Tag: trading strategy

Tag: trading strategy

I’m going to rank the best and worst trading strategies I have used in my seven eight years of trading journey. Not only that, I’m also going to rank other best methods, tools, etc. Basically, I’m going to combine my seven eight years of trading experience into one video so you don’t have to waste years of your life just to know what I know now. Please remember not to get offended if I say your favorite strategy is trash. Everything I’m going to say is based on my ten thousand hours of live trading experience and is what I actually found throughout the years. Everyone’s trading journey will be unique!

This is a Tier List. Strategies I’m going to put near the top of the list are good, and near the bottom of the list are bad.

Let’s start with the Fibonacci Strategy. This is when someone takes trades just because the price bounces slightly from Fibonacci price levels. This strategy is pretty much garbage. When I tested it, the data showed that the Fibonacci levels don’t provide any noticeable edge. It never reliably worked for me in the live market, either. Many times, when it worked, the price was actually reacting to normal support resistance areas or just reversing from a random spot. I will put the Fibonacci strategy in the F Tier. On the other hand, it is a good tool to see if the pullback entry is good or late. For example, in an uptrend, if you place the Fibonacci like this, and the long entry point is below the 50 Fibonacci, I see it as a decent entry.

The next one is Ichimoku Cloud. This is one of the best indicators I have used. It looks like a mess, but it solves a lot of problems beginner traders might have. For example, for a trend trader it filters slow or bad markets. It shows where the price is trending. It even gives an entry point. Other than the confusing aspect of the indicator, the Ichimoku Cloud is pretty good. I would put it in the C Tier.

Next is the Stochastic. To be honest, I found that Stochastic and Stochastic RSI indicators give more false entry points. In my trading journey, I haven’t found them that reliable. When I tested the Stochastic strategy 100 times in one of the previous videos, it only got around a break-even win rate. So, I would place it in the E Tier. Also, remember that by clicking on the card that appears at the top right corner, you can watch the detailed video on the strategies I’m mentioning here.

The next one is SuperTrend. This is one of the best indicators I have seen. It shows where the market is trending in one of the clearest ways possible. Its strategy of taking trades when it switches the trend also had a profitable win rate in my testing. Overall, it’s a very good indicator, especially for day trading. I would put it in the C category with Ichimoku Cloud.

The next one is the Fractal Indicator. This just sucks. This indicator basically spams arrows for every small price reversal. You can adjust its setting to identify bigger reversals. But in my experience, it’s not that reliable at that, either. One of the Fractal strategies is taking long trades when the Fractal arrow appears below the candle. But this just doesn’t work. It got one of the worst win rates in my testing series. On the other hand, when we take long trades after the price breaks above the fractal candle like this, the strategy gets a better win rate. But overall, it still sucks. I would put it in the F Tier. There are better indicators than this.

The next on the list is the Alligator. This is one of the most useful indicators I have used. Beginner traders will benefit most from this. It shows not only the trend direction but also the strength of the trend. It even shows when to not do trend trading. I would rate it in the C Tier.

The next one is the Parabolic Sar. This indicator is mainly used for setting good stop-losses. And to be honest, it does its job very well. I would put it in the C Tier.

Money Flow Index is the next one, and let’s just say it doesn’t flow money in the pocket that well. I would place it in E Tier next to Stochastic.

Next is the Golden Cross Strategy. This is one of those ancient strategies that survived different market conditions and for a good reason. It just works, but mostly on the higher timeframes, such as 1 Day. I would say I have found this strategy more reliable on the stock market higher timeframe. Still, it’s not something I would use as the main strategy. So, it goes in the D Tier.

Next is the Breakout Strategy. This has never reliably worked for me. When I tested it, the data said the same thing. It doesn’t work most of the time. Maybe it did many years ago, and maybe it does work in some specific situations, but based on what I saw, I would rate it in the E category.

On the other hand, I found the pullback of the breakout more reliable. The testing data from previous videos also says the same thing. I would put the breakout pullback entry in the C Category.

The next one is Bollinger Bands. This is one of those indicators that are very good, but it is difficult to use. Basically, the Bollinger Bands strategy that worked for me required me to take opposite trades when the price went outside the Bollinger Bands. This doesn’t sound that difficult, but when we actually try in the live market, we quickly realize that the price goes outside the bands a lot. You have to filter a lot of false setups to make this strategy work. So, even if this strategy worked for me, I would not recommend anyone using this as their first strategy. There are better indicators than this. I would put this in the E category.

But many years after I was done with Bollinger Bands, I realized that there is a new Bollinger Bands indicator called Percent B. Instead of appearing with the candles, this indicator shows up separately on the chart. It also has these upper and lower bands. When the price moves outside the normal Bollinger Bands, it can be confusing. On the other hand, Percent B shows the same thing by moving inside its upper and lower bands. I found this way better! I would rate this Bollinger Band indicator in the D category, just above the normal Bollinger Band.

The next one is the CCI indicator strategy. This just sucks. It got one of the worst win rates in my testing. I will put it in the F category next to Fractal.

Let’s see some Moving Average Strategies. The first one is the 9 EMA. I used this when I was trading on smaller timeframes, especially with momentum strategies. I used this to see where the very short-term trend was heading. For example, if the price moved up strongly and stayed above the 9 EMA for a while, I would wait for the price to move below the 9 EMA and stay there for a while. The price above the moving average would confirm a strong buying pressure, and the price below the moving average would confirm a pullback. When the price breaks above the 9 EMA again, I would look for a long entry. This strategy worked for me, especially when combined with candlestick entry patterns. I would put it in the C Tier.

Similar to 9 EMA, I used 21 EMA to see the medium-term trend or momentum. This was also a reliable indicator. I would put it next to the 9 EMA in the C Tier.

On the other hand, 200 EMA was just better than other moving averages. It not only showed the long-term trend, but I also found that it would act as a weak support resistance many times. I also used it to filter range and slow markets. When the price crossed the 200 EMA multiple times, I would see it as a potential range market because that’s how the price behaves in a range. I even made my own 200 EMA called TR EMA, which disappears in the range market. This moving average is one of my most used indicators. I would put it in the B Tier above all the indicators we have ranked so far. It’s that useful!

But what about Simple Moving Averages? I only talked about Exponential Moving Averages because I like how they react to the latest price movements more quickly. I mostly use EMA instead of SMA. If I had to rank SMA, I would put it just below EMA.

The next one is the ATR indicator. I highly recommend this indicator to beginner traders. This is one of those indicators that can be used with any strategy. I use it to see how far I have to set my stop-loss. For example, if I was taking a long trade near a support area. Normally, I would set the stop-loss just below the support. But this stop-loss could easily get triggered because of the market noise. So, to solve this problem, I can add the ATR value to my stop-loss distance. It’s like adding a market noise distance to the stop-loss. Now my stop-loss is far away, and the trade has a higher probability of winning. I would put ATR in the C Tier. I would have rated it higher, but once you gain enough experience, you can tell how far the stop-loss should be on your own.

The next one is the Keltner Channels Strategy. This indicator is similar to Bollinger Bands. But instead of taking reversal trades when the price goes outside the bands, you take trades in the direction of the breakout. Basically, this indicator says the price movement is slow when the price is inside the indicator. When the price breaks out of the indicator, the momentum in that breakout direction is higher. One can take trades when the breakout happens. I tested this strategy 100 times in the previous videos, and it did give a profitable win rate. Overall, this is as good as the indicators of the C Tier. So that’s where I would put it.

Now, let’s look at some price action pattern strategies. The first one is the Double Top and Double Bottom Strategy. This was a reliable strategy in my trading journey. I would put it in the C Tier.

The Head and Shoulders Pattern, is also similarly good. So goes in the C Tier as well!

But Flag Pattern, especially when the Flag looks like an Ascending or Descending Triangle, is one of the best price action pattern strategies I have used. I mainly used them on smaller timeframes to trade momentum. I would put it in the B Tier.

I would rank other Triangle and Price Action Patterns in the D Category.

Also, when it comes to the Trend Lines, I have only found them reliable when they are drawn on a pullback of a trend. Otherwise, they are pretty average. I would put the Pullback trend line in the C tier and other trend lines in the E tier.

Let’s see some Candlestick Pattern Strategies. The first one is the Engulfing Pattern. I would happily put it in the B Tier. It’s one of the best candlestick patterns I have found. If you remember the Trading Rush Free Price Action Series, you will know that hammer and shooting star patterns also show the same story. In other words, they are just like the Engulfing Pattern. I would put them in the B Tier as well.

