It’s been two days since the fateful day when I blew up my account.

I’ve spent that time trying to ween myself off the markets. I don’t have charts up permanently and I don’t have to keep monitoring Bloomberg constantly. I still pop up the charts occasionally, out of morbid curiosity more than anything else, to see if the markets kept going against me or if they finally turned around. AUD-USD seems to have made a stab moving back up, most likely linked to the slight rise in gold, while the euro is still languishing away.

It’s amazing how powerful the urge to just get back in there and try to fix things is. I know that doing any such thing would be absolutely wrong, but it doesn’t prevent my mind trying to fix whatever is broken in my trading methodology as quickly as possible.

It was especially curious on Wednesday and Thursday when I found myself mentally reviewing technical indicators that I have favourable tendencies towards (i.e. ones that I consider to have at least some worth). The technical indicators in question generally come from work done by Joe DiNapoli or Joe Ross.

I would throw up a 3×3 Displaced Moving Average on the chart or try to visualise how well a Ross Hook would have worked. I’d be looking at the charts from the past two months trying to see whether these indicators would have been any help in averting where I have ended up.

I don’t think there’s anything wrong or bad in doing this.

What does strike me is that in doing this I am probably looking for certainty. I’m feeling lost at sea Every part of my trading methodology is now in question and will have to be closely examined to determine if it is still fit to stick around.

Technical indicators are visual and ever present right there on the chart. You can build hard and fast rules up around them.

Except that deep down I really do know that the certainty that they supposedly represent is just an illusion. I’ve gone through this flailing around and fight with uncertainty before. I’m sure I’ll have further relapses in the future. For now I just have to let them wash over me until their eerie, seductive pull abates.

Trading is uncertainty. It is risk and randomness and chaos.

What can be tamed and controlled is me. I am the key to unlocking consistent money from the markets.

I am the one who is responsible for blowing up my account. The market didn’t take my money. My broker didn’t cheat me out of it. I’m the one who pulled the trigger on the trades. I’m the one who decided what and when to buy. I’m the one who didn’t have a disaster money management plan in place. I’m the one who ended up trading over leveraged positions. I’m the one who let things build up to breaking point. I’m the one who didn’t step back and take a break when I started to make poor trading decisions. I’m the one who didn’t want to cut his losses in the face of a correction that I knew was coming. The responsibility lies solely with me.

The power to fix things and turn them around also lies with me.

Going forward I need to be critical of my current trading plan but I don’t want to throw out the baby with the bath water.

There are many strengths to my current trading plan, aspects of viewing the markets and trading them that suit me well.

There are also now obvious weaknesses that I must remedy to eliminate or mitigate against. These mainly lie in the money management and psychological aspects of my trading. My thoughts on implementing a fixed 100 pip stop loss on every trade is obviously one of the main cures I’m looking at for my money management woes.

On the psychological side of things I’m thinking that I really need to enact a positive feedback cycle. When I do well in a given month I need to have more than just the satisfaction of my trading account being up going into the next month.

A potential course of action that I am seriously considering taking is to withdrawal somewhere around 25% of the profits during a month. When that 25% of profits comes out I’ll have to put aside the tax due on that amount, but I’ll also be able to do something with money that I’ve actually made trading. I’ll be able to take my wife out for dinner, or buy a video game. By turning my successful trading activities into something tangible and real I’ll be able to reinforce the positive aspects of what I’m doing. I’m hoping that it will help to keep me energised and positive going forward.

The only downside is that these monthly withdrawals will diminish the compounding growth of my trading account. Of course if it prevents the possibility of another blow up from ever occurring again then it will have been well worth it.

Looking to take monthly withdrawals from profits made also presents a major shift in my long-term trading objectives.

I am sure that I’m not the only aspiring trader who has the goal of becoming a full-time forex trader. Earlier this month I would have said that if I was able to keep to my consistent returns of the past year I might be able to reach that goal in two, maybe three years.

