April Recap, Trend Signals, and FTMO

My last update post was for the week ending March 14th, 2025. Don’t worry, I haven’t stopped this series of end-of-week updates. 


Leading up to April, I was in preparation mode for back-to-back travels in early April. This was unfortunate because the first half of April saw quite a bit of volatility. When I came back from my travels in mid-April, volatility diminished, and I definitely felt a hit with the lack of entry signals.


That being said, I took this time to revisit my trading log in Excel and FTMO account. All the updates will be shared in this post.


April Recap - First Half


I’m going to split my April recap into two halves. The first half and second half had drastically different price action and signals.


In early April, there were very clean breaks, especially on the euro pairs. Unfortunately, I missed the bulk of these moves since I was traveling to two different cities. As a result, I definitely had FOMO and placed some trades that I shouldn’t have in the second half of April.


A quick recap of early April’s macro-economic events - President Trump announced “Liberation Day” around April 2nd, which entailed a series of new tariffs on most, if not all, US trading partners. An initial 10% tariff was imposed on all countries, with higher reciprocal tariffs placed on countries that exported significantly more to the US.


This escalated so quickly that an 145% tariff rate was imposed on China around April 10th. One point of view for all this madness is that President Trump wanted to accomplish one simple objective - to tank the markets and create a buying opportunity.


S&P500 Daily


Mission accomplished? It’s hard to say what the long-lasting effects are. Some take the stance that this will create new opportunities in European and Asian markets, while others believe this won’t impact the long-term investment potential of US companies.


My personal stance on the equity markets is to follow the money. US companies are certainly impacted by tariffs and will have to downward adjust their profitability metrics. However, they remain fundamentally sound, with a large consumer base and continued innovation push with AI advancements.


Moving onto the currency markets, a lot of euro currency pairs made clean breakouts. Due to my limited screen time, I was not able to mark these levels and capitalize on the moves.


EURUSD Daily


Taking a look at the EURUSD currency pair, there were two momentum plays - one on April 3rd and April 10th, respectively. The EMA20 rested above the EMA60, which indicated that buy entries placed would’ve been in the direction of the trend, according to my signal and entry rules.


April Recap - Second Half


Using the same EURUSD chart, we can see relatively stagnant volatility in the second half of April. By April 9th, we can see the US backtracking with a 90-day pause on tariffs for most countries (excluding China).


EURUSD Daily


As trade talks and negotiations appear to be underway, the markets have experienced a pause due to traders’ anticipation of the outcome. I didn’t notice any clean breakout signals, and the trades I did take resulted in quick reversals. April was undoubtedly a challenging market for trading.


EURSEK Daily


Even going into early May, volatility remains unpredictable. The EURSEK chart shows a trade that I entered. Under normal circumstances, momentum should’ve picked up, and I would’ve hit my take profit target of 0.5x ATR.


As soon as I took this trade, momentum died, and price went against me. There’s nothing that I really could’ve done, as the long-run expectancy should work in my favor for breakouts in the direction of the trend. When faced with a consecutive string of losses, I’ve become more sensitive to reduce my risk percentage.


Trade Log Results


This is a good segue into another topic that’s been on my mind for this post. Since the second half of April was not great, I decided to start analyzing the trade log that I’ve been maintaining.


I don’t think I talked about this in another post, but it was on my mind, so I went ahead and did it. I created a simple Excel sheet as a minimal-effort check to validate my entry rules prior to placing a trade. Below is a screenshot showing a portion of this Excel sheet.


Excel Log (Old)


Here is a summary of the parameters I tracked and why I did them.