As for the Doji candle, I would put it in the C Tier. It shows that there is equal buying and selling pressure.

I would put other Candlestick Patterns in the D category.

The next strategy on the list is the Awesome Oscillator. Unfortunately, it’s not that awesome. Its win rate in my testing series was slightly higher than break even. I would put it in the E category.

The next one is the Gap Strategy. This is when you look for a big gap-up or gap-down in the stock market. After that, one can take trades in the gap-open direction or in the gap-fill direction depending on where the price is showing signs of heading. I would add it to the B Category.

The next one is the V-WAP indicator. This is when you wait for the price to bounce from the V-WAP line in the Stock Market. This is one of my favorite indicators, and I would put it in the B Tier.

The next is the RSI indicator. I have found this to be an average indicator with an average win rate. The popular strategy of taking long and short trades when the RSI becomes oversold and overbought, respectively, did work in my testing. I would put RSI in the C Tier.

When it comes to Chart Types, I have found Renko Charts to be the best for drawing support resistance areas. They reduce the market noise and show the reversal points clearly. I would put them in the C Tier.

As for the Heikin Ashi Chart, they are also good at filtering out the market noise. Furthermore, one can even use them to trail the stop-loss. I would put them in the C Category.

As for the Candlestick Charts, these are simply the best. I would put them in the B Tier. They give a lot of information, which can be used to see the interest of other market participants! It is difficult to do that with Heikin Ashi or Renko Charts.

When it comes to Bar chart, I have never found it useful over other charts. I would put it in the E Tier.

Since Trend strategies are where I made the most money, and since trend trading is easier than range trading, I would put Trend Trading in B Tier and Range Trading in C Tier.

The next one on the list is Market Types. I would put Forex Market in the C Tier. This is where I started my trading journey. But this market has a lot of market noise in my experience. Support resistance areas work very well here. But only a few forex pairs are worth trading. The rest have a bad price movement.

I would put the Stock Market in the B Tier because I can trade a wide range of products very easily. The market noise in the Stock Market is less compared to the Forex market. So I can more reliably trade smaller timeframes.

On the other hand, I would put Crypto in the E Tier. Most of the time, it’s movement is trash. I can’t take technical trades when the price movement looks like this. It randomly starts making random moves and then suddenly starts making good, strong moves in one direction. Basically, crypto is volatile. But that’s also its advantage when it comes to long-term investing. For example, I have around two long positions in Crypto. Since Crypto makes big moves, the profit was made much faster than if I had invested that same amount into the stock market. Still, I only have a small portion of my capital in crypto as the risk of losing almost everything is also high. When it comes to normal trading, I don’t see an advantage in trading crypto over the stock market. So, I would still put Crypto in the E Tier.

The next one is the Donchian Channels Strategy. It’s one of the highest win-rate trend strategies I have found. You can learn more about it by clicking on this card. I would put it in the B category.

Similarly, the MACD crossover strategy is one of the best strategies I have found when it comes to identifying the end of pullbacks in a trend. Its Histogram part is also one of the best things out there! You can use it with any other strategy to see the momentum change. I go into much more detail in this video. I would put MACD and its Histogram in the B category.

Okay, so everything I’m going to say next will be very important.

If you noticed, I haven’t added anything in the A and S tiers yet. That’s for 2 reasons:

Number 1. The best trading strategy that I have found the most reliable in taking entries, booking profits, and setting stop-losses is the Horizontal Support Resistance strategy. I have data that says the way I draw support resistance works around 60% of the time. But that’s not the only reason I’m ranking it higher than anything else. You see, most of the strategies and tools I have mentioned so far are automatically calculated on the chart. In other words, MACD, Ichimoku Cloud, Bollinger Bands, Moving Averages, etc, all appear on the chart based on their predetermined formulas. Most of the time, there is less human psychology part in them.

On the other hand, when it comes to strong support resistance areas, the whole reason they work is because most people think in a similar way at the same time. Most people simply believe that if the price has strongly reversed from a price level before, the price has a good potential to do it again.

Horizontal Support Resistance Strategy is the only strategy I have found in my seven eight years of trading journey that is directly based on the psychology of market participants. On top of that, it is even supported by data! So, it’s the only strategy I would put in the A Tier.

Number 2. S Tier trading strategies don’t exist. But you can get to S Tier by gaining enough live market experience.

For example, when I was new to trading, I thought all trading indicators suck. If I had made this tier list before gaining 10 thousand hours of live trading experience, I would have rated every one of them in the F tier. I hated them all because they just didn’t work. But indicators were never the problem. It was beginner me.

At that time, I only had a few hundred hours of live trading experience. I was not experienced enough to filter good vs bad markets. I didn’t know when to use a trend trading strategy, such as MACD, and when to not use it.

Only when I gained enough live market experience I stopped trading like a bot. By that, I mean most trading strategies don’t work in all markets. We have to use trend strategies only in the trending market. Otherwise, we are trading mindlessly like a bot.

The only way to stop trading like a bot is by learning when to not trade. And I learned when to not trade after I gained more live trading experience.

Basically, what I’m trying to say is. Your trading strategy’s outcome in the live market kind of reflects how much experience you have in trading. If you are new and lack experience, your strategies will lack a high win rate as well.

Think of your experience as a multiplier of these strategies. The better you are, the better these strategies are.

If I was to start trading again, I would mainly focus on the S, A, and B Tier Strategies, Tools, etc. Because that’s what I have found to be the best after trading for seven-eight years straight!

That’s all! Now watch this video where I explain the best part of the MACD indicator with a cat!

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97% Win Rate Trading Strategy (Exposed)

Post author By Trading Rush
Post date November 12, 2023

97 win rate web

Tag: trading strategy

This trading strategy got 97% winning days, and I’m going to find out how!

A few days ago, while I was analyzing charts at my desk, I got this in my inbox. A message that made me feel like a complete idiot when it comes to trading. It contained the real profit and loss days of a random trader from the internet, but the winning days were 97%. I couldn’t believe what I was seeing. It was like this guy had found the holy grail of trading, the ultimate secret. It was like a green unicorn vomited all over the chart so much that a little bit of blood appeared.

This unknown trader’s profit loss chart was shared with me by one of my Patreon supporters, and we quickly came to 2 conclusions about what strategy he might be using.

But I wasn’t satisfied. If the profit loss days were real, why I’m not using the same strategy? Who wouldn’t want months and months of green days? I definitely do. But what even is the strategy this guy is using? But then I remembered, in my many years of trading experience, I have never seen a professional trader get high winning days like this. So something might be fishy in all this. I must find the truth!

To find out the strategy that gives 97% winning days, I planned around 10 experiments. My goal in these tests will be to end up with green profitable days like that unknown trader.

Test 1.

I sat at my desk again and started gathering the best possible ways I could achieve a high-winning day like this. But then I realized, “Oh wait! I have already tested many strategies 100 times. I can use that data to see if I can get 97% winning days.”

The highest win rate in my testing was around 60%, with a 1.5 to 1 Reward Risk Ratio.

So, I created my own stock market simulator that took random trades with a 60% probability of winning.

In the first test, I wanted to see how the profit and loss days would look like if I took 1 trade a day with a 60% win rate strategy. But the results of the first test were disappointing.

But then, in hindsight, I realized how stupid I was. If I take 1 trade a day with a 60% win rate strategy, of course, the profit days will also be around 60%. I must have been overexcited in the first test.

Test 2.

So I lowered my excitement and modified the trading simulator to take 5 trades a day with a 60% win rate and a 1.5 to 1 Reward Risk Ratio.

But the results I got were still not satisfying. The winning days were around 91%, which is good, I guess. But it’s still not what the unknown trader from the internet was getting. I still wanted to see what would get 97% winning days.

Test 3.

But then I remembered that when I was trading on smaller timeframes many years ago, I sometimes used to aim for 10 trades a day. So, in the next test, I increased the maximum number of trades in a day to 10 and hoped it would be the answer.

But this only got me to 93%. There is still 4% missing. But then I noticed that my results only had a winning streak of 1 month, while a random internet guy had 3 straight months of green days. My results are unacceptable!

Test 4.

So, in the next test, I increased the maximum number of trades in a day to 20.

1st month was all green, 2nd month was all green, 3rd month was also all green! Yes! This worked! But who am I kidding?

