Index Arbitrage

Index arbitrage is at the heart of machine-based trading, where computers monitor millisecond-changes and identify mispricing between the present value of the Index future and the sum of the present values of all the individual components of the index.

  • Expected Return: Fixed deposit ++
Quant Investing

Statistical arbitrage

It is a group of trading strategies employing large, diverse portfolios that are traded on a very short-term basis. This type of trading strategy assigns stocks a desirability ranking and then constructs a portfolio that has minimized risk. Statistical arbitrage relies heavily on computational expertise and offers a rigorous market analysis.

  • Expected Return: Uncorrelated returns vis-à-vis equity markets.

Directional strategies

Trading model allows you to outperform benchmark equity index while maintaining low volatility through a quantitative strategy. The strategy takes data from the market as input and identifies investible businesses from S&P BSE 500 universe using a combination of statistical models based on which the position is built in the top ranked stocks.

  • Expected Return: Index return ++
Quant Investing

Hybrid Models

Systematically generate capital appreciation by investing in a portfolio of equity or equity-linked securities while the secondary objective is to generate income through investments in debt and money market instruments, managing risk through active asset allocation.

  • Expected Return: Uncorrelated returns vis-à-vis equity markets.
Quant Investing
Summary I-Alpha Long-Short Alpha Long Alpha Allocation Alpha EIF
Nature Market-neutral, pure arbitrage Market Neutral Long – Short Long Only Hybrid (Equity + Debt Like allocation) Fully hedged arbitrage strategies
Instruments Equity future & options contract Equity future & options contract S&P BSE 500 Equities S&P BSE 500& Equity future & options contract Equity F&O, Currencies, Commodities
Liquidity Notice by 15th of month for end of month exit 1 Month T+ 5 days Notice by 15th of month for end of month exit Monthly subscription and redemption cycle
Expected Return (Net of fees & expenses) FD Rate+ 2.5% 30% p.a Nifty 50 + 5% Crisil Hybrid Conservative Index + 4% 7% annualized dollar net returns
Max Drawdown 0% 8% 20% 5% 0%

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Broad-based market factors tend to drive excess returns. The rest is driven by stock selection. We try to extract value from both.

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Quant funds can also make faster investment decisions than human managers. So they can place orders more quickly and exploit gains from narrow price differentials more effectively. They can be much more effective in implementing trading strategies than human managers due to their neutral bias and negated risk of fat-finger errors.

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