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The VIX Index: step by step

The VIX Index has been introduced by the CBOE in January 1993 and since then it has become the most popular and well known volatility index in the world. The VIX is an index extracted from S&P500 options and its calculation has been changed in September 2003 in order to obtain observations not linked or dependant from any model idiosyncrasy. The present study, inspired by the paper written and compiled by the CBOE, will show how to calculate the VIX Index in a step–by–step fashion. There will be ample explanations about how the index works and we will break down the formula in order to provide a better understanding of the function and weight of every component. Let’s start with the general formula for the VIX Index:

\dpi{120} \bg_white \large \sigma ^2 = \frac{2}{T}\sum_\imath \frac{\Delta K_\imath}{K_\imath ^2} e^ R^T Q (K_\imath )- \frac{1}{T} \left [ \frac{F}{K_0}-1 \right ]^2                                     (1)

Where

\dpi{120} \bg_white \large \sigma = \dpi{120} \bg_white \frac{VIX}{100}\Rightarrow VIX = \sigma x 100

T = Time to expiration

F = Forward Index price (the ATM strike price)

K0=  First strike price below the Forward price F

Ki= Strike of the ith out–of–the–money option. A call option strike will be considered if Ki>K0 while a put option strike will be used if Ki=K0

ΔKi = it is the midpoint between the strike prices. Specifically, the strikes used will be on both the sides of Ki. In other words, ΔK for the lowest strike is just the difference between the lowest strike and the penultimate strike of the option chain while ΔK for the highest strike is equivalent to the difference between the highest strike and the strike immediately below the top one. The formula is the following \dpi{120} \bg_white \Delta K_\imath = \frac{K_\imath_+_1 - K_\imath_-_1}{2}

R = Risk free interest rate (the interest rate used is usually the Treasury Bond yield that more closely matches the option expiration date)

Q (Ki) = The midpoint of the spread between bid price and ask price for each option with a strike Ki

This is the formula that it is currently employed to calculate the most famous risk management index in the world. Before we provide any real example it is necessary to clarify some points. First of all, the VIX index is calculated using 2 expirations: the front month and the second front month contracts. In our study we will be using S&P500 option prices recorded on the 10th of October 2013 and therefore the front month options will be those expiring on the 18th of October 2013 (which will provide us with information about the volatility in the near term) while the second front month options will expire on the 15th of November 2013 and they will provide us with information about the volatility in the medium term. It is important to point out that near term options must have at least 7 days to expiration and when this criteria is no longer met the model automatically rolls to the next available contract. Let’s give an example, our front month options expire on the 18th of October while the medium term options will expire on the 15th of November, hence, on Friday the 12th the VIX will mechanically roll. At this point, the front month options used will be the ones expiring on the 15th of November while the second front month options employed in the calculation will become those expiring in December. This measure has to be adopted in order to avoid mispricing issues that commonly happen when options are about to expire. Another important detail to mention is that T (time to expiration) is calculated in minutes using calendar days, consequently, the time to expiration will be given by

\dpi{120} \bg_white T = \frac {M_c_u_r_r_e_n_t_ \hspace {1 mm}_d_a_y + M _s_e_t_t_l_e_m_e_n_t \hspace {1 mm}_d_a_y + M_o_t_h_e_r \hspace {1 mm}_d_a_y_s }{Minutes\hspace {1 mm}in \hspace {1 mm}a\hspace {1 mm} year}                                  (2)

M current day= minutes remaining until midnight of the same day

M settlement day= minutes remaining from midnight until 08:30 am on SPX settlement day

M other days= total minutes in the days between current day and settlement day

If we assume that the data have been recorded exactly at 08:30 am on the 10th of October and that options will expire at 08:30 am of the 18th of October:

\dpi{120} \bg_white T_1 =\frac {930+510+1,920}{525,600} = 0.0246575

\dpi{120} \bg_white T_2 =\frac {930+510+3,540}{525,600} = 0.1013699

Needless to say that T1 and T2 refer to near term and medium term options respectively. The yield for 1 month Treasury Bills as of the 9th of October 2013 was 0.27% and therefore, given that our October options expire in 9 days while the November options will expire in 37 days, we will use this figure for both near and medium terms.

