Playing  the Expectations Game !
What are your expectations from the trading  business? It is a business where extraordinary profits are possible.  (That is why we are in it.)  But the question is why extraordinary   profits are possible in trading. It is because it is a business where  extraordinary losses are also possible.
 
After all, the business of trading, especially the derivative  trading is a zero sum game! A trader's profits are another one's losses.  If you are to consider the considerable costs of trading, which adds up  to substantial sums over a period, it is actually a negative  expectations game!. It is always better to have a realistic  understanding of the  eventualities one may encounter in the business to  avoid the risk of ruin. Therefore, here are some of the  pieces of  advice or rules I have picked up over a period,  even  though  the  sources and the contexts have been forgotten.
 
You  can  pick   any  one  of  these rules or all  of  them!  They  are  all different   but  they are  all  saying  the one thing !!
 
- Expect the unexpected !
- If anything can go wrong, it  will  !!
- Hope  for the best, but prepare for the worst !!!
All in a day's Trade. 
We  are all normal people. As we are normal, we expect a normal trading day,  OK! The Nifty may trade higher, lower or do both and close higher,  lower or end near the yesterday's close. As normal people our memory  spans are also short. We have a tendency to forget the times on which  the liquidity dried up completely on the one side of the trade and the  index moved one way beyond all expectations.  Therefore, let us refresh  our memory or load it afresh with some real history. Here comes the  Nifty history which explains why the above high sounding cliches are  applicable to trading.
S&P CNX Nifty - Daily Returns in  Per cent
( On a daily close  to close basis )
Chart 1
The above is the graph of daily  returns obtained by the S&P CNX Nifty index calculated as a  percentage change over the previous days close. Here are some  observations about the chart.
-  Volatility increases and  decreases in clusters.
-  Large negative returns are accompanied by large positive returns in  the   cluster and vice versa. 
-  Most of the daily returns are confined to a +/- 5 % range.
-  There are significant numbers of  extraordinary returns in the  data.   That is, Nifty is capable of making extraordinary movements in a  day's  time. 
- Some of these extreme movements were the result of one-off events  like the general election results in 2004 and 2009. 
The three extreme data points of  both,  the positive as well as the negative returns during the period  are  shown in the following chart.
S&P CNX Nifty - Highest  Three Positive and Negative  Daily Returns
Table 1
 S&P CNX Nifty Daily  Returns ( + / - Signs Removed )
Now let us see the above data  from another angle by removing the  positive and negative signs from the  data to get an even better view of the daily movements on a close to  close basis.
Chart 2
The above chart reiterates our earlier observations. So far we  have examined the Nifty on a daily close to close to basis. However,  such an analysis is more suitable for investors than the traders.  It is  seen that the close to close to analysis eliminates the  intraday  extremes of the index and those extremes are more pertinent to traders,  especially to those who have to manage their intraday risk and use stop  losses. Therefore, let us use a technical analysis tool called the 
True Range ( TR ).
"The range of a day's trading is simply 
high −   low. The 
true range extends it to yesterday's closing   price if it was outside of today's range.
Or, in plain English, true range is the largest of the
- most recent period's high less the most recent period's low
- absolute value of (the most recent period's high less the previous   close) or
- absolute value of (the most recent period's low less the previous   close)."
S&P CNX Nifty Daily True  Range ( TR ) 
The following chart shows the  daily true ranges of the Nifty index for the same period. 

Chart 3 
Here  are some basic observations made after a comparison of the daily  returns chart (without the + / - signs) and the true range chart :
- There  are more extreme data points in the TR chart than in the daily returns  chart.
- There are eight TR values which are higher than 10% in the TR chart  whereas there are only three similar values in the daily returns chart.
- The TR data points are significantly higher than the daily returns  chart and therefore a Nifty futures trader is susceptible to  significantly higher risks.
The three extreme data points of TR both the highest as well as  the  lowest during the period are  shown in the following chart.
S&P CNX Nifty - Highest and  Lowest True Range Values 
Table 2
Now, how much is the margin for the Nifty futures?  On an average it is around ten percent. It doesn't require much  extrapolation to find that on all days the index has returned a TR of  ten percent or more , at least one side of the traders would have lost  their entire margins. The brokers would start their margin calls and by  the time the trader either remits the margin or the broker squares off  the position the losses might have become even higher. I have seen  people becoming frozen or paralyzed and incapable of taking  any  decisions on such days. Thankfully the broker  takes the decision and  squares off the positions but mostly at the worst possible prices.
As we have seen the worst let us see what is the normal or 'the new  normal ' values of daily returns and the true range. The following table  shows the average, median and the geometric mean of both the daily  returns and the true range for the sample period.
S&P CNX Nifty - Average, Median  and Geometric Mean of Daily Returns and TR
 Chart 3 
It is observed that the geometric mean of the daily returns and the  average, median and geometric mean of TR are nearly identical at around  2.6 % of the previous day's closing value.
What are the key takeaways from the above statistics? They are very  simple.
- Don't take big leveraged positions in the market. Even small  positions can lead to extraordinary  losses in trading.
- It is better to avoid market turmoil due to the expected event  risks like election results, union budgets etc by keeping no positions  or only positions of long options.    
- Trading is a business in which any skills or advantages of a  trader is used by him to build substantial profits over a period and not  a wham bam game.
- Even if a trader is using all the risk control methods described  in the page named Position  Limits, the trader may be susceptible to significantly higher risks  due to totally unanticipated events or any other reasons. Therefore,  keeping a part of the trading capital as a reserve is a prudent option.
The Tail Piece 
Is it mandatory to have tail piece towards the end  of any discussion?   Even if it is not mandatory or  if it is totally unnecessary, I am  having an inclination to add  a tail piece. Because, there is a very apt  tail piece available!  
Here is a new job description. Measure the heights of 2775 people (  equal to the sample size of the trading days ) randomly and pass the  collected  data through the processes we used for analyzing the Nifty  closing prices. We may find that the average, median and geometric mean  of the new data may fall anywhere between five or six feet. This is  comparable to similar values obtained by us with respect to the Nifty in  the Chart 3.
However, the question is whether we will be able find people with  heights of seven to nine times the average in the sample or anywhere  else. But why?  For example the true range is having an average  of 2.63  ( Table 3) and an extreme value of 22.55 ( Table 2 ) and the ratio  between them is 1: 8.5. Anyone knows that finding a human being with a  height which is  8.5 times the average is an absolute impossibility.  Statisticians say that the data like the heights of people is  distributed normally. It simply means that most of the data points will  be near the average and chances of finding a 45 feet human being is  impossible. 
Statisticians say that financial data series like equity  prices or  indices have long tails. This simply means that  most of the  data  points when plotted on a graph will fall near the average but some of  the data points will be very far away from the average and those points  may  look like long tails in the graph !!
That brings us back to question of whether the discussion needed a tail  piece. And it is settled now !
Beware of long tails in trading !! And sometimes the tail may wag the  dog as well !!!
Cheers and   Prosperous Investing  and    Trading!!!
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