---

Foundations and Purpose of Technical Analysis

1. Overview

Technical analysis is both a science and an art—a compelling field of study that allows practitioners to understand the fundamental dynamics of markets through visual tools. At its core, it involves reading patterns from historical price data using charts and indicators, then inferring the direction and timing of future price movements.

This chapter covers the core objectives of technical analysis, its dual function, the three approaches to price forecasting, and the differences between technical and fundamental analysis. As the chapter that establishes the philosophical foundation and basic assumptions essential before diving into technical analysis, it serves as the groundwork for every chapter that follows.

2. Core Rules and Principles

2.1 The Main Objective of Technical Analysis

Fundamental Human Survival Instincts

At the root of every trader's behavior in the market lie basic human instincts.

• The instinct to survive — the most powerful motivator
• The instinct for comfort — the pursuit of economic stability
• The instinct to propagate — the accumulation of wealth for future generations

The survival instinct is the strongest of the three, and it is the primary driving force behind the pursuit of profit in markets. It explains why traders behave irrationally in the face of losses and become impatient in the face of gains. Technical analysis is the discipline of systematically reading the repetitive price patterns created by these human instincts.

The Mechanical Rule of Profitability: Buy Low, Sell High

• Buy when the price is low and sell when the price is high
• The simplest yet most reliable mechanical rule for generating profit
• Executing this principle requires the ability to anticipate price direction in advance
• The ultimate reason for the existence of technical analysis is to provide this ability

💡 Practical Point: "Buy low, sell high" sounds simple, but determining whether the current price is actually "low" or "high" is the central challenge of technical analysis. A small number does not automatically mean a low price—you must assess the relative position within context.

The Two-Dimensional Action Requirement

Successful trading always requires simultaneous judgment across two dimensions.

• Price Dimension: Determining the precise entry/exit price level — "Where"
• Time Dimension: Capturing the optimal trade timing — "When"
• Price-Time Chart: Tracks both dimensions simultaneously on the vertical axis (price) × horizontal axis (time)

If you get the price dimension right but miss the time dimension, you enter too early and endure unnecessary drawdowns. If you get the time dimension right but miss the price dimension, you enter at an unfavorable price and your risk-reward ratio deteriorates.

2.2 The Dual Function of Technical Analysis

Technical analysis is not merely a tool for predicting the future. It performs two distinct functions—identification and forecasting—and identification must precede forecasting.

1) Identification Function

This function identifies and describes past and present price action. It provides a historical record of what actually happened in the market.

Specifically, it technically expresses the following information:

• Average volatility over specific periods (daily, weekly, monthly, etc.)
• Historical highs and lows (extreme values)
• The location and width of typical consolidation (range) zones
• Average duration and price displacement of trends
• Market liquidity and participation levels
• Average gap occurrence magnitude and frequency
• The magnitude and pattern of price impact from economic releases and events

💡 Cryptocurrency Market Characteristics: Compared to traditional markets, cryptocurrencies exhibit higher volatility, trade 24/7, and remain open on weekends. Therefore, when applying the identification function, you must account for different volatility patterns, gap frequency (relatively low), and time-of-day liquidity variations unique to crypto markets.

2) Forecasting Function

This function interprets identified price/market behavior to infer future price action. It is based on the assumption that price patterns repeat at a reasonable level.

• Builds probabilistic scenarios from data and patterns accumulated during the identification stage
• References how price reacted when specific conditions were met in the past to infer price direction under similar current conditions
• The goal is not 100% certain prediction but securing a probabilistic edge

⚠️ Caution: Using the forecasting function without the identification function is dangerous. Trading based solely on patterns without sufficiently understanding the current market structure means losing context.

2.3 Three Approaches to Price Forecasting

Methods for forecasting future prices in the market fall broadly into three categories. Each approach has unique strengths and limitations, and ideally they are used as complements to one another.

1) Fundamental Analysis

• Analyzes the intrinsic value of an asset through financial statements and accounting data
• Key ratios: P/E (Price-to-Earnings), PEG (Price/Earnings-to-Growth), Price-to-Book, Price-to-Sales, Debt-to-Equity, etc.
• Strength: Useful for deciding which asset to buy
• Weakness: Cannot provide precise entry/exit timing or price levels

In cryptocurrency, fundamental analysis differs from traditional equities. Instead of financial statements, on-chain data (active addresses, hash rate, TVL, tokenomics, development activity, etc.) serves as fundamental indicators.

2) Technical Analysis

• A method of analyzing market behavior through charts
• Forecasts future price action based on historical price data
• Strength: Provides precise entry/exit prices and timing
• Generates real-time buy/sell signals that serve as immediate grounds for action

3) Information Analysis

• Forecasts price using public and non-public information
• Includes the use of insider or proprietary information
• May constitute illegal insider trading in regulated markets
• Regulatory gray areas exist in cryptocurrency markets, though regulations are progressively tightening

Category	Fundamental Analysis	Technical Analysis	Information Analysis
Subject of Analysis	Financial / On-chain data	Price / Volume charts	Public & non-public information
Core Question	"What to buy?"	"When and where to buy/sell?"	"What do others not know?"
Timing Provided	✗	✓	Limited
Price Level Provided	✗	✓	✗
Legality Concerns	None	None	Potential risk

2.4 The Power of Technically Based Market Timing

The most critical advantage that distinguishes technical analysis from other analytical methods is its market timing capability.

