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Oil Fundamentals: Upstream, Midstream, Downstream & Geopolitics

Crude oil is a scarce resource which means that at some point the existing oil wells will be exhausted. The current estimations, given the actual extraction and consumption rates, sustain that the black gold will be available for another 40 years but any increase in the demand would reduce the aforementioned projections. The USA has a Strategic Petroleum Reserve which has been specifically created in order to face shortages in the supply, however, rising oil prices and new technologies are pushing towards alternative source of energy.  Companies and businesses are considering potential substitute for crude oil and the alternative energy sources, that are increasingly becoming popular, are biofuels (like ethanol), hydrogen fuels, fuel cells, solar energy, nuclear power (even though nuclear power is not an environmentally friendly solution) and wind power.

Nevertheless, the demand for refined products is still very high and each oil derivative has its own market and its own price driver. A perfect example of divergence in price drivers for refined products comes for Europe. In the 90s many European governments guaranteed tax incentives to all the drivers who would have bought diesel–powered cars because diesel fuel emits less greenhouse gases than gasoline. Needless to say that such policy provoked a sharp augment in diesel prices but not in other oil derivatives.

Let’s now have a look at the oil industry as a whole.

First of all, it is worth mentioning that the oil industry is subdivided into 3 subsectors: upstream, midstream and downstream. The upstream involves the exploration and the extraction of crude oil, the midstream sector consists of transportation and storage while the downstream segment refers to the refining industry, marketing and distribution of refined products.

Upstream – The supply chain falls within the upstream segment. Here, the most important thing to determine is the capacity of the on–shore or off–shore site because this measurement identifies how big the oil well is and, consequently, the extraction rate. It is worth noting that major companies tend to retain a certain amount of unused capacity in order to face unexpected or sudden explosion in demand (usually caused by geopolitical issues).

Midstream – Once the extraction process is over, the oil “enters” the second segment: the midstream. This sector has to do, predominantly, with the transportation of the extracted petroleum liquids towards the refining centers. The transition can be processed using pipelines, trucks, barges or rail.

Downstream – Downstream operations are strongly connected with the refining industry because it is in this segment of the production chain that diesel, kerosene, jet fuel oil and all the other petroleum liquids get synthesized. Now, refining capacity is often closely related to demand for obvious reasons but not all refineries can deal with a broad range of crude oils so there are certain production boundaries. Nevertheless, the business is straightforward: refineries buy crude oil, they refine it and then sell the synthesized outputs. The income generated by refineries is measured with the so–called “crack spread” (there will be another study entirely focused on this product).

The cost of crude oil is not solely influenced by upstream, midstream and downstream operations. In fact, exogenous variables or unexpected events such as natural disasters, political turbulences and quality reduction of a specific oil well can push market players to increase their inventories. Consequentially, an augment in the short term demand and forward delivery would increase the cost of storage and, in turn, the cost of carry.

Amongst all of the exogenous factors that can alter oil prices, the geopolitical ones are certainly the most dangerous.

Conflicts and political instability in the Middle East have always had a remarkable impact on oil prices. Besides, African or Latin American countries, such as Nigeria and Venezuela, have often “hosted” violent riots that have increased the buying pressure on the oil market. Geopolitical issues create nervousness among market players and increase prices because internal riots, civil wars, unstable or corrupted governments could jeopardize the supply and limit the amount of oil available. Also, extreme forms of governments (fascism, communism, military controlled countries, etc) are not well seen by oil importing countries because dictators and/or non–democratically elected governments could threaten to limit the extraction or the export of oil.

The next chart provides a better clue on the relationship between geopolitical factors and oil prices:

Geopolitics - WTI Crude Oil Futures

The chart shows the fluctuations of WTI Crude Oil futures prices since July 1986 so far. The graph does not really need any comment because the arrows are self explanatory. Wars, civil wars, political turmoil, crises and cuts in the extraction rate have always added a significant pressure on crude prices which have been inevitably pushed higher. The only 3 big events, worth mentioning, that have depressed oil prices have been the Asian Economic Crisis in the mid 90s, the terroristic attack to the Twin Towers in September 2001and the Credit Crunch in 2008–2009.

Clearly, the Middle East is a vital geographical area for oil so any turbulence in this zone is strongly felt by market participants. Likewise, the other OPEC members do not always enjoy a great deal of political and civil stability (the OPEC members are  Algeria, Indonesia, Islamic Republic of Iran, Iraq, Kuwait, Libya, Nigeria, Qatar, Saudi Arabia, United Arab Emirates, Venezuela). The following chart shows the weight of each OPEC member in terms of number of daily extracted barrels:

Weights of OPEC members - June 2013

As previously mentioned, the chart displays the weight of each country expressed as a percentage of the total OPEC daily barrel production (the data are recent and they refer to the period January–June 2013). Saudi Arabia (29.68%), Iran (11.6%), Iraq (9.43%), Kuwait (9.17%) United Arab Emirates (8.78%) and Venezuela (8.63%) are the top 6 largest OPEC members. The fact that 5 out of 6 among the largest OPEC members are all located in the Middle East explains very clearly why this world region is so closely monitored by oil importing countries like United States, China, Japan, India and Germany.

If you are interested in trading oil or oil derivatives markets you might want to read the following HyperVolatility researches:

1) Oil Fundamentals: Reserves and Import/Export Dynamics

2) Oil Fundamentals: Crude Oil Grades and Refining Process

3) The Oil Arbitrage: Brent vs WTI

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.

Oil Fundamentals: Reserves and Import/Export Dynamics

The present study belongs to the Oil Fundamentals project that the HyperVolatility team initiated a few weeks ago with the article “Oil Fundamentals: Crude Oil Grades and Refining Process”. Credit must be given to Liying Zhao (Options Engineer at HyperVolatility) for helping me to gather the necessary material.

