Getting the range wrong can drastically change the meaning! Your FX life will change dramatically with just 5000 yen — Series [Important Material] Part 7 = Analysis / Backtesting = About Understanding the Importance of Range

By the way, are you handling data accurately?

If your height and weight were off by two digits, what kind of data would that produce?

If the error is on the smaller side, height would be 1.6 cm and weight 600 g; on the larger side, height would be 160 m and weight 6 t.

Numbers can make a big difference in outcomes.

And this is not a joke; there are many situations in actual meetings where corrections are required.

When it comes to analysis or retroactive verification, some people suddenly forget the importance of these ranges.

For example, regarding data that has been aggregated, there are people who trust datasets where losses are not recorded and only win rate or profit is listed, or where there is no information on the overall distribution, average profit, average loss, consecutive wins, or consecutive losses—just a plain list of win/lose data.

These kinds of people, when purchasing an EA (Expert Advisor), imagine securing their own profits and their future self, and as a result of overloading the brain's processing capacity, become unable to consider the meaning of the data in front of them and enter a state of cognitive paralysis.

This time, together we will explore why such multidimensional data is necessary.

整理 of what was needed from the information just now.

1. Maximum loss and maximum profit

2. Individual losses and profits

3. Win rate

4. Average loss and average profit

5. Consecutive wins and losses

Among these, regarding 4. Average loss and average profit, we will provide a detailed explanation in the article [Important Materials Part]8=Analysis and Past Validation=Advantage by Averages to gauge superiority.

1. Let's explore the meaning from the maximum loss and maximum profit.

If, for example, there is data that does not record the maximum loss and displays only the maximum profit, would you believe it?

If you are convinced by the impact of, say, a 500-pip profit, you may fail to notice that there was a maximum loss of 2,500 pips.

Some people say it's okay because such losses occur only once every several years or ten years, but when you actually incur such losses, skipping several years of profits, you could say a withdrawal flag is raised.

In fact, I have never seen such people continue trading foreign exchange afterward.

Of course, looking at only this number, the win probability of Bursara bankruptcy risk is 0.2, so if the win rate is maintained at around 90%, the data shows total profit is possible, but if a single downturn erases a lot of profit, that is a problem.

The lack of maximum loss data makes the reliability of these numbers completely unreliable, which is dangerous to understand.

2. Let's look at individual losses and profits.

This is generally displayed for most data.

However, there are some malicious cases where the downturn is deleted and connected, so not impossible.

This data is extremely important for calculating averages and distributions.

If this data is deceived, it becomes difficult to notice even if other elements' reliability is manipulated.

Therefore, for this data, you must confirm the logic and basis on which trades were repeatedly made—this one point is essential.

Then, even if there were tampering, you can extract problems by actually performing past validation on the same data period.

3. Regarding the win rate.

Many beginners fixate on this number.

Those who learned about the bankruptcy probability of Bursara should understand that as long as everything is balanced, the problems can be managed.

Still, isn’t it necessary to understand at least the basics?

For example, if there is a trade with a win rate of 70% and an risk-reward ratio of 0.5, and you conduct 10 trials with a profit of 10 pips per win, then with 7 wins you gain 70 pips, while the remaining 3 losses lose 20 pips each, totaling a net of 10 pips profit.

As long as this figure is maintained, trading is in a normal, problem-free range.

Thus you can understand that a higher win rate is not necessarily better.

However, if even a low win rate makes it impossible to maintain an edge in trading, adjustments become difficult to manage.

In that sense, weaving some higher-win-rate trades into the mix makes averages easier to adjust and maintain.

5. Let's think about consecutive wins and losses.

This number shows how much win rate and average you can expect to maintain performance even in random conditions.

For example, if the number of consecutive wins is 6 and consecutive losses is 4, the win rate is about 60%, and if the profit ratio is 1, the profit calculation would be the same as before: 6 times 10 pips equals 60 pips, and 4 losses of 10 pips each equal -40 pips, for a net performance of 20 pips.

In reality, even trades that are negative can have elements that produce this performance, and by identifying the conditions to avoid losses, total profit can stabilize.

Also, having this number leaning toward profits can ease the mental burden.

Being able to trade with confidence is another important factor when trading.

By examining each data from various angles, you come to realize the risks that appear when this data is missing.

And such data are not only numbers but can be visualized in graphs, making its progression visible.

If you leave traces of win rate, cumulative, and averages using line graphs or distribution charts, you can identify which trades had a broad impact on the overall performance, and for that trade, what measures you should take to avoid such losses in the future; only through such corrections can you truly utilize the data.

Moreover, among various informational products, there are people who claim fraud at the slightest irregularity, but if you cannot provide the necessary data, that is understandable; it would be premature to call the data that doesn't work a fraud.

As mentioned earlier, even a chart that shows losses can be avoided by identifying the conditions at the point where the loss occurred.

Then the data can become completely different.

If there is something that allows you to compare the base data with the finally improved data, you should consider using such data and avoid making inappropriate statements as an analyst.

Questioning the level of analysis means you may be suspected as a failed investor.

What you must do is not to fall into a thinking halt and indulge in profits or fantasies.

Utilize the data in front of you accurately and properly, and transform it into your own profits through analysis and refinement.

With that, this learning ends for now. See you next time.