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Technical analysis

Sándor Bozsik (Ph.D) Miskolc University Hungary. Technical analysis. In efficient market the NPV of all investment decisions is 0. Assumptions: Information efficiency Transaction efficiency Allocation efficiency Consequence: Price movement is a random walk. Efficient market. Weak form

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Technical analysis

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  1. Sándor Bozsik (Ph.D) Miskolc University Hungary Technical analysis

  2. In efficient market the NPV of all investment decisions is 0. Assumptions: • Information efficiency • Transaction efficiency • Allocation efficiency Consequence: • Price movement is a random walk. Efficient market

  3. Weak form Semi strong form Strong form Types of efficient market (Fama)

  4. The price movement has a trend The history repeats itself The price perfectly reflects the effort of market forces. The market has got memory. The prices are sticky. Technical analysis – denies the weak form

  5. Accumulation • Expansion • Dispersion • Exhaustion Discovering with support and resistance lines Stages of trend

  6. Graphic tools • Bar chart • Japanese candlestick • O-X diagram • Statistical tools • Moving average, EMA, MACD • Momentum, oscillator • Market strength, Money Flow Index • Combined tools • Fibonacci-lines • Bollinger-band • Elliott-wave Methods of technical analysis

  7. Bar chart (MOL)

  8. Japanese - candlestick

  9. Trend strengthening forms • triangles • Channels • Mast and flag • Trend changing forms • Double peak • Saucer • Key reversal or inland reversal • Head and shoulders • Spike Trends

  10. Trading rule: if the shorter moving average crosses the longer one below – buying signal, on the contrary – selling signal • Grouping: • By term: 3, 7, 14 days • Simply, weighted or exponential • Direct or Indirect average • The longer is the average, the better follows the trend, the shorter is the average, the quicker gives a signal. Moving average

  11. Equation Exponential moving average (EMA) Stage analysis (Stan Weinstein) Stage 1 – the asset moves in a relative narrow band Stage 2 – developing stage – the asset price increases above the 200 and the 50 days EMA Stage 3 – Peak, the asset price is permanently above the 200 day EMA (profit realisation) Stage 4 – Price drop

  12. McClellan oscillator and summary index Daily breadth – difference between the number of up-closing and down-closing shares – they are cumulated and an EMA with 10% and 5% adjusting parameter is created. The difference between them is the oscillator. MACD – Difference between two EMA (12 days and 25 days) Then the 9 days EMA is taken. If it crosses the difference – trading signal. Two derivative from EMA

  13. Momentums and oscillators • Oscillator • Momentum • Relative strength index (RSI)

  14. Money flow index • Measures the money in and out of the market • Equations:

  15. What does it show? – Resistance and support level • fn=fn-1+fn-1 • The next figure is 1,618 higher than previous one (gold cut) • From 100% we get the followings: • 100%; 61,8%; 38,2%; 23,6%; 14,6%; 9% • 100% is the gap between maximum and minimum price in a given period Fibonacci numbers

  16. Fibonacci line Richter 25 390 20 271 17 104 14 545 11 986 8 819 3 700

  17. Bollinger - band • Usage: To determine the eruptions • Based on: • Relative support and resistance • Moving average + standard deviation • The larger is the volatility the larger is the width of band.

  18. Applying the Bollinger-band

  19. Narrowing band projects meaningful change in price If the price reaches the upper or lower limit, then the trend may go on. If the price leaves one of the limit, but doesn’t reach the another one, then the current trend continues. If the price breaks the moving average, then reaches the opposite limit. The break out of the band is a sign of eruption. Assumption of Bollinger-band

  20. Fundamental analysis

  21. The market is efficient in weak form, but inefficient in semi-strong form. Not everybody can evaluate properly the public information. Analyse the fundamentals to determine the company’s intrinsic value. Invest in medium or long term. Principles of fundamental analysis

  22. Find a benchmark (similar company or industry average) Calculate a market ratio Collect the financial statements, market projections, data on macroeconomic circumstances Analyse and compare the results Try to explain the differences in market ratio How the fundamental analysis works

  23. Operated in the same industry Located in similar region Similar size Similar financial risk profile How to choose proper benchmark

  24. P/E – Price per earning Market to book value P/EBITDA Famous market ratios

  25. P/E – share price/net income per share • Value of shares: • Usage: manufacturing companies P/E ratio • Where: • Px – firm’s share price • EPSX – firm’s earnings per share • P/E* - benchmark’s P/E indicator • d – adjusting factor • DBX – number of share issued • VX – value of equity

  26. DCF analysis Real option models More sophisticated methods

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