Making of Glide Portfolios – Part 3- Efficient Portfolios
One of the most important financial decisions you will ever make is to invest your hard-earned money. The concept of investing, whether in stocks, bonds, fixed deposits, or mutual funds, will confound your thoughts.
Choosing a mutual fund from the enormous number of options is particularly difficult for investors. When an investor has to establish a portfolio of funds, things get much more complicated.
Building a portfolio will only benefit you if you invest in mutual funds. Due diligence performed before investing is generally insufficient to ensure that the investment operates as intended.
The key to ensuring that your money is working for you is to review and manage your investments regularly. A portfolio enables you to do just that: assess your total financial situation, acquire or sell units if they do not meet your expectations, and avoid catastrophic losses.
The financial goals should be mapped to your investments to construct a portfolio. Financial objectives are the dreams that you want to realise and invest for. Short-term and long-term goals are both possible. A goal-oriented portfolio is usually preferable to investing haphazardly and glide investment can help you with that.
If you’re looking for an online wealth management application, then Glide Invest can totally help you. The company focuses on a goal of making investing stress-free and easily accessible to people across India and across income brackets. You might be wondering why you should trust Glide. So, let us tell you, we bring in customers and advise them where to invest in mutual funds. For this, we look at data from multiple sources, to understand the market and customer trends, and improve the advice and service we give to our customers.
Modern Portfolio Theory (MPT), often known as mean-variance analysis, is a mathematical framework for constructing an asset portfolio that maximises the desired return for a given amount of risk.
For most of us, the detailed explanation and formula are jargon, but the underlying premise is straightforward as illustrated by the graphic below
A typical asset portfolio (Portfolio A) has an expected return and matching volatility or standarddeviation.
According to MPT, a portfolio can be made efficient by either increasing return while maintaining the same risk (portfolio C) or reducing risk while maintaining the same expected return (portfolio B). This efficiency is achieved by adjusting the asset weighting in the portfolio to match the desired characteristics.
The mathematical formulae are beyond the scope of this blog, but a simple example can help you understand them.
By adjusting the weight of assets with a return to ratio risk closer to what is predicted, it is possible to maximise returns while limiting risk. The standard deviation of daily returns is used to calculate risk. So you get a ratio by dividing the returns of each asset class by the risk of each asset class, and you build a portfolio that fulfils your return and risk expectations in the same ratio.
Return expectations are required as input in current portfolio theory, which means you are expected to indicate what you believe will be the returns of each asset class while creating the portfolio.
Returns from the past are just that: past. There's no guarantee that what worked before will continue to work in the future.
As a result, projected returns became the preferred method for constructing an efficient portfolio, because you want your portfolio to be efficient in the future, not in the past. Because there is no scientific way to forecast the future, this mathematical framework's input is based on calculated assumptions and models.
As a result, MPT's portfolios were erratic and difficult to apply in real life. Any change in projected returns tended to substantially alter portfolios, with asset classes being removed entirely for slight changes in return expectations.
In an attempt to solve this estimation challenge, Fischer Black and Robert Litterman published their famous BlackLitterman Model in 1992, which serves as a good estimating tool for generating predicted returns that are then used as inputs in the modern portfolio theory framework. The Black Litterman model's expected returns proved to be relatively stable, unlike MPT's, which were prone to frequent adjustments.
As a result, the goalbased investment portfolios that Glide offers are built on this foundation.
PASSIVE STYLE OF INVESTING:
We now have almost all of the pieces in place to put up an effective asset allocation portfolio. The only thing left to decide is which assets should be included in our selection criteria. Glide is a firm believer in investing in a passive manner.
Active investing entails thorough research and analysis with the goal of picking specific assets in a portfolio that will outperform a benchmark against which it is measured. An active large cap mutual fund, for example, will attempt to outperform a large cap benchmark index such as the Nifty 50 or Nifty 100.
Passive investment is a simple, successful, and costefficient method of investing that avoids all of the aforementioned work. It entails investing directly in benchmarks rather than constructing a portfolio to outperform them. In comparison to an active strategy, there is no risk of underperformance, and market rewards are supplied at a very cheap cost.
Wherever possible, Glide's portfolios include passive funds since they provide the best value in terms of performance and cost while showing the characteristics and features of the underlying asset class they represent.
Now that we have all of the pieces, let's look at how we put the portfolios together.
GLIDE GOAL-BASED EFFICIENT ASSET ALLOCATION PORTFOLIOS:
At Glide, we start the process of building a portfolio by selecting a wide range of asset classes.
- Uncorrelated or negatively correlated asset classes (i.e., their return characteristics change in opposite directions) are desired. Domestic equities, international equities, fixed income, gold, and liquid funds have all been included in the selection for our portfolios.
- The risk profile and investment horizon matrix were used to create efficient portfolios that fit all of the profiles and investment horizons. The benchmark indices were substituted by a selection of passive funds that represented those indices after the portfolios were built.
- The selection of passive funds was done with care, with a lower expense ratio taking precedence, followed by a smaller tracking error, and finally AUM size, with a higher AUM receiving preference. For example, in a portfolio, the Nifty Midcap 150 index will be substituted by a Nifty Midcap 150 Index fund that meets all of the criteria.
- As an investor when you approach glide with a goal in mind, an appropriate efficient portfolio is then provided taking your investment horizon, goal size and risk profile in consideration. We do this automatically and without any effort on your part. All you need to do is make one single payment and the rest is managed on our end making for an efficient execution towards an efficient portfolio.
Here is an example of an aggressive long-term portfolio and its historical performance
|Stats||Nifty 50 TR Index||Nifty 500 TR Index||^S&P 500 TR Index||Glide Aggressive Long Term Portfolio|
|15 year CAGR Returns (%)||12.7%||12.9%||14.3%||16.9%|
Not only has the portfolio done better than the individual equity asset class but it has done so with significantly lower risk than the equity indices.
The ultimate solution for all investor needs is a goal-based efficient asset allocation strategy. It minimises volatility and diversifies risk, especially during times of crisis. During a crisis, investors are frightened by the apparent loss of wealth and the instability of their returns.
An effective asset allocation portfolio keeps volatility low, allowing risk to stay within the individual investor's risk tolerance threshold, resulting in the investor staying in the market rather than bailing out.
At the same time, there are no tradeoffs in terms of returns, and an investor may expect their portfolio to provide returns on par with, if not greater than, comparable indices over time.