20 trades a day with a 60% win rate for a year straight? That’s simply not possible! A 60% win rate with a 1.5 to 1 Reward risk ratio is achieved in a good trending market. But in my 10,000 hours of live trading experience, I have never seen the market stay good every single day for an entire year straight!

So, I bet the random internet guy is definitely not using a 60% win rate strategy. But since his profit loss days were real, getting 97% and 3 months straight winning days is possible. So there must be a way I haven’t tested yet!

Test 5.

I must try to use a strategy that has a much higher win rate. But, the easiest way to increase the win rate of a strategy is to reduce the reward-risk ratio. So, in the next test, I used a 0.5 to 1 reward-risk ratio. Even the break even win rate with this ratio is around 67%. So, the probability of strategies getting a 75% win rate is not that rare. I think I even did a backtest a while back where M-A-C-D and 200 E-M-A got around a 75% win rate with a 0.5 to 1 reward-risk ratio.

When I ran the experiment this time, I set max trades in a day to 10. To be honest, I still think finding 10 good trades every single day for a year straight is rare. But it still didn’t work! This looks more like the first test where only 1 trade a day was taken.

Test 6.

But then I set the maximum trades a day to 30. This is completely unrealistic. A trader will most likely never get 75% probability setups continuously for 30 trades in a single day.

If the result of this test is not 97% winning days, I bet that the random trader is doing something completely different.

I was happy to see that the result came back negative. The trader is indeed using something else. But I’m scratching my head at this point because I don’t see a safe way to achieve 97% winning days. And yet, a random trader I saw on the internet is doing it.

Test 7.

So, I’m going to have to break some rules and use the forbidden strategies.

The first one is averaging the losses while day trading. This is when someone takes another trade in the same direction instead of booking losses at stop-loss.

The second one is martingale. This is when someone doubles the position size of the next trade after making a loss. They keep doubling the position size until a trade is won.

These are some of the worst trading strategies a trader can use. Even ChatGPT says this strategies are stupidly risky. If they actually give the 97% winning days I’m looking for, the conclusion will not be something I had hoped for.

But then I realized I would have to modify my stock market simulator to test averaging. So, I created a price simulation and then took the trades in one direction. I used a 0.5 to 1 reward-risk ratio so that the win rate would be high. But I also wanted to see if random trades with averaging can give 97% of winning days. So, I set the probability of the price moving in one direction to 50%. This makes the 0.5 to 1 reward risk ratio have a break even 67% win rate.

If this break even win rate can result in 3 months of winning days, that random guy is basically a new trader and is probably gambling. There is no profitable strategy. It’s just probability, giving an illusion of a profitable strategy.

Previously, this number showed the win rate of the strategy. But for averaging, I changed it to show the probability of the price moving in the entry direction.

But then I realized, “Wait a minute, one cannot average the losses forever. If the price keeps moving in the loss direction, at some point, the trader will run out of account balance required to take the next trade.” So, I set the max averaging limit to 5.

But then I looked at the profit loss days of the unknown trader, and realized that if he is averaging, he is probably only doing that after making a loss, kind of like revenge trading. If the first trade is won, he books the profit and stops trading for the day. If he loses the first trade, he keeps averaging the loss until the loss becomes zero. Then, he stops trading for the day.

So, in my experiment, I used the same rules.

And to my surprise, it actually got 97% winning days, 4 months of green days straight. And it was all gambling. The entry direction was random, the win rate of the strategy was break even, and yet, this gave 97% winning days. My green unicorn threw up more than his.

But hold on a minute. Did I just see gambling or random trades make a profit for 4 months straight and get a 97% win rate?

So, I exported the account balance of the simulation and saw this! Even though there were green days and a high win rate, the profit graph was actually moving in a downward direction.

That was not the case with the random trader I saw on the internet.

Test 8.

So, in the next test, I set the probability of the price moving in the entry direction to 55%. This is like averaging the loss near support resistance, where the price is more likely to move in the entry direction. But when I thought about it more, I realized this is most likely not possible in reality. I mean, averaging loss on stock market indices, such as the S&P500, is good because that price is more likely to move up in the long term. Many people, including me, do that because it works. But I don’t think averaging losses near support resistance or with any day-trading strategy will work.

Still, I wanted to see what the daily profit loss data would be like. So, I ran the next experiment with a 55% probability of the price moving in the entry direction.

After running the test, I couldn’t believe what I was seeing. There were 99% winning days, and the profit graph actually moved up!

But even after many years of trading, I have yet to see a data-backed day trading strategy where averaging works in the long run.

So, this data is, unfortunately, unrealistic for day trading. But since averaging loss or dollar cost averaging works on higher timeframe stock market indices, this is probably what the long-term data looks like for those strategies. A slow and steady rise as the stock market moves up in the long run.

Test 9.

But I still wanted to find what this random internet trader was using. Since this was not it, the next test I did was martingale with a 0.5 to 1 reward risk ratio, 75% win rate, and max trades per day set to 10.

But this only gave me around 86% winning days. The profit graph went in the upward direction though. But then the curiosity got me. From previous experiments, I know that the martingale strategy is bad in the long run. Here, it made a profit in a year. But I wanted to see after how many trades it would blow up the account.

So, I set the maximum trades per day to 100. But even after 26000 trades, the martingale strategy didn’t lose money. It turned $100 into more than $5000.

But then I thought maybe I set the win rate too high. There is no way the market is going to stay the same or good for 26000 trades. So there is no way the win rate is going to consistently stay good for 26000 trades in a row. It can drop to break even and even lower. So, I set the win rate to just about break even, which is 70 percent. With this around 3 percent edge, I ran the experiment again.

But it was still making money. I ran the test again and again and again. But the results always ended up in profit. But I know for a fact that Martingale will blow up the account when the big losing streak starts. So it appears that because the win rate is so high, the probability of a big losing streak has been reduced by a huge amount.

So, I modified the simulation to run 100,000 martingale trades 10,000 times. That’s more trades than I can count using my fingers.

But the results showed that out of 10,000 runs, only 10 lost the entire capital. It means only 0.1% of the martingale runs blew up the account even after taking 100,000 trades with a 70% win rate and 0.5 to 1 reward-risk ratio.

I kind of lost my mind after looking at this number. I was not expecting martingale to be successful 99.9% of the time. But then I remembered I’m a bit stupid. I forgot to track how many runs couldn’t take the next martingale trade because the account balance was insufficient.

So, I ran the code again with this modification. It showed that around 45% of runs couldn’t continue the martingale strategy. They lost so much money that the account balance was not enough to take the next martingale trade.

Based on this data, I saw that if a trader uses martingale even with a high win rate, there is around a 45% chance they will lose at least half of their account. Since they can’t continue, they will have to reset the martingale strategy. Then, they again will have around a 45% chance of losing half of that account size. That sounds risky to me.

I don’t think most traders can handle a 50% loss on their hard-earned money.

But I don’t think the random trader I saw on the internet is using a normal martingale strategy.

Test 10.

So, after gathering my last 2 brain cells, I spent more time analyzing the profit loss days. I was about to give up, but then it hit me. All this time, I was going in the wrong direction. The strategy to get around 97% winning days and multiple months of green days was something I already learned many years ago as a beginner trader. I bet most beginner traders already know about this as well.

While analyzing the profit loss days, I realized that the random internet trader was not just using a low reward-risk ratio. He was using a very, very low reward-risk ratio. If he was risking around 1% of the account, the reward would be ranging between 0 and 0.2% of the account.

But most profits were near 0.1% of the account.

So, in the next experiment, I simulated trades where the reward-risk ratio was ranging between 0 and 0.1

I set the max trades per day to 1 and the probability of the price going in the entry direction to 55%. This is like trading near support resistance or only taking long trades on higher timeframes in the stock market.

And it actually worked! I more consistently got 97 to 98% winning days. There were multiple months of green days. And I even saw the profit graph moving up more consistently. I ran the test again with more trades, and the profit graph went more in the upward direction.

After spending weeks writing code and analyzing things, I found the 97% winning days strategy.

Here’s how it goes.

Step 1. Only take trades where the probability of price moving in the entry direction is higher than break even. This includes support resistance areas, buying good stocks, or the stock market index on higher timeframes.

Step 2. Once the trade is taken, use a very low reward-risk ratio, such as 0.1 to 1. But try to close the trade at break even if the price shows strong signs of moving towards the stop-loss.

