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Trading in financial markets involves significant risk of loss which can exceed deposits and may not be suitable for all investors.
Before trading, please ensure that you fully understand the risks involved
Trading in financial markets involves significant risk of loss which can exceed deposits and may not be suitable for all investors. Before trading, please ensure that you fully understand the risks involved

Wednesday, August 12, 2020

A Golden Strategy: BTST

by Century Financial in Investment Insights

A Golden Strategy: BTST
A Golden Strategy: BTST

Losses can exceed your deposit. Trading in financial markets involves risk.

Consecutive weekly rally in gold: What's next?

Gold has rallied for more than 5 consecutive weeks now. This has happened 14 other times in the past 12 years staring 2008. With prices rallying so high, investors are skeptical of investing in the yellow metal at these levels.

However, back-tested data of past 12 years reveals that post a 5 consecutive rally in the metal, BTST strategy (.i.e buying gold at 11pm UAE time and closing the position next day morning at 7am for a period of three months) has led to a total return of 51.3% historically which is an average return of 4.28%.

What is BTST?

BTST means Buy Today Sell Tomorrow, where one would buy before market close and sell on the next day at the earliest. This strategy has worked well for gold, especially after 5 consecutive weeks of rally when the momentum is high. Data reveals that major spike generally comes in the morning between 3am -7 am. This is when the Japanese and Hong Kong market open leading to a bullish price action during this time period.

The table on the right exhibits the 3-month performance of Gold BTST strategy post a 5 consecutive week rally. The strategy considers a stop loss of -1% and take profit of 2%. The strategy has a robust hit ratio with the trade resulting in profits in 11 out of the past 12 instances.

The metal posted 5 consecutive weekly gains on 05 July 2020, and since then the BTST strategy has already provided returns of 4.7% YTD. The trade is valid for another 8 weeks, however if the metal ends this week in the green, that would mark the 10th consecutive weekly gain and the BTST strategy would be valid for another 3 months.

Dates when Gold rallied for 5 consecutive weeks
3 months BTST return following 5 weeks of rally
13-Sep-09 10.10%

27-Feb-11 2.36%
31-Jul-11 18.33%
16-Sep-12 1.09%

29-Jun-14 -2.24%
26-Jun-16 0.83%
9-Apr-17 3.58%
7-Jan-18 3.03%
16-Jun-19 ***5.71%
03-Jan-20 1%
Total Return 51.3%
Average Return 4.28%

*Return is for 5 months as 10th Aug was followed by a consecutive 5 week rally 10 October 2010.

**Return is for 5 months as 19 Jan 2014 was followed by a consecutive 5 week rally on 2nd March 2014.

***Returns are till date.

NOTE: Returns may vary with transaction costs

Data Source: Bloomberg

Arun Leslie John
Chief Market Analyst


  • The testing environment has not considered transaction or any other costs.
  • Future price movements may not be exactly the same as the historical price movements and this could lead to variation in performance.
  • The strategy might suffer from look-ahead bias which occurs due to use of information or data in a study or simulation that would not have been known or available during the period being analyzed. This can lead to inaccurate results in the study or simulation. Testing can sometimes lead to over-optimization. This is a condition where performance results are tuned so high to the past they are no longer as accurate in the future.
  • The model assumes no slippages in trading. Slippage refers to the difference between the expected price of a trade and the price at which the trade is actually executed.
  • Drawdowns in actual trading can be higher than the tested system and loses could significant in the event of leverage. Unforseen events can lead to variation in performance from the tested trading strategy.
  • The tested result has been computed with price feeds available from Bloomberg. The strategy might suffer from data mining fallacy, selection bias and backfill bias.


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