Updated: Mar 26, 2021
Do you wonder how much to buy from each stock?
It is going perfectly you got the money to invest, you’ve checked that the market will go up, you’ve prepared the research on stocks and selected the very best of them just like Warren Buffett. Last step of the investment process is to assign weights to your chosen stocks and after that you can buy them. In other words assign weights is basically how you are going to distribute your investment budget across selected stocks. In essence this is the heart of investing in stock market, and it is also know as portfolio management. Different kind of investors have different approaches to do that, however it can be synthesized in 5 main categories. The way you assign weights determines what kind of a investor you are. So check in the below table the 5 major approaches to portfolio construction and their good and bad sides:
Depending on your views, knowledge and skills there are several approaches to build your portfolio. So lets explain each of these in greater detail and learn in what case are best usable.
Build portfolio with Convictional weights
This approach is most widely used by retail traders. Constructing your portfolio with convictional weights means that you assign weights simply on your hunch. In this case far more important is which stocks are picked, not how much should you buy from each stock. This is strictly active investing, because investor must have active views on the market in order to select investments. Convictional weights are good for unsophisticated investors because it is simple approach – you simply buy the stocks you believe will outperform in whatever ratio you feel is good. However the main critique is the lack of risk control, because in this way investor disregards volatilities and correlations among assets, therefore is likely to concentrate the risk in several factor that are used for the views and thus maximize the strategy risk. For example if a trader thinks oil prices will rise then it is likely he will buy only stocks from oil industry and will have no diversification, so the success will depend solely on whether the prediction is correct.
Apply Market Cap weights
Oppositely passive investors use market cap weighting to build their portfolios. Market cap weighting is a simple approach and means that investor will buy stock proportional to their market capitalizations. In the perfect case it mean this portfolio will have the same risk-return characteristics as the market portfolio. Therefore market cap weighting is ideal for investors who don’t have active views (don’t know which stocks will outperform) but still want to invest. Key to note is that in this approach investors makes the assumption that stock market is efficient and current market cap weights are optimal and there is no point in changing them.
Just use Equal weights
The simplest portfolio construction approach is to just buy stocks in equal proportions. For example if you have $10k and picked 5 stock then you put $2k in each stock. Equal-weighting is very popular because it does not require any skills and can be applied by everyone. However lets review what is behind this simplicity. Equal weights can be used by both active and passive investors. Passive investor who believes the market is not efficient and doesn’t have active views can resort to equal weighting. On the other hand active investor who has picked n-number of stocks (believe these will outperform) and can’t assign weights by conviction can also use equal weights. Equal weights are so popular because you may not have a lot information (volatilities, correlations, market efficiency, active views) and still can use them, just have to be willing to invest in stock market. Also even simple this approach does give some form of risk control, because in general if you include more stocks in the equal-weighted portfolio it will diversify the risk, although the true diversification cannot be achieved or measured without some knowledge on correlations.
Get more practical with Heuristic weights
Another approach to portfolio construction is heuristic techniques. Such an approach suggest that investor should use some practical technique to determine weights in the portfolio. For example weights can be made proportional to each stock’s expected alpha, or ROE (return on equity). The drawback of such an approach is that it is not guaranteed to be optimal. Heuristic methods are for active only investors who have strong believes that their predictions have value, but do not not anything additional about volatilities and correlations. Therefore heuristic methods are simple and offer strong performance in terms of returns but are not great in risk control.
Classical Mean-variance optimization
Application of MV optimization is the first step in moving from trading to real portfolio management. MV optimization will provide you with weights that are efficient in terms of risk and return in the context of volatilities and correlation between stocks. It sounds really good and it is mostly correct method, the viability is dependent on your information about volatilities and correlations. However with very simple tools like sample covariance matrix you can get good results. Up until that moment everything was step-by-step approaches, here becomes more complicated because math enters in play. The classical MV optimization equation is:
The general idea is that this equation will give you portfolio weights that are maximizing return (based on inputted expectations) subject to set level of risk and concentration. There is a quite a large number of variations based on this equation. The different optimization approaches is where portfolio management gets really interesting. Therefore we will prepare material especially on this topic.
To conclude in this material we reviewed the major approaches to portfolio construction. From naïve to sophisticated and from passive to active there is a tool for every investor on how to estimate the stock weights in the portfolio. In other words how to distribute the investment budget between the selected stocks.