Investing in Direct Equity democratized
Qovar Advisors Private limited
SEBI registered Investment Advisor (Non-individual)
Registration number: INA200011365
Validity of registration: Aug 06, 2018 - Perpetual
Number of complaints (last updated on October 1st, 2020)
|At the beginning of the month||Received during the month||Resolved during the month||Pending at the end of the month||Reasons for pendancy|
Who we are
A SEBI registered Investment Advisor providing Portfolio Advisory services in Direct Equity.
A solution that encompasses a fundamental methodology for stock selection and a quantitative approach to asset allocation. Click here to view the performance summary of our model portfolios.
- ‘Holistic Portfolio’ view and not ‘incremental stocks’ –
Though several recommendations from industry experts are available through different channels, it is a herculean task for an individual investor to choose the right stocks and have the ‘optimal mix’ of stocks in their portfolio. At Qovar, individual’s risk taking ability, investment horizon and the return expectations are key factors to the portfolio recommendation process. Our tailored ‘Holistic portfolio’ construction approach is superior to the typical incremental stock recommendations.
- Deliver Absolute Returns through Active Management; Not ‘Index huggers’ – Changing market conditions demand an ‘Active Management’ approach to wealth creation. We believe that an in-depth analysis of a company, its products, industry, competitors, and macro-economic factors, can identify market inefficiencies to deliver attractive returns for investors.
Technology has changed how things work across different industries and in some cases, re-defined the Product landscape and Service offerings in some of these industries. As an organization, we believe that technology-driven financial advice will enable us to be consistent with our performance, unbiased with our decisions, and will allow us to expand the scope of our offerings over a period of time. For our Investors, we believe this will result in superior and reliable outcomes.
Eswar Suryanarayan is proficient in portfolio management, performance measurement & attribution techniques, and has a breadth of knowledge in quantitative methods. In a career spanning 20 years, he has played different roles including systems analysis, design and software development in the Asset Management industry. Eswar is a Mechanical Engineer from the University of Mysore, a Post Graduate from IIIT-B and holds an Advanced Financial Risk Management certification from IIM-B. He is a long distance runner and has a passion for instrumental music.
Pradeep Kumar is a seasoned marketing executive, leader and strategist. In a career that spans over 25 years, he has worked across business functions such as sales, marketing, business operations and analytics. Pradeep has worked across different industry verticals like Asset Management, Healthcare, Commercial Finance and Technology and has donned multiple hats. Being a passionate marketer he has spent significant amount of time in the Marketing Analytics space helping businesses in acquiring, developing and retaining customers. He has developed several frameworks in the marketing measurement space to assess the performance of traditional and digital marketing efforts. His personal interest revolves around multiple areas like entrepreneurship, farming, financial wealth management, teaching and outdoor sports. He is an Electronics Engineer from UVCE, Bangalore and is a Fellow of IIM-B.
Vijaya Sarathi’s career spans across Fixed Income and Equity markets. Over 13 years, his work experience ranges across securitisation structuring, Fixed Income portfolio analytics and Equity research.
We track Performance of 3 Model portfolios M1, M3 and M5 each constructed for different Risk profiles and the below tables depict the performance of these Model portfolios. Model Portfolio M1 is designed for a Conservative Investor, M3 for a Moderate risk taker and M5 for an Aggressive Investor. Please click here to understand the approach used for Portfolio construction.
|Total Return||2014||2015||2016||2017||2018||2019||2020||Ann. Stdev||Sharpe ratio|
- The Model Portfolio performance between 2014 – 16 are from backtests.
- Annualized Standard deviation and Sharpe ratio are calculated using a 3-year time period
- Chart updated on 10/01/2020
- Total and Trailing returns updated on 10/01/2020
1. Risk profiling
2. KYC compliance and Investment advisory agreement
3. Portfolio recommendation
4. Periodic portfolio re-balances
How it works
At a high level, the Portfolio construction process consists of the following 4 steps –
1. Investable Universe
The initial universe of stocks is selected based on the individual’s risk taking ability. It is then pruned by looking at several fundamental factors – ability to consistently generate free cash flows, good debt management practices, consistent earnings growth rates and Return on Equity to name a few.
2. Expected Return
The expected return of the portfolio which in this case is the weighted average of the expected returns of the individuals stocks is one of the key inputs to the overall portfolio construction process. The Quantitative model enables us to combine our views of the performance of companies and sectors with the market equilibrium expected returns in a manner that results in intuitive, diversified portfolios. The 3 building blocks in the computation of Expected Return is briefly described below –
- In the first step, the broader market portfolio is used to calculate the ‘Market Implied Expected Return’ of the Equity asset class using a ‘Reverse Optimization process’.
- The second step involves formulating a subjective yet quantitative ‘Forward looking Views’ for all stocks in the Investable universe. Among the many sources that we use in this ‘View’ formulation process – company reports, management commentary, analyst reports on companies & sectors, and macro-economic data are of significance.
- Blending the ‘Market Implied Expected Return’ with ‘Forward looking Views’ using a Bayesian approach results in mixed estimate of ‘Expected Return’ for all stocks in the investable universe.
3. Portfolio Construction
Mean-Variance optimization from the Modern Portfolio Theory is used to determine the appropriate stock mix in the portfolio. Estimates from the Variance-Covariance matrix from stock returns and the Expected Returns computed as described above are key inputs into the Optimizer. Additionally, stock, sector and other constraints are applied as appropriate.
4. Portfolio monitoring and Rebalance
Portfolios are constantly monitored for Performance and Risk and are rebalanced at regular intervals or when the portfolio characteristics drift from their intended values.