We now need to determine the F price of the index and in order to do so we take the strike price at which puts and calls have the smallest difference in absolute terms. The below reported table displays call and put prices with their absolute differential:

 S&P500 options

The red back–grounded figures are the strike prices at which calls and puts have the lowest difference, however, the two expiration dates have 2 different strike prices: ATM for October options is at 1,650 while ATM for November options is 1,655. In order to simplify calculations, and given the fact that the difference is extremely small, we will take 1,650 as F price because it is the front month contract. We can calculate F using the following formula:

\dpi{120} \bg_white F = Strike \hspace {1 mm}Price + e^R^T x ( Call \hspace {1 mm}Price - Put \hspace {1 mm} Price)                                 (3)

Obviously, there will be two forward index values, F1 and F2 , the first for near term and the second one for medium term options respectively:

\dpi{120} \bg_white F_1: 1,650+ e^(^0^.^0^0^2^7 \hspace {1mm}^x \hspace {1mm}^0^.^0^2^4^6^5^7^5^)x (23.75 - 22.7) = 1,651.05

\dpi{120} \bg_white F_2: 1,650+ e^(^0^.^0^0^2^7 \hspace {1mm}^x \hspace {1mm}^0^.^1^0^1^3^6^9^9^)x (39.75 - 37.3) = 1,652.45

Now we have both  F1 and F2 , so we can identify K0 which is the strike price immediately below the forward prices. In our case, the closest strike right below F1 and F2 is 1,650. Consequentially, K0,1= 1,650 and K0,2 = 1,650.

The next step is to select all put options whose strike is lower than K0 and all call options whose strike is higher than K0. The selection excludes every option with a bid equal to 0 and it terminates when there are 2 consecutive strike prices that equal zero:

s&p500 options

The above reported table explains very well what stated before. In the month of October the lowest puts are at 790 and 795 but the two red back–grounded options cannot be accepted in our calculation because there are two consecutive 0 in their bid prices and therefore they are our stopping point. In other words, no option with a lower than 800 strike price will be considered into the calculation of the VIX. The same principle applies to calls and in fact 2,095 and 2,100 are the highest call option strike prices that will be considered. The same procedure will be applied to November options. It is important to point out that the option chains will rarely have the same amount of strikes available because according to volatility fluctuations the number of strikes that will be priced by market makers will vary. It goes without saying that high volatility explosions will obligate market makers to price even Far–Away–From–The–Money options on both sides because the demand for these instruments will rise. Consequentially, the number of strikes that will be used for the purpose of calculating the VIX will vary according to volatility fluctuations and swings in S&P500 futures. The following table lists the options that will be used for calculating the volatility index:

ATM options

The ATM strike is highlighted in blue. The put options in the near term contract that will be used start from strike 800 until strike 1,645 while the call options range from strike 1,655 until strike 2,100. The medium term strikes, instead, goes from 985 until 1,645 for put options and from strike 1,655 until strike 2,100 for calls. We now calculate the specific weight that every single strike will have in the calculation by using the following formula and we will take the 800 put as an example:

\dpi{120} \bg_white \frac{\Delta K_8_0_0 \hspace {1 mm}Put} {K^2_8_0_0 \hspace {1 mm}Put} e ^R^T^1 Q(800 Put)                        (4)

Please bear in mind that Q is the midpoint between bid and ask while ΔK is the difference between the last option’s strike and the closest next strike, hence, in our case ΔK is (805 – 800) = 5. Let’s proceed with the calculation:

\dpi{120} \bg_white \frac{5}{(800)^2}\hspace {2 mm}2.71828 ^(^0^.^0^0^2^7 \hspace {1 mm}^x \hspace {1 mm} ^0^.^0^2^4^6^5^7^5^) (0.05)= 0.000000390651

The next table summarizes the contribution of each option strike to the overall computation of the VIX Index:

Option Strike contribution

Now, the weights need to be added up and multiplied by 2/T1 for the near term and by 2/T2for the medium term and by performing this calculation we would have 0.074319519775 for the near term and 0.041553088 for the medium term.