Funny how things can change so dramatically.

After what happened on Wednesday I now have to face the stark reality that while my goal is still achievable, it is rather further off then I had previously thought.

I need to have a change in perception. Instead of my trading activities being solely dedicated to reaching the goal of being a full-time trader I want to switch and view trading as an active part of my life right now. Shooting for only the full-time trading goal is an all or nothing prospect. I either am or am not a full-time trader. The longer I solely focus on just that the longer the negativity of what I am not weighs on me.

A change in perspective is sorely needed. If I can withdraw profits every month consistently then I become a consistent, profitable trader now. I will get to benefit from any success I have now. The long-term goal of becoming a full-time trader can remain in place but I able to enjoy the fruits of my labours along the way.

I think this change is going to be a crucial underpinning of my trading going forward.

I certainly don’t hate my current full-time job. It has its highs and lows just like most jobs I guess. It even has its fun and sense of accomplishment when something turns out well. By only focusing on the trading as a full-time gig as-soon-as-possible scenario I have not paid as much attention to what my goals were with the regular job. If I was going to be doing nothing but trading soon then there wasn’t much need, or so I thought.

Now I see that there is a need to keep things in balance. It is foolhardy to ignore trying to advance my non-trading career.

I am also going to get back to some other hobbies that I used to love. I often spend so much time trading that I neglect other activities that I really enjoy doing.

I need to focus more on living and enjoying the here and now. If I can purge the weaknesses from my trading plan and play to my strengths then my goals will become reality in time.

I need to enjoy the journey and not focus so much on the destination.

Happy holidays. I hope everyone is able to have a joyous time with family and friends as we count down to the end of 2007.

I have been working on three documents. The first of these documents is my trading plan which I wrote again from scratch. Dirk provides a very nice trading blueprint template that can be filled out and customised to be your very own trading plan.

I originally completed one of these blueprint templates in 2006 shortly after I started demo trading the 4×1 methodology. The blueprint has been updated since then, and now includes some major revisions that were not present in the first version that I received.

I completed the latest version of the blueprint template without even looking at what I had written last year. When I compare the newly completed version to the one I wrote last year it is rather striking how similar my responses are to questions and sections that exist in both versions of the template. I see this as a rather good sign; I have not had to radically overhaul any aspect of my trading in that time.

The second document I completed was an evaluation of my trading using the median grid system to date. I have over twenty months of experience using the median grid trading system, so there was an awful lot of trading to cover during this evaluation process. Part of this evaluation was detailing how my trades worked out. This was going to involve extracting some statistics about my live trading over the past seventeen months (the other three months were spent demo trading). The easiest way to accomplish this was to put together a comprehensive spreadsheet detailing all my trades during that period.

To complete the evaluation document I therefore needed to construct a third document: a trading record.

The remainder of this post is going to shine some light into the murky depths of my trading and expose some of the statistics that I have uncovered. The following statistics have been compiled from my live trade records dating from 6 June, 2006 to 31 October, 2007.

Overview statistics

Let’s start off with some numbers that detail the overall trading landscape that I ventured through.

I had 141 profitable trades during the seventeen months, with 31 losing trades. That means I had 81.98% profitable trades, while 18.02% were losers.

I have made 8571 gross positive pips (from winning trades). Gross negative pips amount to 4996. This results in a net gain of 3575 pips overall.

My average pip gain was 52 pips. My average pip amount on a losing trade was -141.

If I break those same statistics down between the two years involved the following is revealed:

2006 (remember this contains seven months of trades)
Profitable trades: 61
Losing trades: 12
% profitable trades: 83.56%
% losing trades: 16.44%
Average pip gain: 43
Average pip loss: -152

2007 (this contains ten months of trading so far)
Profitable trades: 80
Losing trades: 19
% profitable trades: 80.81%
% losing trades: 19.19%
Average pip gain: 58
Average pip loss: -133

Drawdown
Drawdown is an extremely important statistic to keep on eye on. Drawdown measures the decline from an historical peak in some variable. In this case, the variable being measured is my trading capital. Drawdown is an indicator of risk which is why it is important to measure it. The greater the drawdown the riskier the trading method or system.

