Saturday, 27 August 2011
Friday, 26 August 2011
Export & Impot of Crude Oil
Export
In order of net exports in 2009 and 2006 in thousand bbl/d and thousand m³/d:# | Exporting Nation | 103bbl/d (2009) | 103m3/d (2009) | 103bbl/d (2006) | 103m3/d (2006) |
|---|---|---|---|---|---|
| 1 | Saudi Arabia (OPEC) | 7,322 | 1,164 | 8,651 | 1,376 |
| 2 | Russia 1 | 7,194 | 1,144 | 6,565 | 1,044 |
| 3 | Iran (OPEC) | 2,486 | 395 | 2,519 | 401 |
| 4 | United Arab Emirates (OPEC) | 2,303 | 366 | 2,515 | 400 |
| 5 | Norway 1 | 2,132 | 339 | 2,542 | 404 |
| 6 | Kuwait (OPEC) | 2,124 | 338 | 2,150 | 342 |
| 7 | Nigeria (OPEC) | 1,939 | 308 | 2,146 | 341 |
| 8 | Angola (OPEC) | 1,878 | 299 | 1,363 | 217 |
| 9 | Algeria (OPEC) 1 | 1,767 | 281 | 1,847 | 297 |
| 10 | Iraq (OPEC) | 1,764 | 280 | 1,438 | 229 |
| 11 | Venezuela (OPEC) 1 | 1,748 | 278 | 2,203 | 350 |
| 12 | Libya (OPEC) 1 | 1,525 | 242 | 1,525 | 242 |
| 13 | Kazakhstan | 1,299 | 207 | 1,114 | 177 |
| 14 | Canada 2 | 1,168 | 187 | 1,071 | 170 |
| 15 | Qatar | 1,066 | 169 | - | - |
| - | Mexico 1 | 1,039 | 165 | 1,676 | 266 |
Source: US Energy Information Administration
1 peak production already passed in this state
2 Canadian statistics are complicated by the fact it is both an importer and exporter of crude oil, and refines large amounts of oil for the U.S. market. It is the leading source of U.S. imports of oil and products, averaging 2,500,000 bbl/d (397,000 m3/d) in August 2007. [2].
Total world production/consumption (as of 2005) is approximately 84 million barrels per day (13,400,000 m3/d).
Import
| # | Importing Nation | 103bbl/day (2009) | 103m3/day (2009) | 103bbl/day (2006) | 103m3/day (2006) |
|---|---|---|---|---|---|
| 1 | United States 1 | 9,631 | 1,531 | 12,220 | 1,943 |
| 2 | China 2 | 4,328 | 688 | 3,438 | 547 |
| 3 | Japan | 4,235 | 673 | 5,097 | 810 |
| 4 | Germany | 2,323 | 369 | 2,483 | 395 |
| 5 | India | 2,233 | 355 | 1,687 | 268 |
| 6 | South Korea | 2,139 | 340 | 2,150 | 342 |
| 7 | France | 1,749 | 278 | 1,893 | 301 |
| 8 | United Kingdom | 1,588 | 252 | - | - |
| 9 | Spain | 1,439 | 229 | 1,555 | 247 |
| 10 | Italy | 1,381 | 220 | 1,558 | 248 |
| 11 | Netherlands | 973 | 155 | 936 | 149 |
| 12 | Republic of China (Taiwan) | 944 | 150 | 942 | 150 |
| 13 | Singapore | 916 | 146 | 787 | 125 |
| 14 | Turkey | 650 | 103 | 576 | 92 |
| 15 | Belgium | 597 | 95 | 546 | 87 |
| - | Thailand | 538 | 86 | 606 | 96 |
Source: US Energy Information Administration
1 peak production of oil already passed in this state[citation needed]
2 Major oil producer whose production is still increasing[citation needed]
[edit] Non-producing consumers
Countries whose oil production is 10% or less of their consumption.| # | Consuming Nation | (bbl/day) | (m³/day) |
|---|---|---|---|
| 1 | Japan | 5,578,000 | 886,831 |
| 2 | Germany | 2,677,000 | 425,609 |
| 3 | South Korea | 2,061,000 | 327,673 |
| 4 | France | 2,060,000 | 327,514 |
| 5 | Italy | 1,874,000 | 297,942 |
| 6 | Spain | 1,537,000 | 244,363 |
| 7 | Netherlands | 946,700 | 150,513 |
| 8 | Turkey | 575,011 | 91,663 |
Source: CIA World Factbook
Petroleum
Petroleum (L. petroleum, from Greek: petra (rock) + Latin: oleum (oil)[1]) or crude oil is a naturally occurring, flammable liquid consisting of a complex mixture of hydrocarbons of various molecular weights and other liquid organic compounds, that are found in geologic formations beneath the Earth's surface. Petroleum is recovered mostly through oil drilling. This latter stage comes after the studies of structural geology (at the reservoir scale), sedimentary basin analysis, reservoir characterization (mainly in terms of porosity and permeable structures).[2][3] It is refined and separated, most easily by boiling point, into a large number of consumer products, from petrol and kerosene to asphalt and chemical reagents used to make plastics and pharmaceuticals.[4] Petroleum is used in manufacturing a wide variety of materials
Proven world oil reserves, 2009
An oil well produces predominantly crude oil, with some natural gas dissolved in it. Because the pressure is lower at the surface than underground, some of the gas will come out of solution and be recovered (or burned) as associated gas or solution gas. A gas well produces predominantly natural gas. However, because the underground temperature and pressure are higher than at the surface, the gas may contain heavier hydrocarbons such as pentane, hexane, and heptane in the gaseous state. At surface conditions these will condense out of the gas to form natural gas condensate, often shortened to condensate. Condensate resembles petrol in appearance and is similar in composition to some volatile light crude oils.
