Forex Blog

Dollar declined today against the euro, allowing EUR/USD currency pair to rise above the last Friday’s open level. Currently it is trading near 1.4863 — 58 pips above Friday’s open. The decline was most probably caused by the investors’ concerns related to the U.S. financial market.

Initial jobless claims decreased from 445k to 432k last week in the United States — that’s below the median forecast 438k.

Leading indicators showed a more than expected declined posting a -0.7% change in July after 0.1% decline in June and 0.3% decline forecast for this month.

Philadelphia Fed index improved in August. It rose from -16.3 back in July to -12.7 this month. This growth exceeds the average estimate according to which the index should have risen to -13.4 only. Despite the growth it still remains at a very low negative level and is signaling a slowdown of the U.S. economy.

After saying so much about the statistical Forex systems, I think it’s time to give an example of one. But first, I have to warn that this exert advisor «as is» wasn’t profitable during tests — it had its losses and gains, but spread losses took over eventually, so I can’t suggest using it on your real money account. This expert advisor is good only as an example of an actual statistical Forex system. It uses Tom DeMark’s pivot points calculated over the last 5 bars, which are then normalized by subtracting the current Open price. I used it on EUR/USD H1 chart, but I believe that it can be used on any other currency pair and timeframe. It consists of two .mq4 files:

The first file is StatGathererExample.mq4 — as it appears from its name, this MetaTrader EA will only gather statistics. Run it via strategy tester on a 1-2 year history period (it doesn’t have to be a good quality history, because it has nothing to do with price ticks, and uses just your OHLC data from bars; just be sure to have enough bars in your chart). This EA gathers statistics over a period of time and stores it to MapPath file («rl.txt» by default) in your /tester/files/ directory. Copy it to /experts/files/ for further use by the actual expert advisor.

And the second file is StatRunnerExample.mq4 — this EA is used for the actual trading and on-the-fly statistics gathering. This EA uses MapPath file («rl.txt» by default) from your /tester/files/ (for strategy tester) or /experts/files/ (for actual use) to get the initial statistics. It also continues to gather its own statistics and appends it to the initial file, saving it after deinitilizing.

You can freely use these examples to construct your own statistical Forex systems. I am also currently developing a statistical expert advisor that would be profitable and I promise to share it after the testing period.

EUR/USD declined today for the fourth day as the producer price index was reported at a higher than expected level in the United States. Even the worsening of the housing market failed to press on the U.S. dollar today.

Building permits were at 937k in July down from 1,138k in June (revised up from 1,091k). They were expected to fall to 959k annual rate. There were 965k housing starts in July in U.S — down from 1,084k in June (revised up from 1,066k) and slightly above the forecast for July — 960k.

Producer price index (PPI) advanced 1.2% in July — below the 1.8% growth in June but twice as much as the average forecast of 0.6% for July.

The final part of my introduction into statistical Forex system development is dedicated to the complexity of the resulting expert advisor (or automated program if you want to create such strategy for anything else than MetaTrader platform).

When traders think about Forex system, they come to a conclusion that a simple trading system can’t be profitable, because it doesn’t capture all the market parameters that influence the dynamics of the currency pairs. Partially I agree with this point of view but, in my opinion, the complexity of a Forex system should be limited. With the statistical Forex systems the complexity of different parts may vary.

1. The amount of different information and the number of data types that is gathered for the statistical system are the important parameters, which if increased produce a more complex system. One may decide to gather not a single timeframe information, but rather statistics from several timeframes and record not only the price quotes (or OHLC data for bars/candles) but also many indicators, calculations and other parameters. This will lead to rather large database of the statistics that would be hard to interpret in a right way, but if interpreted correctly it will surely yield better results than a more simple strategy.
2. Gathering statistics before the actual strategy running is extremely important and is a necessary step, in my opinion. But making a system that can continue gathering statistics when it runs in a real-time is also important. It shouldn’t add much complexity to your expert advisor, but it will help to react faster on the market changes. Of course, such on-the-fly data gathering can’t substitute the pre-running gathering.
3. Changing the way of the interpretation and statistics comparing is a really advanced method to add the complexity to your statistical system. Having several functions to compare the past and the current data can be helpful if you have some method to choose from these functions. Personally I couldn’t develop a system that would use such an interesting functionality.
4. The complexity of the actual order carrying and position handling is a rather obvious field for the system improvement and upgrading, but it hardly can be connected to the statistics that can be gathered. The only way that would work, in my opinion, is if your system uses real chart-to-chart comparison - that’s a really difficult method, but it opens a whole new set of opportunities for position and order adjustment. In other cases, simple buy/sell/hold decisions are the best market actions available for the statistical Forex systems.

Those are the most obvious ways to make your trading system more complex. Some minor changes can also improve it to make it react more flexibly on the market volatility and evolution. If you have experience with really complex Forex systems that are based on the trading statistics, feel free to comment on this post.

After statistical Forex systems were introduced in my blog, I’ve described the problems of timeframe selection and statistics gathering. Now it’s time to discuss the decision making problem of such trading systems.