My maximum drawdown was -12.51%. The longest drawdown period I experienced lasted for 91 days (this is the longest time it took to reach a new equity watermark high).

Let’s once again breakdown the drawdown statistics for 2006 and 2007 so far:

2006
Maximum drawdown: -8.69%
Maximum drawdown time: 59 days

2007
Maximum drawdown: -12.15%
Maximum drawdown time: 91 days

Standard measures
There are some well-known financial measurements that I would like to cover next. These include CAGR%, the Sharpe Ratio and MAR ratio.

CAGR%
CAGR% stands for Compounded Annual Growth Rate and is also known as the geometric average return. It reflects the rate of growth that when compounded equally over the specific period would have resulted in identical ending equity. A weakness in this measurement is that it can be greatly affected by a single period of unusually high or low returns.

My CAGR% is currently 60.64%.

Sharpe ratio
The Sharpe ratio is an excellent measure of risk/reward in comparing stock portfolio management strategies. It is not an entirely relevant measure for something such as forex trading. The Sharpe ratio was specifically designed as a measure for comparing the performance of mutual funds. With that severe limitation in mind I still calculated the Sharpe ratio of my performance as it is an almost universal metric when calculating trading statistics. Just do not forget that using a Sharpe ratio to compare between anything other than mutual funds is all but pointless.

Note: in my Sharpe ratio calculation I am not including the risk-free rate of return value as this value changes with time and a different risk-free instrument can be chosen by everyone. So it just complicates even more the ability to use this ratio meaningfully outside of this explicit context. As long as I am consistent in not using the risk-free rate of return value in future calculations of the Sharpe ratio then I will not skew attempts when comparing past, present and future calculations of this value.

My Sharpe ratio is currently 1.69.

MAR ratio
The MAR ratio was developed by Managed Accounts Reports, LLC, and is normally used to report on the performance of hedge funds. The MAR ratio divides the annual return by the largest drawdown. It serves as a quick and dirty risk/reward measurement. The same measurement seems to be named the SOL Quotient by Rob Booker.

My MAR ratio/SOL Quotient is 6.44.

2006
Annual return: 14.05%
Sharpe ratio: 1.81
MAR ratio: 3.16

2007
Annual return: 126.26%
Sharpe ratio: 3.39
MAR ratio: 13.40

Robust measures
I’m now going to cover a group of measurements that I came across in Way of the Turtle by Curtis Faith. They all aim to eliminate the weaknesses inherent in the previous three measurements, which can all be impacted terribly by the start and end dates of the trade data used in their calculation. In effect, the measurements for CAGR% and the Sharpe ratio can often be skewed substantially by even small changes in the start and end points of the data set.

The real culprit is CAGR%, as this measurement is used in both the Sharpe ratio and the MAR ratio. The reason CAGR% is sensitive to changes in start and end dates is that it represents the slope of the smooth line that goes from the start of the test to the end of the test period on a logarithmic graph. If you change the start and end points then the slope of that line can be dramatically altered.

Regressed Annual Return (RAR%)
A better measure of the slope is a simple linear regression of all the points in that line. A linear regression line is otherwise known as a best fit line. Using a linear regression on my equity returns results in what Curtis Faith calls the regressed annual return, or RAR%. This measurement is much less sensitive to changes in the data at either end of the test period.

My RAR% is 79.76%.

Robust Sharpe ratio
The Robust Sharpe ratio is calculated in the same way as the original Sharpe ratio but for one small change: the CAGR% value in the original calculation is substituted for the newly calculated RAR% value instead. This makes the Robust Sharpe ratio much less sensitive to changes in the data set for the same reason that the RAR% measurement is less sensitive than CAGR%.

