A mean reversion system, works under the assumption that the current trend is strong and the price at present is deviating away from the mean price (average) and in the given period of the time the prices will revert to its mean.
The change or range from mean to the deviated price is where we tend to make a trade and make profit out of it.
2. TREND FOLLOWING
This type of system tries to align the signals with the current trend of the prices. Suppose if the trend is upwards, the system will generate only LONG position in that stock and vice-versa.
3. Volatility Break-Out Systems
VBOS try to take advantage of explosive moves in the share price and capture one sided movement. The example below will give you the idea what is the underlying idea behind it.
4. Dynamic System
This system is basically used to trade a stock where you try to ride the trend just at the beginning. This system basically gives both SHORT and LONG positions and once it gets trending after triggering the order, it gives a lasting movement.
I personally use, Mean Reversion, VBOS and Dynamic systems. Although, Trend Following systems gives the highest Risk:Reward but the winning % rate takes a hit and psychologically I don’t have the temperament for this sort of System.
Continuing with the previous post (PART – 1), few more things to keep in mind about the systems are as follows:
6. Position Sizing
This in fact is one of the most crucial element of the
system designing process. Without the right position sizing the risk cannot be
controlled and you cannot explore the possibility of de-risking your position.
Position sizing in simple terms mean what is the amount of
shares one should buy/sell when the system generates a signal to go long/short.
This can be better explained by an example given below:
Capital Deployed = 100000 (1Lakh Rupees)
Entry for long in a stock @ Rs. 105
Stop-Loss for the entry is @ Rs. 100
Generally, we risk 1% of the capital per position, so 1% of
capital = Rs.1000 (=1R)
Now, the range for entry and stop-loss = Rs.5 (105-100)
Without risk management any system is bound to fail at any
given point in time.
As a general rule:
One should always risk 1-2% of the capital per
trade which is also known as RPT (Risk Per Trade)
Total Risk exposure for a day ideally should be
6 to 8%. If your system generates 10 trades and keeping in mind 1% RPT then it doesn’t
mean that you take 1% RPT and trade 10 Stocks instead you should divide total
risk by number of trades in a day.
Ex. Trades generated during a day = 10
Total risk = 8%
Then RPT = 8%/10 = 0.8% RPT
3. If you are more conservative in nature and want to take into account brokerages and taxes inside that 1% RPT then ideally advisable RPT is 0.75% (including Slippages)
8. Slippages
Slippages are nothing but the actual price where your order
had been filled versus the expected price.
Ex: If you had put buy trigger order at Rs.100 and your
order got filled at Rs.100.5 then that means you had a slippages of Rs.
0.5*number of shares executed
This does not pose much of a problem in highly liquid F&O
stocks and a capital lower than 20L deployed for day trading. But during fast
moves it might occur.
9. Curve Fitting
Curve fitting is a phenomenon that occurs, when you tune the
entry/exits in a system while backtesting to get optimise results. So, avoid
doing that.
10. Back-testing
Backtesting most of the system happens manually unless your
system is a bit simple in nature or you are a coder. Backtesting refers to checking
of the model or strategy and see how it has performed earlier.
11. Forward Testing
This is done when you have evaluated your system and
backtested it comfortably. Once you are done till Step 10, you go on to trade
your system live generally with 1/10th of your capital.
12. Sample Size
Sample size for backtesting data ideally should be as much
as you can collect and record, more the merrier.
But, it should be more than atleast 200 trades and the
period tested should span over 3 years atleast.
Optimum Sample Size should be as follows:
No. of trades tested > 1000
Time period >= 6 years
Part 1 and Part 2 cover most of the things you require to build your own system, more of it and advanced methods will be shared soon.
Win% = Probability of winning or your winning rate
Ex. If you took 100 trades and 55 of them were profitable then your W%=55% (55/100)
and Loss% = 45% (100-55(or W%)
Avg. Win Size = Your avg. profit on the winning trades
Avg. Loss Size = Your avg. loss on the losing trades
This trading edge or expectancy will give you the rough idea on how your system performs. If it is +ve then it means it makes money and if -ve then the idea is a loss making one.