I have data that says the way I draw support resistance works around 60% of the time with a 1 to 1 reward-risk ratio. So, a 0.1 to 1 reward risk and all these rules should most likely work with that.

If I have bought a good stock, I can also take short trades on it using derivatives such as options. This turns the long stock positions into a low reward-risk ratio long trade. Since a good stock has a higher probability of moving up in the long run, there will most likely be high winning days. If the price doesn’t move up quickly, the short options trades will generate some small profits in the meantime. This is a classic options strategy. I think in Part 2 of “How I Made 100% Profit in a Year, Stock Market Series,” I called this method a better way of generating more consistent income.

After spending an entire week figuring out how a random person I saw on the internet is getting 97% winning days, will I be using this high win-rate strategy?

I actually did use it when I was new to the stock market. But since the reward-risk ratio is so low, the max yearly returns of the strategy on average is around 20%. I think I was averaging around 10% profit in a year. So, I stopped using it as the main strategy.

I mean, I made around 25 to 50% profit from a few trades last year by simply buying and exiting when I saw signs of buying and exiting. I like that kind of higher profit potential.

On the other hand, I also use low reward-risk ratios when I don’t find the market good for higher reward strategies. So, it also depends on the market.

If I see that this 0.1 to 1 reward-risk ratio strategy might be more useful in the current market, I might start using it like before.

Thanks to the Patreon supporters for making this video possible, especially by sending the high-winning days screenshot and giving the martingale idea.

If you liked the video, see how I made 100% profit in a year, what I’m trading right now, and more by supporting Trading Rush on Patreon. Thanks for watching!

Tags 100 times, 97%, experiment, exposed, high win rate, test, trading, trading strategy, win rate

Trading Strategy That Made $2,000,000 (SUPER FAST)

Post author By Trading Rush
Post date December 9, 2022

2 million dollar trading strategy Darvas Box strategy

Tag: trading strategy

If I told you a dancer made 2 Million Dollars with this trading strategy, you would probably believe it. But if I said he made 2 million in just 18 months with a starting capital of only around 10,000 dollars, then the story suddenly becomes unbelievable. How in the world did a dancer turn 10,000 into 2 million in just 18 months? And what trading strategy did he use? I even tested his strategy 100 times in this video to find its win rate, and the results I got were the most shocking yet.

Even though he trained as an economist at the University of Budapest, he found himself drawn to the world of entertainment, eventually becoming a successful dancer. However, his path to success was not without challenges.

He fled the country with a forged exit visa and fifty pounds sterling. He made his way to Istanbul, Turkey, where he eventually met up with his half-sister Julia. The two of them became a dancing team, travelling throughout Europe and eventually making their way to the United States.

They continued to tour and perform, earning a reputation as a talented and dynamic duo and by 1956, they were at the height of their fame, with audiences flocking to see their shows.

During his off hours as a dancer, he devoted himself to studying the stock market, reading over 200 books on the subject.

However, the two books that he returned to again and again were The Battle for Investment Survival, by Gerald M. Loeb, published in 1935, and Tape Reading and Market Tactics, by Humphrey Bancroft Neill, published in 1931. These books proved to be invaluable resources, providing him with the knowledge and tools he needed to become a successful investor.

Later he made a significant profit from a couple of stocks that he had invested in. After this successful trade, he came up with a trading strategy for trading stocks. Using this approach, he was able to earn more than 2 Million dollars in just 18 months during the bull market of 1957-1958. This was seven years after his first trade.

His main source of stock selection was the weekly magazine Barron’s. While this may seem like an unusual choice, there were several reasons why he found it to be a valuable resource. For one thing, he was often travelling with his performing dance troupe, so he needed a way to keep up with the latest developments in the stock market. By reading Barron’s, he was able to stay informed about the latest trends and news, even while on the road.

Another advantage of using Barron’s was that it was usually a week old by the time he received it. This may seem like a disadvantage, but in fact, it allowed him to see which stocks had made good advances on strong volume over the past week. This gave him an idea of which stocks were likely to continue their upward trend and which ones were starting to plateau or decline.

Once he had identified a stock that he was interested in, he would use cables and telegrams to send his buy and sell stop orders to his broker in New York City.

He claimed that his method allowed him to identify the signs of insider trading before a company’s release of favourable news to the public. Of course, there is no way to verify whether his claims about insider trading were true. It is possible that he was simply making a bold and exaggerated claim in order to promote his method.

The name of this professional dancer turned professional trader was Nicolas Darvas, and the effective approach to trading stocks he developed was called the “BOX theory”. It was based on the idea that a stock price wave could be represented as a series of boxes. You draw these boxes by connecting the swing high and swing low like this. According to Darvas, when the price of a stock was confined within a box, he would wait and not make any trades. However, when the price rose out of the box, he would buy the stock and simultaneously set a stop-loss just under the ceiling of the box.

He also used high volume to find the best setups, but the real key to his great success was the stop-loss. If you look closely, you will notice that if the entry is at the top breakout of the box, and the stop-loss is just below the ceiling of the box, the stop-loss distance is so small that even a decent size upward move would result in a huge reward to risk ratio. In other words, when he booked profits, he booked some really big profits, and when he booked losses, he booked really small losses.

At the age of 39, after his success as a stock trader had been widely recognized, Darvas documented his actions in the book, “How I Made $2,000,000 in the Stock Market.”

But the Critics of Darvas’ trading technique believe that his initial success was due to the strong bullish market at the time and that this technique would not be effective in a bear market. However, Darvas himself believed that he was not suited to short selling and suggested that experienced investors should consider it.

But Critics have an interesting point. When Darvas made 2 million dollars in profit, the stock market looked like this.

This bull market was an exciting time for the stock market. It was a period of rapid growth and optimism and provided many investors with the opportunity to earn significant returns on their investments. While there were always risks and uncertainties, the overall mood of the market was one of confidence and positivity. This period is now looked back on as a time of great opportunity and success for many investors and traders.

If you had randomly taken long trades in this market, you would have probably made a profit.

To find out if Darvas Box Strategy was actually good or just luck, we need to test it 100 Times.

Since Darvas used a tight stop-loss and a high reward-risk ratio, in the first test, I used a 5 to 1 Reward Risk Ratio. I also used the S&P 500 1-Day timeframe to test his strategy in around the same bull market that he traded. I used the 200 moving average to find the uptrend, and only took long trades as he did. The results were shocking. The Darvas Box Strategy got an approximate win rate of 45%, even with a high reward-risk ratio of 5 to 1.

The strategy almost tripled the initial account size without even compounding. With compounding, the profit would have been even higher. Then I tested the strategy again with a 1.5 to 1 Reward Risk ratio, and the win rate was approximately 73%. That’s the highest win rate out of all the strategies we have tested. But there was just one problem. You see, at least on TradingView, only the closing prices of the day data is available if we go back to the time period Darvas traded. There is no high-low of the day data available.

So in the first test, I used the closing prices to make buying and selling decisions, and it worked excellently. However, in the second test, I also used high-low prices, and the Darvas Strategy suddenly became the worst strategy we have ever tested 100 times, getting a win rate of just 27% approximately. From the best to the worst in pretty much the same market structure. Adding volume confirmation near the entry is not going to make this low of a win rate better either. For comparison, I tested the Beep Boop Indicator we created in the previous video, and it got a 50% approximate win rate in the same structure even with the high-low data. That’s way higher and better!

The reason why Darvas Box Strategy changed the win rate so drastically has to do with the market noise. If you make decisions only by looking at the closing prices, the price movement looks a lot cleaner. But if you add the high-low prices data, there is more noise in the price movement. This noise is what triggered the stop-losses in the second test. So the critics of the Darvas Box Strategy were not completely wrong. The strategy only works if the price is in an extremely good bull run with less market noise, and luck played an important role when Darvas turned 10,000 dollars into more than 2 million dollars. The Darvas Box Strategy works like magic with special conditions, and doesn’t work in normal market conditions.

See how I made 100% profit in a year, see what I am trading, and get trade alerts by supporting Trading Rush on Patreon. Thanks for watching!

Tags box, box strategy, box theory, darvas, darvas box strategy, Nicolas Darvas, strategy, trading, trading strategy

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The Billion Dollar Trading Strategy

Post author By Trading Rush
Post date November 17, 2022
3 Comments on The Billion Dollar Trading Strategy

Jim Simons Strategy

Tag: trading strategy

If I were to tell you that a mathematician made Billions of dollars with these trading strategies, you would probably laugh. You would say that there is nothing special about these charts, and you see them almost every day. But that’s where 90% of traders make the big mistake that keeps them in the 90%.