My Robust Sharpe ratio is 2.22.

R-Cubed
The final new robust measurement is called the robust risk/reward ratio (RRRR). It is a more robust version of the original MAR ratio. R-cubed uses RAR% in the numerator and a new measure that Curtis Faith calls the length-adjusted average maximum drawdown in the denominator (phew!).

Let’s take a look at this new denominator in more detail. It is composed of two components: the average maximum drawdown and the average drawdown period.

Curtis Faith recommends calculating the averages for both the drawdown amount and period by using five values and dividing by five. I do not have enough medium to large drawdown periods in my trade history to make that viable, so I have used three instead.

I calculated the average drawdown amount by taking my three largest drawdowns for the period being calculated and averaging them.

I did the same thing for the drawdown period: I took the three longest drawdown periods and averaged them. You then take this drawdown period (which is in days) and divide it by 365 so as to express it as a ratio.

The final calculation looks like this: RAR% / ( (average drawdown) x (average drawdown period / 365) )

The R-cubed measure is sensitive to the addition or removal of large drawdowns but less sensitive than is the MAR ratio.

My R-cubed is 39.97.

2006
RAR%: 18.69%
Robust Sharpe ratio: 2.40
R-cubed: 20.85

2007
RAR%: 65.42%
Robust Sharpe ratio: 1.75
R-cubed: 55.15

Making sense of the measurements
These measurements, both the standard and robust ones, are not that interesting or relevant in and of themselves. They are best used when compared to something. Since I don’t have statistics for anyone else to compare myself with, I am left with comparing against myself. This means that I will be comparing my performance over time.

Am I getting better or worse?

I’ll be able to track the things that are having the most impact on my trading performance. Are my returns getting better? Are my drawdowns improved in both size and length?

It’ll probably take another couple of years of data to be able to have a meaningful history to wade through but in the mean time I’ll be able to keep track of things as they occur.

Even more statistics
As well as all these standard and robust measurements I have also calculated various statistics that directly pertain to the grid system that I use. I have broken down which grid each trade entry was made in and what my resulting profit or loss was for that trade.

Using this data I’m able to get a snapshot of where the majority of entries have been made. I’m also able to see from which quadrant most of my losing trades originate, as well as my small, medium and large profitable trades. It’s something that I’ve been curious about and have been meaning to undertake for quite a while, so I’m glad that I actually got around to doing it and now have some hard numbers to look at.

I think that’s enough statistics for now!

• Q4: 1:1 -> 2:1
• Q3: 2:1 -> 4:1
• Q2: 3:1 -> 6:1
• Q1 4:1 -> 8:1

Another recent change to my trading plan has been the introduction of USD-JPY to my trading roster. It is currently unclear whether the carry trade is really dead and buried; it seems to be on life support at the moment, with a tug of war going on with carry trade believers testing the waters against those who think the carry trade is finished.

If I wait till this struggle is over I’ll potentially miss out on some significant strengthening of the Japanese Yen. My opinion is that the yen has enough legs to appreciate considerably over the next six to twelve months, even taking into account the indecisive Japanese economic data.

Doubling the number of currency pairs being traded while also doubling my gearing has been nagging at me lately; it seems to be taking on too much risk too quickly.

To that end I am going to be scaling back my gearing. I’m going to split the difference and set my gearing levels to:

• Q4: 1.5:1
• Q3: 3:1
• Q2: 4.5:1
• Q1: 6:1

Another recent addition to my trading strategy has been the introduction and usage of the Anti-Hedge trade (as termed by Jacko on Forex Factory). This tactic is nothing more than re-entering a trade at the point at which it had been stopped out. You cut your loss early but are unafraid to put that trade back on once price is moving back in the direction of the main trend.