Providing Precise Price/Time Information

• Provides precise entry/exit price levels
• Provides precise entry/exit timing
• Provides real-time bullish/bearish signals
• Provides real-time entry/exit price triggers

Trade Execution Using Technical Tools

• Scaled entries based on key price levels (support/resistance)
• Timing adjustments based on the underlying asset's volatility behavior
• Closing extended trends at technically significant price reversal levels
• Entry/exit timing based on market order flow
• Defining percentage risk and setting stop losses relative to key price levels

Measuring Strength and Direction Using Analytical Tools

• Measuring the strength of a move through volume and open interest analysis
• Assessing the sustainability of a move through market breadth and market sentiment
• Forecasting potential highs and lows through cycle and seasonality analysis

2.5 Core Assumptions

There are fundamental assumptions that must hold for technical analysis to be valid. Without understanding these assumptions, you cannot correctly interpret the results of technical analysis.

Assumption 1: Price Discounts Everything

• Market prices tend to lead known fundamental information
• All known information is already reflected in the price
• Price reflects the aggregate of:
  • All market participants' trading actions
  • Investment decisions and position building
  • Expectations about the future
  • Psychological states (fear, greed, etc.)
  • Biases and beliefs

The implication of this assumption is that a trader does not necessarily need to know the cause of a price movement. The price itself already contains the result of all causes. This is the basis for the technical analyst's claim that "the chart tells you everything."

Assumption 2: Prices Move in Trends

• Prices do not move randomly; they tend to move in a specific direction for a period of time
• Once a trend is established, it is more likely to continue than to reverse
• Identifying trends and trading in their direction is the core strategy of technical analysis

Assumption 3: History Tends to Repeat Itself

• Based on the assumption that market participants repeat the same mistakes as in the past
• Basic human behaviors, temperaments, and deeply rooted biases do not change easily
• Emotional responses to fear, greed, hope, anger, and regret repeatedly produce similar price patterns
• Thanks to this assumption, chart patterns discovered decades ago remain valid today

3. Chart Verification Methods

3.1 Verifying Buy Low, Sell High

There are four basic scenarios for realizing profit—two each for long positions and short positions.

#	Scenario	Entry	Exit	Profit Structure
1	Value Long	Buy at a low price	Close at a higher price	Price appreciation = Profit
2	Momentum Long	Buy at a relatively high price	Close at an even higher price	Additional upside = Profit
3	Value Short	Short sell at a high price	Cover at a lower price	Price decline = Profit
4	Momentum Short	Short sell at a relatively low price	Cover at an even lower price	Additional downside = Profit

💡 Practical Point: Scenarios 1 and 3 are classic counter-trend (reversal) trades, while Scenarios 2 and 4 are trend-following trades. Beginner traders benefit from starting with trend-following (Scenarios 2 and 4), as it is more favorable from a risk management perspective.

3.2 Price-Time Chart Analysis

OHLC Data Structure

The basic building block of every chart is OHLC data.

• O — Opening Price: The price at the start of the period
• H — High Price: The highest price reached during the period
• L — Low Price: The lowest price reached during the period
• C — Closing Price: The price at the end of the period

The closing price is considered the most important of the four. Most technical indicators are calculated based on the closing price, and the position of the close (near the high vs. near the low) provides a summary of the buying/selling pressure during that period.

Time Frames

• Applicable to all intervals: 1-minute, 5-minute, 15-minute, 1-hour, 4-hour, daily, weekly, monthly, and yearly
• Multi-timeframe analysis: Confirming the trend on a higher time frame and identifying entry timing on a lower time frame is extremely effective in practice
• Generally, daily and above time frames carry less noise and produce more reliable signals

3.3 Market Data Analysis Components

The data used in technical analysis follows a hierarchy of priority. Price is the most critical, and all other components serve to complement price analysis.

Priority	Analysis Component	Role
1 (Highest)	Price Action	Directly reveals the market's direction and structure
2	Volume Action	Confirms the strength and authenticity of price moves
3	Open Interest	Measures participation levels in futures/derivatives markets
4	Sentiment	Identifies bullish/bearish bias among market participants
5	Market Breadth	Measures overall market health via advancing/declining asset ratios
6	Flow of Funds	Assesses supply and demand through capital inflow/outflow direction

💡 Cryptocurrency Market Note: In crypto markets, instead of traditional open interest, funding rates, liquidation data, and exchange inflow/outflow volumes serve similar roles. Additionally, on-chain data (whale wallet movements, exchange reserve changes, etc.) is used for flow-of-funds analysis.