The equation (1) that we presented at the beginning of this study is almost completed, in fact, the final part is the only one yet to be estimated. Let’s proceed:

\dpi{120} \bg_white \frac{1}{T_1} \left [ \frac{F_1}{K_0}-1 \right ]^2 = \frac {1}{0.0246575} \left [\frac {1,651.05}{1,650}-1 \right ]^2 = 0.000016423

\dpi{120} \bg_white \frac{1}{T_2} \left [ \frac{F_2}{K_0}-1 \right ]^2 = \frac {1}{0.1013699} \left [\frac {1,652.45}{1,650}-1 \right ]^2 = 0.000021750

We can now complete the calculation by subtracting the two members of equation (1):

Near Term σ21 : 0.074319519775 – 0.000016423 = 0.074303096

Medium Term σ22 : 0.041553088 – 0.000021750 = 0.041531338

The final VIX computation is given by the following formula:

\dpi{120} \bg_white VIX = 100 \hspace {1 mm} x \hspace {1 mm}\sqrt\left \left \{ T_1 \sigma_1^2 \left [ \frac{N_T_2-N_3_0}{N_T_2 - N_T_1}\right] - T_2\sigma _2^2 \left [ \frac{N_3_0 - N_T_1}{N_T_2 - N_T_1} \right ]\right \} x \frac {N_3_6_5}{N_3_0}

The second term of the equation is nothing but the computation of the square root of the 30 day average of σ21 and σ22which are subsequently multiplied by the first term 100.  The weights of σ21 and σ22 are less than 1 or almost equal to 1 when the near term options have less 30 days and the medium term options have more than 30 days to expiration. However, it is worth noting that when the VIX rolls both near and medium term options have more than 30 days to expiration. Let’s now conclude the VIX estimation:

NT1= minutes left before the settlement of near – term options

NT2= minutes left before the settlement of medium – term options

N30= number of minutes in 30 days

N365=  number of minutes in a year composed by 365 days

If we plug in the numbers we have the following outcome:

\dpi{120} \bg_white \sqrt\left \{ 0.0246575 \hspace {1 mm}x \hspace {1 mm}0.074303096 \hspace {1 mm} x \left [ \frac{53,280 - 43,200}{53,280 - 12,960}\right] + 0.1013699 \hspace {1 mm} x \hspace {1 mm} 0.041531338 \hspace {1 mm}x \hspace {1 mm}\left [ \frac{43,200 - 12,960}{53,280 - 12,960} \right ]\right \} \hspace {1 mm} x \hspace {1 mm} \frac {525,600}{43,200}

This leads to the very last step: VIX = 100 x 0.209736087 = 20.9%

Now, the number we came out with is fairly accurate but it is limited to the moment in which the option prices have been “frozen”. Consequentially, the aforementioned procedure and calculation, in order to be precise, has to be automated and repeated every instant because any changes in option premiums will inevitable affect the final assessment of the VIX.

The HyperVolatility Forecast Service enables you to receive statistical analysis and projections for 3 asset classes of your choice on a weekly basis. Every member can select up to 3 markets from the following list: E-Mini S&P500 futures, WTI Crude Oil futures, Euro futures, VIX Index, Gold futures, DAX futures, Treasury Bond futures, German Bund futures, Japanese Yen futures and FTSE/MIB futures.

Send us an email at info@hypervolatility.com with the list of the 3 asset classes you would like to receive the projections for and we will guarantee you a 14 day trial.