The proportion of light hydrocarbons in the petroleum mixture varies greatly among different oil fields, ranging from as much as 97% by weight in the lighter oils to as little as 50% in the heavier oils and bitumens.
Crude oil varies greatly in appearance depending on its composition. It is usually black or dark brown (although it may be yellowish, reddish, or even greenish). In the reservoir it is usually found in association with natural gas, which being lighter forms a gas cap over the petroleum, and saline water which, being heavier than most forms of crude oil, generally sinks beneath it. Crude oil may also be found in semi-solid form mixed with sand and water, as in the Athabasca oil sands in Canada, where it is usually referred to as crude bitumen. In Canada, bitumen is considered a sticky, black, tar-like form of crude oil which is so thick and heavy that it must be heated or diluted before it will flow.[10] Venezuela also has large amounts of oil in the Orinoco oil sands, although the hydrocarbons trapped in them are more fluid than in Canada and are usually called extra heavy oil. These oil sands resources are called unconventional oil to distinguish them from oil which can be extracted using traditional oil well methods. Between them, Canada and Venezuela contain an estimated 3.6 trillion barrels (570×109 m3) of bitumen and extra-heavy oil, about twice the volume of the world's reserves of conventional oil.[11]
Petroleum is used mostly, by volume, for producing fuel oil and petrol, both important "primary energy" sources.[12] 84% by volume of the hydrocarbons present in petroleum is converted into energy-rich fuels (petroleum-based fuels), including petrol, diesel, jet, heating, and other fuel oils, and liquefied petroleum gas.[13] The lighter grades of crude oil produce the best yields of these products, but as the world's reserves of light and medium oil are depleted, oil refineries are increasingly having to process heavy oil and bitumen, and use more complex and expensive methods to produce the products required. Because heavier crude oils have too much carbon and not enough hydrogen, these processes generally involve removing carbon from or adding hydrogen to the molecules, and using fluid catalytic cracking to convert the longer, more complex molecules in the oil to the shorter, simpler ones in the fuels.
Due to its high energy density, easy transportability and relative abundance, oil has become the world's most important source of energy since the mid-1950s. Petroleum is also the raw material for many chemical products, including pharmaceuticals, solvents, fertilizers, pesticides, and plastics; the 16% not used for energy production is converted into these other materials. Petroleum is found in porous rock formations in the upper strata of some areas of the Earth's crust. There is also petroleum in oil sands (tar sands). Known oil reserves are typically estimated at around 190 km3 (1.2 trillion (short scale) barrels) without oil sands,[14] or 595 km3 (3.74 trillion barrels) with oil sands.[15] Consumption is currently around 84 million barrels (13.4×106 m3) per day, or 4.9 km3 per year. Which in turn yields a remaining oil supply of only about 120 years, if current demand remain static.
Proven world oil reserves, 2009
Etymology
The term petroleum was found (in the spelling "petraoleum") in 10th-century Old English sources.[5] It was used in the treatise De Natura Fossilium, published in 1546 by the German mineralogist Georg Bauer, also known as Georgius Agricola.[6] In the 19th century, the term petroleum was frequently used to refer to mineral oils produced by distillation from mined organic solids such as cannel coal (and later oil shale), and refined oils produced from them; in the United Kingdom, storage (and later transport) of these oils were regulated by a series of Petroleum Acts, from the Petroleum Act 1862 c. 66 onward.
Composition
In its strictest sense, petroleum includes only crude oil, but in common usage it includes all liquid, gaseous, and solid (e.g., paraffin) hydrocarbons. Under surface pressure and temperature conditions, lighter hydrocarbons methane, ethane, propane and butane occur as gases, while pentane and heavier ones are in the form of liquids or solids. However, in an underground oil reservoir the proportions of gas, liquid, and solid depend on subsurface conditions and on the phase diagram of the petroleum mixture.[7]An oil well produces predominantly crude oil, with some natural gas dissolved in it. Because the pressure is lower at the surface than underground, some of the gas will come out of solution and be recovered (or burned) as associated gas or solution gas. A gas well produces predominantly natural gas. However, because the underground temperature and pressure are higher than at the surface, the gas may contain heavier hydrocarbons such as pentane, hexane, and heptane in the gaseous state. At surface conditions these will condense out of the gas to form natural gas condensate, often shortened to condensate. Condensate resembles petrol in appearance and is similar in composition to some volatile light crude oils.
