0:02 Welcome to the long and the short a show
0:04 where you can expect an honest take on
0:06 trading something you won't hear
0:09 elsewhere. I'm your host Sepra. In the
0:11 last episode we broke down what trend
0:13 following really is and how Richard
0:15 Donain often called the father of trend
0:18 following helped shape systematic trend
0:20 following as we know it today. We even
0:22 tested some of his ideas right here on
0:24 Nifty. Today we are taking that a
0:25 [music] step further. I'll walk you
0:27 through how to build a simple trend
0:30 following system that actually works.
0:31 [music] And to do that, we'll focus on
0:34 two key concepts. Trading time frame and
0:37 trend identification. Time frames are
0:38 actually the price intervals that you
0:40 trade. And trend identification
0:42 approaches are about methods and
0:45 indicators that can be used [music] to
0:47 identify a trend within a given time
0:49 frame. All of this once again using
0:52 Nifty as a playground. All right, then
1:00 Like I always do, a bit of a side story
1:03 from the world of astrophysics.
1:04 Incidentally, I'm reading the book
1:07 Astrophysics for People in a Hurry by
1:10 Neil Degra Tyson. In it, he describes
1:12 how supernova explosions happen. Most
1:14 stars spend their whole lives just
1:16 burning quietly like a candle that never
1:20 goes out. Inside them, tiny atoms crash
1:22 together and make light. And that's what
1:23 keeps them shining for millions, even
1:26 billions of years. That's what the sun
1:28 is doing right now, just glowing
1:30 steadily. A slow and steady burn of
1:33 sorts while keeping everything on planet
1:36 Earth alive. But some stars are much,
1:39 much bigger than our sun. So big that
1:42 they live fast and burn out young. When
1:44 these giant stars run out of fuel,
1:46 something amazing happens. These stars
1:48 can no longer hold themselves and they
1:51 collapse, exploding into what scientists
1:53 call a supernova. It's like a massive
1:56 boom. That explosion to me feels a lot
1:59 like a breakout. Sudden, powerful, and
2:02 impossible to ignore. That steady burn
2:04 that happens before the supernova, well,
2:06 that's like a moving average. Slow,
2:09 persistent, quietly building momentum.
2:11 Markets tend to work the same way.
2:13 There's a long stretch of gradual
2:15 process, then boom, a breakout. [music]
2:18 That gives us two ways to catch a trend.
2:20 If you want to ride the slow buildup,
2:22 moving averages are your friends. If
2:25 you'd rather wait for the big moment,
2:26 that's where breakout tools like Super
2:29 Trend come in. Of course, there are many
2:31 ways to capture breakouts. Any channel
2:33 or rangebased indicator will do. I just
2:35 prefer Super Trend because it reacts
2:37 faster than most and catches the move
2:39 early. Even if you look at the research
2:41 and literature around trend following,
2:43 almost all of it comes back to these two
2:45 fundamental methods. [music] Take the
2:48 book following the trend by Andreas. I'd
2:51 call it the manual of systematic trend
2:53 following. He dedicates an entire
2:55 chapter to comparing exactly these two
2:57 approaches, breakouts versus moving
3:00 averages. Similarly, Ken Tropins's
3:02 Graham Capital, one of world's leading
3:04 CTA firms, has published several
3:06 insightful papers exploring how
3:08 professional managers identify and
3:11 capture trends. Again, their work also
3:14 highlights the same two pillars, the
3:16 steady signal-driven momentum captured
3:18 by moving averages and the explosive
3:21 threshold-based shifts captured by
3:23 breakouts. So, in a way, I'm not really
3:25 reinventing the wheel here. These
3:27 methods are foundational to trend
3:29 following. Time-t tested, datadriven,
3:31 and battleproven across decades of
3:34 market cycle. That's why we chose them.
3:37 That brings us to the next and perhaps
3:40 the most important question. Do time
3:42 frames of analysis really matter? By
3:45 time frames, I mean daily, 4hour, or
3:48 even 1 hour bars. Some people call them
3:50 time intervals or data intervals, but
3:53 all they refer to is the same thing. the
3:55 frequency at which you look at market
3:57 data. Now, in most books on trend
4:00 following, time frame selection is
4:01 treated as a matter of personal
4:03 preference, something you pick for
4:06 convenience, not as a parameter that can
4:08 truly change outcomes. But I found that
4:10 approach unsatisfying
4:13 except for the book technical analysis
4:15 using multiple time frames by Brian
4:17 Shannon. It also barely scratches the
4:20 surface, but it plants an important
4:22 idea. the power of looking at markets
4:25 through multiple time frames. Shannon
4:27 talks about aligning higher and lower
4:29 time frames so that your trades move
4:31 with the broader tide [music]
4:34 not against it. Later while reading the
4:36 book inside the black box by Rishi
4:39 Narang that concept really clicked. He
4:42 makes a simple but profound point. What
4:44 looks like trend on one time frame might
4:47 appear completely memereting on another.
