Monday, October 19, 2020

How Volatile has the Stock Market been?

 

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After recovering from the March 2020 lows, the major indices (Dow, Nasdaq, and S&P) have been on a tear, reclaiming the earlier highs. 

On its way to retesting the old highs, the market did dip several times, offering better buying opportunities, especially in late May and mid-September. For example, after reaching 27,000 in late May, Dow quickly fell back to 25,000 and provided a similar opportunity again in late September.

Though the growth has not been a perfectly linear, the investors nonetheless fared very well who stayed on or bought the dips.


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The High-to-Low ratio is one of the quickest ways to understand market volatility. Obviously, the bigger the spread, the higher the volatility. In a stable market, this ratio will be range-bound between 101 and 103. When it spikes above 105, the market enters a phase of turbulence.

The above graph confirms that the market experienced a very high level of volatility in late May and early June; for example, from a low of 102.74 on 5/18, it dramatically climbed to 109.98 on 6/8, steadily retracing back to 103.03 on 7/56. 

Many quantitative funds and traders take advantage of this volatility via liquid derivatives like options on Indices, VIX, etc.  

Stay safe!

-Sid Som
homequant@gmail.com

Saturday, October 10, 2020

How to Create a Statistically Significant Fund of Funds from Balanced Mutual Funds

 

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1. Screening Funds: It's important to select funds with very similar attributes, which, in turn, will enhance the collinearity of the portfolio. In selecting the above funds, the following set of criteria has been used: NAV > $7B; Morningstar Rating = 4 to 5; Track > 10 years; Yield = Positive; YTD Return > 8%.


2. Balanced Funds: Balanced Mutual Funds are inherently diversified (40-60% in stable/dividend stocks, 30-40% in fixed incomes, and balance in Cash, Precious metals, and other debt instruments). Since these funds are self-hedged by design, meaning stocks hedged by bonds, etc., no additional hedge component is needed.


3. Fund of Funds: Creating a statistically significant Fund of Funds from a group of Balanced Mutual Funds requires that they are drawn from a highly correlated group, as shown in the correlation matrix above. Thus, while reducing the number of funds, the "least" collinearity must be adhered to. For instance, since Dodge and Cox show lower collinearity than its peers, it must be removed first from this line-up.


4. Risk Mitigation: A Fund of Funds is more prudent from the investment point of view. It helps reduce the general risk embedded in a single balanced fund (risk scenarios: merger, change of ownership, departure of a veteran portfolio manager, etc.). 


Therefore, instead of investing $100K in one balanced fund, it's better to spread the sum over a group of highly correlated balanced funds (again, the highly correlated funds tend to project very similar attributes).


Disclaimer - The author does not advocate any of the funds listed here; instead, this is promoted as alternative research in creating a statistical fund of funds. Consult your Registered Rep, RIA, or Financial Planner for an appropriate asset allocation model and the suitability of mutual funds and other instruments.  


-Sid Som
homequant@gmail.com

Monday, October 5, 2020

A Diversified REIT ETF may Proxy Physical Real Estates in an Asset Allocation Model

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The Correlation Matrix (top graphic) shows the correlation between the S&P 500 and five publicly traded Real Estate Investment Trust (REIT) ETFs. While MORT is a mortgage REIT, the other four are diversified equity (Real Estate) REITs. 


The Correlation Matrix shows almost negligible correlations between the S&P 500 and the REITs. This lack of correlation entices investors to own REITs as a separate asset class in their asset allocation model, proxying a portfolio of diversified real estates (residential, commercial, and industrial) without physically owning and managing them. 


To maintain the tax advantage status, REITs have to pay out at least 90% of their income as a dividend. Since REITs are designed to yield higher dividends, they tend to complement the fixed income (asset) class in the asset allocation model.


Correlation coefficients ranging between + 0.10 and -0.10 are considered uncorrelated. VNQ is the only one that falls outside of that range, showing a slightly negative correlation. Save MORT, the other four equity REITs are moving in lockstep, considering their top holdings (accounting for at least 35% of the portfolio) are virtually alike (e.g., American Tower, Simon Property, Crown Castle, Prologis, Public Storage, Avalon Bay, Equinix, Equity Residential, Digital Realty, etc.).