To gauge the edge or expectancy with the normalized one on the scale of edge is given below which most of the system traders use to make money with all brokerages and taxes included to remain profitable.
Lowest Edge (Breakeven to Trade-able) 0.18 to 0.25
Medium Edge (Decent) 0.35-0.48
High Edge 0.5+
Another ratio for calculating expectancy is = Avg Profit / Avg Loss
Although this does not give a clear picture but can be used for simplistic calculations.
2. Frequency
Frequency is defined by number of trades the system generates on a daily basis. It is not necessary that a system will give entries daily so know the frequency of your system and how many trades on a monthly basis it gives.
3. The “R” Concept
“R” is often used in trading world. This is the simple way to define profit and loss.
R can be annotated to the risk involved.
Ex. My risk for a trade is Rs. 1000
Therefore, 1000 = 1R
If my Stop-Loss is hit then my Loss = -1R
If I make Rs. 3000 Profit then my Profit = +3R
Here risk reward = 1:3 (you risked 1000 (or 1R) and made 3000 (or 3R)
Further on, we will be talking in terms of R more often.
4. Equity Curve
This can be defined as your change in trading capital and how its graph takes off with every trades and cumulative of all the trades.
5. Drawdown of a System
This is basically defined as the decrease in trading capital after series of losing streaks. Every system has a drawdown phase. This happens because the market structure have changed or liquidity is low or because of human/algo errors.
Mostly, any system generating 100%+ returns over one year has a drawdown of 30%.
Ex. If you start with 1000Rs as your trading capital and by the end of the year it becomes 2000Rs (100% return) the 30% drawdown if faced in the consecutive year would bring down your capital to 2000-(30%*2000) = Rs.1400
Drawdowns are very common so do not be afraid of it.
This is what we will be focusing on mainly. A system trader is a one who trades when some or all specific conditions/rules are met.
The rules can vary from as simple as moving averages cross-overs or to as complex as using Fourier series. A trading system will make use of various tools of statistics to gauge its profitability over a period of time. This is what we call it as a, “system’s edge”.
Edge can be defined as a return on every 1$ risked. This defines the systems quality and its performance. There are more parameters to gauge a system but it will be discussed later.
2. Discretionary Trader
A discretionary trader is one who takes trade according to his/her judgement and experience. A discretionary trader can easily beat the returns of a system trader but the only catch here is that the discretionary trading is not sustainable in the long run. It will give way to emotions and change in market structure could ruin the whole process.
Given to the complexity of the Discretion involved it cannot be put into an algorithm or coded.
Hi! I am Anshu, I am 26 years old, currently trading for a living. I have now almost half a decade experience trading the financial markets. I have an engineering degree in Electronics and Communication and I am also MBA in Finance. I am and have been fascinated by the stock markets since my early 20s and I had started my journey few year ago. It took me close to 2 years to become profitable. I have paid hefty fees to the markets and I have attended multiple workshops during that time.
In the period that followed, I had read over 100 books on trading, trading psychology and system development.
I am inclined towards systematic trading because it rules out all possible human intervention and emotions while trading.
I have developed 6 intraday and 2 Swing trading System with positive expectancy and I continue to backtest new ideas.
This is a profession where you have to stay relevant for a long time, therefore the need of developing new system.
I currently trade Options of Nifty and Banknifty mostly on weekly and monthly basis because it gives me clarity on a broader lever and cuts off the intraday noise. My majority of the trading capital is utilized in index trades. I also happen to trade in stocks with my 2 intraday systems.
Trading is an amazing profession if you do it the right way and have passion for it. I look at intraday trading for regular income and not for wealth creation.
For wealth creation, investing in right mutual funds and swing trading suits more.
Reach me out @ Quora Profile or email at mackanshunegi@gmail.com
The Mechanical Trader 