4:49 That's when it hit me. Time frames
4:51 aren't just about convenience. They
4:54 define perspective. So when we build or
4:56 test a trading system, it's not enough
4:58 to pick one time frame and run with it.
5:01 We need to test a system across time
5:04 frames, compare outcomes, and understand
5:06 where the edge truly lies. Later when I
5:08 present the data for three different
5:10 time frames, daily, 4hour, and 1 hour,
5:12 you will notice the difference for
5:14 yourself. So we've spoken about two
5:16 fundamental building blocks of creating
5:19 a trend following strategy. Trend
5:21 identification method and time frame
5:23 analysis. Now let's get to the
5:26 interesting parts that is the back test.
5:28 A fair disclaimer, this is not a
5:30 recommendation to trade any of the back
5:33 tests or simulations that I share. These
5:36 examples use spot prices and are
5:38 discussed only for illustrative
5:41 purposes. Over to the back test. The
5:43 instrument or index I'm testing is Nifty
5:46 Spot. I will be testing all of this on
5:48 three different time frames. Daily,
5:51 4hour, and 1 hour bars. Across these
5:54 time frames, we will apply EMAs and
5:56 super trend to separately compare their
6:00 performance. The data here is from 2015
6:03 Jan to 2025 October. Let me give you a
6:05 quick example of how these strategies
6:07 are defined. For the EMA, we go long
6:10 when the price closes above the EMA and
6:12 continue holding the position as long as
6:14 the price stays above it. We go short
6:16 when the price closes below the EMA.
6:20 This setup is known as an S or stop and
6:23 reverse system. That means the exit for
6:25 a long trade is also the entry for a
6:28 short and vice versa. The system is
6:30 always in the market switching direction
6:32 whenever the signal flips. [music] With
6:35 super trend, the logic remains similar.
6:37 Only the reference point changes.
6:39 Instead of the EMA line, we use the
6:41 super trend bands. If the price closes
6:43 above the upper band, we go long. If it
6:46 closes below the lower band, we go
6:48 short. We will use a similar logic
6:50 across all time frames. The look back
6:53 period for EMAs would change. Of course,
6:55 let's start with the daily time frame.
6:57 For daily bars, I use a 8 period EMA.
7:00 And in super trend, I use the default
7:02 103 parameters. Since super trend is a
7:04 volatility based indicator, the look
7:06 back input [music] in it need not match
7:08 the EMA look back. Hence, I use the
7:11 default 103 across for this
7:13 illustration. In general, the 8 period
7:16 EMA on daily does a pretty bad job
7:18 compared to a 103 super trend. Of
7:20 course, by now, if you have been
7:22 watching the episodes of the long and
7:24 the short, you would know that it makes
7:26 little sense to look at the short side,
7:28 especially on daily time frames. So for
7:30 this one, let's just compare the long
7:32 only parts. Look at the table from the
7:35 top. Total P&L speaks for itself. And
7:38 now look at the average P&L that's 35
7:41 versus 270. That's a massive difference.
7:43 What that means is on an average per
7:46 trade, EMA system makes just 35 points
7:49 whereas super trend makes 270 points.
7:51 This happens because EMA takes a lot of
7:54 trades 256 versus 44 in super trend. And
7:56 that many trades is not always a good
7:59 idea as the system keeps chopping around
8:02 with many loss-making trades. The only
8:04 thing good about the EMA system is the
8:07 return to max draw down ratio. So it's
8:08 quite evident that super trend is
8:11 outperforming on almost all parameters
8:14 on a daily time frame. But what would be
8:17 the reason for such an outperformance? I
8:19 think it's because Super Trend adapts to
8:21 volatility rather than reacting to every
8:24 price fluctuation like the EMA does.