This analysis will provide information regarding the demand and consumption of oil on a global scale and it will subsequently examine the import/export dynamics.

The first variables that will be observed are oil reserves. Oil reserves are those quantities of oil whose availability is documented by geo–physical and engineering studies of the oil–well under examination and whose extraction falls within the parameters indicated by current economic conditions (transactional and operational costs) and structural resources (equipment and technology at disposal). In other words, it is the oil whose presence has been proven and that can be extracted given the current level of transactional costs and machinery’s sophistication. According to recent researches, OPEC countries possess more than 70% of the world proven reserves but Venezuela and Saudi Arabia are the largest “containers” on the planet. There is a standardized and worldwide recognized way to look at reserves: the Reserves–to–Production Ratio. The R/P ratio is a fairly simple number which expresses, in terms of years, how long oil reserves for a specific country would last assuming that the current extraction rate would remain constant over the years. It goes without saying that the calculation for the R/P ratio is trivial because it is performed by simply dividing the oil reserves at the end of the year by the production for the year. The next chart displays the R/P ratio for all continents (the data have been provided by British Petroleum):

Oil Reserves to Production Ratio

The interpretation of the above reported graph is very straightforward: the numbers on the Y axis measures the years it would take to terminate all oil reserves starting from December 2012. For example, Europe and North America would take almost 22.3 and 38.6 years respectively to finish all reserves should the current production rate remains constant in the upcoming years. The African continent would employ 37.7 years, the Asia–Pacific region would need only 13.6 years while the Middle East has 78 years of proven reserves. On the other hand, the “best equipped” part of the world is constituted by Southern and Central American countries with almost 122 years of available oil. It is interesting to notice that the whole world, according to this study, would finish its reserves in the 2065. The reason petroleum liquids have been shrinking is obviously due to an ever increasing global demand which went from 32 – 33 million barrels per day at the beginning of the 70s to 83 – 84 millions in the 2011 – 2012 (the International Energy Agency forecasted that the global demand will increase to almost 92 million barrels per day in 2014). The largest oil consumers are without a doubt the countries with a high industrial development rate: USA and European countries. USA remains the largest single oil consuming country because it employs 25% of the total oil extracted on the planet but the current scenario is changing rapidly. In fact, China, Japan and India are now becoming key market players and their internal markets are heavily weighing on global demand and price levels. Let’s now focus on imports/exports dynamics.

Many countries both import and export large amounts of oil but there are some of them which consume more than what they can produce, so they have to import the rest, and others that use only a very small part of what they extract, so they can export more. The following chart shows the top 20 oil importing countries in 2012 (the data have been provided by CIA World FactBook):

Oil Import

It is evident that the United States are the largest single oil importing country in the world with more than 10 million barrels per day followed by China (5 millions), Japan (4.39 millions), India (3 millions) and Germany (2.67 millions). However, if we group together all the import figures for the European countries in the top 20 we see that the States (10 million b/d) import almost as much as Europe (13.8 million b/d). The chart highlights that many Asian developing countries, excluding China and India, are suddenly augmenting their demand and industrial productivity, in fact, South Korea, Singapore, Taiwan, Thailand and Indonesia import almost as much as the majority of Western European countries: 1.5 million barrels every day.

The next graph ranks the top 20 oil exporting countries (the data have been provided by CIA World FactBook):

Oil Export

The top 5 oil exporters in the world are Saudi Arabia (7.63 million b/d), Russia (5 millions), Iran (2.52 million b/d), Arab Emirates (2.39 million b/d) and Norway (2.18 million b/d). The chart clearly highlights the superiority of Middle East countries in the role of global oil suppliers (almost 16.8 million b/d). The only 2 outsiders are Russia and Norway: the former is the only serious competitor that Saudi Arabia has while the latter is ranked at the 5th place because of the Brent Blend oil whose wells are placed in the North Sea. It’s worth noting that the USA does not export its oil (apart from a small part of Alaskan oil) and this is precisely why the States ranks so low. The ranking, however, has lately changed because Russia used to be the biggest oil exporter in the world for many years but a recent change in the policy adopted by the OPEC has re–shaped the oil supply scenario.

So far we have looked at importers and exporters and we know who buys and who sell the most but at this point an obvious question arises: Who buys from Whom?

There are 3 blocks of large buyers: USA, Europe and Asia (Asia means China, India and Japan) and their suppliers are the following:

1) USA imports oil from South and Central America, Middle East and Canada

2) Europe imports oil from Russia, Middle East and North Africa (Libya, Angola, etc)

3) Asia imports oil from the Middle East, Africa and, to a lesser extent, from smaller Asian countries (South Korea, Singapore, etc)

The inter–market connections are high and they range from Europe to Middle East and from Africa to Asia. Nonetheless, the aforementioned list is important to understand why OPEC countries are so important: the oil supply market is literally dominated by OPEC members

The presents study terminates here but the HyperVolatility team invites you to read our previous researches entirely focused on oil and commodity markets:

“The Oil Arbitrage: Brent vs WTI”

“Commodities and Currencies: Inter – Market Analysis”

Oil Fundamentals: Crude Oil Grades and Refining Process

“The Pricing of Commodity Options”

“Commodity Volatility Indices: OVX and GVZ”

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.

Oil Fundamentals: Crude Oil Grades and Refining Process

First of all, I would like to give credit to Liying Zhao (Options Engineer at HyperVolatility) for helping me to conceptualize this article and to gather the necessary information to develop it. There will be other articles describing the physical side of the crude oil market so this is simply “the first gear of a more complex apparatus”.

