80% of the Traders blow their account in the first 2 years of their Trading career.
Is it because they don’t have enough knowledge of technical analysis?
Is it because they don’t have enough money to trade?
Is it because they did not buy any fancy courses?
The answer is “ NONE OF THE ABOVE ”
Then why are they blowing up their accounts?
The answer is “bad position sizing”
It decides the “HOW MUCH” quantity you will buy or sell in security when you get your entry signal.
It decides how much you will make on a trade.
Now you might have this thought in mind, what the heck this has to do with the profitability of a trader?
Say there are 2 traders, Rahul and Akshay.
Both Follow the same System with a Win rate of 50%, which means out of 1000 trades, 500 trades are likely to be positive and 500 are likely to be losers.
Both have the same amount of capital, i.e 100,000 Rs.
(Win rate is In how many Trades you make Profit out of Total trades.)
Let’s take a sample size of 20 trades, though it’s a small sample size it will work for this example.
First, take a look at the below table, which shows how many losses you can have in a row with different Win rate%.
So a 50% win rate system can have 16 losing trades in a row.
Now, let’s get back to Rahul and Akshay.
First, let’s talk about Akshay.
He is a passionate trader who wants to make a living out of trading, but as of now his capital is low so he has to do his job and Trading side by side.
Though he hates his job and wants to become a full-time trader as soon as possible but with a small amount of 1 lakh, he can’t become a full-time trader.
Because of this, he decides to take higher risks so that he can make money faster.
As his trading system has a 50% win rate and 1:3 Avg Reward to risk ratio.
He calculates that he only has to be right in 3 out of 10 trades to break even/become profitable.
So, he thought about risking 5% of his account on every trade, because he is sure that he will make money in 5 out of 10 trades, because of his 50% win rate.
He is calculating in excel that he needs only 10 profitable trades to double his account, and he is sure that he will 10x his account this year.
He starts to trade and the next 5 trades come to be losers.
This means that his account is down by -25% and now he is only left with 75,000 Rs.
He was shocked that how come he got 5 losers in a row, there must be something wrong, maybe things will take a U-turn and the next few trades will make me profit, he thinks.
The next 4 trades are also losers and his account is now down -45%.
He is Frustrated but he is sure that this is just the worst going on, and the profit is the only thing that is going to come from here on.
His account is now down to 55000 Rs, He thinks of increasing the risk to make the lost money as fast as possible.
So, he increases the risk per trade to 10% of his initial capital.
Bad luck again!
The next 3 trades are also losers, he has lost about 75K of his total account, and now only has 25K left with him.
He is really worried, because he has lost 75% of his capital, and has left with only 25k capital to trade.
Desperately in need of making his lost money back, he again increases the risk to about 15% per trade, he thinks that this must be the end of the losing streak and I will take back everything in just 3-4 trades.
The next 2 trades also come to be losers, Akshay has blown up his trading account.
Now, let’s take a look at how Rahul’s performance looks like-
Because they both were trading the same system, both got the same trades, it’s just that Rahul only took a 1% risk of his initial capital.
Rahul also got the hit because of 16 losers in a row, but because of his low risk he was able to survive the losses, and then because his profitable trades were 2-3 times of his losses, he is only down 6% of his initial capital.
Rahul was not in a hurry to make money, because of his low risk he was able to keep calm during the drawdown phase.
Both Rahul and Akshay were using the same system, Akshay got bankrupt and Rahul was able to continue his trading and will make money in the long run.
But, Akshay came in the grip of Gambler’s Fallacy.
In simple words, if an event occurs too many times in a row then we expect that it will stop occurring in the future.
In the above image you can see that when three heads come in a row, the person thinks that it’s highly unlikely that another head will come up next.
They try to predict the future outcome based upon the last few observations.
What they forget is that each toss has its probability, which is 50%, every time the coin is tossed there will be a 50% chance of the tail to come and a 50% chance for heads to come.
Similar to this, each trade also has a 50% probability of being right and wrong, i.e the result of the last few trades has no impact on the probability of the current trade, it will always be 50%.
In Akshay’s example, we saw that he increased his risk because the last few trades were losers, and he thought that now it’s highly likely that a winner will come, so he kept increasing his betting size, which eventually led to his blowup.
The most famous example of Gambler’s fallacy occurred in Las Vegas at Monte Carlo casino in 1913.
The roulette wheel’s ball had fallen on black many times in a row, so the players think that now it’s highly unlikely for the ball to fall on a black, so they bet heavily on the Red.