Though Mortgage REITs tend to generate much higher yields than their equity (real estate) counterparts, they are inherently more volatile as they are more prone to interest rate fluctuations. MORT currently has a yield of 7.77% compared to 3% to 4% for the equity ones.

   

The weekly graph (bottom graphic) is more telling. While the S&P 500 moved from 2,400 to 2,800 (between 8/1/17 and 7/31/18), both REITs (IYR and VNQ) remained range-bound between $74 and $82. As a result, the diversified equity REITs have low beta (usually between 0.5 and 0.7). 


Again, a diversified equity REIT ETF could be an excellent way to own this asset class (a wide variety of real estates) without physically owning and managing them.


Disclaimer - The author is not advocating any of the ETFs/indices listed here. Consult your Registered Rep, RIA, or Financial Planner for an appropriate asset allocation model and the suitability of stocks and other holdings for your portfolio.


- Sid Som
homequant@gmail.com

Monday, September 28, 2020

Write Covered Calls to Create Cash-flows during Market Corrections

 Pros often use advanced options as one of their market strategies to manage portfolios. While professional options strategies require advanced knowledge of quantitative sciences, simple options hardly require any such experience. Buying some calls to take advantage of the rising markets or buying some puts to hedge downturns is relatively straightforward.

More importantly, the practice of writing covered calls, meaning selling calls against existing positions, to create cash-flows when the market gets overbought or is ready for an imminent correction is considered an excellent market strategy even for the individual investors in stocks, bonds, commodities, foreign exchanges, and real estate. Writing covered calls is even allowed in IRA accounts, considering the safety of it.


Buying vs. Selling Calls


While options-approved individual and professional investors often buy calls to take advantage of the rising markets, buying calls carries an inherent risk if the market suddenly turns negative or moves sideways, thus making those calls worthless or at least significantly eroding their time value. Of course, if the market behaves as expected, those calls gain in value. Therefore, buying calls is a speculative strategy, if not a total gamble. 


On the other hand, writing covered calls could be a very sound investment strategy to hedge market downturns or overbought conditions. For example, if you bought 1,000 X stocks at $30 (cost basis) at the bottom of the last correction and the same stock is now trading at $45, you may consider writing up to 10 covered calls (each option covers 100 shares) to create some temporary cash-flows, without having to liquidate the position. 


Of course, the mere fact that your stock has made a decent run-up should not force you to sell some calls. Make sure your research shows that the market is ready to correct or is way overbought, or at least, your stock is way ahead of the market and shows clear signs of an overbought condition. One such movement could be the breach of a statistically significant trend-line, e.g., the 200-day moving average. In such a changed market situation, writing some covered calls is an excellent way to create meaningful cash-flows.


Ideally, calls should be written against 50% of the covered positions, positioning the rest to ride out the market or take advantage of the further upside potential in the market just if your research turns out somewhat ill-timed. Of course, any such options strategy must always be reached in consultation with a registered investment professional to minimize speculation.


Again, while I am opposed to buying options – calls or puts – I am always in favor of writing limited calls as long as the market conditions, as mentioned earlier, are met and proper professional help is part and parcel of the decision-making process.


In the money vs. At the money vs. Out of the money


Options have two value attributes – intrinsic value and time value. Options contracts expiring shortly, say in six weeks, will have lesser time value than those expiring in six months. Therefore, while buying options, it is always advisable to buy with adequate time, preferably six to nine months remaining on the contract.


Likewise, while selling options, immediate contract months are preferred as market conditions are more predictable. Therefore, if your research shows the market could decline or remain range-bound and choppy in the next three months, consider writing your covered calls keeping the option’s expiration in mind. Of course, the equally important question you would face is: Should you write those calls in the money, at the money, or out of the money? 


If the stock was trading at $45, the $45 strike price would be at the money, $40 would be in the money, and $50 would be out of the money. In other words, in the money options have higher intrinsic value than their counterparts. 


Again, research shows a particular stock has recently made a significant move –- well ahead of the competition with the possibility to retrace more than the overall market and the competition -- writing the covered calls in the money is worthwhile, factoring in the potentially more significant pull-back. On the other hand, if the expected pull-back is in line with the market and the competition, writing at the money or out of the money covered calls will make more economic sense.


