Market Matters | Data Assets & Alpha Group: What JP Morgan Trading Data Assets Currently Say Abou...

Summary

In this episode of *Market Matters*, Eloise Goulder, head of JP Morgan's Data Assets and Alpha Group, shares insights on market trends, data intelligence, and investment strategies. The discussion focuses on the group's use of proprietary data sets, such as positioning intelligence, to offer data-driven insights to clients. Eloise emphasizes avoiding behavioral biases in investment decisions while leveraging them in models. Current market conditions are analyzed using the *Signal from the Noise* framework, which suggests a supportive outlook for U.S. markets driven by positioning signals. Retail investor behavior and long-term market data trends are also explored, offering valuable insights for institutional investors.

Takeaways

• 😀 The Data Assets and Alpha Group at JP Morgan provides tactical, data-driven insights to clients, primarily risk managers in hedge funds and asset management, based on proprietary data sets and positioning information.
• 😀 The group's focus is to avoid behavioral biases in decision-making by sticking to data-driven frameworks and signals rather than opinions or subjective views.
• 😀 Eloise Goulder, head of the Data Assets and Alpha Group, emphasized the importance of avoiding biases such as mental accounting, status quo bias, and loss aversion in investment decisions.
• 😀 The group applies a 'Signal from the Noise' framework, which combines both fundamental signals (like ISM data and earnings revisions) and positioning signals (market volatility and positioning metrics) to guide market outlook.
• 😀 As of now, the 'Signal from the Noise' framework is relatively supportive of US markets, primarily driven by positive positioning signals rather than fundamentals, which are currently neutral due to deteriorating macro data.
• 😀 Retail investor behavior is tracked through two data sources: retail flows (at the stock, sector, and market levels) and retail sentiment (derived from social media commentary), helping to understand retail market sentiment and movements.
• 😀 Despite a decline in US retail volumes in 2022, retail investors have rotated into commodity sectors like energy, and have shown conviction by buying on dips in certain sectors such as large-cap tech, cyclicals, and consumer discretionary.
• 😀 The group's long-term Strategic Index Fundamental Toolkit (SIFT), which includes data going back to the 1960s, has proven valuable in navigating high inflation periods by comparing current conditions to the 1970s.
• 😀 In comparison to the 1970s, energy has been one of the best-performing sectors, and the SIFT toolkit is useful for providing historical context for the current market environment, particularly in relation to inflation and sector performance.
• 😀 JP Morgan's strategists remain positive for the year-end, with a 20% upside forecast for the S&P 500, particularly bullish on energy markets, and these insights are in line with current data trends and positioning signals.

Q & A

What is the primary goal of the Data Assets and Alpha group at JP Morgan?

The primary goal of the Data Assets and Alpha group is to provide clients, typically risk managers at hedge funds and asset managers, with tactical insights on market direction and conditions based on JP Morgan's proprietary data sets. These insights are often delivered daily and are data-driven rather than opinion-based.

How does the Data Assets and Alpha group avoid biases in its analysis?

The group avoids biases by focusing on data-driven signals and frameworks rather than human opinions. They acknowledge that biases exist but strive to minimize them in investment decisions and analyst models by relying on objective, consistent data inputs like earnings revisions and positioning signals.

What is the 'Signal from the Noise' framework, and how does it relate to US markets?

The 'Signal from the Noise' framework is a tool used to evaluate market conditions based on two main components: fundamental signals and positioning signals. The framework has recently shown that the US market is in a relatively supportive position, driven more by positive positioning signals than improving fundamental data.

How does the retail investor data set help in understanding market behavior?

The retail investor data set tracks US retail investor flows and sentiment across different sectors and stocks. This data provides insights into shifts in retail investor behavior, such as rotations from tech to commodities, as well as the impact of retail sentiment on overall market trends.

What have been some key trends in retail investor behavior in 2022?

In 2022, retail investor activity has waned, with many retail investors sitting on losses. However, the data still revealed important shifts, such as a rotation into commodities like energy and a resurgence in buying large-cap tech and cyclical sectors in recent months.

What is the Strategic Index Fundamental Toolkit (SIFT), and how has it been used during periods of high inflation?

The Strategic Index Fundamental Toolkit (SIFT) is a long-term data set that tracks market performance from as far back as the 1960s. During periods of high inflation, such as the 2020s, SIFT has been useful for comparing the current environment with the 1970s, highlighting trends like strong performance in the energy sector and the value factor during similar inflationary periods.

How does the SIFT toolkit compare the current inflationary period with the 1970s?

The SIFT toolkit shows that in the 1970s, energy was the best-performing sector, with a near-tripling of performance over the decade. In comparison, energy in the current period has gained only 55%. Additionally, the value factor performed well in the 1970s, more than doubling, while it has performed more modestly now.

What role does the retail investor play in the tactical positioning monitor?

Retail investor flows are an important input to the tactical positioning monitor, which tracks the positioning and flows across different investor types. This monitor helps capture shifts in market sentiment, with the retail investor's behavior influencing broader market trends.

What does the term 'Signal from the Noise' refer to in terms of market analysis?

'Signal from the Noise' refers to the process of extracting meaningful market insights from the noise of constant fluctuations. The framework identifies key signals such as market fundamentals and investor positioning to assess whether markets are likely to go up or down, providing actionable insights for clients.

What are some of the challenges in providing data-driven market insights?

One of the challenges is managing human biases, which are inevitable in decision-making. While biases like mental accounting or loss aversion can distort decision-making, the Data Assets and Alpha group focuses on reducing these biases by sticking to rigorous, data-driven frameworks and signals.