ViniyogIndia 🧩 Multifactor Portfolio is based on a Multifactor Regime Switching Strategy where Factor exposure is controlled based on Market Regime forecasts. This portfolio is suitable for Aggressive to Moderately Aggressive investors.
ViniyogIndia offers model portfolios based on Quantitative Factor Investing. Factors are quantitative attributes used to explain asset returns.
Factor strategies have been extensively researched globally as well as in India. The below chart for example, summarizes the risk-return characteristics of single-factor portfolios in India between October 2005 and June 2017.
Over the period, all major single-factor portfolios outperformed the S&P LargeMidCap. However, only Low Volatility, Quality & Momentum delivered better risk-adjusted returns (returns per unit of risk) than S&P BSE LargeMidCap.
ViniyogIndia’s factor portfolios use a combination of factors that are proven to work well in the Indian markets.
Macroeconomic and market events affected each factor in different ways. Below chart summarizes performance characteristics of factors in different macroeconomic regimes, including market cycles, business cycles, and investor sentiment regimes in India
Source: S&P Dow Jones Indices LLC. Data from October 2005 to June 2017. Index performance based on total return in INR. Past performance is no guarantee of future results. Table is provided for illustrative purposes. Note: Yellow, upward triangles represent favorable performance (positive excess return with outperformance probability not lower than 50%), while blue, downward triangles represent unfavorable performance (negative excess return with outperformance probability not higher than 50%) versus the S&P BSE LargeMidCap. The two factors with the highest information ratio in each of the market cycle phases are circled.
ViniyogIndia 🧩 Multifactor Portfolio is based on a Multifactor Regime Switching Strategy where Factor exposure is controlled based on Market Regimes.
Market states/regimes are modelled using a combination of proprietary + macro indicators. This is combined with past performance to dynamically control factor exposures over market regimes.
Risk exposure to the overall portfolio is reduced by:
Allocation to Equities is based on a proprietary mathematical function that uses market parameter(s) as the independent variable(s). Excess funds are allocated to Liquid & Gold ETFs.
This portfolio is suitable for conservative to moderately aggressive investors
To estimate alpha and interpret the sources of return for our strategy we perform a regression analysis using Carhart 4 Factor Model. The results are shown in the table below:
| α * | MKT | SMB | HML | WML | |
|---|---|---|---|---|---|
| Factor exposure | 0.86 | 0.49 | 0.07 | 0.04 | 0.31 |
| p-value | 0.00 | ~0.0 | 0.22 | 0.41 | ~0.0 |
The monthly alpha or excess return for the strategy is 0.86%. This is generated using a combination of factors and asset allocation rules that tries enhance portfolio returns while reducing risks.
Additionally, returns from standard factors such as market beta and momentum contribute to the overall portfolio returns. Return from size and value factors are not statistically significant.
Fixed Fee:
Rs. 5499 3999/ 6 months
Asset Based:
1.8% yearly. Offered as smallcases.
Credits
Image by storyset on Freepik
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