Either way, as market trends lower, dragging down the time value, one can always cover (buy back) the position at a fraction of the original selling price, repeating the process at the top of the next bull-run. Conversely, if research proves wrong and the market continues to trend up after the writing of the covered calls, the other unencumbered 50% position will participate in the market.


Always consult a licensed investment advisor before engaging in any options activity as it involves significant risks.


- Sid Som MBA, MIM

homequant@gmail.com


Link to the Book

Monday, April 13, 2020

Understanding the On-going Market Volatility



As discussed in prior posts, there are different ways to study the market volatility. 

The two quickest way to eyeball volatility during very volatile periods: 

1. Develop Scatter Plot of Daily Closing Prices (top graph) -- Due to the Coronavirus outbreak in the US, the Dow Jones Industrial Average (DJIA) daily closing prices fell from 27,091 on 3/4 to 18,592 on 3/23 -- a historic 31% collapse in a mere 14 days. In fact, the intra-day high on 3/4 was 27,102 while the intra-day low on 3/23 was 18,214. 

Then, the index turned around and rose back to 24,009 on 4/9 -- a stunning 28% recovery (from the close on 3/23) in the next 14 days.

Since the first half was significantly more volatile, the Coefficient of Variation (COV) jumped to 13, compared to the second half when the COV fell to 6.   

2. Compute Intra-day High Price to Low Price Ratios (bottom graph) -- The intra-day high to low price ratio gives a pretty good understanding of the volatility during a certain period. Based  on this method, the volatility peaked on 3/13 (108%) and troughed on 4/9 (102%). 

The polynomial trendline is simply ignoring some of the abrupt spikes, retuning a much smoother surface.

Considering that the time series is quite short here, a priori smoothing is unreasonable; otherwise a 2-to-3 day moving average is generally applied to the raw data to smooth out the outliers before a meaningful trendline is derived.

-Sid Som
homequant@gmail.com

Also Read:
Understanding the Market Volatility ... 12/2/2019 thru 3/2/2020

Thursday, March 12, 2020

Understanding the Market Volatility ... 12/2/2019 thru 3/2/2020

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Paula, a Research Analyst with a Master's in Public Health, is interviewing for a Senior Health Care Analyst position. Here is the simulation of the first interview, leading to the final interview.

Interviewer: Paula, since this is a general interview to narrow our choices down to the final ten, it is designed to test candidate's knowledge of the basis data analysis and modeling, rather than the health care data universe per se.

Paula: Sounds very reasonable.   

Question # 1
Interviewer: Lately, the stock market has been going through some serious turbulence so we decided to use the current market data as the basis for this general interview. Does the High/Low Ratio ("Hi/Low") proxy the VIX in this example?

Paula: Yes, it does. A high correlation coefficient of 0.88 confirms that they have been more or less moving in tandem. For example, when the Hi/Low jumped from 101.79% to 115.08%, the VIX also jumped from 17.08 to 40.11. They have a high positive correlation, meaning they move in the same direction.

Question # 2
Interviewer: So, are these two volatility metrics -- Hi/Low ratio and VIX -- interchangeable? If so, is there any need for the Hi/Low ratio? 


Paula: The two metrics are not inter-changeable. The Hi/Low ratio is a descriptive metric that helps analyze the past activity but does not project anything about the future sentiments of the market, whereas the VIX is computed in a more forward-looking manner to project out the short-term future sentiments of the market so they, in a way, complement each other.

Question # 3
Interviewer: In this example, 10 out of the 14 weeks, VIX remained within a tight range of 12.10 to 15.47. How come the average is 18.04?

Paula: Average is heavily influenced by the outliers. The two outlier data points of 40.11 and 41.94 are weighing in, pulling the average up. If you had used the median, it would be around 14, not 18.

Interviewer: Let me quickly check what the median would be. Yes, it's 13.85. Great mental math!

Question # 4
Interviewer: Using your logic of median, if we re-compute all components, what changes would we expect to see?

Paula: The impact of the two lower outlier data points of High, Low and Close would be minimized, thus pushing their median values up. On the contrary, the impact of the two unusually high outlier data points of Volume and Hi/Low would be significantly lessened, thus pushing their median values down.

Question # 5
Interviewer: Is there any other market component that demonstrates a similar relationship with the VIX?

