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Quarter	Letter Date	Fund Name	QTD	YTD	Tickers	Themes	Quick Take

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Spear Advisors 2023 Q2 Investor Letter | Buyside Digest

Back to Fund Profile (Spear Advisors)

Primary Source Intelligence • Q2 2023 Letter Analysis

Spear Advisors Quarterly Analysis

Buyside Digest is not affiliated with, and does not endorse, Spear Advisors. This analysis is provided for institutional research purposes only and is not investment advice.

Fund Returns

QTD+22.3%

YTD+53.5%

Positioning StanceConstructive

GeographyUS

Digest Analysis

Quick Take

"Cloud infrastructure, and cybersecurity. Strong performance driven by Nvidia, AMD, and enterprise software recovery."

Executive Summary

Spear Alpha ETF delivered exceptional performance in Q2 2023 with a 22.3% return versus 8.7% for the S&P 500, driven by their focus on AI hardware and software infrastructure across the value chain. The fund's core thesis centers on artificial intelligence as a transformative technology wave, investing in semiconductors, cloud infrastructure, and cybersecurity rather than just AI applications. Portfolio composition includes 24.8% in cloud/data infrastructure, 24.1% in cybersecurity, and 17.5% in AI hardware, with major holdings including Nvidia, AMD, Snowflake, and Zscaler. Strong performance was driven by semiconductor recovery led by Nvidia, AMD, and Marvell, while enterprise software companies like Shopify and HubSpot continued outperforming. The manager believes they are in early innings of the next tech cycle, with cloud service providers ramping AI capex investments exceeding $100 billion. Key risks include potential inflation resurgence and higher-for-longer interest rates limiting recovery pace. Despite recent outperformance, most holdings remain 50-80% below peak levels, suggesting significant runway ahead.

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Institutional Meta Strategy

Meta Strategy Gauges

Algorithmic conviction, macroeconomic posture, and risk appetite signals extracted from this quarterly letter with qualitative explanations.

Signal Matrix

Market Conviction

72%

CautiousHigh

High Conviction (72%)

The fund demonstrates high conviction through concentrated positioning with named, sized holdings across three main themes (24.8% cloud infrastructure, 24.1% cybersecurity, 17.5% AI hardware). Manager explicitly states maintaining large exposure to semiconductors and provides specific rationale for position sizing decisions like increasing SentinelOne and initiating Confluent. Clear thesis articulation with specific catalyst identification supports high conviction, though some hedging language prevents maximum score.

Growth Outlook

75%

BearishBullish

Bullish (75%)

The manager expresses strong optimism about being on the cusp of the next AI-driven technology wave creating outsized investment opportunities. They believe they are in early innings of the next tech cycle and see AI playing a critical role in addressing productivity and inflation. While acknowledging recession expectations, they believe most end markets already went through recession-like downturns and are on a path to recovery.

Risk Appetite

60%

DefensiveAggressive

Balanced (60%)

The fund maintains large exposure to semiconductors believing they are early in the recovery cycle and is exploring additional investments across the data center value chain. They actively manage risk but generally do not decrease risk during market pullbacks, instead managing through increased idea velocity and asset turnover. Portfolio remains concentrated in growth areas despite acknowledging economic uncertainty.

Capital Deployment

25%

De-riskingDeploying

De-risking (25%)

The fund shows moderate deployment activity by sizing up positions in SentinelOne and initiating a new position in Confluent during the quarter. However, this appears to be funded by capturing alpha from outperformers and redeploying to underperformers rather than deploying new cash. No specific cash level changes are mentioned, suggesting this is primarily rotation rather than net deployment.

Forward Guidance

50%

CautiousExpansionary

Neutral (50%)

The manager shows selective deployment bias, sizing up positions in underperforming areas like SentinelOne and initiating new positions like Confluent. They are exploring other investments across the data center value chain while maintaining conviction in existing holdings. The approach is measured rather than aggressive, redeploying alpha from outperformers to underperformers.

Language Signal

65%

BearishBullish

Bullish (65%)

Language is predominantly bullish with terms like 'strong performance,' 'outsized investment opportunities,' 'early innings,' and 'significant runway ahead.' The manager discusses 'recovery,' 'broadening,' and 'strong demand' while acknowledging risks. Bullish language outweighs cautionary language, though risks are meaningfully discussed.

Perceived Risk

45%

Low RiskElevated

Moderate Risk (45%)

The manager acknowledges moderate risks including potential inflation resurgence, higher-for-longer interest rates limiting recovery pace, and lingering economic uncertainty. However, these risks are discussed in context rather than as central concerns. The manager believes most end markets already experienced recession-like downturns, suggesting risks are manageable rather than systemic.

Opportunity Density

75%

ScarceAbundant

Abundant (75%)

The manager sees abundant opportunities across the AI value chain, describing being on the cusp of the next AI-driven technology wave creating many outsized investment opportunities. They are exploring other investments across the data center value chain and note that despite recent outperformance, most holdings remain 50-80% below peaks, highlighting significant runway ahead.

Time Horizon

65%

Short-TermLong-Term

Multi-Year (65%)

The fund demonstrates a multi-year investment horizon, describing being in the early innings of the next tech cycle and believing they are early in the semiconductor recovery cycle. The manager focuses on structural themes like AI's role in addressing productivity and inflation, suggesting a 2-3 year outlook rather than near-term catalyst dependency.