The proportion of light hydrocarbons in the petroleum mixture varies greatly among different oil fields, ranging from as much as 97% by weight in the lighter oils to as little as 50% in the heavier oils and bitumens.
| Element | Percent range |
|---|---|
| Carbon | 83 to 87% |
| Hydrogen | 10 to 14% |
| Nitrogen | 0.1 to 2% |
| Oxygen | 0.05 to 1.5% |
| Sulfur | 0.05 to 6.0% |
| Metals | < 0.1% |
Crude oil varies greatly in appearance depending on its composition. It is usually black or dark brown (although it may be yellowish, reddish, or even greenish). In the reservoir it is usually found in association with natural gas, which being lighter forms a gas cap over the petroleum, and saline water which, being heavier than most forms of crude oil, generally sinks beneath it. Crude oil may also be found in semi-solid form mixed with sand and water, as in the Athabasca oil sands in Canada, where it is usually referred to as crude bitumen. In Canada, bitumen is considered a sticky, black, tar-like form of crude oil which is so thick and heavy that it must be heated or diluted before it will flow.[10] Venezuela also has large amounts of oil in the Orinoco oil sands, although the hydrocarbons trapped in them are more fluid than in Canada and are usually called extra heavy oil. These oil sands resources are called unconventional oil to distinguish them from oil which can be extracted using traditional oil well methods. Between them, Canada and Venezuela contain an estimated 3.6 trillion barrels (570×109 m3) of bitumen and extra-heavy oil, about twice the volume of the world's reserves of conventional oil.[11]
Petroleum is used mostly, by volume, for producing fuel oil and petrol, both important "primary energy" sources.[12] 84% by volume of the hydrocarbons present in petroleum is converted into energy-rich fuels (petroleum-based fuels), including petrol, diesel, jet, heating, and other fuel oils, and liquefied petroleum gas.[13] The lighter grades of crude oil produce the best yields of these products, but as the world's reserves of light and medium oil are depleted, oil refineries are increasingly having to process heavy oil and bitumen, and use more complex and expensive methods to produce the products required. Because heavier crude oils have too much carbon and not enough hydrogen, these processes generally involve removing carbon from or adding hydrogen to the molecules, and using fluid catalytic cracking to convert the longer, more complex molecules in the oil to the shorter, simpler ones in the fuels.
Due to its high energy density, easy transportability and relative abundance, oil has become the world's most important source of energy since the mid-1950s. Petroleum is also the raw material for many chemical products, including pharmaceuticals, solvents, fertilizers, pesticides, and plastics; the 16% not used for energy production is converted into these other materials. Petroleum is found in porous rock formations in the upper strata of some areas of the Earth's crust. There is also petroleum in oil sands (tar sands). Known oil reserves are typically estimated at around 190 km3 (1.2 trillion (short scale) barrels) without oil sands,[14] or 595 km3 (3.74 trillion barrels) with oil sands.[15] Consumption is currently around 84 million barrels (13.4×106 m3) per day, or 4.9 km3 per year. Which in turn yields a remaining oil supply of only about 120 years, if current demand remain static.
The hydrocarbons in crude oil are mostly alkanes, cycloalkanes and various aromatic hydrocarbons while the other organic compounds contain nitrogen, oxygen and sulfur, and trace amounts of metals such as iron, nickel, copper and vanadium. The exact molecular composition varies widely from formation to formation but the proportion of chemical elements vary over fairly narrow limits as follows:
Composition by weight
| Carbon | 83 to 87% |
| Hydrogen | 10 to 14% |
| Nitrogen | 0.1 to 2% |
| Oxygen | 0.05 to 1.5% |
| Sulfur | 0.05 to 6.0% |
| Metals | < 0.1% |
qualification shares
qualification shares are those which are purchased by a person to become the director of the company
Market maker
A market maker is a company, or an individual, that quotes both a buy and a sell price in a financial instrument or commodity held in inventory, hoping to make a profit on the bid-offer spread, or turn.[1] From a market microstructure theory standpoint, market makers are net sellers of an option to be adversely selected at a premium proportional to the trading range at which they are willing to provide liquidity
In currency exchange
Most foreign exchange trading firms are market makers[3] and so are many banks, although not in all currency markets. In foreign exchange (or FX) trading, where most deals are conducted over-the-counter and are, therefore, completely virtual, the market maker sells to and buys from its clients and is compensated by means of price differentials for the service of providing liquidity, reducing transaction costs and facilitating trade. Recent developments in the over-the-counter FX market have permitted even buy-side (non bank participants) virtually to act as market-makers through the advent of high speed/frequency software engines that submit bids and offers outside prices available on other networks or ECN (electronic communication network) where FX is traded.
In stock exchange
Most stock exchanges operate on a "matched bargain" or "order driven" basis. In such a system there are no designated or official market makers, but market makers nevertheless exist. When a buyer's bid price meets a seller's offer price or vice versa, the stock exchange's matching system decides that a deal has been executed.
New York
In the United States, the New York Stock Exchange (NYSE) and American Stock Exchange (AMEX), among others, have Designated Market Makers, formerly known as "specialists", who act as the official market maker for a given security. The market makers provide a required amount of liquidity to the security's market, and take the other side of trades when there are short-term buy-and-sell-side imbalances in customer orders. This helps prevent excess volatility, and in return, the specialist is granted various informational and trade execution advantages.
Other U.S. exchanges, most prominently the NASDAQ Stock Exchange, employ several competing official market makers in a security. These market makers are required to maintain two-sided markets during exchange hours and are obligated to buy and sell at their displayed bids and offers. They typically do not receive the trading advantages a specialist does, but they do get some, such as the ability to naked short a stock, i.e., selling it without borrowing it. In most situations, only official market makers are permitted to engage in naked shorting. Recent changes to the rules have explicitly banned naked shorting by options market makers.[citation needed]
There are over two thousand market makers in the USA[4] and over a hundred in Canada
London
On the London Stock Exchange (LSE) there are official market makers for many securities (but not for shares in the largest and most heavily traded companies, which instead use an automated system called TradElect). Some of the LSE's member firms take on the obligation of always making a two-way price in each of the stocks in which they make markets. Their prices are the ones displayed on the Stock Exchange Automated Quotation (SEAQ) system and it is they who generally deal with brokers buying or selling stock on behalf of clients.