I have thinking if it would be possible to make greater use of this approach. One of the main reasons for using low geared trades in the upper quadrants of my grid is to be able to hold those trades open if price goes against me. I have generally held those upper quadrant trades open up to 200 pips against me; trying to give them breathing room before taking my loss when price is far below the price I had originally entered at. What I need to do is to check my trade history and try to determine if holding those trades open for an extended period of time has been worth it. My gut feeling is that if price has generally gone more than 100 pips against me in the past then, in the majority of cases, I have had to close out those trades at the 200 pip marker.

Would I be better off just cutting those trades short earlier on? Employing the Anti-Hedge entry technique I will now always re-enter those trades once price comes back to the stop-loss price.

Using the Anti-Hedge method there will of course be times when my stop loss is hit and price then immediately surges back in the main trend direction. I will therefore have taken a loss without price having continued its correction.

In the instances when price does continue with its correction against the main trend then I will have cut my losses early and will have kept more of my trading capital intact for when the main trend does resume.

Another potential positive to not holding positions open against me so far into the red is that I could slightly increase the gearing of my Q3 and Q4 trades. Bread and butter trades in the upper half of the grid are currently nowhere near as profitable as those in the lower half, purely due to the much lower gearing of those entries.

Should I cut my Q3 and Q4 trades much earlier if they are going against me? Would it be advantageous to increase the gearing of my Q3 and Q4 trades knowing that tighter stops are in place and the use of the Anti-Hedge technique is going to get me back in?

These are the sorts of questions currently percolating in the back of my mind. I’m leaving it to my subconscious to sort through all the options. I’m sure that over the coming days and weeks I’ll decide which way to go.

Thanks for your reply. I’m a little confused about guaging the fundamentals – what is the time frame for the fundamental outlook? Is it the long term fundamentals (like 5-10 years) or is it like what the monthly sentiment is after a slew of news events? Maybe if you could provide an example or your “routine” (if any) to approaching fundamentals.

Thanks for answering my questions – I really appreciate it. I’m trying to decide whether I should follow through with studying this method, and your answers are helping me decide.

The time frame I use for my fundamental outlook has a time horizon of three to six months. I’m generally trying to gauge what price might do in those next few months. Anything beyond that goes back into pure randomness for me; pure guesswork.

I don’t have a predefined routine for how I approach the fundamentals. Maybe if I was doing this fulltime I’d lock down a more definitive approach, but I seem to keep it pretty lose. I follow a basic set of daily reports (Daily Pfennig, etc, which I’ve previously mentioned in my blog a few times) and weekly news periodicals (The Economist). There’s no real secret to getting to grips with the fundamentals; it’s more a case of just getting into the flow of things. Once you see the same economic data reports cropping up month after month they become familiar and pedestrian. It becomes easier to see the ebb and flow in the strength of the two currencies that make up the pair you’re interested in.

Price can generally be said to be either trending or range bound, so it is possible to say that there is no trend at a particular point in time. It’s important to also keep in mind that time is the other axis when looking at any chart, and so changing the time scale of your chart will make a seemingly strong trend on the one hour chart turn into a range bound market on the daily chart. Any time you look to identify a trend you also need to be aware of what time frame you are looking at.

Using the 4×1 methodology you aim to extract profits from the market when it is going in your favour (trending in your one direction) as well as when it is range bound. If your one direction is generally right, then you only end up losing money during strong corrections.

Obviously when you’re trading on the hard right edge you have to continually question whether the supposed correction is just that or is it the beginning of a trend in the opposite direction. This is where your interpretation of the fundamentals comes into play. Your strength of conviction in how you see the fundamentals overlaid on your one direction will play an important part in how actively you trade and take new positions. For example, if a correction is unfolding and your analysis is still strongly in favour of your one direction then you should have no problems buying the dips. You are effectively on the look out for a base to form, ready to benefit from price resuming its long term trend. On the other hand if you see mixed data and your conviction about your one direction looks in question you might hold back more on your trading activity until either more data makes things clearer or price makes the trend or lack of it evident.

