Technical Insights, June 2021

Technical Insights has been a labour of love for the CMT India Community. It was born out of a desire for members to have a publication that helped showcase the practice of technical analysis beyond the very narrow frame that most non-practitioners understand it to be. We wanted this to be a platform to celebrate high quality technical analysis.

Led by editor Rashmi, Shastry, CMT, volunteer contributors of the India chapter have managed to achieve their goal. Over the 10 months since its launch, Technical Insights has become a platform for learning technical nuanced applications of technical analysis. Over 10000 page views from a diverse audience from students to seasoned market professionals attest to the value that this publication has added to the financial services industry landscape. It is now time to evolve.

As Technical Insights retires, to be reborn in a new avatar, I want to thank all contributors to the publication during its 10-issue run.

Every month, Rashmi would reach out to CMT charter holder volunteers across India to contribute to the newsletter. These volunteers would send in their contributions by the 1st of the month. I would compile these by the 3rd, and publish them on the 4th. Kaizad Marolia would then compile the monthly mailer and send it out to our mailing list in India.

I would be remiss to not acknowledge two people who made this possible.

Volunteers in focus:

Milan Vaishnav, CMT, MSTA

Milan was one of the first people to reach out to me with the idea of a publication that would help showcase technical analysis to the Indian financial services community. His passion for the project and why it was important got the ball rolling. Milan also was our contributor-of-last-resort. If there was ever a month when we did not have enough contributions, Milan would ensure that he wrote a piece for Technical Insights, that was full of his insightful and unique take on the markets.

His contributions to the Association as a volunteer leader and a contributor to Technical Insights has helped Milan in being viewed as a thought leader in the community, in India and overseas.

 

Rashmi Shastry, CMT

Rashmi brought a unique blend of a background in journalism, a deep understanding of technical analysis, and a burning desire to contribute to the growth of the Association. Every month, with clockwork regularity, she ensured that the content for the newsletter was collated, edited and ready for publication. She provided Technical Insights with an editorial vision that ensured balanced, thoughtful representation to every nuance of technical analysis. Even today, if you go back to past issues of Technical Insights, you will see the continuum of content that is at once timely and timeless.

Her work as editor of Technical Insights, and her enthusiasm as a volunteer have also helped Rashmi grow in her career. It continues to bring her global visibility, and as you will notice in the coming months, this will only grow.

 

On that note, I wish you readers all the very best, and I look forward to sharing my thoughts with you in the next avatar.

Technical analysis majorly considers charts patterns with reference to time. While price and volume are studied majorly with reference to time, time as an independent variable of study can also yield valuable insights for trading decisions. The periodic fluctuations impacting a price series is referred to as time cycles.

There are recurring cycles in financial markets and by identifying the cyclicality, one can forecast the possible tops or bottoms and accordingly take trading or investing positions.

The cycle bottoms are referred to as troughs and the tops are referred to as crest. One complete cycle is movement from trough to trough. The important characteristics of cycles are amplitude, period, and phase.

1. M. Hurst has described a specific set of cycles that can be identified in financial markets. These are called as nominal cycles. The actual cycles that prices follow will be in close approximation to the nominal cycle. Following are the set of nominal cycles in terms of trading days.

Trading days – 112, 56, 28, 14, 7

Cycles are related to one another by the factor of 2. Hurst defined that if there is a cycle of 56 days, then there will be two smaller cycles of 28 days. These 28 days cycles will be composed of two 14 days cycles. Thus, cycles are harmonious in nature and are mostly related by the factor of 2.

In this research we will focus on analyzing the Cycle period and understanding their forecasting ability with respect to the current market environment across different assets

MCX Crude (INR) Futures Chart – 115 Days Time Cycle

Gold Futures (USD) 55 Days Time Cycle:

 

Nifty 15 minutes chart – 46 period Time Cycle:

We used the concepts of Hurst’s Time Cycles and found actual cycles working on Crude Oil, Gold prices and Nifty index.

