Katie Stockton Started with Technicals in College

Episode Summary

Executive Summary: Barry Ritholtz interviews Katie Stockton, chief technical strategist at BTIG, about how technical analysis works in institutional investing. Stockton argues charts measure supply and demand through price, with trend, momentum, support/resistance, and select sentiment/internal indicators guiding risk-managed decisions. She emphasizes technicals as a complement to fundamentals, not a replacement, and highlights the growing legitimacy of the field, software, and AI.

Main Topics: Katie Stockton’s career path into technical analysis (Priority: 5/5): Stockton explains how an early interest in math and a finance major led her to technical analysis in college, followed by internships and roles at Dorsey Wright, Morgan Stanley, hedge fund trading, and BTIG. What technical analysis measures and why price matters most (Priority: 5/5): She frames technical analysis as a price-based study of supply and demand. Volume is now less reliable due to indexing, derivatives, and HFT, so her process relies primarily on price action and trend structure. Technicals as a complementary discipline for timing and risk management (Priority: 5/5): Stockton agrees with the idea that fundamentals tell you what to buy and technicals tell you when, but expands that charts also help with idea generation, entry/exit points, and selling discipline. Core indicators and what she avoids (Priority: 4/5): Her framework centers on trend-following, overbought/oversold signals, and relative strength, with MACD, stochastics, and DeMark tools among her favorites. She avoids Elliott wave and cycle analysis. Market internals, sentiment, and extremes (Priority: 4/5): She uses breadth, leadership, sentiment, and volume spikes mostly at extremes, arguing these are most useful when they confirm climaxes or exhaustion rather than as everyday signals. How macro conditions, passive flows, and asset-class trends shape charts (Priority: 4/5): Stockton discusses range-bound vs trending markets, the strong dollar/euro breakout, global equity relative strength, and how passive investing likely reinforces trendiness in major indices. Institutional use, professionalization, and the future of technical analysis (Priority: 4/5): She notes the field’s growing acceptance, the value of the CMT designation, and the increased use of quantitative tools, software, and AI in technical research.

Key Arguments: Technical analysis is fundamentally a study of price, because price is the cleanest market signal of supply and demand. Volume is less predictive today than in the past because modern markets are distorted by passive index flows, derivatives, and high-frequency trading. Technicals work best as a complementary discipline to fundamentals and macro, especially for timing, entries, exits, and risk management. No single indicator is sufficient; a consistent process combining trend, momentum, and overbought/oversold measures is more reliable. Trend following remains the core edge: long-term uptrends should be owned, while weakening momentum or exhaustion should trigger caution. Sentiment and market internals are most useful at extremes, especially to distinguish climactic lows or tops from ordinary noise. Passive investing likely contributes to a more trend-driven market and may help keep volatility measures like the VIX subdued. The legitimacy of technical analysis has increased due to better computing power, systematic testing, and the rise of quantitative methods. Her preferred tools include MACD, stochastics, DeMark indicators, support/resistance levels, and relative strength; she does not rely on Elliott wave or cycles. Charts help prevent emotional attachment to positions by forcing objective, price-based reassessment.

Data Points: Years in field: about 20 years - Stockton describes her experience level in technical analysis. Universities offering technical analysis coursework at the time: 12 universities - She says University of Richmond was one of roughly 12 schools offering the subject when she studied it. Technical Analysts Award year: 2017 - BTIG received recognition for institutional brokerage/equity research. Number of stock names reviewed in her process: 500 stocks - She says she periodically reviews a list of 500 stocks one by one. Volume decline period: since about 2007 - She says market volume has been declining for roughly a decade-plus. S&P 500 measured-move target after breakout: about 2,400 - Post-Brexit breakout projection she referenced for the S&P 500. Subsequent measured-move target: about 2,640 - A later S&P 500 breakout produced a new projected target. Dollar index decline: about 8%–10% year to date - She characterizes the dollar’s recent downtrend as persistent and significant. U.S. equities long-term performance: up something like 270% - She cites the U.S. versus global equity market outperformance over a decade. Europe long-term performance: up 11% - Used as a rough comparison with U.S. and emerging markets. Emerging markets long-term performance: essentially flat - She contrasts EM’s weaker relative performance with the U.S. Conference timing: October - She mentions attending an IFTA conference in October focused on AI and technical analysis. Short-term averaging example: 20-day moving average - Used as a trigger for reducing exposure in parabolic uptrends like Bitcoin.

Pivotal Quotes: "fundamentals tell you what to buy, technicals tell you when" — Ralph Acampora (quoted by Katie Stockton): Used to describe how technical analysis complements fundamental analysis by improving timing. "Technical analysis as really a complementary discipline" — Katie Stockton: She explains that charts should be used alongside fundamentals and macro, not as a standalone system. "the charts are designed to help us understand what's happening. They're not really designed to give you that story" — Katie Stockton: She contrasts objective price action with narrative-driven market explanations.

Implications: The interview shows technical analysis has matured into a more respected, systematic institutional tool. For listeners, the takeaway is to use charts for disciplined timing, risk control, and objective reassessment, especially as AI and quant methods expand the field.