Anurag Bhatia’s Investment Strategies: From Algorithms to Long-Term Leverage

Investing is a vast and complex field, and Anurag Bhatia, a seasoned professional in the financial markets, has honed his approach to cover a wide spectrum of strategies, from high-frequency trading (HFT) to long-term investments. In this article, we will explore his unique methods for generating returns and the underlying data that supports his decisions.

Quant Automated High-Frequency Trading (HFT): Market Making and Scalping

One of Anurag Bhatia’s strategies in the realm of HFT involves market-making or scalping algorithms. These algorithms are designed to exploit short-term price discrepancies in the market, a process often referred to as arbitrage.

The Hammer algorithm, named with a snarky twist, is an example of such a strategy. This algorithm continuously monitors the historical correlation between a stock and its futures contract at a 250-millisecond level, including the lag between the two. When this correlation deviates from its historical pattern, the algorithm uses an ARMA model to determine whether to take a long or short position.

For instance, take the historical correlation between ACC's stock and its mid-month futures at 0.98283. This means that for every 10000 times that ACC's stock rises by a few points, the mid-month futures will rise 98283 times within a quarter-second unit of time. When the current correlation surpasses this historical level, and the time lag is more than 400 milliseconds, the algorithm will buy futures contracts.

ARMA Model: Autoregressive Moving-Average Model

The ARMA model, a statistical time series model, plays a crucial role in forecasting future values based on past values, both past observations (AR) and past forecast errors (MA). In Bhatia's Hammer algorithm, it helps in predicting the future correlation and making informed trading decisions.

Quant Automated Non-High-Frequency Trading (Non-HFT): Option Selling Strategy

Another of Bhatia’s strategies is non-HFT, involving long-term investments that can sustain hefty returns. Take for instance the STD Steep Theta Decay strategy, named after the rate of change in the value of an option over time, known as Theta. This strategy involves selling deep out-of-the-money options several days prior to expiry.

According to Bhatia, this strategy has a positive carry probability of 92%, ensuring excellent returns if held till expiry. Despite picking up only a few paise to a maximum of a buck per stock per lot, the overall profitability is substantial because of the low standard deviation and the low risk of drawdown.

Transaction Costs and Alpha Members

To minimize transaction costs, traders often use alpha members. These are highly experienced and skilled traders who can execute trades faster and more efficiently, thus reducing the overall cost of the strategy.

Data-Driven Macro Manual: Correlating Real Estate and Stock Markets

Bhatia has also employed a macro-driven, data-backed approach to financial trading. By collecting commercial housing data from builders and online real estate portals, he observed a trend where the number of new office space listings were at a 10-month low. This indicated an increase in net office rentals, prompting further investigation.

Diving deeper, Bhatia correlated this data with air-conditioning revenues, as firms typically install air conditioning when they acquire new offices. He found a strong positive correlation between the two, leading him to purchase Voltas stocks and futures. The chart below highlights Voltas' stock performance over the last nine months, with a particularly strong performance in the last two months.

The performance of Voltas stocks over the last nine months, with the last two months of data highlighted.

Long-Term Leveraged Economic Investments: Structured Products

One of Bhatia's most intriguing strategies is long-term leveraged investments, often structured as structured products. This method requires a deeper understanding of the market, a keen eye on economic prospects, and a hint of luck. For example, Bhatia and his associates established a private limited firm, capitalizing it with funds and selling convertible debentures to an institutional investor.

The money from these debentures was then used to go long on NIFTY futures at a strike price of around 7300. The goal was to achieve a milestone NIFTY value of 10000 in the next five years, with the investment leveraged at around 3x. While this strategy involves significant risk, it also has the potential for substantial returns.

The Role of Leverage in Structured Investments

Leverage, though risky, can significantly amplify returns. In structured products, the strategic use of leverage can translate a modest increase in the underlying asset into a more significant gain, as seen in Bhatia's anticipation of NIFTY hitting 10000.

Conclusion

With a diverse array of strategies, Anurag Bhatia exemplifies the complexity and creativity required in the financial markets. From algorithmic trading to macroeconomic insights and leveraged long-term investments, Bhatia’s approach emphasizes the importance of data and strategic planning. His strategies not only illustrate the power of technical and quantitative analysis but also the significance of macroeconomic factors in shaping investment decisions.

Keywords: investment strategies, market making, long-term investments