The ball fell on the Red square after 27 turns, Gamblers lost millions of dollars during this event.
Extreme examples are more likely to be found in small rather than large samples.
In Akshay’s example, you saw that the winning probability of his system was 50%, which means that out of 1000 trades 500 will be losers and 500 will be winners.
So, one may say that every 5 out of 10 trades will be profitable, Right?
Wrong! When you take a random and very small sample size there is a chance that extreme events can happen like we saw that their system got 16 losers in a row, which was highly unlikely, yet it occurred,
His system has a 50% winning probability, but only over large sample size.
So, now we can say that a trader is more likely to be profitable in the long run if he keeps trading, over a large sample size, with small risk.
The need to make the money fast can be fatal for our accounts.
Now we know how position sizing can affect our performance. Let’s know how to calculate position sizing.
There are several position sizing methods, here are a few of the most important methods.
As the name suggests in this position sizing method we are risking a fixed percentage of our account on every trade, irrespective of the account size.
If the account size says 1 lakh and we are risking 1% on every trade, our risk per trade will be 1000, so now if we make some profit and our Capital grows to 1,10,000 then we will riks 1% of it, which will be 1100, and say if we make some losses and our capital reaches to 90k, then we will risk 1% of that, which will be 900.
The main things you need to use this method are a stop loss level and the percentage you want to risk on every trade.
Let’s take an example to understand this method more.
Say you want to buy Reliance at 2000, and according to your method, the Stop-loss level for this trade should be 1950.
And you decide to take 1% risk on every trade that you take and your capital is 1 lakh Rs.
The position size in this example comes to be 20, which means that you have to buy 20 qty of this stock.
Let’s take an example of short selling also –
Say you want to short a stock at 1000 Rs and your SL for this trade is 1020.
Your risk% per trade is 1% and your account size is 1 lakh.
The only change in the case of short selling is that to calculate Risk points, you have to subtract entry price from stop-loss price, otherwise, the risk points will come in negative.
In this trade, you have to short 50 qty of a stock.
Now let’s move on to the next position sizing method.
In this method, we allocate an equal amount of money to each trade, irrespective of our stop loss level.
We divide the total equity into parts, say 5, and then we allocate the same amount to the 5 stocks that we buy in our portfolio.
For example, if we have 1,00,000 in our account, and the max position we want to hold at a time is 5, then we can divide the total capital into 5 parts, which will be 20K each.
So, we will allocate 20k of our account on each trade that we get, irrespective of anything else.
Say we got a signal to buy Icici bank at 600 Rs, your account value is 1,00,000 and you decided to put 25k in each stock that you Trade.
So, this is how you will decide your position sizing using this method.
This method is mostly used in investing or portfolio building, where we buy a bunch of stocks, with similar 5-10% below SL levels.
The equal unit approach allows you to give equal weightage to each investment in your portfolio.
Now, let’s move on to the next method.
This Position sizing method is based upon the Volatility of a stock, By volatility what we mean to say is the daily movement of an instrument.
To calculate the daily movement of a stock we have to subtract the Low of the day from the high of the day.
Say, Reliance stock Opened at 2000 and it made a high of 2150 and a low of 1980 and closed at 2020.
Then its daily movement is High – low = 2150 – 1980 = 70
So we can calculate the last few day’s volatilities by calculating the average daily movement of the last few days, but we are ignoring the gaps if we use this method.
To counter this we use the ‘Average true range’ to measure the stock’s volatility.
This method is used in combination with the percent Risk method that we discussed earlier.
Let’s see how, with the help of an example
Say, Our Trading account value is 1,00,000 and we don’t want to risk more than 2% on any trade.
Say we get a buying signal at 145 because the stock had found buying in this zone many times in the past.
Then we check the ATR indicator value, which is around 7 Rs at the time of entry, so we subtract 7 rs from 145, which is 138, which will be our stop-loss price for this trade.
Calculating the Position sizing
So you would have to buy 285 Qty of this stock according to this method.
The main merit of using this method is that it takes into account the volatility of the stock, as different stocks have different volatility, and even the same priced stocks can have different volatilities.
So, this method gives us an objective way of setting our stop loss according to the volatility of a stock, without any guessing work.
Many times when a stock gaps down, most people lose heavily because they use stop losses based upon guesswork or intuitive levels, but when you use the ATR, you are at least ready for 1 ATR gap down which is the normal volatility of the stock.
So, this is all for today from my side. If you learned something new, then please share this article on your social media handles.
See you all in the next article, till then goodbye.