It’s important to remember that any currency pair is made up of two currencies; it’s the relative strength of the two currencies that results in the current price. Both currencies might have strong fundamentals. If so, what you need to determine is which one has the stronger fundies. Which one is stronger relative to the other? It’s generally easier if one currency is strong and the other is weak. Similarly, if both have weak fundies, it comes down to determining the relative difference between the levels of weakness.

When any data release comes out, you try to see how that piece of the jigsaw puzzle affects the strength or weakness of the affected currency. And then try and see if you can read how it will play out in the relative strength/weakness between your two currencies.

It is the relative nature between the two currencies that is key. In the same way that speed is something that can only be measured relative to something else. We generally measure the speed of a car relative to how fast it is moving compared to the Earth. Let’s equate the speed of our car to the strength of currency A. Now let’s introduce another car which is moving parallel to our first car, but at a different speed. I’ll equate this second car to currency B. The way to determine the relative strength between the two currencies A and B is just like determining the speed difference between the two cars.

Before I tackle that question I’d like to quickly recap how I handled the events of Friday’s NFP release.

Price didn’t make it into the lower half of Q3 during Friday’s London session; instead it just hung around the 1.3550 level. That was good enough for me and I entered a Q3 position at 1.3561.

The headline NFP employment change number was only 88,000 with a downward revision for the previous two months. These were the first downward revisions in quite a long time. Coupled with the slightly weaker than expected headline number we saw a pop in the euro to just above 1.36. Some profit taking took things to just below 1.36 again, but price stablised and remained at that level going into the weekend.

Both the Fed and the ECB will make interest rate decisions this coming week. How I trade this week will depend on how price plays out in the run-up to these announcements. If the euro stays stong, well in the 1.36 range, then I’m going to be wary of a ‘sell the fact’ scenario unfolding if the ECB does raise rates this week. On the other hand, if the euro fades back down to 1.35 or below then I think that a ECB rate hike could easily bounce the euro back up to its recent highs and maybe even into 1.37 territory.

With my quick market analysis out of the way, let me answer my initial question of whether my prediction for the NFP release was luck or skill.

I don’t really see it as either to be honest. What I wrote in my last post was more a plan of action. I reckoned that there was a good chance that the NFP would not be a great number. No surprises there, as neither did any of the economists who were polled to generate the consensus number. A duff number after a week of mildly positive US data offered a good probability setup that price would venture back up above 1.36.

The key phrase there is ‘good probability setup’. I didn’t know for certain, nor did I have any concrete expectations, that price would go back up on an in-line or slighly weaker than expected data release. I did feel that there was a better than 50-50 chance that it would, based on my own observations and research. Someone else with a different viewpoint could easily have reached the opposite conclusion. Those people who do reach those opposing viewpoints are an absolute necessity in the trading world. They’re the people that take the opposite side of your trade.

I am currently reading Way of the Turtle by Curtis Faith, who was one of the original Turtle traders. While the book primarily takes the approach of a mechanical or systematic trader, he offers many valuable insights into the world of trading that any trader can learn from.

He dedicates a chapter to examining the four major sources of discrepancies that traders often find between their historical test results and what actually happens when they trade live. One of these four sources is the effect of randomness. How much of a role does pure random chance play?

Another way to answer my question at the beginning of this post is given by Curis Faith when he writes:

When you are looking at a short-term track record, you should realize that much of what you are seeing is attributable to luck. If you want to know whether a particular trader is one of the lucky average or one of the excellent few, you need to dig deeper than the track record and focus on the people behind the track record.

Good investors invest in people, not historical performance. They know how to identify traits that will lead to excellent performance in the future, and they know how to identify traits that are indicative of average trading ability. This is the best way to overcome random effects.

Not to make it sound like I’m repeating myself, but I also try to make this point clearly on the page where I detail my past performance.