We often refer to volatility as risk! yes it is a barometer of Financial Risk indeed.
Before I start writing this blog in detail, let me ask myself few basic research questions as shown in the order given below:
- But is there a difference between Good and Bad Volatility?
- Why should we distinguish between Good and Bad Volatility?
- Are all Volatility term structures having the same consequences?
- Can one form of volatility bring profits and the other do the opposite for investors?
- Are all types of volatility observable?
- Has investor risk appetite got to do something with this differentiation between good and bad volatility?
- How can we separately quantify Good and Bad Volatility adjusted return performances ?
lets bring forward a simple description of Volatility in this Blog! that would make our life much easier.
what is this stuff?
Well its the standard deviation in vanilla arithmetic terms. I don’t wanna introduce more esoteric and exotic explanations beyond this term! If your level is higher, you are advised to read some other scholarly journal articles or Carol Alexander’s Book on this subject.
I believe this is not the right place for you 😉
Anyways….so back to blogging blah blah!..
So Volatility is basically a measure of dispersion around a mean value as observed in contextual and conceptual settings of a probabilistic distribution (As we are discussing Volatility from a primarily Market Risk Perspective, this probabilistic distribution is most likely to be that of Normal and / or Log-normal returns).
Having said that we must ALSO FIRMLY avoid this misconception about Volatility Analyses that it is always a Market Risk Phenomenon which analyzes the value movements of Financial Asset Prices, Indices, Rates and Returns, Etc.
No that’s just another major fallacy of assumption !
Credit Risk Factors and Models are as much sensitive to changes in volatility as any other types of risk attribution factors that interface the universe of Financial Risk (Those who have calculated Portfolio Credit VaR Measurements, know what I am saying ..over here). Hope I have made the basic distinction Market and Non- Market led Volatility and ostensibly its versions stand out well and truly distinguished from one another !!!
So once we have a measure of volatility, we may develop a measure of risk tolerance level and also a way of quantifying the investor’s risk appetite!
- If the investor is “risk averse” , than he or she should have very little to no appetite for volatility itself. For e.g. stocks with Beta value < 1.00 and much lower are selected.
- If the Investor is “risk taker /lover”, than he or she should prefer higher levels of excess volatility and so on.For e.g. stocks with Beta value > 1.00 and beyond are selected.
- If the investor is “risk neutral”, than he or she should have a very balanced appetite for volatility.For e.g. stocks with Beta value =1.00 are selected.
It goes without saying that the golden rule in Financial Economics tells us that higher risk should always be accompanied by higher level of return (loss). So for a risk manager the positive side of return is slightly an unobservable factor; hence I (for biased reasons may be) analyze volatility only in terms of loss!
To me a higher risk transaction has the probability of incurring a higher loss and vice-versa.
So here we get a difference in perceptions towards volatility! Hence its not just a choice between Profit and Loss Outcomes and Statistical Distributions. Its also a very perceptible argument that we are highlighting in this blog.
Volatility to you may be good and for me it may turn out to be bad ! depends on which side of the market and profession you are! So we can now comfortably say that Fund managers may like that little bit of excess volatility or even more in some cases and Risk Managers often dislike Volatility because they dislike Financial Losses! Got my point.
I hope we are on the same page ……Gosh this is getting longer ….
So back to Volatility and whats the difference between Good Vol and Bad Vol in Price Risk Terms Only!!
- Good Volatility instigates profits and is generally a movement of the asset prices on the upside.
- Bad Volatility instigates Losses and is generally a movement of the asset prices on the downside.
Got that ! Have a cig and come back… take a break 😉
So now going by the above definitions, we can easily bifurcate volatility and get a better grip over this discussion. Right??
Now we understand that Volatility doesn’t always affect the investor outcomes and perceptions in the same way. A trading asset class that appreciates in terms of price value witnesses a Good Volatility Phenomenon, if profits are made from such a market upturn.
Hence Fund Mangers are always waiting for such a ” magical momentum effect” to take place during trading hours. They get paid for striking when the “Iron is Hot”.
So it all depends on which side of the market you are. Well…if you make money you would call the momentum “Good Volatility” and if you lose you will have the opposite definition and explanation of events.
But that may confuse the reader? So………………………..
I would again for the last time in this blog always categorize VOLATILITY as :
- Good Volatility -> an opportunity and/or positive market event (when prices are rising) in which money can be made through an exit strategy or by holding onto their existing trading position!!
- Bad Volatility -> is a threat and /or a negative market event (when prices are falling) because of which Investors lose money as they try to exit or when they try to hold onto their existing trading position !!
Done! that hopefully ends the conceptual problem 😉 .
Now how a risk averse/taker and /or neutral investor may accept or reject these forms of Good and Bad Volatility may open up new debates in altogether with respect to Indifference Curve Analyses, Rational Investor Preferences and Mean- Variance Optimization Models.
Not the topics we need to touch over here.
Sorry this is a blog writing exercise and not a journal article in the making . But you can go on with the research if you may like to do so at your expense.
So how do we measure this difference between Good and Bad VOLATILITY?
Is it quantifiable or just blah blah..another drop in the Econ 1o1 literature for endless student- teacher confabulation ?
It is believe you me very much quantifiable, if you are accepting standard deviation metric as the sole representative of volatility as expressed purely in “statistical terms”.
Lets start -off by analyzing the time-tested and beloved original version of the Sharpe Ratio (that is a risk to reward measure that analyzes the outcome of a portfolio of securities / investments in Market Risk Adjusted Performance Terms).
- SR = Actual measured return of the asset class – risk free rate / standard deviation of asset class returns
- But the standard deviation being a measure of overall volatility does not distinguish between Good and Bad Volatility Factors by itself. Its a blind metric!!
- see the problem now……we cannot differentiate between positive and negative price trends using cumulative standard deviation of a sample or population alone.
- So what to do ? give up ?? No way!
- Break the Standard Deviation into two ? may be !
- How..read Below !
The Sortino Ratio is an answer to the Sharpe Ratio.
It uses a revised Volatility Metric such as the downside deviation and / or standard deviation of all the negative returns or lets say returns that fall below a (MAR) minimum acceptable return level . For e.g. a return below the 3 month T- Bill Rate or any other benchmark rate.
Hence Sortino answered the question in mathematical terms and provided an easier route to understanding the definitions and outcomes of both Good and Bad Volatility.
Obviously in both Sharpe and Sortino Ratios, any value greater than 1.00 is deemed to be “Good” as an outcome and a feasible investment decision which should be accepted in risk adjusted terms (provided all other things are kept constant) .
If your SORTINO’s are negative or below 1.00, that implies you are either taking on too much of bad volatility or the asset you selected is not good enough at beating the downside risk!! Hence your Look Back Period does matter too!
But again its how you and when you calculate the ratio(how much history is added). Also a Post Ante and Ex Ante Analyses of Volatility adjusted returns would have a different decision output and provide distinct interpretation of the two ratios. Again I am not going to touch Model Development and Validation Issues in this round up on Volatility !
So would like to conclude by saying that yes Volatility may be Good OR Bad! Both possibilities exist. its not just a mathematical difference but also a perceptible one!
Make sure you are in the right tail of the market at the right time!!
take care…and do drop your relevant feedback. That shall be much appreciated as always!
thanks for reading this much.