This made me curious back then. Is day trading really just gambling? Was I wasting my time? In this video, I want to test his arguments. The guru said that there are 2 reasons why day trading is like gambling.
He explained the first thing by giving an example of two people: one is a fundamental analyst, and the other is a day trader. A fundamental analyst researches companies and makes decisions based on that information. They look at what the company does, what it will do in the future, how much money it makes, and what its previous earnings were.
On the other hand, a day trader puts their favourite indicator on the chart and uses that to make decisions. If there is a crossover on the chart, they make a trade. The trading expert on the news channel argued that this doesn’t make sense and is nothing more than gambling. He said that you couldn’t predict the direction of the market in short time frames as you can in longer time frames.
For example, if a company is doing well and making progress, its stock price will go up. If you do good fundamental analysis and think that the company will continue to do well based on its data (like if it’s releasing a new product that will be popular), then you can predict that its stock price will go up.
A company’s progress is a key factor in driving its stock price upwards. Through fundamental analysis, which relies on long-term information, there is a strong likelihood that the stock price will increase as the company performs well.
Many Day traders, on the other hand, don’t pay attention to this information. They don’t care about what the company does or how it’s doing. It’s like gambling in a casino, the news trading guru said. You place a bet, and if you’re lucky, you win. If not, you lose.
The second main reason why the guru said day trading was gambling was this:
There are many different types of people who participate in the stock market. Some trade in longer time frames, while others trade in shorter time frames. Some do swing trading, and some do day trading. Some people invest for a long time, while others exit their positions quickly. Some people use algorithms to trade, while others trade based on their emotions.
All these different types of people executing different trading techniques at the same time in the market create what’s called “market noise.” People who trade in longer time frames don’t pay attention to what’s happening in shorter time frames. They don’t care if the market is going up or down in the short term. They make their decisions based on their own time frame.
Investors also don’t pay much attention to technical analysis. If there is a technical pattern that suggests they should sell, they might not care if they are looking to buy for the longer term. This difference in thinking between technical traders and fundamental traders also creates market noise.
Market noise is also known as randomness. It is more visible in shorter time frames. This is what the trading expert on the news channel said was making day trading just like gambling. But is he right?
To test the trading expert’s ideas, I created my own stock market simulation. If he is right, then we should be able to create random noise in the stock market and see what it looks like. If the random noise looks like a good trend or a technical pattern in shorter time frames, then I’m afraid we can say that a technical trader might place trades based on those patterns. If that’s the case, then the trading expert might be right.
But let’s see what it looks like in reality. I wrote a code in Python to do this. The code has two parts: one part simulates different types of people executing different trading techniques on different timeframes at the same time in the market. Basically, creating randomness or market noise, and the other part shows it in different time frames, like stock market prices.
I simulated 1440 random noise candles to create an entire day’s worth of price movement. This means we can look at time frames from 1 minute to 1 day using this Python script. We want to see if we create noise in 1 day. Can we see a trend or pattern in shorter time frames?
So let’s run the code and see what happens. The charts have opened, and this is the chart for 1 day. The candles opened at 100, and the highest price was 132, while the lowest price was 87. It finally closed at 130. After opening, the price moved up and down before finally closing at the top. This is a bullish candle for 1 day. Remember that this is all randomness, just like the real market noise.
Now let’s see what this randomness looks like in a 4-hour time frame. We can see that the price went down, then up, then up again. Interestingly, this looks like a strong bullish move. But this is all just randomness.
In the 2-hour time frame, we can see that the price went up, then down, then up and down and up again. There isn’t a clear pattern yet. We can see a bullish engulfing candle being formed, and then the price went up. Some people might say that the bullish engulfing candle pattern worked because the price went up after it formed.
But since we know that this is just randomness, it doesn’t really mean anything. If someone had made a trade based on this pattern, they would have been gambling. But this is just a small example from the 2-hour time frame.
