The Trading Game: By Rajan Dhall MSTA

Randomness is one of my favourite subjects and I don’t really fancy getting into the subject of the efficient market hypothesis but I want to explain a story about technicals and odds analysis. At one of my previous places of employment I was responsible for looking after the interns for one month and teaching them some of the fundamentals of trading. These fresh-faced university graduates used to come to me and ask me about why I would take some of the trades I took, what factors I would consider in entry, position management and exit.

I proceeded to talk to them about the importance of account and position management, two very different things in my book. Some of the interns looked at me like I was crazy, ‘so you place more emphasis on trade management than taking the trades?’ I then said of course ‘a monkey can place a good trade but they cannot tell you when to exit or tell you how to manage a position’. So they then proceeded to ask me why, I explained at any moment and at any time there could be news or a major development that could change my whole trade. Case in point I once had a great AUD/USD position in great profit, walked into a meeting with a manger and came out and found it in a loss. This was all due to the governor of the RBA speaking at an unscheduled event in the USA, not even his time zone!

It was then I devised a plan, we fabricated a game based on the role of some dice:

I had 10 interns and split them into groups of 5.

Group 1 traded a 1hr chart, group 2 a 4hr, group 3 a daily chart and the
last group the weekly chart.

We then rolled the dice and anything under 6 was a short position and
anything over was a long position.

Then if the number was under 3 the risk to reward was 1 – 3 and between
3/6 was a 1 – 1 risk to reward.

Above 6 long with risk reward of 1 – 1 and between 9 and 12 the risk to
reward was 1 -3.

This went over all 4 time frames.

I must also explain some of the variables – the asset classes where Gold/EURUSD/Nasdaq futures/WTI there was one roll per asset and the size of the risk was dependent on the volatility. Example on the 1hr EURUSD the rise was 50 pips. Which was 50% of the average daily range on a 10 day period at the time. Basically it was based on a variation of an ATR function.

Now this experiment was over 4 years ago but I remember the results as clear as day. The highest time frame (weekly) based on 1 -3 risk to reward was the most successful; in second place was the daily time frame with a 1 -3 risk reward.

Most all of the lower time frame trades where losing especially those on the 1 – 3 risk reward. Interestingly on the lower time frames the 1 – 1 risk to reward trades where slightly more successful.

This was all based on random trade selection but with controlled risk to reward.

In conclusion, we then proceeded to do this but using technical levels to identify the risk parameters. The traders soon learned that levels on the charts were much better than the randomness of the dice. One lesson remained with them, the future is something that cannot be controlled, market forces shift but technicals helped us control risk and become more selective for entry. I am happy to say that many of them lasted in the industry and may even read this article and remember the test. One thing I can say it was a good learning experience for me as well as the
interns.

Share Share Share Share Share
Posted in Finance, Markets, STA charts, STA education, STA news, Technical Analysis, Technical Analysis Courses, Technical Analysis Training, Trading, Trending

Leave a Reply

Your email address will not be published.

Disclaimer

The views and opinions expressed on the STA’s blog do not necessarily represent those of the Society of Technical Analysts (the “STA”), or of any officer, director or member of the STA.

The STA makes no representations as to the accuracy, completeness, or reliability of any information on the blog or found by following any link on blog, and none of the STA, STA Administrative Services or any current or past executive board members are liable for any errors, omissions, or delays in this information or any losses, injuries, or damages arising from its display or use.

None of the information on the STA’s blog constitutes investment advice.

About Nicole Elliott

Nicole Elliott

A graduate of the London School of Economics and Political Science (BSc Social Psychology) Nicole Elliott has worked in banks in the City of London for the last 30 years. Whether in sales, trading or forecasting technical analysis has always been the bedrock of her thinking. Key expertise lies within all areas of treasury: foreign exchange, money markets, fixed income and commodities.

She has also added to the body of knowledge of the industry writing the first western book on Ichimoku Cloud Charts. Strong media links and a cult following are due to her prescient calls on the markets and often entertaining format.

Nicole can be contacted at trending@sta-uk.org

Posts by Date

Sign up to the STA newsletter

Sign up to the STA newsletter

Our newsletter is designed to bring you the latest information on technical analysis, educational courses, conferences and events . Sign up now!

Previous Newsletter Archive

* required

Sign up to the STA newsletter

  html
  text