The present analysis is not a quantitative research on the oil market and its aim is to list the most important aspects to consider before investing or trading the black gold. Consequently, the focus will primarily be on the petroleum physical market and on how the oil industry works. The HyperVolatility team spends a great deal of time analyzing and trading commodity markets, hence, crude oil positions have always had a considerable weight in our portfolio. Also, the great attention towards commodity markets generated by the credit crunch and the consistently high volume on crude oil futures and options are some of the reasons that convinced us to put together a general guideline for those who choose to venture into energy markets and in particular fossil fuels.

First of all, it is worth mentioning that there are almost 250 different types of crude oils in the world but the ones that are mentioned the most are primarily 2: the American West Texas Intermediate and the European Brent Blend (which is now the global benchmark).It is not unusual to hear financial journalists talking about other crude oils like the Nigerian Bonny, the Arab Light (Saudi) or the Dubai (UAE); nevertheless, the spotlight is almost exclusively on WTI and Brent. The reason these markets, particularly the Brent, have so much media coverage is due to their importance when pricing other crude oils worldwide. Again, the Brent is the nowadays global benchmark (although the WTI used to have this role) so every oil producer or buyer will have to know its price; the question is why?

Why all other crude oils have to be priced according to Brent price fluctuations?

The answer to this question is API gravity, sulphur content and export.

As we previously mentioned there are many types of crude oils in the world but the chemical composition of each crude grade differs slightly. Crude oil is a fossil fuel and it is made of hydrocarbons (molecules of hydrogen and carbon atoms) but what makes the real difference, in terms of commercial value, is the weight of the hydrocarbons. The rule is simple: the lighter, the better. In order to determine how heavy or light petroleum liquids are the American Petroleum Institute introduced a standardized scale called API gravity. The API gravity system is a standardized way to compare and rank the “lightness or heaviness” of diverse crude oils. The system is very simple: the API gravity coefficient measures how heavy or light petroleum liquids are with respect to water. Crude oils with an API gravity greater than 10 are considered to be light (so they float on water) while oils with API lower than 10 are classified as heavy (so they sink when mixed with water). Crude oils with high API values (10 and higher) are lighter and produce greater quantity of marketable product, hence, they are more commercially desirable. This concept can be better understood by looking at the following chart (source: The International Crude Oil Market Report):

Grade of Crude Oil

The graph displays the distribution of different crude oils according to API gravity (X axis) and sulphur content (Y axis). It is easy to notice that WTI and Brent are both located in the right – hand side of the chart and they are very close to the X axis. The reason these oils are situated in this area is because their API gravity is very high (which means they are light types of oil) and their sulphur content is lower than 0.5% which means they are sweet (the word “sweet” in technical jargon means that there is a low level of impurity).

Let’s summarize what has been stated so far:

1) API gravity measures the lightness / heaviness of crude oils

2) API higher than 10 means that the crude oil is light and more profitable in terms of commercial value

3) API lower than 10 means that the crude oil is heavy and produces a minor quantity of commercial product after refining

4) Sulphur content measures the degree of pureness of crude oil, the level of impurity that each crude oil type contains

5) Sulphur content higher than 0.5% indicates a high level of impurity (sour crude oil) that has to be removed

6) Sulphur content lower than 0.5% implies a low level of impurity (sweet crude oil). This condition is preferred because less work is needed and the refining process is faster

7) All the crude oils ranked at the bottom of the right hand side of the chart are considered to be the most attractive under a commercial point of view

The aforementioned bullet points explain fairly well why the Brent is one of the best crude oils in the world but why is it better than the WTI?

The answer is straightforward: the European Brent is exported while the West Texas Intermediate remains within the US.  Consequently, the WTI has a “minor impact” on international markets (in reality, a part of the Alaskan oil output is exported to Japan and South Korea but the quantity is so small to be irrelevant in terms of international impact).

There are other chemical and physical aspects that need to be mentioned when talking about crude oil and one of these is certainly viscosity. Viscosity is the “ability” of a specific crude oil or refined product to flow.

Why is this factor important?

The degree of viscosity is very important to determine how crude oil will be stored or transported which means that the cost of carry will be primarily influenced by this variable. Crude oils can be classified according to their viscosity coefficient:

1) Paraffinic crude oils have low viscosity but they are easily flammable. Most of the engines lubricating oils are made of paraffinic crude oil. Paraffinic oils have a high API gravity and therefore tend to be light types of crude oil

2) Naphthenic (or Asphaltic) crude oils have a high viscosity coefficient but they are not easily flammable. This is the case of bitumen. Naphthenic oils have low API gravity and therefore tend to be heavy types of crude oil

This classification is very useful because it helps us understand a bit better how the refining process works. Let’s combine all the information together:

– Light and sweet crude oils (Brent, WTI, Bonny) have high API gravity, low sulphur content, low viscosity, high flammability and therefore are paraffinic oils. Light and sweet crude oils, once refined, tend to produce high quantity of gasoline

– Heavy and sour oils (Venezuelan BCF, Russian Urals crude, etc) have low API gravity, high sulphur content, high viscosity, low flammability and therefore are naphthenic oils. Heavy and sour crude oils, once refined, tend to be used as bitumen feedstock

The refining process aims to separate petroleum liquids in different chemical components which will be subsequently treated and combined with solvents to generate new oil derivatives.

How does the process work?