But to understand how this mathematician saw profitable patterns to make billions, you will have to start with his Colombian story because I doubt he would have made billions if it wasn’t for his interesting background.

You see, before the mathematician saw profitable patterns on charts like these, he made a small investment with his Colombian friends. He urged them to start a business together, and they did. He owned 10% of the business with the money he had borrowed from his family.

But the problem was he wasn’t making enough as an instructor at MIT and later as an assistant professor at Harvard to pay back his debt. So he went to the Institute Of Defense Analyses in Princeton. This was a highly classified government operation designed to crack codes, and they paid very well.

This was great, but later, he left the institute and went to Stony Brook University to become the head of the math department. And while he was here, the business he started with Colombian friends got sold. And as a result, the mathematician was left with a good amount of profit.

Now, many people, when they stumble upon good capital, will invest in something safe. But the mathematician decided the trade currencies instead.

This was when he was in his late 30s, and he did pretty well. He didn’t believe in the efficient market theory, which says that it is pointless to search for undervalued stocks or to try to predict trends in the market through either fundamental or technical analysis. There are multiple reasons not to believe in this theory. Two of them are Warren Buffett consistently doing better than the markets in the long run, and market crashes where most things are trading below their fair price.

So the mathematician read newspapers to try to predict where the currencies were going. And even though he made quite a lot of money doing this, he believed it was pure luck because it was not based on mathematical models.

This is where things changed. After looking at the data, he realized that there was a pattern here.

So he hired mathematicians and started working on models. They would design an algorithm and then test it to see if it works. This was similar to the kinds of things he did at the Institute Of Defense analyses to crack the codes.

But he was not good at hiring the right people. The fundamental analyst he hired to work on the model made some money and then lost some money. So he decided to hire scientists because he knew better in that department. Later he said he didn’t like hiring people with an investment background, because he liked to think, that you can teach a physicist finance, but you can’t teach a finance person physics.

With more scientists working on creating the best way to make money from the market, their model kept getting better and better. What they were doing was gathering a lot of data and then finding patterns that were predictable and happened more often. We will see some of these working patterns in this video in a moment.

But what’s really interesting is that they didn’t just stop at analyzing the price data tick-by-tick but also looked at the weather conditions, annual reports, quarterly reports, historical data itself, volumes and almost everything that can move the price. Furthermore, they didn’t just stop at hiring mathematicians, they also hired astronomers and physicists. This was one of the most in-depth analyses done by scientists to make a profit from the financial markets.

Now, with all the experts working on the strategy, you might think their win rate would be very high, right? Well, this is where 90% of traders make a mistake and stay in the bottom 90%.

You see, the name of the mathematician was Jim Simons, and he used the strategies they created to form Renaissance Technologies, the asset manager that manages the Medallion Fund. While Warren Buffett compounded at around 19% annually, Jim Simons’ Medallion Fund generated a 66% gross annual return, or a 39% net annual return from 1988 to 2018. With this high compounding rate, they generated $100 billion in profit pretty quickly, resulting in Medallion Fund becoming the best fund of all time.

But even though the fund made a very high-profit percentage in a year on average, according to some sources, their win rate was only around 51%, or just above breakeven. That’s because when all those scientists were analyzing a large amount of data, they were not trying to find a pattern that had a very high win rate. Instead, they were trying to find patterns that have a very high probability of working consistently in the long run. If there was a pattern that only had a 1% edge, you could simply take a high number of trades to make a lot of money, which is exactly what they did.

On the other hand, 90% of traders won’t do that. Even if you give them a statistically proven strategy that has a very high probability of making money in the long run, they will not stick to a proven model and will chase the unrealistic high win-rate strategies.

After seeing how Medallion Fund generated high returns using predictable price patterns and data, new funds have emerged trying to do the same. Now, this can be a bit problematic because if you are a top fund that is creating strategies using market data that is publicly available, someone at some point can come up with a similar profitable strategy.

So their key to staying ahead of everyone was gathering a tremendous amount of data every single day, finding new approaches, and adapting to the new market as quickly as possible.

Out of these approaches, 3 strategies they used to make Billions over the years are known to the public on the surface level.

Number 1. Jim Simons said, in the old days, commodities and currencies prices had a tendency to trend. Not a continuous trend but a short-term trend. So if they decided to predict the direction, they would look at the average move of the last 20 or 10 days and make a prediction based on that trend direction. This is similar to many trend trading strategies we have tested 100 times on the Trading Rush channel.

Then there is strategy number 2. Since the price moves around its fair price in the long run, they tried to find charts where the price has moved away from the fair price in the short term. For example, if the price is moving like this, and this is the average line, when the price goes too far from the average price, they would trade towards the average price. This is also known as the Mean Reversion Strategy.

Then there is the third strategy. You see, in the financial markets, there are multiple exchanges and instruments to trade. So when they saw abnormalities in the prices, or in other words, if security was priced lower on one side and the same security was priced higher somewhere else, they would buy and sell the security at the same time, and profit from the difference in the prices. That’s a 100% guarantee of making a profit. But the third strategy will be difficult to execute in today’s market for retail traders as computers have taken over that department.

The first two strategies still work today, and you can find their data on the Trading Rush Channel.

See how I made 100% profit in a year, see what I am trading, and get trade alerts by supporting Trading Rush on Patreon. Thanks for watching!

Tags billion, billions, jim simons, jim simons strategy, mean, reversion, strategy, trading strategy, trend

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$0 to $100,000 Trading Rule: That Most Traders Get Wrong

Post author By Trading Rush
Post date February 3, 2022

trading that will keep you po

Tag: trading strategy

Would you do me another favor? By the end of this video, I can prove that the way you are trading right now is most likely wrong. But to prove that, I want you to look at these three back-testing clips, while I tell you a short story about how Warren Buffett made money when he was young. By the end of the story, these three back-testing clips will have the exact same win rate and will have risked 1% of the account per trade, and still, one of them will make way more money than the others. I want you to guess why one of them is making more money than the others because if you can correctly guess that, you will understand what Warren Buffett and these three clips have in common.

See, before Warren Buffett started to make his billions, one of the businesses he ran involved setting up pinball machines in barber shops. Many times people have to wait in line before they can get their hair done, which can be quite boring. Young Buffett saw a business opportunity in this. In 1946, Buffett and his friend Danley bought a pinball machine for 25 dollars and installed it in a barber shop. Now, instead of getting bored, customers can play pinball while they wait. This business was a hit from day one. The first night, Buffett and Danley made 4 dollars, and after one week, they had already made 25 dollars in total. They reinvested this amount into the business, bought another pinball machine, and installed it in another barber shop. Then, the profit made from two machines was reinvested to buy 2 more machines. 2 machines became 4, 4 became 8, and so on. They kept reinvesting the profit, and soon, Buffett had pinball machines in barber shops all over Washington, D.C.

Young Buffett ended up selling the business, which he started with just 25 dollars, for over 1000 dollars after a year.

This story and the 3 back-testing clips have one thing in common: the reinvesting part, and that’s also the part most people get wrong.

Recently, one of the members of the Trading Rush Discord Server asked: “how often is reinvesting profits recommended?”. Since I personally reinvest, or in other words, compound whenever I’m approximately 30% in profit, that’s what I replied. But then I remembered the Turtle Traders and their trading rules, and started to question if my method of compounding was even right?

You see, in the previous episode, we saw how multi-millionaire Richard Dennis taught random traders how to make millions. These random traders were called turtle traders and they together ended up making more than 175 million in around 5 years. One of the rules they followed was “risking only 2% of the account size on a single trade”, which doesn’t sound any different than the risk management rule most traders use today. However, if there was a 10% profit in the account, they were told to reinvest the profit, and risk 2% of the new total account size. Furthermore, if there was a 10% loss, they were told to risk 2% of the new smaller account size.

See, in my compounding method, I am reinvesting the profit when I am up 30%. Furthermore, I’m adjusting my position size so that the risk per trade is 1 to 2% of the new and bigger account size. If I lose 30%, I’m not changing anything. But in Richard Dennis’s compounding method, he is not only reinvesting and adjusting the position size when he is in profit, but he is also reducing the position size when the account size gets smaller. Which method of compounding is right? Which one makes more money? And does reducing the position size when there is a loss even make sense?