Proponents of the official market making system claim market makers add to the liquidity and depth of the market by taking a short or long position for a time, thus assuming some risk in return for the chance of a small profit. On the LSE one can always buy and sell stock: each stock always has at least two market makers and they are obliged to deal.
In contrast, on smaller, order-driven markets such as the JSE Securities Exchange it can be difficult to determine the buying and selling prices of even a small block of stocks that lack a clear and immediate market value because there are often no buyers or sellers on the order board.
Unofficial market makers are free to operate on order driven markets or, indeed, on the LSE. They do not have the obligation to always be making a two-way price but they do not have the advantage that everyone must deal with them either.
Examples of UK Market makers since Big Bang Day are Peel Hunt LLP, Winterflood Securities [6], Liberum Capital, Shore Capital, Fairfax IS and Altium Securities.
Prior to the Big Bang, jobbers had exclusive rights of market making on the LSE.
How a market maker makes money
A market maker aims to make money by buying stock at a lower price than the price at which they sell it, or selling the stock at a higher price than they buy it back. Ordinarily they can make money in both rising or falling markets, by taking advantage of the difference between "bid" and "offer" prices.
Stock market makers also receive liquidity rebates from electronic communication networks for each share that is sold to or purchased from each posted bid or offer. Conversely, a trader who takes liquidity from a bid or offer posted on an ECN is charged a fee for removing that liquidity.
In currency exchange
Most foreign exchange trading firms are market makers[3] and so are many banks, although not in all currency markets. In foreign exchange (or FX) trading, where most deals are conducted over-the-counter and are, therefore, completely virtual, the market maker sells to and buys from its clients and is compensated by means of price differentials for the service of providing liquidity, reducing transaction costs and facilitating trade. Recent developments in the over-the-counter FX market have permitted even buy-side (non bank participants) virtually to act as market-makers through the advent of high speed/frequency software engines that submit bids and offers outside prices available on other networks or ECN (electronic communication network) where FX is traded.
In stock exchange
Most stock exchanges operate on a "matched bargain" or "order driven" basis. In such a system there are no designated or official market makers, but market makers nevertheless exist. When a buyer's bid price meets a seller's offer price or vice versa, the stock exchange's matching system decides that a deal has been executed.
New York
In the United States, the New York Stock Exchange (NYSE) and American Stock Exchange (AMEX), among others, have Designated Market Makers, formerly known as "specialists", who act as the official market maker for a given security. The market makers provide a required amount of liquidity to the security's market, and take the other side of trades when there are short-term buy-and-sell-side imbalances in customer orders. This helps prevent excess volatility, and in return, the specialist is granted various informational and trade execution advantages.
Other U.S. exchanges, most prominently the NASDAQ Stock Exchange, employ several competing official market makers in a security. These market makers are required to maintain two-sided markets during exchange hours and are obligated to buy and sell at their displayed bids and offers. They typically do not receive the trading advantages a specialist does, but they do get some, such as the ability to naked short a stock, i.e., selling it without borrowing it. In most situations, only official market makers are permitted to engage in naked shorting. Recent changes to the rules have explicitly banned naked shorting by options market makers.[citation needed]
There are over two thousand market makers in the USA[4] and over a hundred in Canada
London
On the London Stock Exchange (LSE) there are official market makers for many securities (but not for shares in the largest and most heavily traded companies, which instead use an automated system called TradElect). Some of the LSE's member firms take on the obligation of always making a two-way price in each of the stocks in which they make markets. Their prices are the ones displayed on the Stock Exchange Automated Quotation (SEAQ) system and it is they who generally deal with brokers buying or selling stock on behalf of clients.
Proponents of the official market making system claim market makers add to the liquidity and depth of the market by taking a short or long position for a time, thus assuming some risk in return for the chance of a small profit. On the LSE one can always buy and sell stock: each stock always has at least two market makers and they are obliged to deal.
In contrast, on smaller, order-driven markets such as the JSE Securities Exchange it can be difficult to determine the buying and selling prices of even a small block of stocks that lack a clear and immediate market value because there are often no buyers or sellers on the order board.
Unofficial market makers are free to operate on order driven markets or, indeed, on the LSE. They do not have the obligation to always be making a two-way price but they do not have the advantage that everyone must deal with them either.
Examples of UK Market makers since Big Bang Day are Peel Hunt LLP, Winterflood Securities [6], Liberum Capital, Shore Capital, Fairfax IS and Altium Securities.
Prior to the Big Bang, jobbers had exclusive rights of market making on the LSE.
How a market maker makes money
A market maker aims to make money by buying stock at a lower price than the price at which they sell it, or selling the stock at a higher price than they buy it back. Ordinarily they can make money in both rising or falling markets, by taking advantage of the difference between "bid" and "offer" prices.
Stock market makers also receive liquidity rebates from electronic communication networks for each share that is sold to or purchased from each posted bid or offer. Conversely, a trader who takes liquidity from a bid or offer posted on an ECN is charged a fee for removing that liquidity.
Mathematical Finance
Mathematical finance is a field of applied mathematics, concerned with financial markets. The subject has a close relationship with the discipline of financial economics, which is concerned with much of the underlying theory. Generally, mathematical finance will derive and extend the mathematical or numerical models suggested by financial economics. Thus, for example, while a financial economist might study the structural reasons why a company may have a certain share price, a financial mathematician may take the share price as a given, and attempt to use stochastic calculus to obtain the fair value of derivatives of the stock (see: Valuation of options).