The crude oil is essentially pumped into a furnace and here the raw petroleum releases gases and liquids which are subsequently channeled in a tower to start the fractional distillation process. The point of directing the oil in this tower is to separate or fractionate different chemical components using heat. Specifically, each chemical component will have a specific boiling point and by increasing the temperature every constituent will start vaporizing as soon as its own boiling point will be reached. This process is gradual so the crude oil will fractionate into different gases at different temperatures but it is also continuous, which means that new raw petroleum liquid will be injected into the distillation tower at regular intervals to replace the fluid that has been already fractioned. The refining process usually produces a standardized set of oil derivatives such as gasoline, jet fuel, diesel fuel and asphalt. Nevertheless, other products (methane, propane, kerosene, etc) are often distillated. Oil derivatives have a wide range of applications; here we list some of them:

1) Methane also knows as natural gas, can be used for heating

2) Ethane is usually employed as a feedstock for other production processes (like the one followed to produce plastic)

3) Propane can be used for both cooking and heating

4) Gasoline is primarily used as fuel for vehicles

5) Naphtha is another feedstock and it is generally reused in the petrochemical industry

6) Kerosene (known as paraffin in UK, Ireland, South Asia and South Africa) is predominantly employed to produce Jet fuel oil

7) Gas oils are used to distillate diesel engine fuels or for home heating

8) Fuel oils are reused to power refineries or power stations. Alternatively, they are often utilized as a fuel for ships but in this case they are referred to as bunker fuel or bunker fuel oil

Now, this information is surely very important to anyone who is seriously thinking to invest or trade oil markets. Oil fundamentals are sometimes overlooked but a sound understanding of the dynamics underlying the fossil fuel industry is essential to fully comprehend market movements. As we anticipated at the beginning of this article, this is only the first part of a broader project.

If you are interested in trading crude oil you may want to read some HyperVolatility researches dealing with this topic:

“The Oil Arbitrage: Brent vs WTI”

“The Pricing of Commodity Options”

Commodity Volatility Indices: OVX and GVZ

“Commodities and Currencies: Inter – Market Analysis”

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.

The Pricing of Commodity Options

The present research will prove particularly useful to option traders. The analysis proposed by the HyperVolatility Team will explain, in a few bullet points, how the most popular commodity options pricing models behave and what the practical divergences in terms of prices are. The present study is very valuable to anyone interested in trading options because most trading platforms allow the trader to choose the model via which the theoretical value of the options will be calculated and consequently shown (the HyperVolatility Forecast Service provides market projections for many asset classes. Send an email to info@hypervolatility.com and get a free 14 days trial). The pricing models that will be analyzed are the Barone–Adesi –Whaley, the Bjerksund & Stensland (the 2002 version), the Black–76, the Binomial Tree and the classic Black–Scholes–Merton one. The models have been tested against each other and the following charts graphically show the divergence of 1 pricing model with respect to all others. The research has been performed assuming that the underlying asset (S) is a WTI crude oil futures contract, that the volatility (σ) is 20%, that the interest rate (r) is 0.5% and that the Cost of Carry is 0 (which is normal when dealing with commodity options).

As previously mentioned, the study will examine 1 pricing model at the time and, in order to avoid confusion and make things simpler, we decided to list the most important aspects below each graph:

Barone Adesi Whaley model

1) The Barone-Adesi-Whaley model overprices options when compared to other formulas. The pricing spread with respect to other models is on average between 0.06% and 0.08%

2) The Barone-Adesi-Whaley prices tend to get closer to other models as the expiration increases

3) The Barone-Adesi-Whaley model, on average, tends to overprice options with respect to the Binomial Tree (~ 0.16% higher) for short maturities. The trend is higher for out-of-the-money options and particularly for put options

4) The prices derived from the Bjerksund & Stensland model are always lower than Barone-Adesi-Whaley prices. The difference is bigger for 1 month options (~ 0.16%)

5) The Black-76 performs as well as the Black–Scholes–Merton model, however, their results overlap and that is why the Black-76 curve is not visible

6) The difference with the Black–Scholes–Merton model becomes larger as the expiration increases but it is not higher than 0.1%

 

Bjerksund & Stensland model

1) The Bjerksund & Stensland model under–prices options in respect to other models. On average the difference ranges between 0.05% – 0.06%

2) The under–pricing tends to reduce as the expiration increases

3) The Bjerksund & Stensland  model produces prices which are lower than the Barone–Adesi–Whaley one for any expiration

4) The Black–Scholes–Merton model approximates to the Bjerksund & Stensland one from the 8th month onwards

5) The Black–76 performed as well as the Black–Scholes–Merton model and that is why the overlapped curve cannot be seen  in the chart

6) The Binomial Tree approach shows the highest differential with respect to the Bjerksund & Stensland model. The divergence in pricing oscillates around 0.15%

 

Black-76 model

1) The Black–76 model over–prices options only with respect to the Bjerksund & Stensland one (almost 0.05%)

2) The divergence between Black–76 and Bjerksund & Stensland attenuates when longer expirations are approached

3) The Barone–Adesi–Whaley model prices are slightly higher than Black–76 ones and the discrepancy augments with the passage of time (between 0.08% and 0.1% for 10 months and 1 year expiring options respectively)

4) The Binomial Tree approach, if we exclude the short term, delivers higher prices than the Black–76 model but the divergence oscillates around the interval 0.03% – 0.04%

5) The Black–76 model performed as well as the Black–Scholes–Merton one and that is why the BSM curve is flat to 0. Needless to say that the Black–Scholes–Merton curve suggests that there is no difference in pricing

 

Binomial Tree model

1) The Binomial Tree under–prices options with respect to other models in the short term (around 2.5%) but the divergence is much lower for longer dated derivatives

2) The Barone–Adesi–Whaley model and the BSM model perform as well as the Black–76 one therefore their curves are hidden in the chart

3) The Bjerksund & Stensland model provided higher prices for short dated options but in the long term the Binomial Tree approach shows a slight over–pricing tendency with respect to the former. However, the spread is no higher than 0.04% – 0.05%

 

Black Scholes Merton model

1) The performances of the Black–Scholes–Merton formula with respect to other pricing models match perfectly well with the outcome generated by the Black–76 model

2) The above reported chart is identical to the graph extrapolated for the Black–76 model, in fact, the green curve does not move from the 0 axis

If you are interested in trading options you might want to read also the HyperVolatility researches entitled “Options Greeks: Delta, Gamma, Vega, Theta, Rho” and “Options Greeks: Vanna, Charm, Vomma, DvegaDtime”

The HyperVolatility Forecast Service enables you to receive the 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.

