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In Backtest/Optimization or Simulation, in generally I don't use position sizing. Just fixed contracts. Otherwise, some metrics like "minimum capital required" is useless. Another reason with position sizing is, that good results will amplified to, let's say "perfect" result, and bad gets even worse.
Position sizing comes into play, if everything is done and when it is already decided that a strategy will be used for real trading. Then I play around with position sizing.
What is your approach? Do you apply position sizing from the beginning? Some details would be great.
I always test my systems with 1 contract, or 2 if I have some special dual exit type setup.
I see people post great equity curves, that obviously include position sizing. That is very misleading in my opinion, since if the order of the trades was a little different, the equity curve could be totally different. Also, it is hard to distinguish what is from the strategy itself (which is most important) from the position sizing (which can easily be done after the fact).
That being said, I know of one popular and successful trader (you'd probably recognize his name, and years ago he wrote a book on money management), who almost always tests with position sizing.
His theory is that if you ignore position sizing during development, you might end up with a strategy that looks good with one contract, but does not lend itself to easy position sizing. He makes a good point.
I actually have a strategy like that, very profitable, Tharp expectancy of 0.62, SQN of 3, average trade value over $2K per contract, but it is extremely difficult to position size with it unless you have a huge account. So, for 4 or 5 years I have traded it with small size. I probably would have been better off trading a worse strategy that worked better with position sizing.
So, once again, I can't say there is only one "right" way to do things.
Week #2 is in the books. Only 2 trades taken all week, both winners.
Close to breakeven now. This reminds me of the Combine - flat to down performance.
As you can see, these strategies can be very boring.
Comparing "perfect" performance with "actual" performance, it looks like I am doing better with my actual account. Fills have been better than anticipated.
Thanks, that is insightful. How much does experience influence this process? Do you still need to research 100-200 ideas to come up with a good system, or does that number go down when you get better in your craft?
Edit: How long do you think that your strategies, on average, remain active? I can imagine that, if so much ideas need to be researched, the ideas that are found need to be 'active' for a longer time.
If that strategy is for forex, why not use spot forex instruments instead of the much larger futures? That way, you have much more granularity over position size.
As time goes on, the process does get easier with experience. It becomes much easier to eliminate bad ideas at an early phase. Plus, ideas at the start become better, since a more experienced person will know what generally works or not.
Some strategies I have developed last years. an example is below. It has traded decently for 3.5 years now. But this past year has been flat to down. Others I have traded for 5+ years. One I've been trading a year, but the last 6 months have been awful. I guess I am saying there is no predictable "shelf life" for these strategies. The key is to have new ones ready to take the place of any strats that turn bad.
Regarding forex: The strategy I am referring to unfortunately does not trade forex. It is an ag seasonal program, trades only 16 times per year, been going great since I took it live, but like I said does not lend itself to position sizing. Its equity curve is below.
Sometimes, after 20 plus years of trading, so tasks become so rote and routine to me that I forget that I had to learn them at one point. Such is the case with creating equity and drawdown curves. It is simple to me, but to someone who has never done it before, it can be a daunting task.
So, in this post I'll go thru the math behind creating an equity curve and a drawdown curve. If you use Excel, you can download the spreadhseet at the end to help you out.
Equity Curve
The equity curve can be built on a closed trade by trade basis, or on any timescale you wish. I like using a daily equity chart, in part to eliminate the noise from intraday price changes. You can use your daily account statement to get your current equity balance.
Here is exactly how to build an equity cruve based on daily data:
Day 0 Equity = Initial Starting Balance
Day 1 Equity = Day 0 Equity + Change in Equity During Day 1
Day 2 Equity = Day 1 Equity + Change in Equity During Day 2
...And So On...
Then, you simply plot the Day X Equity values, and you have your equity curve.