To find out, I ran 5 experiments, took 600 trades, and simulated 9000 trades. The data you are about to see is not only surprising, but you will most likely end up using the best compounding method we have found.

In the first experiment, we will test if reducing the position size when there is a loss is a good move or not. Here, I have the probability section of the Official Trading Rush App. On one side, we will simulate 1000 trades with no adjustment to position size when there is a loss. For example, we will risk 1% per trade, and if there is a loss, we will still risk 1% of the initial capital. On the other side, we will simulate 1000 trades, but this time we will reduce the position size when there is a loss. For example, if the account gets smaller, we will risk 1% of the current capital, and not 1% of the initial capital.

To make sure there will be more losing trades in the experiment, I used a 30% win rate and a 1.5 to 1 reward risk ratio.

As soon as I started the simulation, the account balances of these two accounts started to fall like it was a market crash. By the 400th trade, the first account that didn’t use any adjustment methods and risked the same amount every trade, blew up the account. On the other hand, the second account where the position size was reduced when there was a loss, didn’t blow up the account even after 1000 trades. Furthermore, at the 400th trade, the second account still had 40% of the initial capital left. The 1st experiment shows us that reducing the position size when there is a loss and when the account gets smaller is actually a good thing.

But what if your win rate is good? Let’s say your win rate is good like 55% and you are pretty confident in what you are doing. Then what? Will reducing the position size when there is a loss even make sense since we are not going to lose money in the long run? To find out, I simulated 1000 trades with a 55 percent approximate win rate on two separate accounts. The first account will compound when there is a profit, but will not reduce the position size when there is a loss. On the other hand, the second account will compound when there is a profit, but will also reduce the position size when there is a loss.

As soon as I started the simulation, the account balances of these two accounts started to move in the upward direction. And after 1000 trades, the first account was up by approximately 3000%. What’s interesting is that the second account was also up by approximately 3000%. The second account however was slightly better than the first one. What this means is, reducing the position size when there is a loss won’t make a big difference in the long run if the win-rate is good, but since it significantly reduces the probability of making a big loss and blowing up the account in the short term, it is a better idea to reduce the position size when there is a loss and the account size gets smaller, just like the multi-millionaire Richard Dennis recommended to Turtle Traders.

In the second experiment, to find the best compounding method, I opened the Trading Rush Website, selected the trading strategy that got the highest TR Score as well as the highest win rate after 100 trades. Then, I took 100 trades again on the exact same market structure 3 times. The First time, I didn’t use any compounding method. The second time, I compounded when there was a 10% profit, and reduced the position size when there was a 10% loss. The third time, I compounded every time there was a profit and reduced the position size every time there was a loss.

In this experiment, the account with no compounding or adjustment method made 55% profit. The account that compounded and adjusted the position size at 10% change made 68% profit. And the account that compounded and adjusted the position size after every trade, made 71% profit.

In other words, with the highest win rate trading strategy, compounding and adjusting the position size after every trade was the best compounding method. But what if, the results were too good because of the high win rate strategy?

To make sure the data is correct, in the 3rd experiment I used the worst trading strategy we have ever tested 100 times. This strategy after 100 trades got a 33 percent approximate win rate with a 1.5 to 1 reward risk ratio. Since the win rate is so low, all three adjustment methods in the third experiment should make a loss. But, if our previous data is correct, and compounding and adjusting position size after every trade is actually the best method, then the same method should also make the lowest amount of loss with a bad strategy. And in the third experiment, it did.

The account with no adjustment method made the highest amount of loss. The account that compounded and adjusted the position size at 10% change had a slightly lower loss. And the account that compounded and adjusted the position size after every trade had the lowest amount of loss.

After looking at all of this data, we can safely say that we have found the best compounding and adjustment method, but unfortunately, not everyone has the same win rate in trading. The win rate in trading also depends on your Market View, on how good you are at identifying the good vs bad markets. I have shared how to identify the good vs bad markets in the Trading Rush Price Action Series, but let’s see how compounding and adjusting the position size at every trade would look like with a 50% win rate. A 50% win rate is fairly easy to achieve. Even the Trade Alerts I gave on Patreon had a higher win rate than this.

In the fourth experiment, I simulated 1000 trades with no compounding on one side, and 1000 trades with compounding and adjustment after every trade on the other side. In the end, the account with no compounding was only up by 260%, whereas the account with compounding plus adjustment after every trade was up by 1300%. Even with a 50% win rate, compounding and adjusting position size after every trade made a big difference in the long run.

But what if your win rate is even worse? Let’s say you are an absolute beginner and are getting a win rate just above breakeven. With a 1.5 to 1 Reward Risk Ratio, the breakeven win rate is 40%. So in the fifth experiment let’s see if compounding and adjusting after every trade will even work when the win rate is just above breakeven, something like 45%.

With no compounding, the first account was only up by 140%, whereas the second account with compounding and adjustment after every trade was up by 350%. There is clearly a big difference.

Till now, I have been compounding around 30% profit without making any adjustment to the position size when there is a loss. But after 5 experiments, we have enough data that says compounding and adjusting position size after every trade is not only better but adjusting position size when there is a loss significantly reduces the probability of blowing up the account. So I will change my compounding method as well.

That’s all! I hope you learned something. Get trade alerts, see how I take high probability trades by supporting Trading Rush on Patreon. Thanks for watching.

Tags best, buffett, compound, compounding, experiment, illusion, re-investing, reinvest, reinvesting, trading, trading strategies, trading strategy, warren, warren buffet, warren buffett

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I Risked 100 Trades Against The Trend! (MACD FLIPPED)

Post author By Trading Rush
Post date July 26, 2021

trading rush macd trading strategies trend flipped tested 100 times 12

Tag: trading strategy

In this video I am going to take 100 trades against the trend! When you buy at the long MACD crossover in an uptrend, most of you know you are going to have a 60 percent approximate win rate. But one of you asked to flipped that strategy to see what happens. So now we take long MACD signals in a downtrend and short MACD signals in an uptrend. What will be the win rate of this flipped strategy? Let’s find out!

The first two trades are lost, but the MACD indicator showed the reversal point quite accurately, but the downward momentum was not strong enough. This is because we are breaking one of the most important rules in trading, “Don’t trade against the trend”. But let’s see what happens if we dare to go against the trend.

Surprisingly the Flipped MACD Strategy is still winning a decent amount of trades. It loses multiple trades in a row when the price is trending, and then wins a couple of trades at the end of the trends. In the range market, it gives better entry signals than some of the worst trading strategies we have tested 100 times.

If this flipped MACD strategy can get a 40 or higher win rate, it will be better than the worst strategy that actually gives entry signals in the direction of the trend. Interestingly, the worst strategy we have tested is the MACD Zero Lag. That strategy only got a 33 percent approximate win rate.

Since we are trading against the trend, you might think that the win rate will be lower than breakeven, which in this case is 40 percent because of the 1.5 to 1 reward risk ratio, but interestingly the MACD was showing the end of the upward and downward moves quite accurately. Many times the price did not touch the profit target because of the stronger pressure in the direction of the trend, but the Flipped MACD strategy managed to win multiple trades at the end of the trends.

So if you take trades in the opposite direction of the trend with one of the best trading strategies we saw on the Trading Rush Channel, you most likely will get a breakeven percentage, because the Flipped MACD didn’t make or lose any money after 100 trades. That’s all!

Tags 100 times, flipped, macd, opposite, trading, trading strategy

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BEST Bitcoin Trading Strategy EVER with PROOF tested 100 TIMES

Post author By Trading Rush
Post date July 24, 2021

macd bitcoin 22

Tag: trading strategy

Does this Trading Strategy even make money in the Crypto Market? In this video, I’m going to take 100 trades with one of the best trading strategies to find its win rate and to see how much money it can actually make on the world’s largest cryptocurrency, Bitcoin.

We have tested a lot of trading strategies 100 times till now, but the best trading strategy we have tested on the Trading Rush Channel, was the MACD strategy. This strategy not only got the highest win rate, but the profit graph was also consistently going in the upward direction. Furthermore, it even got the highest score in the reliability category, and everyone who watches Trading Rush most likely knows by now that the reliability score of a trading strategy is more important than the win rate.