Options Greeks: Vanna, Charm, Vomma, DvegaDtime

The present article deals with second order Options Greeks and it constitutes the second part of a previously published article entitled “Options Greeks: Delta,Gamma,Vega,Theta,Rho”. Before getting started it is important to highlight the great contribution that Liying Zhao (Options Analyst at HyperVolatility) gave to this report. All the calculations and numerical simulations that will be shown and commented are entirely provided by Mr Zhao.

Second-order Greeks are sensitivities of first-order Greeks to small changes in different parameters. Mathematically, second-order Greeks are nothing else but the second-order partial derivatives of option prices with respect to different variables. In practical terms, they measure how fast first order options Greeks (Delta, Vega, Theta, Rho) are going to change with respect to underlying price fluctuations, volatility, interest rate changes and time decay. Specifically, we will go through Vanna, Charm (otherwise known as Delta Bleed), Vomma and DvegaDtime. It is important to point out that all charts have been produced by assuming that the underlying asset is a futures contract on WTI crude oil, the ATM strike (X) is 100, risk-free interest rate (r) is 0.5%, implied volatility is 10% while the cost of carry (b) is 0 (which is the case when dealing with commodity options).

Vanna: Vanna measures the movements of the delta with respect to small changes in implied volatility (1% change in implied volatility to be precise). Alternatively, it can also be interpreted as the fluctuations of vega with respect to small changes in the underlying price. The following chart shows how vanna oscillates with respect to changes in the underlying asset S:

Options VannaThe above reported chart clearly shows that vanna has positive values when the underlying price is higher than strike (in our case S>$100) and it has negative values when the underlying moves just below it (S<$100). What does that imply? The graph highlights the fact that vega moves much more when the underlying asset approaches the ATM strike ($100 in our case) but it tends to approximate 0 for OTM options. Consequently, the delta is very sensitive to changes in implied volatility when the ATM area is approached. However, it is important to point out that delta will not always increase if the underlying moves from, say, $80 to $100 because in many risky assets (stocks, equity indices, some currencies and commodities) the implied volatility is inversely correlated to the price action. As a result, if WTI futures go from $80 to $100 the implied volatility will probably head south and such a phenomenon would decrease vanna which, in turn, would diminish the value of delta.

Charm (or Delta Bleed): Charm measures delta’s sensitivity to a small movement in time to maturity (T). In practical terms, it shows how the delta is going to change with the passage of time. The next chart displays graphically the relationship between the aforementioned variables:

Options Charm

The chart suggests that, like in the case of vanna, the charm achieves its highest absolute values when the options are around the ATM area. Therefore, slightly in-the-money or out-of-the-money options will have the highest charm values. This makes sense because the greatest impact of time decay is precisely on options “floating” around the ATM zone. In fact, deep ITM options will behave almost like the underlying asset while OTM options with the passage of time will approach 0. Consequently, the deltas of slightly ITM or OTM options will be the most eroded by time. Charm is very important to options traders because if today the delta of your position or portfolio is 0.2 and charm is, for instance, 0.05 tomorrow your position will have a delta equal to 0.25. As we can clearly see, knowing the value of charm is crucial when hedging a position in order to keep it delta – neutral or minimize portfolio risk.

Vomma: Vomma measures how Vega is going to change with respect to implied volatility and it is normally expressed in order to quantify the influence on vega should the volatility oscillate by 1 point. The fluctuations of vomma with respect to S are shown in the next chart:

Options VommaAs displayed in the above reported chart out-of-the-money options have the highest vomma, while at-the-money options have a low vomma which means that vega remains almost constant with respect to volatility. The shape of vomma is something that every options trader should bear in mind while trading because it clearly confirms that the vega that will be influenced the most by a change in volatility will be the one of OTM options while the relationship with ATM options will be almost constant. This makes sense because a change in implied volatility would increase the probability of an OTM options to expire in-the-money and this is precisely why vomma is the highest around the OTM area.

DvegaDtime: DvegaDtime is the negative value of the partial derivative of vega in terms of time to maturity and it measures how fast vega is going to change with respect to the time decay. The next chart is a visual representation of its fluctuations with respect to the underlying asset S:

Options DvegaDtime

The above reported graph clearly displays that the influence of time decay on volatility exposure measured by vega is mostly felt in the ATM area especially for options with short time to maturity. The fact that DvegaDtime is mathematically expressed as negative derivatives makes sense because time decay is clearly a price that every options holder has to pay. In order to make things easier have a look at the plots of vega and theta because you will immediately realize that both volatility and time decay have their highest and lowest values in the ATM area. It goes without saying that ATM options have the highest volatility potential and therefore vega will be effected the most by the passage of time when the strike of our hypothetical options and the underlying price gets very close.

The HyperVolatility Forecast Service enables you to receive the 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.

Options Greeks: Delta,Gamma,Vega,Theta,Rho

First of all I would like to give credit to Liying Zhao (Options Analyst at HyperVolatility) for helping me to conceptualize this article and provide the quantitative analysis necessary to develop it. The present report will be followed by a second one dealing with second order Greeks and how they work.