Crude Oil 115 Days Cycle: We can see that all the major lows formed on Crude Oil is near 115 days Time Cycle. This includes the low formed during the crash seen in April 2020 when Crude in USD turned negative cited to the Oil glut created as a result of ongoing Pandemic. But if one were to follow this cycle period it very clearly suggested that the upturn was imminent; while the majority were focusing on news. The recent low was also near the low of this cycle.

Gold is near 55 days cycle including the recent one formed in April 2021 near 1700 and a rally of more than 12% from there is seen. Once the trend is clear on a longer time frame a trader can then drill down to smaller time frame charts in order to time the exact entry using simple methods of Time and CandleSticks.

Nifty 15 minutes chart – 46 period Time Cycle shows the application of Time cycles on Intraday charts and it is working very well by helping traders catch short term lows. Majority of upturns on nifty have come from this cycle lows on the Intraday chart.

The above examples clearly show the application of simple yet powerful Time Cycle methods across different assets with varied time frames. This method can help traders time the entry accurately and identify the trend much earlier than others who are busy analyzing the news or events that seem like logical reasons for the move. But events do not help traders to be placed in correct direction of the trend but only results into volatility.

Timing the market has become a lot more important with the breakout of Covid-19 pandemic in the year 2020 as there are big swings on either side that traders can capitalize by knowing about important Time Cycle methods.

References for above research: Book – Effective Trading in Financial Markets Using Technical Analysis by Smita Roy-Trivedi, Ashish H. Kyal

Introduction
Bitcoin is in the grips of a significant reset after deteriorating technical momentum, excessive leverage and a slew of negative headlines culminated in a two week sell off that has caused massive liquidations across exchanges.
For the uninitiated, investing in the cryptocurrency/digital asset space can be a daunting task. Access to markets, insane leverage, extreme volatility and the confusing crypto native nomenclature set it apart from traditional assets. Not surprisingly, market analysis is also very different to that of legacy financial assets.
At its core, the Bitcoin blockchain, is a financial network and therefore can be viewed through the lens of Metcalfe’s law which states the value of a network is proportional to the square of the number of connected users of the system (n²). Bitcoin along with other public blockchains, also provide a rich source of new and interesting data for analysis. Combining this “on-chain” data with price action can provide a more holistic understanding of the market structure, strength of the network and the utility of the underlying asset. Finally, Bitcoin is a macro asset. It was birthed into the world during the 2008 Global Financial Crisis and its correlation to central bank monetary policy is undeniable. The following analysis looks to draw from all these analytical disciplines.

Analysis
The bitcoin halving, which occurs approximately every four years, is an event where the reward which accrues to the miners for verifying each new block of transactions is cut in half. Understanding the supply/demand dynamics is key to appreciating Bitcoins store of wealth characteristics. Assuming demand is constant (or rising) then the programmatic deflationary supply schedule should support a rising Bitcoin price.
Bitcoin is currently experiencing a 50% drawdown which compares to the previous post-halving periods, where it experienced mid-cycle pullbacks of 70% and 40% (white oval shape) before going on to new all time highs and a cycle peak. Based on linear and logarithmic regression of the long term trend, Bitcoin’s six fold increase since May 2020 is still shy of the projected target of $100,000-$150,000 for this cycle.

Chart 1:
Bitcoin Halving Cycles

On-chain data shows that during the current drawdown, the number of active addresses (green line), a proxy for network strength, has fallen 21%. On the other hand, the number of addresses holding a Bitcoin balance (pink), an indicator for Bitcoin’s utility as a store of value, fell by only 2.5% and is now back near the all time highs.

Chart 2:
On-Chain Data: Active Addresses & Number of Addresses with a non Zero Balance

Addressing the short term price action, the move over the past two weeks was preceded by a large bearish divergence in the daily RSI. The Head and Shoulders top which formed upon the break in the neckline at approximately $48,000 brought in a downside target of $30,000 which was reached in very quick fashion.
The collapse to 30,000 also broke through the 200 day moving average (blue) for the first time this cycle.