But here’s the thing. If the MACD Trading Strategy got the highest win rate out of all the strategies we have tested so far if we test it again on a different but good market structure, it should get a high win rate again, right? Remember, on the Trading Rush Channel, we don’t simply believe a strategy works. Instead, we analyze the real data the strategy produced in the real market and think logically. If data says it makes money, we use it and make money. If the data shows a bad win rate, we simply don’t use it!

In this video, we are going to test two things by taking 100 trades, first, if the Highest Win Rate Strategy we saw on the Trading Rush Channel can also give a similar high win rate on a different market. And the second thing we are going to test is, if the strategy works in the Crypto Market especially on Bitcoin, and how much money you would have made in this year, especially in approximately the last six months with this high win rate trading strategy.

On the world’s largest cryptocurrency, Bitcoin, the MACD strategy conditions are pretty much the same, except there is one thing different with Bitcoin that can make you lose money quickly. We will learn more about that at the end of the video.

Before we take 100 Trades, here’s how the MACD strategy works on Bitcoin:

Step 1. Buy when the MACD line crosses above the Signal line, below the zero line, only if the entry candle is above the 200 period moving average. Similarly, Sell when the MACD line crosses below the Signal line, above the zero line, only if the entry candle is below the 200 period moving average. If this sounds confusing, I have already made two to three detailed videos on the MACD indicator, the mistakes people make with it, and the best part about it.

Step 2. As you probably noticed, we are using the 200 period moving average to find the trend direction, in other words, it is still a trend trading strategy. In the long setup, set the stop loss below the pullback of the trend. And in the short setup, set the stop loss above the pullback of the trend.

Step 3. Set the profit target 1.5 times the size of the stop loss. This number is not randomly selected. It is the best reward to risk ratio we have found after taking 300 trades.

I tested this MACD strategy 100 Times on the largest cryptocurrency, and here’s what happened, and here are the points you should note.

Number 1. We are testing strategy on the latest market structure, because we are going to trade on the current market structure, and not on some few years old data where the market was slow and ranging and not worth day trading.

If you look at the chart, you can see that when the price was above the moving average, the MACD showed the end of the pullback using the crossover, and many of these trades at the beginning were won. When Bitcoin was in a downtrend, the MACD strategy simply gave good short entry signals and many of those trades were won.

As you can tell, the MACD strategy is not only giving good entry signals like it did when we tested it 100 times on the Forex Market, but the price movement of Bitcoin itself looks very similar to a good Forex price chart. Since the MACD strategy we saw on the Trading Rush channel does one job better than other indicators, show the end of the pullback with high accuracy, it doesn’t matter if it’s Bitcoin or Forex Market, if the price is trending, the MACD strategy will show the end of the pullback with great accuracy.

When we tested the MACD last time, the profit graph looked like this. The price was more consistently moving in the upward direction. And as you can see, on Bitcoin, the profit line in the Trading Rush App is also consistently going in the upward direction.

Also, this profit graph is way better than some of the other ones we have seen so far. For comparison, here is the profit graph of another strategy we tested 100 times, and here’s the profit graph of the MACD strategy. As you can see, MACD’s profit graph looks a lot better in the long run.

In fact, while taking 100 trades, the MACD trading strategy on Bitcoin only lost 3 trades in a row. This means the MACD strategy was just as reliable on Bitcoin as it was on the Forex Market.

But that’s not all. There is another reason the MACD strategy is performing so well on Bitcoin.

You see, when Bitcoin was all over the news for the first time for making this big upward move, the volatility on smaller timeframes was high. In other words, the price was making big moves and not staying at the same place for a longer period of time. After Bitcoin made a move in the downward direction, the volatility was relatively lower and the price was staying in the sideways direction for a longer period of time.

Now the MACD strategy is performing so well in the latest market structure, is because most of the current market structure is making good moves like before. Since the MACD strategy is a trend following strategy, and since the current market structure is making good moves, the MACD strategy that we saw in the very first video on the Trading Rush Channel, is giving a high win rate on Bitcoin just like it did in the Forex Market, and the profit graph is consistently moving in the upward direction.

But there is one important thing you should keep in mind. You see, Bitcoin is still Bitcoin. One time it is going to the moon, and the other time it is crash landing. The price movement of Bitcoin is different than what you see on a good stock, or even in the Forex Market.

When the price movement is good like it is right now, the MACD win rate will be good because the MACD strategy needs a trend. But if the Bitcoin movement slows down like it did last time, and the price starts to stay in a range for longer periods of time, the win rate will be obviously lower because the MACD strategy is not a range market strategy. If the price itself is not moving, you can’t magically make money. But right now the price movement is good, and the MACD trading strategy on Bitcoin is giving a very high win rate even with a high reward risk ratio, and we have the data that proves it!

After 100 trades on the world’s largest cryptocurrency, Bitcoin, the MACD strategy got an approximate win rate of 62 percent with a 1.5 to 1 reward risk ratio. Remember that the reward to risk ratio was 1.5 to 1, so a 62 percent win rate is actually very high. If you want a higher win rate, you can reduce the reward risk ratio to 1, but in the data we saw by taking 300 trades, the 1.5 to 1 reward risk ratio was the sweet spot. The MACD strategy performed excellently on Bitcoin, and only lost 3 trades in a row and won 9 trades in a row. And the profit graph consistently went in the upward direction just like we expected!

You can improve the win rate of the strategy even more, by combining it with the high probability strategies I talked about in the Trading Rush Price Action Course. The link is in the description! Also, Support Trading Rush on Patreon, and get to see more In-Depth Trade Analysis with the current best strategies I use. That’s all!

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I made a Trading Indicator that DISAPPEARS in the Choppy Market – Trading Rush Choppy Market Indicator

Post author By Trading Rush
Post date July 15, 2021
1 Comment on I made a Trading Indicator that DISAPPEARS in the Choppy Market – Trading Rush Choppy Market Indicator

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Tag: trading strategy

(FREE) Trading Rush Choppy Market : https://www.patreon.com/posts/trading-rush-52806962

I made a Trading Indicator that disappears in the choppy markets, so you don’t have to lose money in them. We are also going to take more than 100 trades with this disappearing indicator to see if it actually increases the win rate of a trading strategy. First, we created the Beep Boop indicator in the AI trades video, and it was surprisingly good! Then we created the Trading Rush Moving Average that disappears in the range market, and now, introducing the Trading Rush Choppy Market, which disappears in the choppy market, and even shows the strength of the good market.

If you have watched chapter 14 in the Trading Rush Price Action Course, you probably remember the simple but effective technique that you can use to filter the choppy markets. The Trading Rush Choppy Market indicator improves that technique even further.

The TR Choppy Market has three main components. When the price movement is good, the Trading Rush Choppy Market will indicate it with light green bars. When the price movement is extremely good, the Trading Rush Choppy Market will indicate it with dark green bars. However, if the price movement is choppy, the green bars will simply disappear.

But then there is this line that looks like a moving average because it is and it is showing the average strength of the good price movement. For example, when the price movement is good, and multiple green bars are formed in the Trading Rush Choppy Market Indicator, the average line will move in the upward direction. But when the price is choppy and not worth trading, the green bars will not only disappear, but the average line will start falling towards the zero line.

The TR Choppy Market Indicator ranges from zero to a hundred, and the higher the average line is, the better the price movement is. As you can see here, when the price movement is good and not choppy, the average line is staying above 20. And when the price gets choppy, the average line falls towards the zero line, and stays below 20 for the most part.

This is the first version of the Trading Rush Choppy Market Indicator, and while testing I have found that 20 is the starting level that differentiates the good vs bad market, and the higher you go, the more choppy market you are going to filter. By default, the Trading Rush Choppy Market will come with a horizontal line that you can adjust. If you noticed that on a particular chart 50 is the level that differentiates the good vs bad market, you can simply move the horizontal line to 50, and with that, you will also adjust the size of the green bars.

But now, let’s put the Trading Rush Choppy Market Indicator to the real test, to see if it actually filters the choppy markets.

But, we need a trading strategy that gives many entry signals in a short amount of time, and a market that is choppy and trending, so we can see if the win rate increases with the Trading Rush Choppy Market indicator.

For the indicator, we simply come to the Trading Rush website, look at the TR Scores of many different strategies that we tested 100 Times, and then select the indicator that gave a bad win rate.

Let’s use the CCI indicator that only got a TR Score of 3.5 in the win rate category, and I found AUD JPY, which is trending and is choppy on the 5 mins timeframe.