Options are way older than one might imagine. Aristotele mentioned options for the first time in the “Thales of Miletus” (624 to 527 B.C.), Dutch tulip traders began trading options at the beginning of 1600 while in 1968 stock options have been traded for the first time at the Chicago Board Options Exchange (CBOE). The pricing of options has always attracted academics and mathematicians but the first breakthrough in this field was pioneered at the beginning of the 1900 by Bachelier. He literally discovered a new way to look at option valuation, however, the real shift between academia and business occurred in 1973 when Black, Scholes and Merton developed the most popular and used option pricing model. Such a discovery opened an entire new era for both academics and market players. Being one of the most crucial financial derivatives in the global market, options are now widely adopted as an effective tool to leverage assets or control portfolio risk. Nowadays, it is easy to find articles, researches and studies on option pricing models but this article will instead focus on options Greeks and in particular first-order Greeks (derived in the BSM world). Options Greeks are important indicators for assessing the degree of risk coming from exogenous variables, in fact, they measure option premium’s sensitivities to small changes in different parameters. Mathematically, Greeks are the partial derivatives of the option price with respect to different factors such as volatility, interest rate and time decay.

The purpose of this article is to explain, as clearly as possible, how Options Greeks work but we will concentrate only on the most popular ones: Delta, Gamma, Vega (or Kappa), Theta and Rho. It is worth mentioning that all the charts that will be presented have been extrapolated by assuming that the underlying is a WTI futures contract, that the options have a strike price (X) of 100, that the risk-free interest rate (r) is 0.5%, that the cost of carry (b) is 0 while implied volatility is 10%.

Delta: Delta measures the sensitiveness of the option’s price to a $1 fluctuation in the underlying asset price. The chart displays how the Delta moves in respect to the underlying price S and time to maturity T:

options delta

The chart clearly shows that in-the-money call options have much higher Delta values than out-of-the-money options while ATM options have a Delta which oscillates around 0.5. Call options have a Delta which ranges between 0 and 1 and it gets higher as the underlying approaches the strike price of the option which means that out-of-the-money call options will have a Delta close to 0 while ITM options will have a Delta fluctuating around 1. Many traders think of Delta as the probability of an option expiring in-the-money but this interpretation is not correct because the N(d) term in its formula expresses the probability of the option expiring ITM but only in a risk-neutral world.  In real trading conditions higher Delta calls do have a higher probability to expire ITM than lower Delta ones, however, the number itself does not provide a reliable source of information because everything depends on the underlying. The Delta simply expresses the exposure of the options premium to the underlying: a positive Delta tells you that the premium will rise if the underlying asset will trend higher and it will decrease in the opposite scenario. Put options, instead, have a negative Delta which ranges between -1 and 0 and the below reported chart displays its fluctuation in respect to the underlying asset.

put option delta

It is easy to notice that as the underlying asset moves below the $100 threshold (the strike price of our hypothetical put option) the Delta approaches -1, which implies that ITM put options have a negative Delta close to -1, while OTM options have a Delta oscillating around 0. In practical trading the value of the Delta is very important because it tells you how the options premium is going to change in the case the underlying moves by $1. Let’s assume you purchase a 100 call options on crude oil with a Delta of +0.5 and the premium was $1,000.  If the option is at-the-money the WTI (the underlying asset) will be at $100 but if oil futures go up by $1 dollar to $101 the premium of your long call will move to $1,500. The same applies to put options but in this case the ATM Delta will be -0.5 and your long put option position will generate a profit if WTI futures move from $100 to $99.

Gamma: Gamma measures Delta’s sensitivity to a $1 movement in the underlying asset price and it is identical for both call and put options. Gamma reaches its maximum when the underlying price is a little bit smaller, not exactly equal, to the strike of the option and the chart shows quite evidently that for ATM option Gamma is significantly higher than for OTM and ITM options.

option gamma

The fact that Gamma is higher for ATM options makes sense because it is nothing but the quantification of how fast the Delta is going to change and an ATM option will have a very sensitive Delta because every single oscillation in the underlying asset will alter it.

How Gamma can help us in trading? How do we interpret it?

Again, the value of Gamma is simply telling you how fast the Delta will move in the case the underlying asset experience a $1 oscillation. Let’s assume we have an ATM call option on WTI with a Delta of +0.5 while futures prices are moving around $100 and Gamma is 0.08, what does that imply? The interpretation is rather simple: a 0.08 gamma is telling us that our ATM call, in the case the underlying moves by $1 to $101, will see its Delta increasing to +0.58 from +0.5

Vega (or Kappa): Vega is the option’s sensitivity to a 1% movement in implied volatility and it is identical for both call and put options. The below reported 3-D chart displays Vega as a function of the asset price and time to maturity for a WTI options with strike at 100, interest rate at 0.5% and implied volatility at 10% (the cost of carry is set to 0 because we are dealing with commodity options).

option vega

The chart clearly highlights the fact that Vega is much higher for ATM options than for ITM and OTM options. The shape of Vega as a function of the underlying asset price makes sense because ATM options have by far the highest volatility potential but what does Vega really tell us in real trading conditions? Again, Vega (or Kappa) measures the dollar change in case of a 1% shift in implied volatility, therefore, an at-the-money WTI options whose value is $1,000 with a Vega of , say, 100 will be worth $1,100 if the implied volatility moves from 20% to 21%. Vega is a very important risk measure for options traders because it estimates how your P/L is going to change as a function of implied volatility. Implied volatility is the key factor in options pricing because the price of a single options will vary according to this number and this is precisely why implied volatility and Vega are essential to options trading (the HyperVolatility Forecast service provides analytical, easy to understand projections and analysis on volatility and price action for traders and investors).

Theta: Theta measures option’s sensitivity to a small change in time to maturity (T). As time to maturity is always decreasing it is normal to express Theta as negative partial derivatives of the option price with respect to T.  Theta represents the time decay of option prices in terms of a 1 year move in time to maturity and to view the value of Theta for a 1 day move we should divide it by 365 or 252 (the number of trading days in one year). The below reported chart shows how Theta moves:

option theta

Theta is evidently negative for at-the-money options and the reason behind this phenomenon is that ATM options have the highest volatility potential, therefore, the impact of time decay is higher. Think of an option like an air balloon which loses a bit of air every day. The at-the-money options are right in the middle because they could become ITM or they could get back into the OTM “limbo” and therefore they contain a lot of air, consequently, if they have got more air than all other balloons they will lose more than others when the time passes. Let’s look at a practical example. Let’s assume we are long an ATM call option whose value is $1,000 and has a Theta equals to -25, if the day after both the underlying price and volatility are still where they were 1 day before our long call position will lose $25.

