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Directional Changes A new concept for summarising price movements Edward Tsang Presenter Richard Olsen Inventor Han Ao Demonstrator.

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Presentation on theme: "Directional Changes A new concept for summarising price movements Edward Tsang Presenter Richard Olsen Inventor Han Ao Demonstrator."— Presentation transcript:

1 Directional Changes A new concept for summarising price movements Edward Tsang Presenter Richard Olsen Inventor Han Ao Demonstrator

2 How History Is Recorded By key events –1918: £, US$, Franc, … unlinked with gold –1926: £ tied to gold, but only exchangeable in bars –1931: Floating exchange rates –1944: Bretton Woods: US$ as exchange standard – : US$ unlinked with gold – : Smithsonian Agreement: fixed exchange rate –1973: Fluctuating fiat currencies Not by snapshots at end of years

3 How Price Movements Are Recorded Interval-based summary

4 Problem with interval-based Summary Important movements not captured

5 Directional Changes Richard Olsen Inventor Attempt to capture significant changes Where significance is user-defined

6 Directional Changes Definition Threshold (%)Directional ChangesOvershoots See video for more information

7 DC-based Summary Threshold (%)Directional ChangesOvershoots Down- ward Trend Upward Trend Down- ward Trend See video for more information

8 Why Directional Changes?

9 DC vs Interval Coastline With the same number of points DC captures significant changes missed by Intervals FTSE 100 June 2007 to October 2012

10 Potential for Profits Given perfect foresight: (Buy low, sell high) –Interval based return: 171% –DC-based return: 304% FTSE 100 June 2007 to October 2012

11 Potential for Profits Given perfect foresight: (Buy low, sell high) –Interval based return: 171% –DC-based return: 304% FTSE 100 June 2007 to October 2012 DC-based summaries have longer coastlines

12 Potential for Profits Given perfect foresight: (Buy low, sell high) –Interval based return: 171% –DC-based return: 304% FTSE 100 June 2007 to October 2012 DC-based summaries have longer coastlines Longer coastline  potential for higher profit

13 DC-based Market Analysis Tools Olseninvest.com

14 Statistical Properties Observed Average overshoot: same as threshold (approx.) Average overshoot time: approx. to 2×DC time t ≈2t t θ ≈θ θ DC OS Reference: Glattfelder, J.B., Dupuis, A. & Olsen, R. Patterns in high-frequency FX data: discovery of 12 empirical scaling laws, Quantitative Finance, Volume 11 (4), 2011,

15 DC-based Algorithmic Trading Can trading algorithms be derived around DC? Research in progress BuySell

16 Conclusion History recorded by events, not snapshots at fixed intervals; so should market prices! Directional Change (DC) events defined –They capture ‘significant changes’ Useful for summarising price movements –DC give new perspectives in price movements DC enables discovery of regularities not captured by interval-based summaries –A rich, new world to be explored

17 Supplementary Information

18 5% Directional Changes (DC) Day Day 3Day 5Day 7Day 2Day 4Day 6Day 8Day 9Day 10Day 11Day 12 Directional Change Event Overshoot Event Increased >5%; DC confirmed Decreased >5%; DC confirmed Extreme point confirmed in hindsight (on Day 6) Upward Trend Downward Trend Confirmed extreme point Overshoot Event Directional Change Event Confirmation point Downward Trend Confirmation point This example shows what Directional Changes are, and how to find them

19 Directional Change Example (1) First we define what we consider a significant price change –Suppose we consider 5% to be significant Suppose the price of an asset in day 1 is 100 We don’t know whether we are in an upward or downward trend If the price goes to 105, then we conclude that the market is in an upward trend If price goes to 95, we’re in a downward trend

20 Directional Change Example (2) Suppose on day 2, price is 95. So we are on a downward trend In a downward trend, we record the lowest price –Currently, the lowest price is 95 Suppose on day 3 the price goes up to 98 –It is not 5% above 95, hence no directional change Suppose price drops to 90 on day 4 –We are still in a downward trend –We record 90 as the lowest price Let price go up to 92 on day 5 –We are still in a downward trend

21 Directional Change Example (3) If price goes to 96, then we conclude that a directional change has happened –Because 96 is >5% above 90 Now we confirm that 90 (day 4) was an extreme point At day 4, the downward trend ended –At day 4, the upward trend started In an upward trend, we record the highest price –Currently the highest price is 96 –(Not 100 in day 1) We are now looking for a downturn directional change

22 Directional Change Example (4) Suppose subsequent price change are: 99, 97, 105, 110, 108, is more than 5% below 110, the highest recorded price So we conclude at 104 a downturn directional change –110 was an extreme point We define the price changes from 90 to 95 a directional change event The price changes from 95 to 110 an overshooting event These events summarise market movements

23 Definitions

24 Directional Change Events Overshoot Events

25 Directional Changes (DC) A Directional Change Event can be a –Downturn Event or an –Upturn Event. A Downward Run is a period between a Downturn Event and the next Upturn Event. An Upward Run is a period between an Upturn Event and the next Downturn Event.

26 Length of coastline Maximum profit opportunity after transaction costs with no leverage and perfect foresight Long coast line (>2,000%) means huge opportunities to be exploited! opportunities

27 DC in Different Time Systems Downturn Event Downward Overshoot Event Upturn Event Upward Overshoot Event Event-based system Point-based system Downturn Point Downturn Confirmation Point Upturn Point Upturn Confirmation Point Physical Time Line Downturn Event Interval Downturn Overshoot Interval Upturn Event Interval Upturn Overshoot Interval Interval- based system

28 Resources OANDA Tools –http://fxtrade.oanda.com/analysis/labs/http://fxtrade.oanda.com/analysis/labs/ Long-short ratios Order book Heatmap (based on directional changes) Heatmap (weekly, monthly, yearly) OlsenScale

29 Striking observation 17 scaling laws discovered so far, e.g. –When a directional change of r% occurs, it is on average followed by an overshoot of r% –The time for the overshoot to happen is also highly correlated to the time taken for the change of direction to happen! Further observation and analysis needed Machine learning needed for function fitting

30 Shaimaa Masry Deciphering Market Activity Along Intrinsic Time

31 Diminishing Activities in a Trend


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