In terms of practice, mathematical finance also overlaps heavily with the field of computational finance (also known as financial engineering). Arguably, these are largely synonymous, although the latter focuses on application, while the former focuses on modeling and derivation (see: Quantitative analyst). The fundamental theorem of arbitrage-free pricing is one of the key theorems in mathematical finance. Many universities around the world now offer degree and research programs in mathematical finance; see Master of Mathematical Finance.
History
The history of mathematical finance starts with The Theory of Speculation (published 1900) by Louis Bachelier, which discussed the use of Brownian motion to evaluate stock options. However, it hardly caught any attention outside academia.
The first influential work of mathematical finance is the theory of portfolio optimization by Harry Markowitz on using mean-variance estimates of portfolios to judge investment strategies, causing a shift away from the concept of trying to identify the best individual stock for investment. Using a linear regression strategy to understand and quantify the risk (i.e. variance) and return (i.e. mean) of an entire portfolio of stocks and bonds, an optimization strategy was used to choose a portfolio with largest mean return subject to acceptable levels of variance in the return. Simultaneously, William Sharpe developed the mathematics of determining the correlation between each stock and the market. For their pioneering work, Markowitz and Sharpe, along with Merton Miller, shared the 1990 Nobel Memorial Prize in Economic Sciences, for the first time ever awarded for a work in finance.
The portfolio-selection work of Markowitz and Sharpe introduced mathematics to the “black art” of investment management. With time, the mathematics has become more sophisticated. Thanks to Robert Merton and Paul Samuelson, one-period models were replaced by continuous time, Brownian-motion models, and the quadratic utility function implicit in mean–variance optimization was replaced by more general increasing, concave utility functions.[1]
Main article: Black–Scholes
The next major revolution in mathematical finance came with the work of Fischer Black and Myron Scholes along with fundamental contributions by Robert C. Merton, by modeling financial markets with stochastic models. For this M. Scholes and R. Merton were awarded the 1997 Nobel Memorial Prize in Economic Sciences. Black was ineligible for the prize because of his death in 1995.
More sophisticated mathematical models and derivative pricing strategies were then developed but their credibility was damaged by the financial crisis of 2007–2010. Bodies such as the Institute for New Economic Thinking are now attempting to establish more effective theories and methods.[2]
[edit] Criticism
Contemporary practice of mathematical finance has been subjected to criticism from figures within the field notably by Nassim Nicholas Taleb in his book The Black Swan[3] and Paul Wilmott. Taleb claims that the prices of financial assets cannot be characterized by the simple models currently in use, rendering much of current practice at best irrelevant, and, at worst, dangerously misleading. Wilmott and Emanuel Derman published the Financial Modelers' Manifesto in January 2008[4] which addresses some of the most serious concerns
Mathematical finance articles
Mathematical tools
Asymptotic analysis
Calculus
Copulas
Differential equations
Expected value
Ergodic theory
Feynman–Kac formula
Fourier transform
Gaussian copulas
Girsanov's theorem
Itô's lemma
Martingale representation theorem
Mathematical models
Monte Carlo method
Numerical analysis
Real analysis
Partial differential equations
Probability
Probability distributions
Binomial distribution
Log-normal distribution
Quantile functions
Heat equation
Radon–Nikodym derivative
Risk-neutral measure
Stochastic calculus
Brownian motion
Lévy process
Stochastic differential equations
Stochastic volatility
Numerical partial differential equations
Crank–Nicolson method
Finite difference method
Value at risk
Volatility
ARCH model
GARCH model
Derivatives pricing
The Brownian Motion Model of Financial Markets
Rational pricing assumptions
Risk neutral valuation
Arbitrage-free pricing
Futures contract pricing
Options
Put–call parity (Arbitrage relationships for options)
Intrinsic value, Time value
Moneyness
Pricing models
Black–Scholes model
Black model
Binomial options model
Monte Carlo option model
Implied volatility, Volatility smile
SABR Volatility Model
Markov Switching Multifractal
The Greeks
Finite difference methods for option pricing
Vanna Volga method
Trinomial tree
Optimal stopping (Pricing of American options)
Interest rate derivatives
Short rate model
Hull–White model
Cox–Ingersoll–Ross model
Chen model
LIBOR Market Model
Heath–Jarrow–Morton framework
See also
Computational finance
Quantitative Behavioral Finance
Derivative (finance), list of derivatives topics
Modeling and analysis of financial markets
International Swaps and Derivatives Association
Fundamental financial concepts - topics
Model (economics)
List of finance topics
List of economics topics, List of economists
List of accounting topics
Statistical Finance
Brownian model of financial markets
Master of Mathematical Finance
In terms of practice, mathematical finance also overlaps heavily with the field of computational finance (also known as financial engineering). Arguably, these are largely synonymous, although the latter focuses on application, while the former focuses on modeling and derivation (see: Quantitative analyst). The fundamental theorem of arbitrage-free pricing is one of the key theorems in mathematical finance. Many universities around the world now offer degree and research programs in mathematical finance; see Master of Mathematical Finance.
History
The history of mathematical finance starts with The Theory of Speculation (published 1900) by Louis Bachelier, which discussed the use of Brownian motion to evaluate stock options. However, it hardly caught any attention outside academia.
