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“What has happened in the past will happen again. This is because Markets are driven by humans and human nature never changes.”

Now, markets are primarily driven by two emotions — greed and fear.

When the market is greedy, you get an uptrend.

When the market is fearful, you get a downtrend.

And when the market is undecided, you get a consolidation or range markets.

The stock market correlates closely with the growth of the GDP. All the companies in the S&P BSE 500 Index are a good reflection of the economy, even though some large private companies are not in the index. The index is compiled of a diverse mix of industries such as finance, technology, and consumer.

The never-ending fight between market technicians and fundamental analysts has a new player Quantitative analysts or as we refer them as ‘THE QUANTS”.

Each analytical theory has merits and flaws, obscure concepts that lack empirical evidence to prove or disprove the theories, and yet each also has universally accepted principles that have stood the test of time as well as history.

Each type of stock analysis is so utterly unique from the other that it is extremely rare to see any analyst who incorporates all three into their analytics. Yet logic and common sense should dictate that coalescence of all three would substantially improve stock analysis for all Market Participant Groups.

Fundamental, Technical, and Quantitative Analysis are separated by a great divide in use, interpretation, acceptance, and popularity. All three analyses are actively used by different Market Participant Groups yet not one dominates with consistent success over time for all groups.


Technical analysis is a form of market analysis based on historic price patterns. The basic assumption of technical analysis is, that human behaviour does not change over time, and thus similar historic market behaviour will lead to similar future behaviour. Technical analysis is a predictive form of analysis, a technical analyst will try to estimate what the market might most probably do over the next period of time.


Technical analysis is using indicators and patterns. Some of these tools have been around for a couple of hundred years, e.g. candlestick patterns defined in Japan in the 17th century.  Technical analysis also uses highly subjective graphical tools, like trend lines, support&resistance levels, head and shoulder patterns, Fibonacci numbers and more obscure tools like Elliot waves.



When using fundamental analysis to make investing decisions, in most cases you are most likely planning on buying and holding that investment for the long term. Why? Because the underlying pieces of information that are analyzed are factors that indicate longer-term values.

Among the many pieces of information analyzed when using fundamental analysis on a company are:

  • Revenues: How healthy are the current reported revenues for the company as compared to others in that industry? How do their current revenues compare to previously reported revenues? Are they improving and growing?

  • Earnings Per Share (EPS): EPS is the company earnings per share of stock after dividends have been paid. In other words, the net income for the company divided by the total number of outstanding shares of stock equals the company earnings per share.  How does the company EPS compare to its previous historic returns? How does this compare to the industry standard? What does the future look like for their forecasted EPS?

  • Price to Earnings Ratio (P/E ratio): The price to earnings ratio compares the company current stock price to the EPS. If a company stock price is $100, and they have an EPS of $10 per share, then their P/E ratio would be 10 ($100 share price / $10 EPS = 10). This means that investors are willing to pay $10 for every $1 the company earns. How does this compare to their historic returns and the industry standard for the respective company?

  • Profit Margins: A company’s profit margin is the difference between the operating costs of providing their product or service and the price at which they sell that product or service to the public. If you are a grocery store, it may cost you $1 for each gallon of milk you buy, but you sell that gallon of milk for $3 to the public. Your profit margins would then be $2 ($3 sell price – $1 wholesale cost = $2 profit margin). The higher the profit margins of a company, the more likely investors will be attracted to that investment.



Leveraging technology to analyze significant amounts of data, a quantitative or “quant” approach often uses mathematical and statistical modelling to analyze and/or rank various investments. This can be especially useful for smaller teams that do not otherwise possess the necessary resources to analyze an entire peer group of investments. Similarly, a quant approach can make sense if travelling for due diligence purposes is overly challenging. For example, a U.S.-based firm that invests in international/emerging market small-cap stocks may rely on quant analysis in place of meetings with management.

Ranking investments is where a quant approach can shine. Many managers often incorporate factors related to quality (ie. Return on equity (ROE)), momentum (ie. Relative strength) and value (ie. P/E ratio) into their ranking models. A model can easily be customized to weight each factor differently, and results can be monitored daily to reflect changes in the market.


  • Unbiased: Quant tools take human emotion and biases out of the equation.

  • Efficient: Once a quant system is built, it can be an extremely effective tool for analyzing vast amounts of investment opportunities in any geography. Can also be updated daily with new data.