8:27 Since it uses the average true range to
8:29 set its bands, the super trend naturally
8:31 widens during volatile phases and
8:34 tightens when markets are calm, allowing
8:36 it to filter out noise and capture only
8:39 sustained directional market moves. On
8:41 an index like Nifty which has a strong
8:45 long-term upward bias, this volatility
8:46 adjusted approach keeps the system
8:49 invested during the large trending
8:52 phases and avoids frequent whips saws in
8:54 the faster indicators. In essence, Super
8:57 Trend strength lies in its built-in
8:59 noise filter, its ability to stay
9:03 committed to a direction until a genuine
9:05 reversal occurs, resulting in longer
9:08 profitable holds, higher average trade
9:10 returns, and overall better risk
9:13 adjusted performance, but with a higher
9:16 max draw down. Now, if you look at the
9:18 equity curves of both EMA and super
9:20 trend, it becomes quite clear. Let me
9:23 show you. The blue line trending up is a
9:25 line representing the long only on
9:28 daily. Almost no action till 2020 and
9:30 then it picks up. Now compare this with
9:32 the equity curve the super trend on
9:34 daily. Looks smooth, isn't it? More
9:37 importantly, it picked up the trend much
9:40 earlier from 2017 onwards with a minor
9:44 dip in 2020. So all in all on a daily
9:46 time frame, super trend wins on
9:47 consistency and risk adjusted
9:50 performance while EMA wins a bit on
9:52 speed and efficiency. Nothing much
9:54 otherwise. With the daily time frame
9:56 done, let's [music] now go one level
9:59 deeper. The 4hour time frame. Here the
10:01 look back period [music] for the EMA is
10:04 set to 21. Why 21? Because it maps to
10:07 the same 1.5 week duration similar to
10:09 the 8 period look back on daily. and the
10:11 super trend parameters remain the same
10:14 at 103. Here I want you to see both the
10:16 long only and the short only sections of
10:18 the table. On the 4hour chart, the
10:20 absolute P&L for longs may appear higher
10:22 at first glance. But what truly matters
10:26 is the average P&L per trade. 48 for EMA
10:29 and 153 for super trend. This is where
10:31 super trend clearly leads mainly because
10:34 it generates few trades. On the long
10:36 side alone, EMA triggers nearly four
10:39 times as many trades as super trend.
10:41 Once you factor in transaction costs,
10:43 most of the EMA's apparent edge may
10:46 disappear. Interestingly, as we shift to
10:48 this lower time frame, the short side
10:51 starts turning profitable. Particularly
10:53 for EMA, look at the table. While the
10:55 short trades on super trends are in
10:58 negative of close to 4,000 points, EMA
11:00 based shorts are slightly positive at
11:04 700. That's because emas react faster
11:06 and in nifty short trends tend to be
11:09 sharp and swift giving emas a natural
11:11 advantage there. When it comes to
11:13 drawdowns, super trend still shows
11:16 higher max draw down compared to EMA but
11:17 the gap between the two narrows
11:20 significantly. On the daily chart, Super
11:23 Trend's draw down was about 70% higher
11:26 whereas on the 4hour chart it's around
11:28 20% higher compared to the EMA. Also
11:30 note how the total points captured
11:33 increase as we move to a more granular
11:35 time frame. A sign that shorter time
11:37 intervals can pick up more market
11:40 movement though often at a cost of
11:42 higher trade frequency. Now let's look
11:44 at the equity and the draw down charts
11:47 for EMA. It is slightly more smoother
11:49 than the super trend. Look at the period
11:52 post 2024 especially. This smoothness
11:54 comes from the faster reaction time of
11:57 EMAs. As you can see, the draw downs in
12:00 the super trend on 4hour period are more
12:02 deeper. All in all, if you are exploring
12:05 the 4hour time frame, you may have to
12:07 drill down deeper to analyze the year
12:09 and monthwise returns and the average
12:12 P&Ls and then find the sweet spot. So,
12:14 we're now done with the [music] daily
12:16 and the 4hour bars. Now, let's move to
12:19 the 1 hour time frame. Among the three,
12:21 this is the fastest time frame that we
12:23 are going to look at. Here the EMA uses
12:26 a 50 period look back exactly what I
12:28 track in our weekly market metric series
12:30 while the super trend parameters remain
12:33 unchanged at 103. Let's start with the
12:35 tables on this time frame. We will
12:38 compare all the three long plus short
12:41 long only and short only. Now the key
12:43 difference [music] between the two on
12:46 this time frame lies in the gross P&L
12:48 points that is the total P&L. On that
12:50 metric [music] EMA definitely takes the
12:53 lead. However, when we focus on the
12:56 average P&L for long only trades,
12:58 [music] Super Trend still outperformed
13:01 but not as much as it did on daily. Same
13:03 on win rate. Super trend offers a way
13:05 better win rate for a trend following
13:07 system compared to the 50 period EMA.