When a completed strategy has enough statistical information and a sample from the current market situation it should have some methods of comparing the statistical information with the sample and make the decision regarding its further actions on the market. For the majority of the systems these decisions would be limited only to buy, sell, hold and close previous position actions, while more advanced systems may include position adjustment actions into their arsenal.

The most obvious way to make the decision for the statistical Forex system is to calculate the differences between the sample data and the data stored in the statistics and the lowest difference will point out the most probable recorded outcome. For example, if you recorded RSI indicator values and the current RSI reading is 75.2, while the lowest difference from your statistics is 0.1 and it suggests that the price goes down near that RSI level, then your system should probably generate a sell signal. This method looks simple, but it’s also flawed as the comparing multiple parameters of the two samples is impossible.

In general, quotes-derived parameters should be compared with some method similar to Euclidean distance (best distance, average distance, etc.) with possible weighing of the different parameters according to their importance. Meanwhile, the comparison of the time- and fact-based parameters should be rather strict — e.g. if you recorded some information specific for Fridays and it’s Monday today, then you should disregard this information.

Another noteworthy idea regarding decision making would also require a special statistics gathering method used in the system. Using self-organizing maps (or Kohonen maps) is a popular decision making method that is widely used in finance. Unfortunately, my own tests of the self-organizing maps within the statistical Forex systems (in a form of MetaTrader expert advisor) didn’t bring any interesting results. There are many other ways of utilizing the self-organizing structures to store and compare the quote-derived statistical information, but their complexity doesn’t look to be necessary in such systems.

Chart-to-chart comparison can be used if the statistics stored is a raw or normalized market data, which brings a lot of opportunities based on the graphical chart analysis and the difference calculations. It’s also necessary to note that such comparison would require a lot more CPU power and time to complete. It would also produce a more long-term aimed result than the immediate decision that would be true for the next bar or candle.

In my opinion, it’s optimal strategy to store the statistics in three separate «containers», where statistics in the first container would correspond to the buy action, in the second — to the sell action and third — hold action. Finding the best Euclid distance for the current market sample among all three «containers» gives you a hint for your next action. In this case, it’s more important to collect the right data and to format it in a right way for further comparison.

EUR/USD trend: sell.
GBP/USD trend: sell.
USD/JPY trend: buy.
EUR/JPY trend: sell.

EUR/USD declined to its new minimum level since February 20 — 1.4700. Although it’s currently trading significantly above that level (at 1.4743), there’s a little doubt regarding further trend direction of this currency pair.

According to a report that was released today NY Empire State index rose to 2.8 in August compared to -4.9 in July. It was expected to decline to -5.0.

Net foreign purchases of the long-term U.S. securities declined in June — from $83.2 billion (revised down from $67 billion) to $53.4 billion. It appeared below $57.5 billion median forecast.

Industrial production gained 0.2% in July after 0.5% increase in June. It was expected to remain unchanged. Capacity utilization rose from 79.8% (revised down from 79.9%) to 79.9%, while average forecast was 79.8%.

Dollar rose today against the euro but EUR/USD pair still remained in a mainly sideways trend. A good report on CPI and a rather low decline in the initial jobless claims were mostly ignored during today’s trading session. EUR/USD is currently trading near 1.4901.

Seasonally adjusted CPI rate was at 0.8% in July — that’s below June’s 1.1%, but above the average forecast of 0.4%.

Initial jobless claims declined to 450,000 last week down from 460,000 a week before. Average estimate for this indicator was at 436,000.

EUR/USD rose slightly today, probably as a result of the technical correction processes that should have followed the recent rapid growth of the dollar. Today’s fundamental releases from U.S. were average and they couldn’t move the currency pair too far up or down. EUR/USD is currently trading at 1.4937 with the daily high still below the important level of resistance located at 1.5000.

Export and import prices gained 0.8% and 0.9% respectively in U.S. in July. That growth followed the 0.9% advancement on both indicators in June.

Retail sales dropped 0.1% in July. Although it’s quite a negative result, the markets were ready for it, because the average forecast was also at 0.1% decline. In June retail sales gained 0.1%.

Business inventories rose faster than expected this June — they advanced 0.7% after 0.3% in May and 0.6% growth forecast for June.

U.S. crude oil inventories decreased by 0.3 million barrels last week after gaining more than 1.6 million barrels a week earlier.

Although, EUR/USD moved slightly above its opening level, this currency pair remained highly volatile today and reached a new minimum record since February 26 at 1.4815. The bullish spiked reached 1.4964 level. It failed to break above the 1.5000 resistance which may form a new psychological roof level for the next couple of weeks.

Trade balance deficit shrank in June as the exports grew significantly faster than imports. The deficit decreased to $56.8 billion — down from $59.2 billion in May and below the pessimistic $61.9 billion forecast.

Treasury budget report for June showed $50.7 billion surplus compared to $36.4 billion deficit in June 2007. Economic strategists expected the widening of the deficit to $86.8 billion.