Rho: Rho is the option’s sensitivity to a change in the risk-free interest rate and the next chart summarises how it fluctuates with respect to the underlying asset:

option rho

ITM options are more influenced by changes in interest rates (negative Rho) because the premium of these options is higher and therefore a fluctuation in the cost of money (interest rate) would inevitably cause a higher impact on high-premium instruments. Furthermore, it is rather clear that long dated options are much more affected by changes in interest rates than short-dated derivatives. The below reported chart displays how Rho oscillates when dealing with put options:

put option rho

The Rho graph for put options mirrors what it has been stated for calls: ITM have a larger exposure than ATM and OTM put options to interest rate changes and long term derivatives are much more affected by Rho than in the short term (even in this case the 3-D graph displays negative values). As previously mentioned Rho measures how much the option’s premium is going to change when interest rates move by 1%. Hence, an increase in interest rates will augment the value of a hypothetical call option and the rise will be equal to Rho. In other words, the value of the call option will increase by $50 if interest rates move from 5% to 6% and our WTI call option has a premium of $1,000 but Rho equals 50.

As stated at the beginning of the present report this is only the first part and a second article dealing with second order Greeks will be posted soon.

The Oil Arbitrage: Brent vs WTI

It is no secret that the most important crude oils in the world are the European Brent (extracted by 15 oil fields located in the East Shetland Basin in the North Sea) and the American WTI which is extracted in the US and delivered at the Cushing in Oklahoma. It is well known that the Brent Crude oil has become the global benchmark and it is used to price crude oils worldwide. Although they are extracted in geographically distant locations the chemical composition of WTI and Brent is not exceptionally different because both of them are considered to be “sweet oils” which means that both contain a low concentration of sulphur: 0.37% for the Brent and 0.24% for the WTI. This small introduction is necessary to understand that the supply/demand forces driving price fluctuations are dissimilar and the discrepancy is even clearer if we add that the Brent is exported in the whole Europe and worldwide while the WTI does not leave the US.

The Brent/WTI arbitrage (the word arbitrage is a misnomer because we are buying and selling two different asset classes) is a fairly popular trading technique within the energy sector and its aim is to profit from price discrepancies. The strategy is reasonably simple and it consists of contemporarily selling the WTI and buying the Brent (short arb) or selling the Brent and buying the WTI (long arb). Clearly, this is a spread trading technique rather easy to implement and control because both Brent and WTI futures share the same size (1,000 barrels) while the tick value (1 cent per barrel) equals to $ 10 for both contracts.

How does the trade work? Let’s assume that a trader decides to sell WTI and buy Brent futures (short arb). He sells the WTI at $ 100 and buys the Brent at $ 110 and he will make money if the 2 asset classes will move in opposite directions. If the WTI drops to $ 97 while the Brent closes at $ 112 our hypothetical trader would have made a $ 3,000 profit from the WTI and $ 2,000 from the Brent for each contract traded.

What happens if WTI and Brent move in the same direction? The strategy would still be profitable if the price augment in the Brent market outweighs the rise in WTI futures. If the Brent gains $ 3 and the WTI $ 1.5, the trader would make a $ 3,000 profit from the long Brent position but he would lose $ 1,500 on the short WTI contract which implies that the overall profit would be equal to $ 3,000 – $ 1,500 = $ 1,500

As you can see the trade would still show a profit because in our example WTI and Brent experienced different volatilities and consequently their fluctuations were not symmetrical in terms of magnitude (the first moved 3 dollars and the second only $ 1.5). However, should the Brent had moved lower and the WTI higher the short WTI / long Brent position would have lost money.

The chart #1 shows how the most important oils oscillated since 2009 until 2011:

Brent and WTI futures

It is evident that until 2011both WTI and Brent were moving symmetrically but for some fundamental reasons, such as global demand and some logistic problems with the WTI, the prices started to diverge and the spread became rather large. On the other hand, the narrowing of the arb from September 2011 onwards is mainly due to an increased demand and to the construction of the Seaway pipeline which facilitates the transportation of the WTI from the Cushing in Oklahoma to Freeport in Texas. Let’s have a look at the WTI/Brent spread now:

Brent / WTI spread

The chart #2 shows very clearly that since 2009 until the beginning of 2011 the differential oscillated following a mean reverting process (because it always tended to get back to the 0 line) and it used to fluctuate within fixed boundaries (because it rarely surpassed the $ 2.5 threshold and infrequently remained below the – $2 level for an extended period of time). However, the scenario has quite changed because in 2011 the Brent/WTI spread increased substantially and achieved the $ 25 level. If we go back to the first chart we can immediately understand what caused such a high spread: the Brent price kept increasing while WTI futures prices kept dropping.

How can a trader take advantage of such divergence? When the trade should be triggered?

Buying or selling the oil arb is up to the trader and it depends on fundamental data such as supply/demand forces, industrial productivity, etc but it is possible to identify when the trade could have a higher probability of success. The chart #3 will help us prove our point:

Brent / WTI correlation

The graph shows the correlation (which fluctuates within -1 and 1) between Brent and WTI since 2009 until the end of the 2011 and its interpretation is straightforward: the higher the correlation, the stronger the relationship between the 2 asset classes. The correlation on average is rather high which means that Brent and WTI tend to experience similar fluctuations, although with different volatilities, but there is a second important characteristic that it is very useful in practical terms: the correlation is mean reverting because it tends to drop and then explode again.