To see if the win rate goes up with the Trading Rush Choppy Market, I took more than 400 trades in total with different settings.

When I took 100 trades with the CCI indicator without the TR Choppy Market filter, it got a 29 percent win rate with a 1.5 to 1 reward risk ratio. The win rate is so low because the CCI has a bad win rate in the first place, and on top of that, we are testing it in the choppy market. But when I tested it again with the Trading Rush Choppy Market filter, with the 20 level to differentiate clean vs choppy market, it increased the win rate by 3 percent on the same market structure. And with the 30 level, the win rate was 4 percent higher. And when the 40 level was used to differentiate good vs bad market, the win rate was 12 percent higher, but I ran out of data and was only able to take around 80 trades. Adding around 20 more trades shouldn’t make a big difference to the win rate, because others had pretty similar win rates at the 78th mark as they did at 100.

In other words, the win rate significantly improved with Trading Rush Choppy Market Indicator, and it got better with higher filtering levels.

If we compare charts side by side, you can see that on this chart, the price got choppy in an uptrend. The CCI indicator on its own gave 8 false entry signals. But with the Trading Rush Choppy Market filter, 6 out of 8 signals disappeared. Here, CCI on its own gave 8 signals in the choppy market, but with the TR Choppy Market filter, only 2 remained. On this chart, the CCI indicator gave 10 bad signals, but with the Trading Rush Choppy Market Indicator, 60 percent of the bad trades were filtered.

Does this mean the third Trading Rush indicator we created is successfully filtering the choppy and bad markets? According to the data, it definitely is, and you can try it yourself because it is absolutely FREE just like all the indicators we have created so far! I will share the source code in a public Patreon Post with the installation steps! LINK is in the description! Also, support Trading Rush on Patreon and get to see In-Depth Trade Analysis and Trade Opportunity Signals. Thanks for watching!

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I took 5000 TRADES with these RIDICULOUS Trading Strategies and got this SURPRISING RESULT!!

Post author By Trading Rush
Post date June 2, 2021

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Tag: trading strategy

I have taken over 5000 trades in total when I took 100 trades with many different and popular trading strategies to find their win rates. Subscribers of the Trading Rush channel saw how some trading strategies gave good profitable win rates as expected, and how some less-known strategies gave unexpected win rates.

We even gave them a Trading Rush Score, or TR Score for short, to not only compare the strategies by win rates, but also by reliability, consistent profits, easy to use, and quality of trades category. If you have been watching Trading Rush videos for a while, or if you have looked at the TR Score chart on the Trading Rush Website, you might have noticed an interesting pattern in the data we collected by taking more than 5000 trades so far.

If you are a beginner trader still struggling to make money in the Forex and Stock Market, this video will most likely make you see what makes you lose money in trading.

Out of all 5 categories that make up the TR Score, let’s start with the win rate. In this category, all strategies are rated based on the win rate they got when we took 100 trades with them.

For example, the Aroon Trading Strategy got a breakeven percentage of 40 percent with a 1.5 to 1 reward risk ratio. So the Aroon strategy got 4 in the win rate category. Similarly, the worst trading strategy we have tested got a score of 3.3, and the best trading strategy we have tested on the Trading Rush channel, got a score of 7.8.

In other words, the win rate score ranges between 3.3 and 7.8.

However, if you plot all of the win rate data as a histogram, you will see that most trading strategies got a score between 4 and 4.9.

Remember, 4 is the breakeven point because we tested with a 1.5 to 1 reward risk ratio. Why 1.5 to 1, and not 2 to 1? Because when we took 300 trades to find out what reward risk ratio is the best, we found out that 1.5 to 1 is the sweet spot.

But the results get more interesting.

If we plot the same data using a pie chart, we will see that 76.5 percent of strategies made a profit, 9.8 percent got a breakeven percentage, and only 13.7 percent actually lost money. This means that 86.3 percent of trading strategies didn’t make a loss. But apparently, 90 percent of traders lose money in trading. We will get to that in a moment but watch this.

If you look at the Easy to Use category, you will realize that most trading strategies got a score between 7 and 7.9. This indicates that most strategies that actually made money in the long run, were simple strategies that even your dog can understand easily.

The Reliability category is based on the number of false signals and other reliability issues. A good score is anything above 4. And as you can see, most strategies performed well. If you have watched the Strategies Tested 100 Times series, you saw that most strategies that make money, in the long run, lowered their win rate and became very unreliable near the end of the trends. That’s why, even though most trading strategies made money and got good win rates, their reliability score was slightly lower and close to breakeven. This also means win rate is not the only thing you should be focused on, because some strategies will give more false signals in a row, and some are more reliable in the long run.

The Consistent Profits Category shows if the profits graphs of the trading strategies, or in other words, your profit graph with the strategy will look something mediocre like this or something good like this. As we can see, the consistent profits filtered the strategies even further. It shows that more trading strategies got messy profit graphs that looked like a range market or even worse. That’s another reason not to focus on the win rate alone. But as we can see, there were trading strategies that made more consistent profits, and the profit line was going more consistently in the upward direction.

The Quality of Trades Category shows how good the signals were, whether the entry signals were too early or too late, and more. As we can see, most strategies gave okay trade signals, many gave good entry signals, and some gave excellent trade signals.

But after looking at all of this data, we now know that most strategies make money in trading, and most of them have just above breakeven percentage. In other words, the trading gurus you watch, who claim to have a win rate in trading just above the breakeven percentage, are probably the good trading gurus, because trading is not much different than flipping a coin. When you flip a normal coin, there is a 50 50 chance of the coin landing on heads. But if you find a way to win just 55 percent of the time, your long-term success is guaranteed. The trading gurus you should be running away from are the ones who claim to have high win rates like 80 percent in the long run with a high reward risk ratio, because that’s highly unlikely, and who plays a game where the opponent has an 80 percent chance of winning and makes 2 times the money they invested?

80 percent with a high reward risk is possible in the short term, but the way to get a high win rate like 80 percent in the long run, is by reducing the reward risk ratio. Occasionally, you will see some ads claiming to have indicators that got 70 80 percent win rate after backtesting even with a high reward risk ratio. They usually tell the truth, but they are also misleading.

You see, anyone who claims to have gotten a very high win rate like 80 percent with a high reward risk ratio while backtesting, is probably backtesting the strategy on smaller timeframes like 5 and 15 mins, which is a really bad idea and can lead to misleading results.

You see, most of the time the price moves like this. It goes up, down, and in the sideways direction. Most of the time it moves in the sideways direction. If you test a trading strategy on this market structure, there is no problem as this is what you will see most of the time in the live markets. But if you test a strategy on timeframes like 5 mins, you are forgetting that there are a lot of timeframes above the entry timeframe, and on some of these timeframes, the price makes sudden big moves in one direction. When the price moves strongly in one direction on a higher timeframe, the 5 min entry timeframe will be in one of the best uptrends you will see. This trend will be more like a market crash. If you take trades in the direction of the market crash, you will win a lot of trades and get a crazy high win rate. But every day is not a market crash. When the price on the higher timeframe will slow down, the entry timeframe will most likely be trending, but will no longer have that high win rate. That’s one of the reasons I don’t test scalping strategies on smaller timeframes, the results will be misleading.

The best way to get a higher win rate in trading is by using the same higher timeframe thing I just said. If you have seen the live trading videos on the Trading Rush Channel, or the live trade analysis posts on Patreon, you know that I always analyze the higher timeframe first, and trade in the direction of that higher timeframe.

But wait a minute, after taking 5000 trades, we found out that most trading strategies make money in the long run, and the lowest win rate strategy didn’t even lose 50 percent of the account, how do people lose money in the Forex and Stock Market?

Well, beginner traders switch trading strategies once they lose a few trades with it. But since most strategies only have just above average win rates, they switch again, and again, and the cycle continues, when they should be focusing on money management and trading psychology. I have already made videos on money management and trading psychology, and in the next videos, we will see how to trade price action strategies like a pro. Subscribe to Trading Rush and ring that notification bell to see that. Support Trading Rush on Patreon and get to see in-depth trade analysis and trade opportunity signals.

Thanks for watching!

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I took 100 TRADES with these 2 INCREDIBLY SIMPLE Moving Averages that create a better CHANNEL than..

Post author By Trading Rush
Post date May 29, 2021
1 Comment on I took 100 TRADES with these 2 INCREDIBLY SIMPLE Moving Averages that create a better CHANNEL than..

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