4. Common Mistakes and Pitfalls

4.1 The Certainty Fallacy

• Wrong approach: Believing that technical analysis guarantees certain outcomes
• Correct understanding: Technical analysis deals with probabilities and never provides absolute certainty
• Practical implication: Even the most perfect-looking signal can fail, so you must always set a stop loss and manage position sizing. What matters is not winning or losing individual trades but whether the expected value across many trades is positive.

4.2 The Misconception About Relying on Historical Data

• Criticism: "Predicting the future from past data has inherent limitations"
• Rebuttal: Every forecasting method (statistical, fundamental, behavioral) uses historical data
  • Regression analysis requires sampling of past data
  • Behavioral finance uses quantitative measurements of past behavior
  • Weather forecasting is based on historical weather pattern data
• Key point: The use of past data itself is not the problem—what matters is how rationally you assess the likelihood that past patterns will repeat

4.3 Confusing Fundamental and Technical Analysis

These two methods are not mutually exclusive but mutually complementary. However, the role and limitations of each must be clearly distinguished.

Category	Fundamental Analyst	Technical Analyst
Focus	Intrinsic value	Market behavior structure and dynamics
Pursuit	Understanding the root cause of potential market moves	Capturing the outcome of potential market moves
Core Question	"Is this asset worth investing in?"	"Is now the time to enter or exit?"
Strength	Deciding which asset to invest in	Determining precise trade timing and price levels
Limitation	Does not know when to start or finish	Cannot assess intrinsic value or over/undervaluation

💡 Optimal Combination: Screen promising assets with fundamental analysis (What), then determine the optimal entry timing and price with technical analysis (When & Where). This approach leverages the strengths of both methods.

4.4 The Danger of Relying on a Single Indicator

• Making trading decisions based on a single technical indicator or pattern is risky
• Confluence principle: Signal reliability increases when different types of indicators point in the same direction
• Example: When a price pattern (Head and Shoulders) + declining volume + RSI divergence appear simultaneously, the probability of a reversal increases significantly

5. Practical Application Tips

5.1 Precise Understanding of Trading Terminology

It is essential to accurately distinguish trading terms that are easily confused.

Term	Definition	Position Change
Go Long	Open a new buy position	Flat → Long
Liquidate	Sell to close an existing long position	Long → Flat
Go Short	Open a new short-sell position	Flat → Short
Cover	Buy to close an existing short position	Short → Flat

⚠️ Caution: "Buying" and "going long" are not the same. Buying to cover a short position is not a new long position. Likewise, "selling" and "going short" must be distinguished. Selling to liquidate a long position is not a new short position.

5.2 Leveraging Both the Art and Science of Technical Analysis

To use technical analysis effectively, you must develop both its artistic and scientific dimensions.

The Artistic Dimension (Art)

• Identifying trend reversals at a relatively early stage
• Developing the patience to ride and hold a trend
• Improving visual pattern recognition ability
• Building experiential intuition accumulated through repeated observation of diverse charts

The Scientific Dimension (Science)

• Systematic approach based on probabilities
• Utilizing quantitative analytical tools (moving averages, RSI, MACD, etc.)
• Minimizing emotional judgment through the application of objective rules and conditions
• Backtesting to validate strategies

💡 At the beginner stage, focus on the scientific dimension (clear rules and systems). As experience accumulates, gradually integrate the artistic dimension (intuitive judgment).

5.3 Understanding the Classification Framework

Technical analysis is broadly divided into four categories, each viewing the market from a different perspective.

Category	Description	Representative Tools / Concepts
Classical Analysis	Traditional chart patterns and indicators	Bar charts, candlestick patterns, trendlines, moving averages, oscillators
Statistical Analysis	Quantitative and mathematical approaches	Regression analysis, standard deviation, Bollinger Bands, Monte Carlo simulation
Sentiment Analysis	Measuring market participants' psychological state	Fear & Greed Index, put/call ratio, VIX, social media sentiment analysis
Behavioral Analysis	Analyzing human behavioral biases and patterns	Herd mentality, anchoring effect, loss aversion bias

These four categories are not mutually exclusive; in practice, tools from multiple categories are combined.

5.4 Optimizing Market Timing

The following are core principles for optimizing market timing with technical analysis in real trading.

• Volatility-based scaled entries: Rather than taking a full position at once, enter in portions at key support/resistance levels to optimize average cost basis
• Volume confirmation: Verify the authenticity of price movements by checking whether volume accompanies them. A breakout without volume has a high probability of being a fakeout (false breakout)
• Cycle analysis: Reference Bitcoin's halving cycles, seasonal patterns, and other cyclical tendencies to gauge macro-level high/low timing
• Pre-built response framework: Establish a trading plan in advance (entry price, stop loss, target price, position size) so you can act immediately when a signal triggers

💡 Core Principle: Technical analysis is a tool for building trading plans, not a tool for reacting impulsively. Always remember the maxim: "Plan your trade, trade your plan."