Equity Volatility Indices: VIX, VXN, VXD, RVX

The present research will go through the most popular equity volatility indices proposed by the CBOE. The aim of the research is to identify how they fluctuate and to quantify the magnitude of their movements. The actual study will be followed by a second one entirely focused on commodity volatilities and the examined asset classes will be Gold and WTI Crude Oil (the HyperVolatility Forecast Service provides market projections for the VIX, Gold, WTI crude oil and many other asset classes. Send an email to info@hypervolatility.com and get a free 14 days trial). The great attention towards volatility indices and the remarkable popularity gained by VIX futures are surely undeniable but what is the risk involved in these markets? What is the volatility index that best fits your trading style and portfolio needs? Do you know how the VIX performs compared to other volatility indices? The HyperVolatility team trades and analyzes volatility movements on a daily basis on different asset classes and the present study is a summary of some of our findings. The examined data sample goes from January 2011 until April 2013 and the present research will examine 4 equity volatility indices: the VXN (Nasdaq 100), the VXD (Dow Jones), the RVX (Russell Index) and the VIX (S&P500). The first chart displays the distribution ranking of each index and it is a good approximation of how volatile the aforementioned indices can be:

Volatility Indices - Distribution Ranking

The graph clearly indicates that, on average, almost all indices move within the 18% – 22% interval (the RVX is the only one above this range as its median is 23.43%). The lowest fluctuations, for all indices, are concentrated within the 9% – 12% range (the VXD is the only index showing a figure lower than 10%) while the wildest volatility explosions tend to group around the 45% – 48% area (the RVX again is the only outsider with a 58.84% peak). Statistically speaking, the most important intervals to consider are the 25%, the median and the 75% ones because they represent the most common spectrum of oscillation. Consequently, in case of low volatility most of the indices will tend to move within the 15% – 18% range (the RVX does not go below 20% though) while in high volatility environments equity volatility indices will tend to oscillate between 20% and 24% (the RVX is again the only outsider with 28.1%). The RVX is definitely the index showing the highest figures, which is normal given the fact that it tracks the volatility of less liquid stocks, but is it really the most volatile one? The answer is no because the fact that the RVX has an average value of 23.43% does not mean that it experiences the highest degree of fluctuations; it simply implies that the RVX is constantly higher than the others. In order to clarify this issue it is necessary to quantify the magnitude of the equity volatility indices’ movements. The next chart displays the volatility of the volatility indices. This time, however, the oscillations are expressed in monthly volatility because the CBOE indices are already annualized:

Volatility of Volatility

The chart evidently shows that the most volatile equity index, amongst those proposed by the CBOE since 2011 so far, is the VIX and not the RVX. The second most volatile is the VXD and the least volatile is the RVX. How is this possible? Wasn’t the RVX the index showing the highest values? The explanation is simple. The VIX and VXD indices have a higher variability rate because a fairly good amount of moves tend to be large, fast and powerful. On the other hand, the RVX has a lower variability because it tends to fluctuate more often around its mean value and consequently the dispersion is lower. The next graph, which plots the ranking of the dispersion rate for the volatility of CBOE equity volatility indices, will help to expand more this concept:

Volatility of Volatility - Distribution Ranking

The graph confirms what previously stated: the VIX and the VXD are, on average, the most volatile indices. The 3rd index is the VXN while the RVX is the one that experiences the lowest degree of diffusion. The dispersion of the VIX and VXD is the largest even for small and large moves indicating that these 2 volatility indices move a lot more quickly than the others. Almost all indices do not go over the 30% threshold but when large market moves happen the monthly volatilities reach 50% and in some cases, like the VIX, 60%. To sum up, the VIX and VXD are the most volatile indices while the VXN and RVX ranked 3rd and 4th respectively (it is worth reminding that the sample analyzed goes from January 2011 until April 2013). Financial markets have different risk dimensions and equity volatility indices make no exception. The next table tries to provide empirical evidence to quantify 1 of those dimensions: the intraday risk

Intraday Risk

Before getting started it is important to point out that the numbers reported in the table are volatility points. The intraday risk, on average, is around 1.35% for all equity volatility indices but the RVX reaches 1.5%. On the other hand, the table suggests that very large market moves can push equity volatility indices up or down by 13%, 14% or 15% in one single day.