  1. Date: enables time-based filtering, especially on a monthly basis
  2. Pair: enables analyzing performance and outcome by currency pairs
  3. DIR: identifies if I’m taking a trend or counter-trend signal, and enables analyzing the outcome of each signal
  4. Daily ATR: informs my take profit and stop loss placement
  5. TF Weekly: identifies trend direction and strength on the weekly timeframe
  6. TF Daily: identifies trend direction and strengthn on the daily timeframe
  7. TF Hourly: identifies trend direction and strength on the hourly timeframe
  8. Exhaustion: if price is breaching a major level, check to see if there was a pullback move; my thesis was exhuastion indicated stronger signal quality/breakout momentum since price failed to trade in the opposite direction
  9. Trade: signals long or short direction
  10. TP: take profit that was actually configured in the trade, usually 0.5x ATR
  11. SL: stop loss that was actually configured in the trade, usually 0.5x ATR
  12. Outcome: take profit hit, stop loss hit, manual close profit/loss


For example, let’s say I’m looking to place a “buy” trade on the EURUSD pair. If the EMA20 is above the EMA60 on the daily timeframe, then I consider this a trend trade. Counter-trend trades have a very specific trend-line breach to the opposite direction.


I would do a scan of the weekly, daily, and hourly timeframes to identify the trend direction on each. If the EMA20 is above the EMA60, then it’s considered “Up.” The second step is to classify the direction on each timeframe as strong or weak, and this is where it gets tricky.


If the direction is “up,” but the move isn’t very clean, then I would classify it as “up (weak).” However, this is a really subjective classification because I don’t have a standardized definition for what is considered “weak.”


I tracked the majority of my trades since February and compiled a data set of 110 trade entries. I used a pivot table to analyze relationships across these metrics, and here are the findings:


  1. There is no clear relationship between strong vs. weak trends and outcome
  2. There is no clear relationship across the timeframes and outcome
  3. Trend trades are twice as likely to hit take profit vs. stop loss as opposed to counter-trend trades, which have a take profit to stop loss ratio of 1:1
  4. Exhaustion = Yes did not yield a more positive outcome; therefore, my hypothesis that weakness in the opposite direction yielded stronger momentum moves is invalid


#3 is what I found most interesting. I thought that when trend failures, classified by “Counter-Trend,” I would be able to capitalize on strong moves in the opposite direction. If I kept doing this, I would’ve only achieved a win rate of 50%. If I focused only on taking trades in the direction of the trend, classified by “Trend,” I would’ve achieved a win rate of closer to 67%.


For the month of May, and the rest of this year, I will be focusing primarily on “Trend” trades. If the EMA20 is above the EMA60, I will only look for opportunities to trade upward momentum. I’ve already created a new tracker for this.


Another change that I’m making is tracking breakouts from major daily levels. This is another thesis that trades breaching daily levels should more reliably hit a positive take profit outcome. Below is a screenshot of my updated tracker.


Excel Log (New)


FTMO


The final update for this post is that I actually have been running an FTMO swing trading challenge for a few weeks now. I picked the Swing account because it allows me to hold trades through weekends and news. It’s not that I will actively be holding trades through weekends or news, but rather, it may take several hours or days for my trades to play out.


My FTMO account started strong. I kept my reward-to-risk ratio at 1 because each trade had a 0.5x ATR configured for the take profit and stop loss. My win rate was over 50% and my equity curve was on a steady climb.


Once mid-April hit, I took quite a string of losses. Admittedly, I did overtrade by entering positions based on lower quality signals. In addition, a lot of the counter-trend plays that I made did not pan out.


My account is still alive so there is potential to clawback and recover by:


  1. Focusing on trend trades, filtering out counter-trend signals
  2. Focusing on signal quality, and only going for structural breakouts


That being said, FTMO provided one very useful insight for me. For each trade, FTMO allows you to analyze MAE, or Maximum Adverse Excursion. This metric looks at how far the trade goes against you before the particular position is closed.


By analyzing all my trades, I learned something very insightful. For the trades that hit my take profit, the MAE metric was very low, less than 10 pips on average. This means that the trades that work out usually move in my favor very quickly and hardly move against me. 


Therefore, I can manually close a trade that moves against me for a smaller loss rather than letting it hit my stop loss. The stop loss is more of a protective measure in case I’m not in front of the screen to actively manage the trade in real time.


This was a great learning experience that I can exit my losing trades much more quickly.