Chart 3:
Bitcoin Price, RSI and 200 day moving average

Of the 19 previous times the price broke below the 200dma, 11 times Bitcoin was higher 100 days later with an average return of +13.81%. However, the average return in the first 60 days is negative suggesting further downside is most likely for the asset, before a recovery sets in.

Chart 4:

Statistical Analysis: Forward returns from a cross below the 200 day moving average

The unsettling aspect to the parabolic move over the past six months was that was being increasingly driven by the use of derivatives. The recent sell off has provided the opportunity for the market to reset as $9b in leverage was wiped from exchanges.

Chart 5:
Futures Open Interest

The perfect storm of last year’s May Halving event just two months after the Federal Reserve’s unprecedented Covid19 pandemic response was what gave Bitcoin the rocket fuel it needed to 15x off the March 2020 lows. It is clearly evident from the chart below, that Bitcoin outperforms during periods of monetary expansion. On the flipside any moderation of asset purchases (or tightening) has coincided with the previous cycle peaks in late 2013 & 2017.

Chart 6:
Bitcoin Price Cycles and the Fed Reserve Balance Sheet

Summary

Chart 7:

Crypto Technology Adoption Curve vs. The Internet Adoption curve of the 1990’s

Global Macro Investor Newsletter

Crypto as a whole is seeing the fastest rate of adoption of any technology in human history (113% per annum vs 63% for the internet) and similarly to network effect equities (AMZN, FB) as long as the participants in the network keep growing over time, the value of the network should rise exponentially. Furthermore, the macro thesis for Bitcoin, the world’s most decentralised financial network and store of value remained unchanged despite the recent dramatic selloff. Whilst the technicals suggest further downside potential for the next several months, the asset is likely to make new all time highs over the next 12-18months.

In the analysis in December, PSU stocks looked like they would outperform the others. And it seems like that has been the flavour of the quarter for the short term traders in 2021. Many  might have missed the bus to the PSU rally but it’s not late yet. One sector in PSU is yet to outperform Nifty in the quarters ahead. and that is PSU BANKING SECTOR.  

Recently, we witnessed some tremendous moves on stocks like SBIN and CANARA BANK but the rally is nowhere near the end when it comes to BOB and PNB. 

 

The above chart is of CNX PSU BANK weekly time frame and we can see that it is trading exactly at the three-year resistance line as of 4th June 2021. We have seen a 40% bounce back from the lows of 2020, but there is still a long way to go!. Coincidentally, the three-year resistance trend line at 2514 is the same as the 200 WEEK SMA resistance for close to two years now. The PSU index has recently broken out of a short term channel, confirming the momentum for a fresh leg up. But most importantly, it has underperformed NIFTY (orange line) since 2018 and the divergence has widened to most in recent months. By observing MACD’s internal crossover and RSI’s bounce back from 50 level mark, it seems like the resistance at 2514 would be breached with volumes within weeks and divergence with Nifty could be matched up. So it’s better late than never and we could see a 20% up move on the PSU BANK index to 3000 from 2500. 

Here is a novel way of arriving at a target for Nifty Bank. The method used for projecting Nifty Bank target is through its components. Here the target and stop loss for each of the Nifty Bank is arrived using Technical Analysis.