However, one question, given the above mentioned results, would be particularly appropriate: wasn’t the RVX the least volatile index? If that is true, how come the intraday risk is higher?

The RVX index is more “dangerous” than other volatility indices as far as intraday risk is concerned. Nevertheless, even if the RVX fluctuates more wildly during trading hours its mean reverting pressure is higher in the medium term. In other words, the RVX is fairly volatile on a daily basis but it tends to mean revert towards its mean much more quickly than other indices. Furthermore, violent volatility bursts or aggressive drops tend to counterbalance themselves more effectively and in the medium term they result in a lower dispersion of the RVX with respect to its mean. The aforementioned phenomena explain why the RVX has a higher value in terms of volatility points but it is generally less volatile than the VIX or the VXD.

Conclusions

1) On average all indices tend to oscillate within the 18% – 22% interval

2) In case of low volatility, indices will tend to move within the 15% – 18% range while in high volatility environments the equity volatility indices will likely oscillate between 20% and 24%

3) The RVX is definitely the index showing the highest value in terms of volatility points but it is the less volatile because the mean reverting pressure is higher in the medium term

4) The most volatile equity indices, amongst those proposed by the CBOE, are the VIX and the VXD

5) The dispersion rate for the VIX and VXD indices is the largest even for small and large moves which means that they oscillate more quickly and frequently than others

6) Intraday risk is around 1.35% for all equity volatility indices but the RVX reaches 1.5%

 The HyperVolatility Forecast Service enables you to receive statistical analysis and projections for 3 asset classes of your choice on a weekly basis. Every member can select up to 3 markets from the following list: E-Mini S&P500 futures, WTI Crude Oil futures, Euro futures, VIX Index, Gold futures, DAX futures, Treasury Bond futures, German Bund futures, Japanese Yen futures and FTSE/MIB futures.

Send us an email at info@hypervolatility.com with the list of the 3 asset classes you would like to receive the projections for and we will guarantee you a 14 day trial.

Portfolio Hedging: Risky Assets vs Safe Havens

The credit crunch changed the game and we all know it. Financial markets have been completely reshaped, in fact, the old way to invest is not yielding the results it used to and the composition of market participants have been totally revolutionised (perhaps permanently). The attention towards the management of portfolio risk augmented dramatically soon after the 2008 – 2009 and words like “safe havens” and “risky assets” started to consistently appear on many financial newspapers; but how the “safe havens” relate to “risky assets” nowadays? Which markets can today still be considered to be “safe”? The continuous weekly analysis of inter-market relationships that we perform, here at HyperVolatility, brought us to write this research. Let’s proceed with order.

Risky assets are all those markets that are traded mainly for speculative purposes so in this category we primarily find equity indices (S&P500, DAX, Dow Jones, FTSE100, Nikkei225, etc), stocks (Apple, Microsoft, Amazon, etc), some currencies (essentially Euro vs US Dollar and Yen vs US Dollar) and the most popular commodities such as WTI Crude Oil (this list is far from being exhaustive). Clearly, some of the aforementioned markets are more prone to speculation than others because of the nature of their market players (for instance equity indices are mainly traded by hedge funds, banks and retail traders whilst WTI Crude Oil is traded even by large commercial players that enter futures or options positions purely to hedge their physical exposure) so the way they move and react to market news and changes in the fundamentals vary vastly. On the other hand, the “safe assets” are the ones that fund managers and traders use in order to limit losses during sharp retracements in equity indices. In other words, they are employed in portfolio management as a sort of insurance. The markets that have historically played this role are Gold, Japanese Yen, US Dollar, Swiss Franc, Treasuries such as the American Treasury Bond or the German Bund and the “more recent” VIX Index (the adjective “recent” refers to the fact that the VIX Index could not be traded in the past). The reason they are called “safe havens” is because they tend to rise when risky assets fall, consequently, they are inversely correlated to equity indices and stocks; but is it really so? Do they really provide a valuable parachute against crash landings?