Drawdown Curve
The drawdown curve is the difference, on any given day, between that day's equity, and the maximum equity up to that point. So, let's say an account starts out with $10,000 on Day 0. On day 1, it hits a new equity high of $10,500. The drawdown on Day 1, since it is a new equity high, is $0. On Day 2, let's say the equity falls to $9,700. Now, the drawdown on Day 2 is $10,500 - $9,700 = $800. And so it goes through the rest of the days. On days where a new equity is reached, the drawdown will simply be $0. On all other days, the drawdown will be the difference between that day's equity, and the maximum equity up until that point.
Day X Drawdown = Minimum Of $0 or (Day X equity - Max Equity From Day 0 to Day X)
Excel Spreadsheet
I created a simple Excel spreadsheet, with chart, that does all these calculations for you. You just have to enter your starting balance, and then the daily equity changes. If you know Excel, you can easily add to this and make the spreadsheet an even better tool.
I think that sometimes when people say that all you need is a simple bar chart to trade (and perhaps one or two indicators that work with your particular style of trading), they are forgetting that to get to that point, one must gain a whole bunch of knowledge (over time) as to what works and what doesn't. And also spend a whole lot of screen time to be able to put to practice all that knowledge. I'm barely a couple of months into all this and there are so many things that now just seem like "common knowledge" or "common sense", that two months ago were giving me a major head ache just trying to grasp. I think that once you do have that knowledge base, then it is simple, in once sense.... but then there is that next step of mastering your on psychology to be able to put that knowledge to work. I'm a lot further along than day one, but see that the road ahead as a lot longer than I was imagining.
Thanks for this post, and all the other great information you pass along for all of us.
You make some good points, especially for a new trader.
A lot of people think that trading is getting to a point and then staying there. As if being a good trader is a destination, meaning - once you are at that point, you have "arrived" and can just take it easy.
I've been at that point many times - where I thought "wow I've made it as a trader." Coincidentally (or not), soon afterwards I almost always found myself licking my market inflicted wounds.
Now I keep in mind that there is no destination, no arriving to a land of sunshine and never ending profits. The journey itself is the destination, and it is a never ending struggle to stay sharp and ahead of the pack.
I've done a Monte Carlo Simulation with the Data Kevin provided me.
I'm currently building up my own Monte-Carlo-Risk model for trading. Currently, I can only provide the metrics below. As already mentioned , I use the Excel add-on @risk.
The first two simulation have following inputs:
Data: 614 trades
Distribution: Discrete! (I will do a simulation with fitted data distribution another time)
Iterations: 10.000
Initial Capital: 10.000
Let's have a look at the Standard Risk scenario (Sim 1): It tells: The probability that the Equity will not fall below 10.990 is 5% (after 100 trades done). Or: the probability that the equity will exceed 10.990 is 95%.
The last two lines shows the unexpected risk. 95% is the standard scenario risk. And 99% the stress scenario risk.
I have named it Value at Risk "Drawdown", because I compare it to real drawdown. This figure gives a orientation, when to stop a strategy in real trading (depending on your own risk appetite)
Notice: The calculation is totally different to real draw down calculation! Value at Risk "Drawdown" has a weakness, the the more trades, the smaller the VaR-DD (if strategy shows a positive expectancy). So I have to compare simulations with smaller amount of trades with simulation with higher amount of trades (sim 1 and sim 2).
Simulations with smaller number of trades is absolutely necessary. It gives you more detail about the risk. Because if you have a positive expectancy, naturally the end values of an Monte Carlo simulation will be better with higher number of trades.
Interpretation Example for VaR-DD: The probabilty that the drawdown is 39% or larger is 5%.
The most important figure for me is the VaR-DD. All other metrics is more or less playing with numbers.
@Kevin: I've first done a discrete distribution simulation, so that we can directly compare our figures. Could you do the same simulation with your method with the above inputs, so we can compare?
I can recommend SimulAr. I think it is inspired by @risk because the menu is designed very similar. It covers all basic functions and it is free (read the licences agreement!).
It is powerful Monte-Carlo Simulation add-on for Excel. If you think time is money, then @risk is the right tool (I think Oracle has also a risk tool, but I have never tested it).