Paula: Yes, the Volume component. In fact, VIX and Volume show even a higher correlation of 0.90. Case in point: When the Volume spiked from 1.096B to 3.019B, VIX jumped from 17.08 to 40.11, proving how they move almost in lockstep.

Question # 6
Interviewer: In terms of Volume, does anything else stand out?

Paula: Yes, the two traditionally-low Volume weeks of 12/23 and 12/30. If you compare the Volume of 12/23 with that of 2/24, you see a huge change -- in fact, a factor of 4.5. Of course, it's an aberration, not a norm.

Question # 7
Interviewer: Why did it happen?

Paula: It's strictly news-driven. The news pertaining to the outbreak of Coronavirus has been making the financial markets around the world very nervous. The uncertainty surrounding this outbreak has a prolonged impact. The financial community needs to have more clarity about this breakout before a real sense of calm returns to the market.    

Question # 8
Interviewer: You seem to think that the many unanswered questions about this outbreak are impacting the market. Please name one such unanswered question that is plaguing the healthcare industry. 

Paula: We do not know who will pay for the tests and possible hospitalizations for the millions that are uninsured. Even the millions that are insured with high deductibles are very nervous. For instance, my mom is self-employed so she pays for her own insurance, but to keep the premium manageable, she opted for a plan with a high deductible which is making her very nervous now.

Question # 9
Interviewer: Why do you think the Low and the Closing prices ("Close") have near-perfect positive correlation?

Paula: When the market has been trending down, Low and Close go more or less hand in hand. The flip-side is equally true -- simple collinearity!

Interviewer: Congrats, Paula! You have moved on to the final round. Any questions?

Paula: Thank you very much. If I get this job, do I get to report to you directly? Actually, I would love to be on your team.

Interviewer: I would love to have you on my team, too!

- Sid Som, MBA, MIM
sidsom1@gmail.com




Friday, February 7, 2020

Did Russell 2000 Outperform S&P 500 in 2019?

        Intended for New Graduates

(Click on the image to enlarge)


Emily, a new graduate with co-concentrations (Econ & Finance), is interviewing for Equity Analyst position. 

Question # 1
Interviewer: Explain to us the basic difference between these two indices. 

Emily: While the S&P 500 index measures the performance of 500 large-cap stocks, the Russell 2000 index measures the performance of 2000 small-cap stocks. S&P 500 is the most widely followed stock market index.

Question # 2
Interviewer: Is there a market definition of large-cap stock? Also, can you name a few large caps?

Emily: Typically, a large-cap company has a market value of at least $10 Billion. Microsoft, Apple, Amazon, Google and Facebook are examples of large-caps. 

Question # 3
Interviewer: Can S&P 500 include one such large-cap stock that is listed on Nikkei only?

Emily: No. S&P 500 comprises large-cap stocks that are listed on US Exchanges.     

Question # 4
Interviewer: The data table shows S&P 500 has higher volatility than Russell's. What "quick" metric did we use to arrive at these volatility figures? And why?

Emily: I believe the quick metric you used is the Coefficient of Variation (commonly known by its short form COV). COV is the ratio of standard deviation to mean. Since you are making inter-index comparisons, you used the "normalized" metric. 

Question # 5
Interviewer: By glossing over these two graphs, do you notice any similarity?

Emily: Yes, between August and December, they both produced linear growth. Spectacular growth, indeed!

Question # 6
Interviewer: Any striking dissimilarity, per se?

Emily: Yes, the correction in August was way more pronounced for Russell than that of S&P's. 

Question # 7
Interviewer: By looking at the data table, can you tell us how S&P outperformed Russell in terms of overall growth?

Emily: Because S&P produced 8% growth between January and August, whereas Russell remained on a slippery slope, failing to hang on to its gains. 

Question # 8
Interviewer: To take advantage of these indices, what investment vehicles would you recommend to our clients?

Emily: Index Funds, Index ETFs, S&P Futures and Options, etc.

Question # 9
Interviewer: Of these two indices, which one would you recommend to our conservative clients? Or, would you recommend both?

Emily: Russell 2000 would not be appropriate for them.

Good Luck!

-Sid Som, MBA, MIM
President, Homequant
homequant@gmail.com

                     Link to the Book

How Volatile has the Stock Market been?

  (Click on the image to enlarge) After recovering from the March 2020 lows, the major indices (Dow, Nasdaq, and S&P) have been on a tea...