SR. NO.	STOCK	WEIGHTAGE	CMP	TARGET	SL	BANKNIFTY
1	HDFCBANK	27.41%	1512.00	1715.00	1375.00	CURRENT CLOSE	35344
2	ICICIBANK	21.09%	651.00	716.00	609.00	VIEW	BULLISH
3	AXISBANK	14.30%	745.00	854.00	686.00	FORECASTED	39688
4	KOTAKBANK	13.02%	1797.00	2040.00	1705.00	SL	32459
5	SBIN	11.74%	432.00	449.00	375.00
6	INDUSINDBK	4.57%	1008.00	1293.00	880.00
7	BANDHANBNK	1.93%	302.00	334.00	285.00
8	AUBANK	1.84%	984.00	837.00	1035.00
9	FEDERALBNK	1.38%	86.00	104.00	86.00
10	IDFCFIRSTB	1.26%	57.00	76.00	47.00
11	PNB	0.73%	42.00	53.00	35.00
12	RBLBANK	0.72%	211.00	231.00	201.00

Particularly in the above calculation the parameters such as Fibonacci Time Series, Elliott Wave Analysis, Short-term moving averages like 20DMA and 40DMA and long-term moving averages like 100DMA and 200DMA are used. On the momentum indicator front, KST, MACD and RSI are used for price momentum analysis whereas OBV is used for Volume Analysis. Based on these Technical parameters the target and stop loss are arrived for each stock. Using this calculation and the weightage of each stock in Nifty Bank the contribution of these stocks is calculated which is summed up to arrive at the final target for the Nifty Bank (as well as the reversal level). This method helps to cross check the analysis done simply on the chart of Nifty Bank. It also helps to figure out which stock will lead and contribute how much. This also helps in positioning the trade as well. The individual stock targets taken are on a conservative basis and no extension is accounted for hence the Nifty Bank target is also conservative one and it may extend on the upside as well

Above is the daily chart of Nifty Bank

The Index seems to have completed its wave 4 correction and with the recent reversal from the lower levels appears to be in wave 5 up. The momentum indicator MACD is back above the zero-reference line which is quite positive in the short term. The monthly MACD is already into the buy mode indicating that the long-term trend is already up. Wave 4 corrected 38.2% of wave 3 whereas wave 2 had corrected more than 50% of wave 1 hence the guideline of alternation is also met. Now, wave 5 is expected to take Nifty bank well above its wave 3 swing high i.e., 37,708.75 on a conservative note and with the help of reverse channeling the channel target comes to 45000 levels. Since, wave 3 was extended, wave 5 is expected to be equal of wave 1 and in that case the equality target comes to 47000 levels.

Conclusion: The Standalone chart of Nifty Bank indicates that the trend is up in the medium to long term and the targets are in the range of 37000-47000. The above model also shows that the medium to long term trend is positive and Nifty Bank is likely to move upwards.

Note: One can have one’s own method for calculating the target and stop loss and thus can have different views and values, however, the above model can help to judge where the strength is likely to come from and thus provide interesting insights.

Source: Bloomberg

A 20 year backtest of the NIFTY’s monthly chart shows that a strategy that bought the NIFTY whenever the 14-month RSI crossed above 50 has generated an average 12-month forward return of nearly 24%. Interestingly, there have been 10 such instances in the 20-year period and in 90% cases, the 12-month return was higher. The 10^th signal was generated in July 2020 and hasn’t been evaluated for its returns as 12 months haven’t come to pass yet.

Please note that this indicator is based on an investing horizon of 12 months after the signal is generated; there is no explicit technical signal to exit the long NIFTY trade triggered when the monthly RSI goes past 50.

Now, how has this strategy played out for individual stocks in the NIFTY? We have to acknowledge that the said analysis will suffer from survivorship bias, aka, many stocks that were in the NIFTY over the period of analysis may not be in the NIFTY in 2021, while a few others might have been added only recently. The following table summarises the mean returns for the “now” members of the index over a 30-year range.

Source: Bloomberg

From the table above, one can see that the 12-month mean return is highest in the case of HDFC bank (91.7%) while it is the lowest for Coal India (-4.97%). Interestingly, for 48 out of 50 stocks, the 12-month forward returns have been positive whenever one has bought with the monthly RSI crossing 50.

Moral: If passive investing is the way forward for investors, the above evidence should help spread a lot of cheer.