Let’s look at shorter time frames to see if we can find more patterns. In the 1-hour time frame, we can see that there are 3 candlestick patterns formed, similar to a buy entry signal we see in many candlestick guides. There is an engulfing pattern and something that looks like a doji. The price went down strongly, then slowed down, formed a doji, and then gave a bullish entry sign.
If you had made a trade after this bullish engulfing pattern and placed a stop loss under the entry candle, you could have made a good profit. But again, this is just randomness similar to the real market noise day traders encounter every day.
In the 30-minute time frame, we can see something that looks like an uptrend. It’s not a clear uptrend yet, but even in this price pattern, we can see an upward swing, a downward swing, a higher high, a higher low, and another higher high.
Things get even spicier when we switch to the 5 min timeframe because it actually looks like a normal chart. Some day traders might say that the uptrend is clear.
If we added indicators like RSI and MACD, someone might say that there is even an entry point. Someone might try to enter at the breakout of the trend.
But this is nothing compared to the 1-minute chart. If I had shown you this chart at the start of this video, I doubt any of us would have been able to tell that this was all randomly generated. I’ll zoom in a little so we can see better. Here, we can see something that looks like an uptrend pattern. The price went up and down without forming any clear patterns until it reached this point. From here, we can see higher highs and higher lows.
This part some might call ranging or choppy. If we go further to the right, we can see that another trend-like pattern is forming. It’s even clearer here.
Let me zoom in a bit on the chart. We can see that the price goes up and forms a higher high, then a lower high, and then another higher high. Near the previous higher high, another lower high is formed. This creates a support area according to price action.
And look, there’s an entry pattern. Here, we can see a candlestick pattern forming: a bullish engulfing pattern. Price action traders often make long trades based on this pattern.
So if we showed this chart to a price action trader without telling them that it was just random market noise, do you think they would make a trade based on this entry pattern? The price is making an uptrend and forming a trend pattern. On top of that, an engulfing pattern is formed near the previous support. I bet many day traders would because even I myself would.
If someone had entered a trade here, they would have made a good profit. If they had placed a stop loss here below the support, they would have made 3-4 times their initial investment.
If you said yes, that a price action trader would make a trade here if they weren’t told that it was just market noise, then was the trading expert on the news channel I saw many years ago actually right?
If market noise can look like a trend or an entry pattern in shorter time frames, does that mean that trading in shorter time frames is just gambling? Are traders who trade in shorter time frames, such as 1 minute, just gambling?
When I first started trading, I also traded in shorter time frames. I used price action strategies, but my profit graph was pretty much flat most of the time. When it went up, it wasn’t consistent like an uptrend.
I followed all the rules and managed my money well, but still, the progress was slow. Then after hearing about market noise, I decided to try trading on higher time frames, such as 30 minutes and above.
After switching to the 30-minute time frame, the exact same thing I was doing on the smaller timeframes worked more often. The market respected the price structures, such as support resistance, and my price action entries more. As a result, my profit graph started to move up better than before.
In my experience, what the trading expert said was mostly true. I say mostly because now, after gaining many years of live trading experience, I have also learned what works on smaller timeframes that are not gambling. If you remember, I even had multiple green days in a row and a very high win rate even after trading on the smaller timeframes. So, now, I want to show you some of my secrets or things that I learned that work in this gambling environment.
I’m not going against everything we agreed that the guru said was right. If you are day trading on smaller timeframes, market noise and another randomness will make you an accidental gambler. But there are just a few things that I myself use or do to have a high probability of making money even on the smaller timeframes. Here are some of them:
If you have used the Trading View chart before, you might find this chart familiar. Trading View separates time frames into minutes, hours, seconds and days. If I could, I would group these time frames in a different way. Let’s call these groups A, B, C and D.
Group A contains all timeframes below the 5 minutes.
Think of trading in shorter time frames, using a simple story about a skateboarder named Bill.