In order to answer the above mentioned questions we take 2 risky assets, E-Mini S&P500 and Crude Oil futures, and we compare their fluctuations against American Treasury Bond futures, German Bund futures, Gold futures, Japanese Yen futures and the VIX Index (the weekly analysis of all the aforementioned markets is covered by the HyperVolatility Forecasts service, send us an email at info@hypervolatility.com to know more). The study of the inter-market relationships has been performed using the correlation analysis and the dataset consists of weekly data for the years 2010, 2011 and 2012 (the last observation for the 2012 has been registered on the 24th of August 2012). Let’s examine E-Mini S&P500 futures:

As we can clearly see from the above reported chart the American index is negatively correlated to all the “safe havens”, which means that while E-Mini S&P00 futures were retracing the safe assets were going up and vice versa. Nevertheless, the correlation index fluctuated a lot throughout last years and the fact that Gold and Japanese Yen futures show an incredibly strong positive correlation in 2010 proves what it has been just stated. Therefore, any hypothetical fund manager or trader willing to hedge any S&P500 long position with these instruments would have obtained fairly poor results in 2010. However, it is worth noting that in 2011 and 2012 the futures on the Asian currency performed fairly well and proved to be moderately good when offsetting the risk coming from long positions on risky assets whilst gold futures worked out well only in 2011. Additionally, the futures on the German Bund had a fairly good negative correlation in 2011 but the performances registered in 2010 and 2012 are not really encouraging which means that there were extended periods of time where both instruments (E-Mini S&P500 and German Bund futures) were moving in the same direction. The same thing can be said for Treasury Bond futures, which display a more solid negative correlation in 2012 than German Bund, but the overall performance is still not that good. The only market which showed a constant and reasonably robust negative correlation with E-Mini S&P500 futures is the VIX Index that can be traded via VIX futures and options offered by the CBOE. Let’s now see if the scenario is different for WTI Crude Oil futures:

The chart displays a significant negative correlation and all the “safe havens” seem to be very good when hedging crude oil positions, although, in 2012 there is a considerable positive relationship with Gold futures (we will explain why later). Specifically, Japanese Yen futures and the VIX Index both show a negative relationship which was evidently much stronger in 2011 than it is now and the analysis manifestly highlights that the best products to use, when hedging any crude oil position, are definitely Treasury Bond and German Bund futures because the negative coefficients that they display are very solid and the inverse rapport seems to be quite stable over time.

So, why are Gold futures a sub-optimal choice? There are no definite answers to that but there are two contributing factors which could help to explain what is happening:

1) The CME increased margin calls for gold futures in August 2011, hence, many traders could not afford to keep their positions open anymore and had to cut them. This resulted in a large drop in gold prices, even if investors were heavily using them to hedge against the massive plunge that risky assets experienced over the summer of 2011, and by looking at the above reported chart it is easy to notice that in 2011 Gold futures were the worst performers (the correlation is still negative but it is definitely weaker than the one registered for the remaining “safe havens”)

2) Gold prices are still used for hedging purposes; the only problem is that they are now employed to counterbalance a different type of risk: over-inflation. In particular, gold futures are being purchased to cope with a higher inflation that can be caused by the “expansive monetary policies” recently adopted by the Fed and the ECB (the Fed will purchase 40 billion dollars worth of mortgage backed securities on a monthly basis and the ECB just launched an apparently unlimited bond buying programme). This explains the uptrend in gold prices and the positive correlation with the so-called risky assets in 2012

According to our findings the best markets to use when hedging positions on E-Mini S&P500 futures are the VIX Index, Treasury Bond and Japanese Yen futures whilst Crude Oil futures are best covered by Treasury Bond and German Bund futures with the Asian currency and the VIX being the 3rd best option (they are equally good so we can both place them at the 3rd place in our ranking).

Conversely, Gold prices proved to be the worst performer and the least reliable market, amongst all the “safe havens” analysed in the present research, when trying to minimise the downside risk on equity indices and risky assets.

