1. Day Trading with Opening Range Breakout Strategies
Christian Lundström

2. Written for the Canadian Society of Technical Analysts
Umeå, Sweden

3. Who am I? Christian Lundström Currently:
PhD Candidate in Economics. Department of Economics, Umeå University Sweden. Doctoral Thesis: On the Profitability of Technical Trading Rules
Independent Consultant in Absolute Return Strategies, Fund Advisor. Folksam Bank.
Previously:
Chief Investment Officer, Fund Manager, Developer of Technical Trading Rules for Asset Management. IIG AG, AB.
Who am I?

4. Crabel, T. (1990): Day Trading With Short Term Price Patterns and Opening Range Breakout, Greenville, S.C.: Traders Press.
Holmberg, U., C. Lönnbark, and C. Lundström (2013): ”Assessing the Profitability of Intraday Opening Range Breakout Strategies,” Finance Research Letters, 10,
Lundström, C. (2013): “Day Trading Profitability across Volatility States: Evidence of Intraday Momentum and Mean Reversion,” Working Paper. Umeå University.
Williams, L. (1999): Long-Term Secrets to Short-Term Trading, John Wiley & Sons, Inc., Hoboken, New Jersey.
Earlier Work

5. The ORB strategy is based on the premise that if the price moves a certain percentage from the opening price level, the odds favor a continuation of that move until the closing price of that day. The ORB strategy suggests that long (short) positions are established at some predetermined price threshold a certain percentage above (below) the opening price, respectively. Crabel (1990).
Profitability of the ORB strategy imply that the asset price must follow so-called intraday momentum at the price threshold levels, i.e., the tendency for rising asset prices to rise further and falling prices to keep falling, Holmberg et. al. (2013).
Rationale

6. Rationale The Contraction-Expansion (C-E) principle:
The principle is based on the observation that daily price movements seem to alternate between regimes of contraction and expansion, or, periods of modest and large price movements, respectively.
In particular, the prices are characterized by intraday momentum during expansion days, whereas during contraction days, prices move randomly.
As most days are contraction days an ORB strategy may be viewed as a strategy of identifying and profiting from days of price expansion and avoiding contraction days.
Rationale

7. Figure 1. An ORB strategy trader initiates a long position when the intraday price reaches 𝜓 𝑡 𝑢 and then closes the position at 𝑃 𝑡 𝑐 with a profit.
Strategy

8. Strategy Thresholds in log, at day t, can generally be given as:
𝜓 𝑡 𝑢 = 𝑃 𝑡 +𝜌 and 𝜓 𝑡 𝑙 = 𝑃 𝑡 −𝜌 where
𝜌>0
and 𝑃 𝑡 is the opening price at day t
Strategy Returns in log, at day t, are hence given by:
Strategy

9. Strategy Thresholds in specific form varies among studies Robustness?
𝜌(𝑡)=𝑆(𝑡−𝑥), Crabel (1990)
𝜌(𝑡)=𝑎𝑅 𝑡−𝑥 , Williams (1999)
𝜌(𝑡)=𝑏+𝑐, Holmberg et al (2013)
Where a, b, c are positive constants. x>1 denotes lagged x time periods.  is the standard deviation of open-to-close returns.
Robustness?
Strategy

10. Probability Enhancing Filters (Trend and/or Volatility, the CE Principle)
Crabel (1990); Inside days, NR(4), Hook Days, and more.
Lundström (2013); Volatility Filters alone.
Strategy

11. Illustration Empirical illustration from Lundström (2013)
Lundström, C. (2013): “Day Trading Profitability across Volatility States: Evidence of Intraday Momentum and Mean Reversion,” Working Paper. Umeå University.
Illustration

12. Illustration Robustness: Testing a vast number of thresholds
Filters: Testing the relation between volatility and the strategy returns
Assessing the Profitability using a GLS specification:
Illustration

13. Data:
Left: The daily closing prices in levels for crude oil futures adjusted for roll-over effects from January 2, 1991 to January 26, Source: Commodity Systems Inc.
Right: The daily closing prices in levels for S&P 500 futures adjusted for roll-over effects from January 2, 1991 to November 29, Source: Commodity Systems Inc.
Illustration

14. Illustration The ORB Strategy provide larger average return (Mean),
Table 1: Descriptive statistics for the price returns series
Table 2: Descriptive statistics for the ORB strategy returns series for ρ=0.5 percentages
The ORB Strategy provide larger average return (Mean),
as well as smaller average risk (Std.Dev)
Illustration

15. Table 3: Empirical results of the long-run ORB profitability test.
The ρ is the per cent distance added and subtracted to the opening price.
T is the number of trades. freq gives the proportion of trades that result in positive returns,
while A gives the average returns.
The p-values are calculated based on the HAC standard errors.
We find significant positive long-run profitability for some,
or all, thresholds depending on the asset, and that the ORB strategy is a relative robust strategy w.r.t thresholds.
Illustration

16. Left: The strategy performance (in log prices starting with 100 USD) for crude oil futures from January 2, 1991 to January 26, No costs or slippage.
Right: The strategy performance (in log prices starting with 100 USD) for S&P 500 futures from January 2, 1991 to November 29, No costs or slippage.
Illustration

17. Volatility determines the most of the results!
Illustration

18. Illustration

19. Day trading with opening range breakout strategies can generate value if the cost is small enough (Crabel, 1990; Williams, 1999; Holmberg et al, 2013; Lundström, 2013)
Lundström (2013) shows that the ORB profitability is linked to intraday volatility and there could be as much as 2 % differences in daily returns during high and low volatility states. Consequently, the ORB strategy should always be used in combination with volatility filters.
Although not explicitly shown here, ORB returns are uncorrelated with other strategies such as long only as well as trend following strategies, CTA or Managed Futures.
Conclusion

20. Testing ORB strategy returns for other filters than volatility
Volume probably matters, see Crabel (1990)
Intraday data to study intraday trends in prices
Future Research

21. Thank you for listening!