Imagine Bill standing at the top of a steep hill with a skateboard at his feet. He gives himself a push and starts rolling downhill. This downhill journey that Bill is on is like a long-term market trend in trading. In this case, Bill is heading downwards, just like how a stock price in a downtrend is heading downward over a longer period of time.
But the road Bill is on isn’t perfectly smooth. It has tiny bumps and cracks that cause Bill to vibrate up and down as he moves. This vibration is similar to ‘market noise’, the same randomness we saw earlier. Even though these smaller up-down movements are nothing, not even visible to a higher timeframe trader, they create their own up-and-down trends when zoomed in. If you use indicators such as MACD, RSI, and other things that give crossover entries, the probability of them working will be lower as these vibrations are just market noise of the long-term movement.
But let’s imagine there’s a big speed bump in the middle of the hill. Bill is moving fast and having fun, so he doesn’t stop. When he hits the speed bump, he and his skateboard fly into the air. This is interesting because even though the overall direction Bill was moving was down the hill, for a moment, he moved upwards. This little upward movement is like a short-term trend that goes against the bigger, long-term trend.
Why did this happen? Yes, it was obviously because of this little speed bump. But in our story, the speed bump is what day traders call a ‘catalyst’. A catalyst is something that causes a big change. In trading, a catalyst could be a piece of news or an event that causes the stock price to move strongly in a certain direction. So, when I’m trading in these smaller time frames, I look for these ‘speed bumps’ or catalysts. I like to trade when the price is moving strongly in a certain direction because of a catalyst. Because when this happens, the price moves from gambling and randomness to more towards high probability and edge. The market noise will still be present as there will still be different types of traders taking their own trades on different timeframes, but this catalyst makes the entry direction stronger. An entry taken in the catalyst direction will have a higher probability of working as long as the little bit of market noise doesn’t immediately trigger your stop-loss.
That brings me to another important point. As I just said, the catalyst trading method won’t work on every kind of market. For example, the Forex Market on timeframes lower than 5 minutes has a lot of noise compared to the stock market. So I prefer trading smaller timeframes of Group A in the Stock Market instead.
Now you might be wondering, how do we find the catalyst? Well, there are multiple methods. I made videos on it on the Main Channel. You can also watch them on the official Trading Rush website and app.
Another important thing to note is that in time frames below 5 minutes, sudden moves are more common, which results in indicator data becoming less reliable. If you use a crossover entry with RSI, MACD, etc., the indicator can give you a late or early entry. So on smaller timeframes of group A, I prefer using indicators only to analyze things such as trends and momentum. As for entry, I take them using other things that are not lagging, such as candlestick patterns.
The B group is for time frames from 5 minutes to below 30 minutes. Imagine that our little Bill has upgraded his skateboard with larger tires. Now when he rides down the hill, the vibrations of the road are felt less. Similarly, when you move to group B timeframes, the market noise is reduced. Don’t get me wrong. The timeframes are still relatively small and have a good amount of market noise, but that market noise is less compared to the even smaller timeframes we saw in Group A. Crossover Indicators can be used in this group in my experience. The timeframes are big enough that the price respects the support and resistance areas. Remember that I have data that shows my support resistance work around 60% of the time. So when I say support resistance work, I’m saying that the way I draw them works. I don’t draw trendline support resistance and those other weak areas. In my experience, they don’t work that well. You can learn more about them in my support resistance video.
The third group is for time frames between 30 minutes and 4 hours. Here, we can compare trading to driving a car instead of a skateboard. In this group, you can use any strategy you want. When I switched from trading in 1 minute to trading in 30 minutes, I saw a big difference in the price action strategy. In our metaphor, this would be like Bill moving from a skateboard to a small car. The small car is even less affected by bumps and cracks in the road, making the ride even smoother. Similarly, the market noise in these time frames is even less than in group B. The car’s suspension system can easily handle speed bumps without getting airborne, much like how the market’s ‘catalysts’ have a less sudden impact on these time frames. Here, the price action strategy also works well, and the price respects support and resistance better. The crossover entries are also more reliable. That’s not that surprising because most of the technical strategies, especially support resistance, work well when almost everyone can see them.