The first influential work of mathematical finance is the theory of portfolio optimization by Harry Markowitz on using mean-variance estimates of portfolios to judge investment strategies, causing a shift away from the concept of trying to identify the best individual stock for investment. Using a linear regression strategy to understand and quantify the risk (i.e. variance) and return (i.e. mean) of an entire portfolio of stocks and bonds, an optimization strategy was used to choose a portfolio with largest mean return subject to acceptable levels of variance in the return. Simultaneously, William Sharpe developed the mathematics of determining the correlation between each stock and the market. For their pioneering work, Markowitz and Sharpe, along with Merton Miller, shared the 1990 Nobel Memorial Prize in Economic Sciences, for the first time ever awarded for a work in finance.
The portfolio-selection work of Markowitz and Sharpe introduced mathematics to the “black art” of investment management. With time, the mathematics has become more sophisticated. Thanks to Robert Merton and Paul Samuelson, one-period models were replaced by continuous time, Brownian-motion models, and the quadratic utility function implicit in mean–variance optimization was replaced by more general increasing, concave utility functions.[1]
Main article: Black–Scholes
The next major revolution in mathematical finance came with the work of Fischer Black and Myron Scholes along with fundamental contributions by Robert C. Merton, by modeling financial markets with stochastic models. For this M. Scholes and R. Merton were awarded the 1997 Nobel Memorial Prize in Economic Sciences. Black was ineligible for the prize because of his death in 1995.
More sophisticated mathematical models and derivative pricing strategies were then developed but their credibility was damaged by the financial crisis of 2007–2010. Bodies such as the Institute for New Economic Thinking are now attempting to establish more effective theories and methods.[2]
[edit] Criticism
Contemporary practice of mathematical finance has been subjected to criticism from figures within the field notably by Nassim Nicholas Taleb in his book The Black Swan[3] and Paul Wilmott. Taleb claims that the prices of financial assets cannot be characterized by the simple models currently in use, rendering much of current practice at best irrelevant, and, at worst, dangerously misleading. Wilmott and Emanuel Derman published the Financial Modelers' Manifesto in January 2008[4] which addresses some of the most serious concerns
Mathematical finance articles
Mathematical tools
Asymptotic analysis
Calculus
Copulas
Differential equations
Expected value
Ergodic theory
Feynman–Kac formula
Fourier transform
Gaussian copulas
Girsanov's theorem
Itô's lemma
Martingale representation theorem
Mathematical models
Monte Carlo method
Numerical analysis
Real analysis
Partial differential equations
Probability
Probability distributions
Binomial distribution
Log-normal distribution
Quantile functions
Heat equation
Radon–Nikodym derivative
Risk-neutral measure
Stochastic calculus
Brownian motion
Lévy process
Stochastic differential equations
Stochastic volatility
Numerical partial differential equations
Crank–Nicolson method
Finite difference method
Value at risk
Volatility
ARCH model
GARCH model
Derivatives pricing
The Brownian Motion Model of Financial Markets
Rational pricing assumptions
Risk neutral valuation
Arbitrage-free pricing
Futures contract pricing
Options
Put–call parity (Arbitrage relationships for options)
Intrinsic value, Time value
Moneyness
Pricing models
Black–Scholes model
Black model
Binomial options model
Monte Carlo option model
Implied volatility, Volatility smile
SABR Volatility Model
Markov Switching Multifractal
The Greeks
Finite difference methods for option pricing
Vanna Volga method
Trinomial tree
Optimal stopping (Pricing of American options)
Interest rate derivatives
Short rate model
Hull–White model
Cox–Ingersoll–Ross model
Chen model
LIBOR Market Model
Heath–Jarrow–Morton framework
See also
Computational finance
Quantitative Behavioral Finance
Derivative (finance), list of derivatives topics
Modeling and analysis of financial markets
International Swaps and Derivatives Association
Fundamental financial concepts - topics
Model (economics)
List of finance topics
List of economics topics, List of economists
List of accounting topics
Statistical Finance
Brownian model of financial markets
Master of Mathematical Finance
Trade Weighted US dollar Index
The Trade Weighted US dollar Index, also known as the broad index, is a measure of the value of the US Dollar relative to other world currencies. It is similar to the US Dollar Index in that its numerical value is determined as a weighted average of the price of various currencies relative to the dollar, however it differs in which currencies are used and how their relative values are weighted.
HistoryThe trade weighted dollar index was introduced in 1998 for two primary reasons. The first being the introduction of the euro, which eliminated several of the currencies in the standard dollar index; the second being to keep pace with new developments in US trade.[1]
[edit] Included currenciesIn the standard US Dollar Index, a significant weight is given to the euro. In order to more accurately reflect the strength of the dollar relative to other world currencies, the Federal Reserve created the Trade Weighted US Dollar Index,[2] which includes a bigger collection of currencies than the US Dollar Index. The regions included are:
Europe (euro countries)
Canada
Japan
Mexico
China
United Kingdom
Taiwan
Korea
Singapore
Hong Kong
Malaysia
Brazil
Switzerland
Thailand
Philippines
Australia
Indonesia
India
Israel
Saudi Arabia
Russia
Sweden
Argentina
Venezuela
Chile
Colombia
HistoryThe trade weighted dollar index was introduced in 1998 for two primary reasons. The first being the introduction of the euro, which eliminated several of the currencies in the standard dollar index; the second being to keep pace with new developments in US trade.[1]
[edit] Included currenciesIn the standard US Dollar Index, a significant weight is given to the euro. In order to more accurately reflect the strength of the dollar relative to other world currencies, the Federal Reserve created the Trade Weighted US Dollar Index,[2] which includes a bigger collection of currencies than the US Dollar Index. The regions included are:
Europe (euro countries)
Canada
Japan
Mexico
China
United Kingdom
Taiwan
Korea
Singapore
Hong Kong
Malaysia
Brazil
Switzerland
Thailand
Philippines
Australia
Indonesia
India
Israel
Saudi Arabia
Russia
Sweden
Argentina
Venezuela
Chile
Colombia
U.S. Dollar Index
The US Dollar Index (USDX) is an index (or measure) of the value of the United States dollar relative to a basket of foreign currencies.
