Thursday, February 28, 2013

Relationship between drawdown and risk-reward ratios

Seasoned traders should already know this. Suppose you're given two systems with the same profit factor, but one uses a reward-to-risk of 2-to-1, while the other is 0.67-to-1.
 
Which system is better? Hopefully you'll answer the 0.67-to-1, even though most "gurus" suggest 2-to-1 or even greater. Why?
 
Both systems have the same profit factor. But this doesn't automatically mean that they behave the same. Systems with higher R:R ratios tend to suffer a drop in win rates. If you're losing more often, what does this mean? Yep, you're encountering drawdown more often.
 
To illustrate this point, I'll compare two systems that I've developed.
 
System A has a profit factor of 1.2, and uses a reward-to-risk of 2.5-to-1. Here is its equity curve, assuming a risk level of 1% equity per trade.

Here is System B's equity curve, using the same level of risk (1%).  System B has a lower profit factor, being 1.13, but it uses a reward-to-risk of 0.67-to-1.

 
Looking at the final result of each chart, it's clear that system A is more profitable. But doesn't the equity curve for system B look more linear as it progresses to the right? This is a good thing, as we want our equity curve to be as upwardly linear as possible (perfect linearity would suggest zero drawdown).
 
The maximum drawdown for system A was 24% while system B had 13%. It seems counter-intuitive to think that a system with a higher profit factor can have greater drawdown. While drawdown is influenced by your risk level (% equity per trade), it is also affected by your R:R ratio. A higher R:R ratio will usually result in more losses "clumping" together, leading to a higher drawdown.
 
My beliefs are that a 1-to-1 reward-to-risk will be most ideal, although I'm prepared to accept 2.5-to-1 all the way down to 0.25-to-1. I'll try to choose an R:R ratio within this range that'll provide the highest profit factor.
 
If you must trade extremely large R:R ratios, or follow trends with a trailing stop, I think it's best to risk a smaller amount of your equity to counter the "clumpiness" of your losses and reduce your drawdown.

Latest developments...

I'm just putting the finishing touches to a (hopefully) new trading system. I'll probably post more details over the next week. There's not much left to do, I've already tested 9 out of 11 currency pairs so I should have it wrapped up by tomorrow or Friday.

Wednesday, February 20, 2013

The trader's source of profits

While I was meditating by the river today, I thought about how traders exactly profit from the market. In order for a trader to win, someone else must "lose", right?
 
To a large extent, this is true. However, the market is an open system with a large variety of players, and not all players are profit-driven. Here is a (most-likely partial) list of profit sources for a trader:
 
  1. Negative-edge traders. These traders have a negative expectancy. Perhaps their trading methodology is flawed, or they may even have no methodology at all and are simply gambling. Whatever the case, every time they put on a trade, someone else profits. Unless they inject new funds regularly, these traders eventually blow up or quit.
  2. Risk-unmanaged traders. Trading is all about risk management. These particular traders may have a successful trading system or methodology, but end up losing due to poor risk management. They may risk too much per trade. They may only concentrate on only one system or currency pair. While they may have a positive edge on paper, some sort of systemic risk puts them in peril of blowing up.
  3. Discouraged positive-edge traders. I suspect that this is a significant source of profit. Even traders with a positive edge will encounter a nightmare period of drawdown during their career. If these traders become discouraged and quit the market permanently, their losses are crystalised into someone else's profit.
  4. Commercial players. These guys enter the market either to hedge prices or to accumulate forex reserves for their operations. Their actions on the forex market are not profit-driven, per se. This may grant traders an edge over commercial players, especially during large orders that move the market (every pip that moves against a commercial player equals profit for the counter-party i.e. traders).
 
I thought about including central banks and governments and the games they play, but these entities simply print money (or confiscate them from private citizens). When you profit from these entities, they're not really "losing".
 
Anyway, I threw this list out there. What other ways do traders profit from the market?

Thursday, February 14, 2013

Future of the blog...

Some regular vistors may've noticed the absence of my trade reviews for last week. There's a reason for that. My trading has become quite routine and I've found updating the blog over menial details a bit of a time-sink. I also work two jobs. This, in combination with relentless system development and backtesting, doesn't leave me with alot of time to do other things. It boils down to my return on time and regurgitating details from my personal trading journal doesn't provide much return to me.
 
I'll probably stop posting trade reviews unless one particularly catches my eye. Instead I'll focus more on "bigger picture" topics, insights and achievements I've attained.
 
On the system development front...
 
After investing three weeks investigating pinbars on the daily timeframe, I've designed a new trading system. All I need to do is type it up into an official document, and start trading it live next week. The sample size is a little over 600 trades across 11 currency pairs, from 2001 to mid-2012. The overall profit factor was 1.25. It's tradable.
 
Almost of my developed trading systems are based on price action. If you're stuck for ideas, price action is a good place to start. Design some mechanical rules to follow and backtest thoroughly. It really is as simple as that. The most difficult part is actually putting in the time to perform your backtest (and optimisation).