In practical terms, all the time the correlation index drops the relationship between Brent and WTI weakens, hence, the probability of dissimilar fluctuations amplify. Conversely, an increasing correlation would imply the opposite scenario.

We now know that a plunge in the correlation index would increase the probability of maximizing our profits because it would highlight that the relationship between the 2 asset classes is not going to be strong and that the spread will likely expand.  However, in real trading conditions we will need specific entry points, some numerical thresholds to look at in order to trigger our trades and the following tables should be a valuable tool for anyone interested in trading the oil arb:

Brent / WTI spread price distribution

Bear in mind that these are not trading recommendations but merely a guide and the price / correlation levels refer to the period 2009 – 2011.

The table #1 represents the price distribution of the Brent/WTI spread. The outcome of our research shows that the lowest price achieved by the spread is $ -5.42 (which means that the Brent was lower than the WTI) while the highest point was $ 26.84. The percentage row displays the percentage of observations below the reported price levels. In other words, the 24.97% of  total observations were below the $ -0.36, almost 50% of the Brent/WTI spread prices were below the $ 2.28 level while the price fluctuated below the $10.98 threshold in the 74.77% of cases. Now let’s see what the correlation key points are:

Brent / WTI correlation distribution

On average the correlation is around 0.82 but in the 25% of cases it dropped to 0.62 and it remained lower than 0.91 almost the 80% of the time. The extreme points are -0.35 and 0.99 that have been touched only once.

 Strategy Analysis

1)   The Brent/WTI spread fluctuated within $ 2 and $ 2.3 most of the time

2)  The correlation is usually fairly strong and it frequently oscillates around 0.78 and 0.82

3)  In order to have a reliable entry point both price and correlation should be out of their ranges. We should be in a situation where there is an evident mismatch

4)  Entry points are signalled by a breakthrough of the aforementioned price and correlation levels because if the arb price is higher than $ 2.3 and the correlation is lower than 0.78 then the probability of success is higher. Needless to say that good opportunities arise also when the arb price is lower than $ 2 dollars and the correlation is higher than $ 0.8

In our HyperVolatility Forecast Service we dig deeper through news and calculations. We provide financial forecasts based on volatility analysis and statistics that you will not find in a retail trading platform. The HyperVolatility Forecast Service enables you to receive the 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.

E-Mini Crude Oil Futures Volatility Forecast (05/10/2011)

E-Mini Crude Oil futures opened at 81.2 on Monday, rose to 83.6 on Tuesday, sharply dropped to 80.8 on Wednesday, jumped back to 82.8 on Thursday and plummeted to 78.6 on Friday.

The actual volatility is 2.3% (36.5% in annual terms) whilst the plot is displaying a downward sloping volatility curve which should keep plummeting over the next trading days although the mean reverting point is not that far from current levels.

It is worth pointing out that oil prices are not mirroring their “fundamental reasons” anymore but are entirely driven by macroeconomics events and the great drop of the Single currency had a massive impact on E-Mini Crude Oil futures prices.

The HyperVolatility team is moderately bullish this market because a short term recovery of the Euro against the US dollar, the extremely cheap oil prices and a softening volatility curve should back the price action which could eventually retest the $ 80 threshold by Friday.

A further plunge in the Euro vs Dollar exchange rate would irremediably drag E-Mini Crude Oil futures prices down in the $ 73 area.

E-Mini Crude Oil Futures Volatility Forecast (27/09/2011)

E-Mini Crude Oil futures opened at 85.6 on Monday and remained around this level on Tuesday as well but on Wednesday the price action plunged to 84.6 whilst on Thursday a $4 dollar drop dragged futures prices to 80.2 and the week closed at 80.1 on Friday.

The actual volatility is 2.6% (41.2% in annual terms) and the TGARCH curve is evidently showing an upward sloping curve which seems to suggest that further volatility should be expected over the next trading hours. On the other hand, the current readings have been reached only 2-3 times over the past 5 months and all the time the curve surpassed this threshold the mean reverting pressure became so intense that the fluctuations rate “had to collapse” towards its medium term equilibrium point; that is 1.7% – 1.8 % (26.9% – 28.5% annualised).

The Crude Oil market is not following fundamentals anymore. The latest news regarding Crude Oil inventories and Cushing showed a massive draw which, in normal trading conditions, would have pushed the price up but clearly over the last week we “went through” the opposite scenario.

The HyperVolatility team is moderately bullish E-Mini Crude Oil futures because the volatility should probably mean revert and support the price action although some short term retracements are quite likely to occur, particularly in the first half of the week.

Futures prices, ceteris paribus, are likely to retest the $ 83 – 84 area but an ulterior macroeconomics shock would depreciate the Euro, appreciate the dollar and depress oil prices.

E-Mini Crude Oil Futures Volatility Forecast (19/09/2011)

E-Mini Crude Oil futures opened at 88.8 on Monday, retested the 89.95 resistance on Tuesday, dropped to 88.55 on Wednesday, achieved 89.22 on Thursday and closed at 87.85 on Friday.

The actual volatility is 2% (31.7% annualised) and the TGARCH plot is showing a fairly stable volatility curve which is now trading within its medium term average. Nevertheless, the actual level is still extremely high if compared to the average volatility of this market and the fact that the curve is slightly upward sloping could imply that a higher fluctuations rate should be expected in the upcoming hours although the augment should not be critical.

The long term picture is still highly bearish and the fact that the conditional variance is now trading sideways on its equilibrium point could signal that an increased degree of market fluctuations should be expected in the upcoming trading hours.

The HyperVolatility team is bearish E-Mini Crude Oil futures because the volatility curve is probably going to head north in the next hours whilst the price should touch the 83-84 area by Friday.

Needless to say that the FOMC statement can change the overall picture but the high pressure on the Single currency is going to indirectly influence oil prices.

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