The D Category is for time frames above 4 hours and up to 1 week. This is like upgrading from a small car to a luxury sedan. The ride is incredibly smooth, and even the biggest speed bumps are barely noticeable. The noise and vibrations are practically non-existent, and the journey is comfortable and predictable. In trading terms, this means the market noise is so low that price action, patterns, and indicators can be used with a high degree of reliability. The higher timeframe smoothens out the smaller fluctuations and provides a clear view of the bigger picture. Many people, including investors, news and day traders, watch the 1-day time frame. Patterns are more important in this time frame. I’m not including the monthly timeframe in any group because that timeframe is too big for technical entry, in my experience. It’s so big and slow that multiple fundamental events can take place before the profit target and move the price against the technical entry direction. But I do pay attention to the support resistance of the monthly timeframe, like the price reaching near the previous all-time high. Those areas are talked about even on the news channel. And as I said earlier, if everyone is seeing and thinking the same thing, those areas will work well!
Alright, now I want you to play a game with me. I’m going to take on a different role and challenge my own points of view. One thing people might be wondering about is if this random noise we’re talking about really looks like actual market movement. Some of you might argue that it doesn’t quite look like the real thing. So let’s do a little experiment.
I went to TradingView and extracted 1-minute data of various currency pairs and stocks. With this data in hand, I moved to Python and fed this data into the simulation I built earlier. Now, the Python price simulation does something interesting. It creates a random market noise and also displays the real price movement data on a separate chart. This allows us to compare the randomly generated price movement and the real movement side by side.
Now tell me something, if I showed you charts side by side like this, would you be able to figure out which chart shows real market movement and which one shows randomly generated market movement? I’ll show you five charts in total. Let’s see how many you get right. Ready? Here’s the first chart. Is the top one the real price movement, or is the bottom one real? You have three seconds to decide. Time’s up! The top one is real. Now, what about the second chart? Is the top one real, or is the bottom one real? You guessed it; the top one is real again. Let’s look at the third chart now. Is the top one real or the bottom one real? The top one is real once more. Now, the fourth chart. Is the top one real, or is the bottom one real? Do you see a pattern here? The real one is the top one again. Can you spot any pattern in the real one? Which one is real? The top one or the bottom one? It’s the top one again. Finally, let’s look at the fifth chart. Is the top one real again? If you said yes, you’re correct.
But why did I put the real charts at the top every time? I’ll tell you, but first, I want you to take another test. This time, the top chart won’t always be the real one. It’ll be random. Let’s look at the first chart. Now the second chart. The third price movement. What about the fourth price movement? Now the fifth chart. What did you answer this time? If you picked the top one again, you’re wrong. If you picked the bottom one, you’re wrong too. All of these charts were randomly generated. There wasn’t a single real chart.
Now, why did I do that? I’ll explain, but let’s take one more test first. This time, the game will be fair. I won’t always put the real charts at the top, and the charts won’t be all randomly generated. Let’s see how you do in a fair game. We’ll look at the first, second, third, fourth, and fifth charts again. Did you spot any differences? Some of these charts were random, and some showed real price movements. How many did you get right?
The reason I set up the tests this way, the first with all real charts on top, the second with all fake charts, and the third as a fair game, was to make the following point. If there was a way to filter out market noise, or if there were experts who could tell real charts from fake ones, they would have figured out the second test was all fake. They would have known the first test had all real charts on top, and they would have gotten the right answers in the third, fair game. They would have answered almost all the questions correctly. Did you get them all right? Most people wouldn’t because it’s hard. I have spent thousands of hours on smaller timeframes in the live market, but I can’t always tell real from fake. The real and fake ones look very similar, right?
Of course, this is my opinion, based on my experiences. But now, having taken these tests, you’ll likely have formed your own views on the matter. I’m very much interested to hear what you think.
