be compensated by high return. Second, investment portfolios should be diversified to achieve this goal. Finally, the theory assumes that an investor will seek low risk in constructing his or her portfolio.
Let's start with the most interesting point – diversification. The concept of diversification means the inclusion of different types of assets in the investment portfolio. For example, ETFs, precious metals, and corporate stocks. However, over time, the concept of diversification has become more flexible. You can diversify anywhere, even within a single asset class.
Venture capital is no exception. Here, we can diversify the portfolio according to criteria such as stage, industry, or key geography of the client base. These are all considered different asset classes.
Diversification is designed to minimize what is known as idiosyncratic risk (asset-specific). In other words, if one asset fails, another will compensate. This is achieved by having assets in the portfolio with different correlations to each other. Correlation can be positive or negative, ranging from -1 to +1. A positive correlation is bad, and a negative correlation is good. Let's take the venture capital industry as an example.
Let's say you have two early-stage ed-tech startups operating in the Latin American market. The correlation between these two startups is positive (+1) because they are very similar and therefore exposed to the same risks.
If you have the same startups but with different markets, the correlation will be around 0.7. Still positive, but less so.
But between the ed-tech startup mentioned above, and a biotech company focused on the European market, and at a late stage, the correlation will be negative (e.g., -0.8 points).
Efficient Frontier
Also known as the portfolio frontier. This is a graph that shows the relationship between profit (y-axis) and risk (x-axis) for the entire portfolio. As you can see in the figure below, the higher the potential return, the higher the risk, and vice versa. The investor's job is to find investments that are well-balanced. By balanced, we mean maximum return with minimum acceptable risk.
Note the x-axis. The risk level of a portfolio is calculated based on the assets' idiosyncratic risks, their weight in the portfolio, and the degree of correlation. There is also a systematic risk, which is shared by all assets.
Now let's look at the y-axis. There is a formula for calculating the expected return on an investment, which is best illustrated with an example.
Suppose you have two startups in your portfolio. You invested $10,000 in the first and $25,000 in the second. That adds up to $35,000. You estimate that the first startup should return 14%, while the second is around 18%. The formula would be
Expected Return = [($10,000/$35,000) * 14%] + [($25,000/$35,000) * 18%] = [0.29 * 14%] + [0.7 * 18%] = 16.66%
The final undisclosed element of the chart is the Capital Allocation Line (CAL) or Sharpe Ratio. This line represents the ratio of risk to return for assets that carry idiosyncratic risk. The curve will be different for each investment category, such as the venture capital industry or oil trading. Such a calculation can be based on historical data, analysis, or forecasts.
According to Modern Portfolio Theory, the best investments are those at or near the frontier.
In the classic chart, you will also find two other labels: Risk-Free Rate and Market Portfolio. We didn't include them intentionally because they are of little relevance in the venture capital industry. I think the simplified version is more than enough for a basic understanding.
As a result of calculating CAL, Expected Return, and Standard Deviation, our portfolio gets a certain place on the graph: optimal or not.
You can't draw such a graph blindly by hand. This is a job for professionals. You'll need a deep knowledge of markets, different types of assets, mathematical formulas, calculations, and even special software.
Nevertheless, each of you can try to create a similar chart, albeit simplified, based on the information available.
Post-Modern Portfolio Theory (PMPT)
Post-modern portfolio theory is an evolution of its predecessor, with some modifications. In general, the two theories are very similar. The main distinction lies in the different understanding of risk and its impact on portfolio value. That is, portfolio optimization is based on slightly changed criteria.
The authors of the novelty criticized the modern theory for its limitations. In fact, modern portfolio theory is based on the assumption that investors will always prefer low risk. But what if investors don't mind taking more risks? As a result, Post-Modern Portfolio Theory uses downside risk to estimate the x-axis. What does that mean?
MPT takes the average of all returns to determine the risk level of an asset. The math decides what's good and what's not.
PMPT uses the possibility of negative returns to determine the risk level of an asset. In other words, how much the asset can lose in value? The minimum acceptable return (MAR) is set by the investor. Are you willing to get less than expected or nothing at all? No problem, let's add the asset to the portfolio. In modern theory, this would be denied.
Such an approach allows for more flexibility in adapting to investors' tastes because different people have different risk tolerances. As a result, there are many efficient frontiers in the PMPT that are based on human factors rather than mathematical formulas.
As a consequence, the same asset can have different values from the perspective of different theories.
Generally, MPT is popular with passive investors, while PMPT is more active in contrast. The purpose of active investing is to get the so-called alpha – indicators that exceed the market average. You can't do without additional risks.
Passive Investments versus Smart Money
In the previous section, we touched on another important aspect of investing – the passive approach and the active approach. The meaning of these terms varies depending on the area of investing, whether it is the stock market, trading, or something else.
In venture capital terms, the passive approach means exactly what you think it means. The investor provides capital to the startup and then humbly waits for the results and quietly watches. This method is good because investors do not interfere with the startup. After all, who says they know better than the company? With passive investments, the startup decides what to do and how to do it. This not only removes unnecessary stress but also greatly shortens the decision-making chain.
On the other hand, the startup team may lack experience and knowledge, which increases the risk of failure. In this case, not all investors like to see their capital go to waste. That’s when smart money comes into play. In the venture business, they can be considered a form of active investment.
In this case, investors give money in the form of certain benefits, not cash. The range of benefits is quite wide and may include the recruitment of new staff, expertise and advice, partnerships, useful products from trusted companies in the network, and even new clients. Smart money investors actively participate in a startup's life and help the team in any way possible to increase its chances of success.
The main stumbling block in the case of smart money is the competence of the investors themselves. In fact, the venture capital world is full of investors, but not everyone has the expertise to really help a company. Moreover, not all investors are willing to commit their time to startups.
Typically, smart money is the prerogative of professional funds that have made connections over the years, acquired skillfulness, and know what to do and what not to do. In addition, these people are essentially involved in portfolio companies on a full-time basis.
Another difficulty for smart money is the fact that startups are not always eager to raise money this way. The startup team often prefers real money in their bank account to do with as they see fit.
The choice of one or the other investment approach depends on both the investor's skills and capabilities and the startup's needs.
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