🔍 One of the major goals of market analysis is to understand how prices move and how trends/cycles emerge over time.
But explaining these dynamics is tricky, even for practitioners. As any trader will tell you: sometimes, explaining risk management to a newcomer is harder than placing the trades themselves! 😅
👉 Launch the Interactive App ▶
📉 The Reality Behind Price Action
Markets don’t move in straight lines. They trend, consolidate, and revert: these are the rhythms of price cycles.
Understanding these movements helps to:
- anticipate momentum shifts,
- design robust trading/hedging rules, and
- make more informed portfolio decisions.
I illustrated this by analyzing NVIDIA (NVDA) in 2024 using classic technical indicators:
- SMA20 (short-term trend)
- Bollinger Bands (20,2) (volatility envelope)
- RSI(14) (momentum)
- MACD(12,26,9) (trend/momentum crossover)
📊 Visualization
Legend:
- Candlesticks: Daily price
- SMA20: Moving average (trend)
- Bollinger (20,2): Upper/Lower volatility bands + midline
- RSI(14): Overbought/oversold gauge
- MACD(12,26,9): MACD line, signal line, and histogram
🧰 Methodology & Data
- Period: 2024-01-01 → 2024-12-31
- Data source: Yahoo Finance via
yfinance - Indicators: SMA20, Bollinger(20,2), RSI(14), MACD(12,26,9)
- Tools used: Python (
pandas,plotly,talib)
🧠 Why It Matters
Whether in cooking, medicine, or markets: precision matters.
- In cooking: a wrong dose can ruin the dish.
- In medicine: a milligram too much can have serious consequences.
- In trading: misreading a signal or reacting late can deepen drawdowns or miss opportunities.
⚖️ Does any of this work? The efficient-market objection
Technical analysis deserves an honest confrontation with the theory that rejects it.
The efficient market hypothesis (Fama, 1970) holds that prices continuously reflect all available information. Past prices, public information (earnings, macro releases) and even private information are already embedded in the quote. If NVDA beats expectations, the price reacts almost instantly, because investors have already priced it in. Under that reading, staring at past prices should confer no durable edge: it is already in the price.
So why do practitioners still use these tools? Because the goal is not prophecy. In practice, quants and traders use candlesticks, moving averages, RSI, MACD, Ichimoku, VWAP, the Stochastic and OBV to detect trend and momentum, frame risk, and time execution (entries and exits) across horizons that run from intraday and algorithmic trading down to the millisecond, and up to long-term portfolio management.
The pragmatic position sits between the two camps: run rigorous out-of-sample backtests, account for transaction costs and market frictions, and stay alert to documented anomalies (momentum, value, calendar effects) which can persist depending on horizon and market regime. Technical analysis then earns its keep by pacing risk and improving timing, not by guessing the future.
That is exactly why the MACD + SMA backtest in this collection reports a strategy that loses to buy-and-hold: the point of testing is to find out, not to confirm.
⚠️ Disclaimer
This is an educational tool and a demonstration of interactive visualisation (Python, Shiny for Python, Plotly) and web deployment. It is not investment advice.
📚 Suggested Readings
- Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. The Journal of Finance, 25(2), 383–417.
- Murphy, J. (1999). Technical Analysis of the Financial Markets
- Elder, A. (2014). The New Trading for a Living
🏷️ Tags
#NVDA, #TechnicalAnalysis, #BollingerBands, #RSI, #MACD, #SMA, #Plotly, #Python, #yfinance