 

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VIX Index Volatility Forecast (05/10/2011)

The VIX index opened at 39% on Monday, dropped to 37.7 on Tuesday, climbed to 41 on Wednesday, plummeted to 38.8 on Thursday and closed to 42.9 on Friday.

The volatility is around the 7.8% – 8% level (26.6% – 27.7% monthly) and the TGARCH chart is now displaying a volatility curve which is primarily moving sideways even if it is still very close to the 4% (13.8% monthly) long term equilibrium point. The actual situation of the VIX is neither indicating panic nor greed but uncertainty and indecision because many investors are not really sure which way the price is going to head to. Additionally, most of the uncertainty has been caused by both European and American politicians who keep promising new and robust policies to tackle the crises but are not implementing them.

The HyperVolatility team is bearish the VIX index because the stochastic volatility of the S&P500 implied volatility index is not giving any signal of potential bursts. As a consequence, we believe that the high volatility levels at which the VIX is currently trading will not hold for long implying that we could have a closing around the 38% – 39% by Friday.

However, a further round of sell-offs would push the VIX even higher and given the panic surrounding financial markets readings around the 48% – 50% could be easily achieved.

VIX Index Volatility Forecast (27/09/2011)

The VIX index opened at 32.7 on Monday, rose to 32.8 on Tuesday, jumped to 37.3 on Wednesday, achieved 41.3 on Thursday in a very volatile session and closed to 41.2 on Friday.

The actual volatility is 8% (27.7% monthly) and the TGARCH plot is showing an upward sloping curve which, in the very last part, does present some signs of retracement that, however, should be carefully interpreted given the delicate financial situation we are in.

The massive sell-off we saw the last week provoked an augment in volatility of volatility but the spike was not proportioned to the violence of the underlying movements. The VIX closed for 2 consecutive days above the 41% level and even during the big market drop occurred in May 2010 the aforementioned point was only barely touched implying that the probability for a mean reverting movement are now very much increased.

The HyperVolatility team is bearish the VIX index because the very last part of the chart should be considered as a short term explosion which is not going to affect VIX fluctuation over the medium term. Consequently, we could see the S&P500 implied volatility index to retrace and eventually close around the 30% level before Friday.

 

VIX Index Volatility Forecast (19/09/2011)

The VIX Index opened at 38.59 on Monday, dropped to 36.91 on Tuesday, plunged to 34.6 on Wednesday, settled at 31.97 on Thursday and closed at 30.98 on Friday.

The current volatility is 7.5% (25.9% monthly) and the TGARCH chart is showing a volatility curve which is quite close to its long term equilibrium point and therefore about to complete its mean reverting process. The last week saw some ups and downs in volatility, which are evident in the very last part of curve, but a break through the 7% level (24.2% monthly) should signal an ulterior drop of the oscillation rate and a potential settlement of the latter around the 4% threshold (13.8% monthly).

The HyperVolatility team is moderately bearish the VIX Index because the overall movement is still pointing towards a total retracement of the volatility towards it long term equilibrium point. Consequently, the VIX should touch the 25% area by the next Friday but, given the actual market conditions, short term bursts of the volatility are very likely to occur.

Even in this case the FOMC statement is going to play a key role.

VIX Index Volatility Forecast (06/09/2011)

The VIX Index opened at 32.2 on Monday, rose to 32.8 on Tuesday, dropped to 31.6 on Wednesday, touched 31.8 on Thursday and closed at 33.9 on Friday.

The current volatility is around 8% (27.7% monthly) and the TGARCH plot is still showing a downward sloping curve which is still trying to complete its mean reverting process and settle around the 4% threshold (13.8% monthly). However, like for the VXN Index, the speed at which the curve was collapsing decreased significantly meaning that the selling pressure that hit the market on Friday had a significant impact on the implied volatility and consequently on the volatility of volatility.

The HyperVolatility team is bullish the VIX Index because its mean reverting speed diminished drastically and a short term burst of the conditional variance is expected to occur within this week.