  • Useful for screening: Effective at narrowing-down large investable universes into shorter lists to then be analyzed in more of a fundamental fashion.


  • Incorrect data can produce misleading results. This is often referred to as “garbage in, garbage out.” Increases emphasis on high-quality data.

  • Unable to measure sometimes-obvious yet critical qualitative aspects like company culture, morale, leadership quality or changes in the regulatory or competitive landscape.


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The rules are:

  • Buy on break of previous day high/low and first 5 min candle high/low break on a closing basis.

  • define VPL/VPH by instructing the algo as last 4 day's H/L. This is yielding some good result

  • trailed the stop loss to 0.33% only after receiving 1:1 RISK REWARD RATIO

  • All trades were exited on EOD.


For the most part, money is actively managed. While index funds and their similar exchange-traded funds (ETFs) cousins are rapidly growing, investors still seek active management in the hopes of getting an edge on the market returns, called seeking risk-adjusted excess returns, leading to the selection of investment discipline. An increasing number of portfolio managers have now realized that fundamental analysis alone often does not make the best investment approach and have therefore begun to utilize technical, behavioural, and quant analyses as well. Proper use of fundamental techniques is required for selecting investments that are designed to generate risk-adjusted excess returns.

Fusion analysis (not to be confused with other uses of the word “fusion” that permeate the world today in areas such as making lipstick, cars, and cuisines). The Fusion blending is both exciting and challenging, as it covers uncharted territory Some investors then claim, “We tried fundamentals and we tried technicals and putting them together, they don’t work. We’ll just stick with fundamentals.” When the fundamental news is bad, the technicals may be very good. Investors therefore, need to know how to blend these analyses, and for this reason, I use quant. Think of it this way: If you have a button and fabric, they will not magically be joined together. You’ll need the thread to sew the button to the fabric. Consider that thread the quant portion of the Fusion process.

When some investors say they find it hard to justify using technicals with fundamentals, one can only be amused. Some fundamental strategies already incorporate technicals, behavioural, and quant through the back door. For example, a value low P/E strategy already has quant criteria. The low P/E could be low because investors are already cautious of the fundamental outlook and their pessimism means they will not bid up the price. And high P/E could be the opposite, as great expectations and bullishness mean that they may be willing to bid up the prices beyond the true fundamental requirements.


The company is a diversified conglomerate with a lot of uncorrelated businesses under its umbrella. In such a case each business has its own operating structure and a set of competitors. The largest revenue contributing businesses are Petroleum, Refining, Petrochemicals and Retail. The company has 1.24+ Mbpd (Million Barrel per day) of crude processing capacity 1400+ petroleum outlets. The Jamnagar refinery is the largest in the world and has a complexity Index of 21.1 which is the best in the industry. In the petrochemicals business, it has 38 Million Metric Tonne capacity which is the highest in India.

Reliance is also the largest integrated polyester producer in the world. In the retail business, the company has expanded rapidly across 6700+ cities and towns in India and operates 11,000+ stores, which again is one of the largest retail chains in India. The company is also a market leader in digital services through its Jio Platforms.

The revenue has shown a CAGR growth of 27.5% over the last 4 years. The capital expenditure has increased which also indicates an aggressive expansion in the near future. The working capital is negative due to the nature of refining business but is expected to improve as the company expands further into digital and retail

The stock is currently trading very near to its 52-weeks high but the valuations are now based on future growth especially through the Jio platforms. This, however, is only market expectations. Digital business has historically remained very unpredictable and is dependent on the fickle customer base. Therefore there might be additional risk associated with the Jio Platforms which the market may consider once the Covid-19 situation clears.


Technically, the stock has recovered beautifully from the corona induced sell-off lows. It moved in a channel and followed the fib levels beautifully.

So with the rising volumes and a PE multiple of less than 20 during the sell-off was a perfect techno funda setup to buy this gem.

Now we discuss some Quantitative Strategies to trade reliance in the last six months.

There are two indicators on the charts namely donchian channel and WILLIAMS R%.

Now what we program the algo to do is


This algo works beautifully and can make us a decent profit on every move up and down in the stock with a great probability.

So is there any use anywhere for such a form of analysis? Of course, in the investing world, nothing is cut and dried, and this article makes that patently obvious. Backtesting helps, numbers are critical, but ultimately fusion analysis relies on market experience, the integration of disparate fields of study, and the touch of an artist. Even though the apt description might not be there for such an analysis, but this article must have dictated some direction towards this analysis.

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