Thursday, February 7, 2013

What role do traders have in the market?

I got into a bit of a heated thread over at Babypips, regarding the role that traders play in the market.
 
There's a school of thought that traders and speculators serve no useful function since trading is a zero-sum activity and thus no wealth is actually being generated. This is somewhat misleading. If there are ONLY traders within a market, then yes, I believe it is a zero-sum activity and any wealth generation is arguable.
 
Of course, traders are not the only players in the market. We have corporations who participate in the market for operational reasons, whether it be to raise cash via an IPO, hedge their risk, or supply the market. We have mutual and retirement funds seeking long-term investments. We have debtors liquidating assets to balance their sheets. We have governments and central banks pulling fiscal and monetary levers to direct the economy.
 
Bearing this in mind, I believe the trader serves three useful functions in the market:
 
1) We increase liquidity. An illiquid market means higher transaction costs and longer times for orders to fill. By adding our liquidity, we decrease both and ensure a smoother, quicker and efficient market.
 
2) We provide risk management for risk-averse companies. It may be tedious, if not dangerous, for a company to see fluctuations in the price of raw materials or currencies. To hedge this risk, a company may lock in a futures contract, guaranteeing a stable price for the foreseeable future. Traders serve as a counter-party towards this hedge. Without traders, there may be no counter-parties, and thus no hedge, and companies will be disadvantaged.
 
3) We bring the market closer to equilibrium. Without our input, markets may be manipulated or distorted beyond reason. Our goal, as speculators, is to define what we consider "fair value" and bring the market towards this level. If we believe something is cheap, we buy. If it's too expensive, we short. We exit when price is at "fair value", having completed our duty in punishing any unwarranted hysteria or panic.

Monday, February 4, 2013

How to calculate profit factor across different currency pairs

I stumbled upon this by accident last month as I was reviewing my systems.

I normally develop my system via a simple process:

1) Develop a hypothesis to base my system on
2) Test my hypothesis against 11 currency pairs (the majors + Yen crosses) from 2001 to 2012

Every currency pair is unique,. Each pair is influenced by a unique set of technical and fundamental factors, so you'll never see perfect replication between two pairs. There will always be some correlation, but this correlation ebbs and flows.

Since each pair is more-or-less unique, I treat the data from each pair as a discrete set.

I will iterate my hypothesis across one set of data (currency pair), which in the end will provide me with important metrics like win% and profit factor.

Do this eleven times, and you'll have eleven profit factors describing each data set. If the hypothesis stands in the vast majority of data sets or currency pairs you test against, then you most likely have a robust tradable system.

In the past, I would then find the average of the eleven profit factors I've calculated, and assume that this averaged profit factor would describe the profitability of my new trading system.

Example:

Suppose you test an hypothesis or idea on two pairs, the USDCAD and AUDUSD. The profit factor for each pair is 1.5 and 2.0. Our averaged profit factor is thus 1.75, and it would make sense to think that the profit factor of our newly-developed trading system is 1.75 if we trade the USDCAD and AUDUSD.

This is errornous once you being to dissect the mathematics involved.

Suppose we test another idea against two pairs, EURUSD and GBPUSD. We collect ten sample trades from each pair using a 1:1 R:R.

With the EURUSD, we find that we win 1 trade, and lose 9. with 1:1 R:R, our profit factor is thus 1/9 = 0.11.

With the GBPUSD, it's the opposite and we find ourselves with 9 wins and 1 loss. Our profit factor is thus 9/1 = 9.

If we find the average profit factor from both pairs, we get (9 + 0.11)/2 = 4.55.

Wow! A trade system with a profict factor of 4.55 would be extremely good.

Intuitively, however, we know this is wrong. If we combine the results from both pairs, we have 10 wins and 10 losses using a 1:1 of R:R.

Therefore, to get an accurate answer, we must combine our wins and losses from each data set, and THEN compute our profit factor. In our case, 10 wins / 10 losses = 1.

This may be highly irrelevant to some traders, depending on how they trade or develop their own trading systems. For me personally, this is an important lesson.

The lesson: when you're combining data from different sets or currency pairs, calculate profit factor at the END. Don't take a shortcut and use the average.

Week in Review: 27th January 2013 to 2nd February 2013

Last week has been pretty good. I put in three trades and won them all.

TRADES IN REVIEW

GBPUSD

Saw an entry signal per my Daikoku system on the weekly chart, and won.


The GBPUSD closed last week with a strong bearish bias. I wouldn't be surprised if it continues to fall this week. But I took profit already so it doesn't quite matter.

USDCHF

I took two trades here.

The first trade resulted from an entry signal using my Daikoku system on the weekly chart. The result was a win.



My Hermes system provided an entry on the daily chart on the close of 28th Jan.


I took profit nice and early as my system suggested, but as you can see, price continued to fall for the rest of the week. This trade would've carried a nice 5:1 reward:risk if I had held on to it.