Should the panic prevail once again we would, almost certainly, see the S&P500 implied volatility index to retest the 40% – 41% although Thursday’s speech will prove decisive in the medium term.

VIX Index Volatility Forecast (30/08/2011)

The VIX Index opened at 42.4 on Monday, dropped to 36.2 on Tuesday, settled at 35.9 on Wednesday, jumped back up on Thursday, when it touched 39.7 and closed at 35.5 on Friday.

The volatility is around 13% (45% monthly) and the TGARCH plot is displaying an overall downward sloping curve which should continue its mean reverting journey in the upcoming hours. The very last part of the chart shows a small retracement but, as mentioned for the VXN Index, the waiting for Bernanke’s speech on Friday made many investors a bit nervous and this caused the conditional variance to increase.

However, even if some short retracements of the volatility can always happen it is worth pointing out that the oscillations of the VIX Index are decreasing and, given what we can see in the chart, it is likely that the next trading days will see an ulterior flattening of the variance.

The HyperVolatility team is bearish the VIX Index because its rate of fluctuations should diminish and the mean reverting process should become more and more evident. Consequently, we expect the VIX to retest the 30% threshold by Friday.

VIX Index Volatility Forecast (22/08/2011)

The volatility decreased in the first half of the week, as we managed to forecast, but the bad macroeconomics data accompanied by some nonsensical rants pushed the fear index through the roof. In fact, the VIX Index opened at 31.87% on Monday, rose to 32.85% on Tuesday, settled at 31.58% on Wednesday, jumped to 42.67% on Thursday and closed at 43.05% on Friday.

The actual volatility is 17% (58.8% monthly) and the TGARCH plot is showing an upward sloping curve implying that the panic in the market is far from being over and that the next trading days are likely to experience even wilder market oscillations. Additionally, the contemporary volatility readings are higher than the ones observed during the big drop that the market experienced in March 2004. Also, the VIX Index climbed so high only in the middle of the credit crunch: rough waters ahead!!

Panic and fears are still the predominant feelings amongst investors and the fact that the VIX closed 2days in a row above the 40% threshold is more than a word of warning (again, such a phenomenon did not occur since the first phase of the credit crunch).

The HyperVolatility team is bullish the VIX Index because many traders and investors will keep buying downside protection in the options market driving the index up. In particular, we are expecting the VIX to reach the 50% level by Friday.

On the other hand, good macroeconomics news could push the implied volatility index down towards the 30% level but it’s difficult that we will see readings below this level because most of the market participants will wait for Bernanke’s speech on Friday before making up their minds.

VIX Index Volatility Forecast (14/08/2011)

The HyperVolatility team forecasted an increase in the VIX index which would have pushed its value around the 40% level and, also in this case, the previously mentioned target was not just achieved but surpassed. In fact, the VIX Index opened at 48% on Monday, plummeted to 35% on Tuesday, touched 42.9% on Wednesday, plunged to 39% on Thursday and closed at 36.3% on Friday.

The current volatility is 18% (62% monthly) and the TGARCH plot is displaying a significant explosion of the conditional variance, which is even higher than the one we had during May 2010, but that is probably going to mean revert soon towards the 4% threshold (13.8% monthly).

The volatility is now moving a bit sideways but it is normal, for the conditional variance, to experience some short term “interruptions” during its journey towards the long term balance level and such a phenomenon is observable in every mean reverting process which follows a big spike in the volatility.

The HyperVolatility team is bearish the VIX because the stochastic volatility plot of the S&P500 implied volatility index is now displaying an-out-of-order and unsustainably high volatility curve. Therefore, the VIX should keep plummeting and possibly touch 25% – 28% by Friday.

Furthermore, the rumours of a potential downgrading of France’s triple A have been immediately vanished by the credit rating agencies themselves and the bargain hunting type of trading which is now hitting the market will push more and more traders to buy equities: all these factors together should favour a recovery of the price and a softening of the conditional variance.

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