Summary
Highlights
Joey 'Jungle Funk' introduces himself and explains that this is the fourth and final part of a webinar series. He briefly recaps the previous three webinars: multiple time frame analysis, identifying most likely scenarios (using Fibonacci retracements), and entry techniques (patterns like bottom fish, falling wedge, inverse head and shoulders, stair step, and simple trend change).
Market correlations refer to names trading in similar fashions. These correlations are primarily driven by algorithmic trading (estimated 60-75% of market volume) and trader sentiment. Correlations can exist between seemingly unrelated assets (e.g., Bitcoin and S&P 500) and can even be influenced by single company earnings impacting the broader market. Correlations can be direct (moving in the same direction) or inverse (moving in opposite directions), and can range from tight, tick-for-tick correlations to looser, general sentiment-based correlations. Identifying them involves observing peaks and troughs in charts.
Correlations are commonly seen between individual stocks and their corresponding ETFs (e.g., Bank of America and XLF), individual names and the S&P 500, sector ETFs and the S&P 500, and even between high-risk assets (e.g., growth names and small caps like IWM, Bitcoin and QQQ/SPY, or altcoins and Bitcoin).
Signs of a bullish correlation include one name holding support while another makes lower lows, one name breaking resistance while another lags, shallow retracements versus deep retracements, and strong bounces versus weak bounces. Bearish correlations are the opposite: one name making lower lows while another holds support, one failing to break resistance while another has, deep retracements when another has shallow, and weak bounces when another has strong ones. These are evaluated by comparing technical analysis metrics between two or more correlated assets.
The simplest approach is to play strong names bullish and weak names bearish, increasing success odds due to market tailwinds. A higher-risk, higher-reward approach involves playing strong names bearish and weak names bullish, anticipating a shift. Shifts in relative strength/weakness often occur at key levels (e.g., double bottoms/tops, resistance rejections). Ratio charts can also help pinpoint these shifts.
Ratio charts plot the quotient of two names (e.g., QQQ divided by SPY). An upward-trending ratio chart indicates relative strength in the numerator, while a downward trend indicates strength in the denominator. A key insight is that standard technical analysis (trends, support/resistance, EMA riders) applies directly to ratio charts. It's crucial to distinguish if relative strength means going up more or going down less, and vice versa for relative weakness. Optimal trades often align with the main correlating ticker's most likely scenario.
A bullish ratio divergence occurs when the ratio chart holds a higher low while the underlying asset makes a lower low. A bearish divergence is when the ratio chart holds a lower high while the underlying makes a higher high. These divergences can indicate an upcoming shift in relative strength/weakness. Stair steps are effective entry techniques for playing divergences, especially when seeking reversals after support breaks. Relying on an individual ticker's setup for risk management is crucial, even when guided by ratio charts.
The speaker covers several advanced applications: lowering probabilities on directional patterns if strong opposing relative strength/weakness exists (e.g., a rising wedge that might break bullish if peers are weaker), identifying low-risk bottom fishing opportunities when a correlating name makes lower lows but your name holds support, and using correlations to determine whether the market is in a rotational or unified trending environment. Tracking historical rotation within market cycles can also provide macro probabilities (e.g., 'dash to trash' where weaker names pump last before a cycle top).
Four categories are discussed: confirmed bull (clear relative strength, leading the pack), anticipatory bear (a confirmed bull that could shift to weakness), confirmed bear (clear relative weakness), and anticipatory bull (a confirmed bear that could reverse). Lead bulls can become lead bears, but lead bears don't always become lead bulls (death/bankruptcy). Larger time frame most likely scenarios on ratio charts help determine anticipatory plays.
This strategy is used with a group of correlated names, typically futures (ES, NQ, RTY, YM). If three out of four names break to lower lows (bearish example), the 'last man standing' (the one holding support) offers a low-risk bottom fish opportunity, especially if the weaker names are extended and 'due' for a bounce. This play provides clear relative strength and an easier entry point compared to trying to bottom-fish names that have already broken support. Visualizing these relationships on a multi-chart layout is essential.
Examples are shown comparing ES and NQ futures, highlighting NQ's relative strength by clearing resistance or holding higher lows even when ES made lower lows. A Link/Bitcoin example illustrates a simple bullish correlation where Link held support while Bitcoin made lower lows, positioning Link for a strong bounce. Multiple 'Last Man Standing' examples from Oct 2022 and recent daily charts of ES, NQ, RTY, and YM demonstrate identifying the strongest asset for a low-risk long when others are oversold and making new lows.
The speaker demonstrates how correlations can shift (e.g., from bullish to bearish) often driven by key support or resistance holds, using AI as an example. Ratio charts like RTY/SPY and NQ/ES show how holding support or riding EMAs can indicate sustained relative strength or weakness. Patterns on ratio charts (e.g., monthly equilibrium on APE/BTC or UR/SPY) can provide significant directional clues, with breakouts leading to substantial follow-through. A Tesla vs. QQQ example on an intraday timeframe highlights clear relative weakness in Tesla at market open.
An example combines a 12-hour rising wedge on Tesla's 'IO' chart (ratio) with a head and shoulders pattern on the regular chart for an aggressive short entry. Another example with NVDA/QQQ ratio shows a tightening range (2-day equilibrium) on the ratio chart, indicating potential for major shifts in NVDA's relative performance. This pattern, combined with price action, informed a short position on NVDA. The speaker emphasizes how ratio charts provide context for most likely scenarios, preventing 'bamboozling' by short-term strength or weakness.
The speaker recounts a mentor session scouting crypto pairs (LTC, APE, SAND, SUSHI, MANA) based on their BTC-pair ratio charts, categorizing them as confirmed bull, anticipatory bear, confirmed bear, or anticipatory bull, even when Bitcoin itself was in a tight range. Examples of APE/BTC, LTC/BTC, SUSHI/BTC, and MANA/BTC show how these ratio-based forecasts led to significant percentage gains or losses in their USD pairings, demonstrating the power of ratios for directional plays irrespective of the main asset's volatility.
The example of SOL/BTC illustrates a high-risk, high-reward play by nailing a long entry based on a quarterly higher low on the ratio, leading to a 240% gain. Subsequent plays on SOL/BTC also demonstrate entry points at support holds. The overall crypto market rotation is discussed: early strength in Bitcoin, then rotation into alts whose BTC pairings were already off their lows (e.g., SOL, LINK, AVAX), with 'junkers' following later. Ratio watchlists help identify these rotational leaders.
Joey addresses questions about using ETH ratios (less common, BTC ratios generally preferred), spotting higher lows (using multiple time frame analysis, retracement sizes, and entry techniques like inverse head and shoulders or falling wedges), and how to manage risk/position sizing for lower time frame stair steps. The importance of familiarity with frequently traded instruments and quick mental math for risk management (e.g., calculating shares based on a fixed dollar risk) is emphasized.