ViFinance Idea
The idea of creating our own index emerged during attempts to optimize index investing.
An evident fact: passive index investing is most suitable for the majority of retail investors, as it is the simplest and most effective approach, allowing them to achieve market-average returns. However, this approach is not without drawbacks.
Professor Hendrik Bessembinder from the University of Arizona, in his 2017 Research, examined the dynamics of 26,000 American stocks over 90 years and 61,000 global stocks over nearly 30 years. The key finding: almost all market gains come from 1.33% of companies. In other words, nearly 99% of stocks ultimately lose their value.
When an investor adds a broad market index ETF to their portfolio, they are buying all companies at once. Out of these, only 1% will be successful in the long term, while 99% will perform worse than the market.
The growth of an index (such as the S&P 500) is based on the market capitalization-weighted growth of the constituent companies' stocks and has averaged around 10% per year since the second half of the 20th century. It's important to understand that among all the companies in the index, there are those significantly outperforming the average growth rate (e.g., Adobe ADBE: +70.22% in 2017, +29.10% in 2018, +45.13% in 2019) as well as those lagging behind the average or even declining (e.g., The Kraft Heinz Company (KHC): -10.95% in 2017, -44.65% in 2018, -26.32% in 2019).
If we look at the annual dynamics of individual companies included in the index composition, we will see the following picture:
The idea of creating our own index emerged during attempts to optimize index investing.
An evident fact: passive index investing is most suitable for the majority of retail investors, as it is the simplest and most effective approach, allowing them to achieve market-average returns. However, this approach is not without drawbacks.
Professor Hendrik Bessembinder from the University of Arizona, in his 2017 Research, examined the dynamics of 26,000 American stocks over 90 years and 61,000 global stocks over nearly 30 years. The key finding: almost all market gains come from 1.33% of companies. In other words, nearly 99% of stocks ultimately lose their value.
When an investor adds a broad market index ETF to their portfolio, they are buying all companies at once. Out of these, only 1% will be successful in the long term, while 99% will perform worse than the market.
The growth of an index (such as the S&P 500) is based on the market capitalization-weighted growth of the constituent companies' stocks and has averaged around 10% per year since the second half of the 20th century. It's important to understand that among all the companies in the index, there are those significantly outperforming the average growth rate (e.g., Adobe ADBE: +70.22% in 2017, +29.10% in 2018, +45.13% in 2019) as well as those lagging behind the average or even declining (e.g., The Kraft Heinz Company (KHC): -10.95% in 2017, -44.65% in 2018, -26.32% in 2019).
If we look at the annual dynamics of individual companies included in the index composition, we will see the following picture:
Each point represents a company. Green points — companies outperforming the average market, red — underperforming.
Every year, there are companies whose stocks show returns of +20%, +30%, +100%, and even more, as well as a significant number of companies whose stocks experience declines of -30%, -50%, and so on. In other words, the range of return variations is ALWAYS quite wide, but in aggregate, it results in an 8-10% average annual market return. "The average temperature across the hospital patients, including morgue."
A hypothesis emerged: If companies with high-quality businesses (best fundamental indicators) are retained in the portfolio and companies with the worst indicators are excluded, the returns of such a new index, a "cleansed S&P500," might exceed the average returns of the original benchmark or reduce risk.
To test the hypothesis, the first version of the ViFinance US Stocks index was created in 2017.
Company Selection Method
The formation of the ViFinance Index involves a three-tiered exclusion process of potentially underperforming companies based on fundamental indicators and derived metrics calculated over the past 7-10 years. A total of 19 parameters are utilized.
As a result of meticulous annual analysis, companies with the best fundamental indicators, exhibiting the strongest dynamic performance, and having the greatest long-term prospects are selected. Next, the ViFinance Index is formed from these companies.
In 2022-2023, based on our company selection algorithm, we developed our own analytical software. Now, all financial analysis is conducted automatically, with manual verification of selection results in the final stage. This has significantly accelerated the process of annual and quarterly analysis, eliminated potential errors and the impact of human factors, as well as subjective judgment when making decisions about adding/removing companies from the ViFinance Index.
Rebalancing of the ViFinance Index's composition occurs once a year in April (after the annual reports of all companies in the original index are published). Minor changes to the ViFinance Index composition are possible on a quarterly basis (after companies publish their quarterly reports).
A hypothesis emerged: If companies with high-quality businesses (best fundamental indicators) are retained in the portfolio and companies with the worst indicators are excluded, the returns of such a new index, a "cleansed S&P500," might exceed the average returns of the original benchmark or reduce risk.
To test the hypothesis, the first version of the ViFinance US Stocks index was created in 2017.
Company Selection Method
The formation of the ViFinance Index involves a three-tiered exclusion process of potentially underperforming companies based on fundamental indicators and derived metrics calculated over the past 7-10 years. A total of 19 parameters are utilized.
As a result of meticulous annual analysis, companies with the best fundamental indicators, exhibiting the strongest dynamic performance, and having the greatest long-term prospects are selected. Next, the ViFinance Index is formed from these companies.
In 2022-2023, based on our company selection algorithm, we developed our own analytical software. Now, all financial analysis is conducted automatically, with manual verification of selection results in the final stage. This has significantly accelerated the process of annual and quarterly analysis, eliminated potential errors and the impact of human factors, as well as subjective judgment when making decisions about adding/removing companies from the ViFinance Index.
Rebalancing of the ViFinance Index's composition occurs once a year in April (after the annual reports of all companies in the original index are published). Minor changes to the ViFinance Index composition are possible on a quarterly basis (after companies publish their quarterly reports).
Advantages of ViFinance:
Portfolios constructed according to ViFinance indices combine the benefits of both Active and Passive approaches while minimizing the drawbacks of each.
Advantages of the Passive Approach:
Portfolios constructed according to ViFinance indices combine the benefits of both Active and Passive approaches while minimizing the drawbacks of each.
Advantages of the Passive Approach:
- Simple and understandable methodology for construction
- Requires minimal time and attention
- Minimal fees and tax expences
- Unlimited capacity for the strategy
- Potential risk at benchmark level
- Potential for higher returns than the benchmark
- Purchase of only quality assets
- Beneficial for the market (promotes fair asset valuation)
The Goal of the ViFinance is the optimization of index investing through the construction of improved indices that demonstrate returns higher than the market average while maintaining identical or even lower levels of risk.
This optimization allows investors to create efficient portfolios based on ViFinance indices, increase capital faster than the overall market due to positive alpha, and reach their financial goals more quickly.
This optimization allows investors to create efficient portfolios based on ViFinance indices, increase capital faster than the overall market due to positive alpha, and reach their financial goals more quickly.