It is a weighted geometric mean of the dollar's value compared only with
Euro (EUR), 58.6% weight
Japanese Yen (JPY) 12.6% weight
Pound sterling (GBP), 11.9% weight
Canadian dollar (CAD), 9.1% weight
Swedish krona (SEK), 4.2% weight and
Swiss franc (CHF) 3.6% weight
USDX goes up when the US dollar gains "strength" (value) when compared to other currencies.
USDX started in March 1973, soon after the dismantling of the Bretton Woods system. At its start, the value of the US Dollar Index was 100.000. It has since traded as high as 148.1244 in February 1985, and as low as 70.698 on March 16, 2008, the lowest since its inception in 1973.
The makeup of the "basket" has been altered only once, when several European currencies were subsumed by the Euro at the start of 1999.
It is a weighted geometric mean of the dollar's value compared only with
Euro (EUR), 58.6% weight
Japanese Yen (JPY) 12.6% weight
Pound sterling (GBP), 11.9% weight
Canadian dollar (CAD), 9.1% weight
Swedish krona (SEK), 4.2% weight and
Swiss franc (CHF) 3.6% weight
USDX goes up when the US dollar gains "strength" (value) when compared to other currencies.
USDX started in March 1973, soon after the dismantling of the Bretton Woods system. At its start, the value of the US Dollar Index was 100.000. It has since traded as high as 148.1244 in February 1985, and as low as 70.698 on March 16, 2008, the lowest since its inception in 1973.
The makeup of the "basket" has been altered only once, when several European currencies were subsumed by the Euro at the start of 1999.
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Wednesday, 17 August 2011
Gold reserve
A gold reserve is the gold held by a central bank or nation intended as a store of value and as a guarantee to redeem promises to pay depositors, note holders (e.g., paper money), or trading peers, or to secure a currency.
At the end of 2004, central banks and investment funds held 19% of all above-ground gold as bank reserve assets. It has been estimated that all the gold mined by the end of 2009 totaled 165,000 tonnes.
The IMF maintains an internal book value of its gold that is far below market value. In 2000, this book value was SDR 35, or about US$47 per troy ounce. An attempt to revalue the gold reserve to today's value has met resistance for different reasons. For example, Canada is against the idea of revaluing the reserve, as it may be a prelude to selling the gold on the open market and therefore depressing gold prices
The gold listed for each of the countries in the table may not be physically stored in the country listed, as central banks generally have not allowed independent audits of their reserves.
Gold Holdings Corp. a publicly listed gold company estimates that the amount of in-ground verified gold resources currently controlled by publicly traded gold mining companies is roughly 50,000 tonnes.
At the end of 2004, central banks and investment funds held 19% of all above-ground gold as bank reserve assets. It has been estimated that all the gold mined by the end of 2009 totaled 165,000 tonnes.
IMF gold holdings
As of June 2009, the International Monetary Fund held 3,217 tonnes (103.4 million oz.) of gold, which had been constant for several years. In Fall 2009, the IMF announced that it will sell one eighth of its holdings, a maximum of 12,965,649 fine troy ounces (403.3 t) based on a new income model agreed upon in April 2008, and subsequently announced the sale of 200 tonnes to India, 10 tonnes to Sri Lanka, a further 10 Metric tonnes of Gold was also sold to Bangladesh Bank in September 2010 and 2 tonnes to the Bank of Mauritius. These gold sales were conducted in stages at prevailing market prices.The IMF maintains an internal book value of its gold that is far below market value. In 2000, this book value was SDR 35, or about US$47 per troy ounce. An attempt to revalue the gold reserve to today's value has met resistance for different reasons. For example, Canada is against the idea of revaluing the reserve, as it may be a prelude to selling the gold on the open market and therefore depressing gold prices
Officially reported gold holdings
Foreign currency reserves and gold minus external debt based on 2010 data from CIA Fact book
Gold reserves per capita
The International Monetary Fund regularly maintains statistics of national assets as reported by various countries. These data are used by the World Gold Council to periodically rank and report the gold holding of countries and official organizations. The gold listed for each of the countries in the table may not be physically stored in the country listed, as central banks generally have not allowed independent audits of their reserves.