13:10 42% versus 29%. Makes a difference on
13:13 the margins. Where things get really
13:15 interesting is on the short side here.
13:18 The EMA clearly wins with 4,700 points
13:21 versus 1,400 points on super trend
13:24 because it reacts faster and on a 1 hour
13:26 time frame, short trends in Nifty tend
13:30 to develop and fade quickly. The EMA's
13:32 responsiveness helps it to capture those
13:34 swift downward moves far better than
13:36 super trend does. If you want to see
13:38 that difference, look at the equity and
13:41 the draw down curve chart. You'll notice
13:44 that the gap between the long short and
13:46 the long only results is much wider for
13:49 EMA. That tells you something simple but
13:52 powerful. The value added by the short
13:54 trades in super trend is almost
13:56 negligible. Whereas for EMA, the shorts
13:58 contribute meaningfully to overall
14:01 profitability. You can look at the short
14:03 only equity curve as well. [music] The
14:05 green line in the super trend version.
14:07 It tends to give up on the gains more
14:10 often than not. Now that we've compared
14:13 EMA and [music] super trend across three
14:16 time frames, daily, 4hour, and 1 hour,
14:18 you might be wondering what exactly is
14:21 the conclusion here. Well, there's no
14:24 one answer. But what I can offer is a
14:27 framework, a way to think about it
14:29 systematically so that you can decide
14:31 for yourself which model fits your
14:33 trading style best. [music] Now, let's
14:35 go back to the key ideas. We started
14:38 with the time frame of trading and the
14:40 method of capturing trends. Talking
14:42 about time frames, you'll notice that as
14:45 we move to lower time frames, the gross
14:47 P&L increases. Now, that's an important
14:51 insight. One possible reason is that
14:54 maybe a large part of the trends often
14:57 unfolds intraday in what is called an
15:00 impulse leg, the first strong move of a
15:02 trend. Another factor is that market
15:04 corrections and crashes tend to start
15:07 during the day and continue over to
15:09 subsequent days. An hourly system can
15:12 therefore help exit long trades faster,
15:15 protecting profits during sudden drops
15:17 and that I think makes a huge
15:20 difference. Slower time frames like the
15:22 daily chart often miss this early
15:24 momentum. Of course, this behavior can
15:27 vary from one asset to another depending
15:29 on how its intraday price action tends
15:32 to be, but in our case with Nifty,
15:34 shorter time frames clearly seem to
15:37 capture more of the trend. Now, let's
15:39 turn to the two indicators we used, EMA
15:42 and super trend. Here's what stands out.
15:45 In certain contexts, like capturing the
15:47 short side trends, EMA performs better
15:49 because it reacts faster. But for
15:52 longside trends, super trend often comes
15:54 out ahead. It takes fewer trades and
15:57 gives each position more room to breathe
16:00 thanks to its volatility adjustment. So
16:02 maybe the final choice depends on what
16:05 you want to capture. If you want to play
16:08 the long only game, super trend might
16:09 suit you better. But if you want to
16:12 include short trades, EMA gives you that
16:14 extra edge. Or perhaps the best approach
16:16 is a blend of both. combining [music]
16:19 the stability of super trend with the
16:22 agility of EMA. But here's the thing,
16:24 don't take any of what I shared as
16:26 gospel. I just shared an illustration
16:28 with you all. On top of that, if you
16:30 tweak the lookbacks, add buffers to
16:33 reduce the trades, especially for EMA,
16:35 you may be able to get better results
16:37 than what I shared. Same with super
16:39 trend as well. I'll leave that work to
16:42 you. And that brings me to the end of
16:44 this part two episode on trend
16:46 following. I hope you found these ideas
16:48 useful. If you have any questions, drop
16:50 them in the comments and I'll do my best
16:53 to answer them. In the next episode,
16:55 I'll focus on the idea of trend
16:57 following across two uncorrelated
17:01 assets, Nifty and gold. And yes, don't
17:03 forget to subscribe to this channel. See
17:05 you in the next episode of the Long and
17:08 the Short Show. Till then, trade safe
