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About Fund Manager

Sonam Srivastava

Sonam Srivastava, the driving force behind Wright Research, brings over 10 years of extensive experience in investment research and portfolio management to the firm. She began her career at Mumbai-based Forefront Capital, which was later acquired by Edelweiss, where she served as an algorithm designer at the institutional equity broking desk. Her journey continued at HSBC Europe as a quant, where she developed factor-driven portfolio solutions, and later at Qplum, managing portfolios for an artificial intelligence-driven robo-advisor. A graduate of IIT Kanpur with a master’s in financial engineering from Worldquant University, Sonam is a globally recognized researcher who also contributes her expertise as a visiting faculty member at the AI in Finance Institute in New York and BSE Institute Limited.

Investment Philosophy

 

Wright Research has built its reputation on a sophisticated and innovative investing philosophy that combines advanced quantitative strategies with a deep understanding of market dynamics. The company’s approach is designed to deliver optimized returns while managing risk, ensuring that clients can achieve their financial goals with confidence. Below is an overview of the core pillars that define Wright Research’s investment philosophy.

Factor Investing: Finding What Drives the Market

Wright Research employs factor investing to identify and capitalize on the key drivers of market performance. By analyzing factors such as value, growth, and volatility, the company constructs portfolios that are strategically positioned to outperform the market over the long term.

Momentum Investing: In Line with the Trends

The company leverages momentum investing to align its strategies with prevailing market trends. By identifying and investing in assets that exhibit strong upward momentum, Wright Research ensures that its portfolios remain dynamic and responsive to market movements.

Artificial Intelligence: Finding Complex Patterns

Wright Research harnesses the power of artificial intelligence to uncover complex patterns in financial data that are often invisible to traditional analysis. This AI-driven approach enables the company to make more accurate forecasts and optimize portfolio allocations for superior returns.

Risk Management: Stronger in Tough Times

Risk management is at the heart of Wright Research’s philosophy. The company employs robust strategies to protect client portfolios during challenging market conditions, ensuring resilience and stability even in turbulent times.

Tactical Investing: For Dynamic Markets of India

Recognizing the unique characteristics of India’s dynamic markets, Wright Research uses tactical investing to adapt its strategies to local conditions. This approach allows the company to seize opportunities and mitigate risks specific to the Indian financial landscape.

Hedging: Protect and Grow in the Downside

Wright Research incorporates hedging techniques to safeguard client investments against market downturns. By balancing growth-oriented strategies with protective measures, the company ensures that portfolios can thrive even in adverse conditions.

Investment Strategy

 

Data-Driven Investing

A large part of active investment alpha can be replicated using systematic investment strategies. Their approach is a top-down analysis of these factors to create high high-yielding, low-risk multi-strategy portfolio.

Factor Investing

Empirical research has shown that the equity market returns can be decomposed into a set of discrete uncorrelated factors. They look at more than 300 factors from 10 factor groups that include fundamentals, technicals as well as alternative datasets.

Long Term Focussed

Earnings Momentum, Price Momentum, Quality, and Size are some of the strongest factors in India.

Use Technology To Forecast Risk

Markets go through discreet persistent regimes and the behavior of the asset classes is very different in each regime We use machine learning-based predictive models for modeling regimes using macroeconomic data and technical signals.

Fund Overview

The Wright Factor Fund, offered by Wright Research, represents a sophisticated, data-driven quantitative multi-factor tactical strategy designed to deliver consistent returns over time. This fund is built on a foundation of multiple equity factors, including smart beta and alternative data, combined with advanced position sizing techniques and market regime modeling powered by machine learning models.

The Wright Factor Fund is engineered to generate stable, long-term returns while maintaining low correlation to the broader market. By leveraging a multi-factor approach, the fund identifies and capitalizes on key drivers of equity performance, ensuring a diversified and resilient portfolio. The integration of smart beta strategies and alternative data allows Wright Research to uncover unique opportunities that traditional investment methods might overlook. Additionally, the fund employs machine learning models to analyze market regimes and optimize position sizing, enhancing its ability to adapt to changing market conditions.

Wright Factor Fund is ideal for investors seeking a disciplined, quantitative investment strategy that prioritizes consistency and risk management. With its focus on low correlation to the market, the fund offers a unique opportunity to diversify portfolios while achieving steady, long-term growth. Backed by Wright Research’s expertise in quantitative investing, the Wright Factor Fund is a powerful tool for building wealth in an ever-evolving financial landscape.

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