World official gold holding (December 2010) | |||
Gold (tonnes) | |||
- | 10,792.6 | 60.7% | |
1 | 8,133.5 | 73.9% | |
2 | 3,401.8 | 70.3% | |
3 | 2,846.7 | - | |
4 | 2,451.8 | 68.6% | |
5 | 2,435.4 | 67.2% | |
6 | 1,054.1 | 1.7% | |
7 | 1,040.1 | 16.4% | |
8 | 775.2 | 6.7% | |
9 | 765.2 | 3.0% | |
10 | 675 | 57.5% | |
11 | 614.8 | 8.1% | |
12 | 522.7 | 27.9% | |
13 | 466.9 | 4.6% | |
14 | 421.6 | 81.1% | |
15 | 401.1 | 52.4% | |
16 | 322.9 | 3.0% | |
17 | 310.3 | 16.8% | |
18 | 300.0 | - | |
19 | 286.8 | 27.6% | |
20 | 281.6 | 38.6% | |
21 | 280.0 | 56.2% | |
22 | 227.5 | 36.8% | |
23 | 184.4 | 19.2% | |
24 | 175.9 | 14.0% | |
25 | 173.6 | 4.5% | |
26 | 143.8 | 5.6% | |
27 | 127.4 | 2.5% | |
28 | 125.7 | 11.1% | |
29 | 124.9 | 12.2% | |
30 | 120.0 | - | |
31 | 116.1 | 6.0% | |
32 | 111.7 | 78.7% | |
33 | 103.7 | 9.1% | |
34 | 102.9 | 4.5% | |
35 | 100.1[12] | 3.8%[12] | |
36 | 99.5 | 2.5% | |
37 | 79.9 | 8.1% | |
38 | 79.0 | 13.5% | |
39 | 75.6 | 8.7% | |
40 | 73.1 | 3.6% | |
41 | 67.3 | 10.0% | |
42 | 66.5 | 3.3% | |
43 | 54.7 | 4.5% | |
44 | 49.1 | 20.6% | |
45 | 39.9 | 9.9% | |
46 | 36.5 | 12.2% | |
47 | 36.4 | 1.5% | |
48 | 32 | 24.5% | |
49 | 34.7 | 3.6% | |
50 | 33.6 | 0.5% | |
51 | 31.8 | 65.4% | |
53 | 28.3 | 13.4% | |
53 | 27.2 | 3.5% | |
54 | 26.3 | 31.0% | |
55 | 25.8 | - | |
56 | 22.0 | 4.2% | |
57 | 21.4 | - | |
58 | 17.5 | 11.9% | |
59 | 14.4 | 0.2% | |
60 | 13.9 | 50.8% | |
61 | 13.5 | 5.2% | |
62 | 13.1 | 4.2% | |
63 | 13.1 | 36.3% | |
64 | 12.8 | 4.3% | |
65 | 12.7 | 1.2% | |
66 | 12.4 | 14.4% | |
67 | 12.4 | 2.1% | |
68 | 8.8 | 36.5% | |
69 | 7.7 | 4.0% | |
70 | 7.3 | 10.6% | |
71 | 7.1 | 2.3% | |
72 | 6.9 | 5.3% | |
73 | 6.9 | 1.1% | |
74 | 6.8 | 12.7% | |
75 | 6.8 | - | |
76 | 6.0 | 11.8% | |
77 | 5.8 | 3.8% | |
78 | 4.7 | - | |
79 | 3.9 | 6.8% | |
80 | 3.4 | 0.2% | |
81 | 3.3 | - | |
82 | 3.2 | 13.4% | |
83 | 3.1 | 17.7% | |
84 | 3.1 | 0.3% | |
85 | 2.6 | 6.5% | |
86 | 2.2 | 11.7% | |
87 | 2.1 | 0.0% | |
88 | 2.0 | 11.4% | |
89 | 2.0 | 1.6% | |
90 | 2.0 | 2.9% | |
91 | 1.9 | 0.8% | |
92 | 1.6 | 2.8% | |
93 | 1.6 | 1.1% | |
94 | 0.9 | 1.2% | |
95 | 0.9 | 2.4% | |
96 | 0.7 | - | |
97 | 0.7 | 0.7% | |
98 | 0.6 | 1.0% | |
99 | 0.4 | 0.8% | |
100 | 0.4 | 6.2% | |
101 | 0.3 | 8.4% | |
102 | 0.3 | 2.4% | |
103 | 0.3 | 0.4% | |
104 | 0.3 | 0.1% | |
105 | 0.2 | - | |
106 | 0.2 | 0.3% | |
107 | 0.2 | 0.0% | |
108 | 0.2 | 1.6% | |
109 | 0.1 | 0.1% | |
110 | 0.0 | 0.1% | |
111 | 0.0 | 0.5% | |
112 | 0.0 | 0.0% | |
113 | 0.0 | - | |
114 | 0.0 | 0.0% | |
- | World | 30,562.5 | - |
Privately held gold
As of October 2009, gold exchange-traded funds held 1,750 tonnes of gold for private and institutional investors.Gold Holdings Corp. a publicly listed gold company estimates that the amount of in-ground verified gold resources currently controlled by publicly traded gold mining companies is roughly 50,000 tonnes.
Privately held gold (May 2011) | |||
1 | 1.210,75 | ||
2 | 259,79 | ||
3 | ZKB Physical Gold | 195,53 | |
4 | COMEX Gold Trust | 137,61 | |
5 | Julius Baer Physical Gold Fund | 93,50 | |
6 | NewGold ETF | 47,75 | |
7 | 32,27 | ||
8 | ETFS Physical Swiss Gold Shares | 27,97 | |
9 | Allocated storage | 21,36 | |
10 | Allocated storage | 17,99 | |
World gold holdings
World gold holdings (2008) (Source: World Gold Council) | |
Holding | Percentage |
Jewelry | 52% |
Central banks | 18% |
Investment (bars, coins) | 16% |
Industrial | 12% |
Unaccounted | 2% |
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