Profit At Risk
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Profit At Risk
Profit-at-Risk (PaR) is a risk management quantity most often used for electricity portfolios that contain some mixture of generation assets, trading contracts and end-user consumption. It is used to provide a measure of the downside risk to profitability of a portfolio of physical and financial assets, analysed by time periods in which the energy is delivered. For example, the expected profitability and associated downside risk (PaR) might be calculated and monitored for each of the forward looking 24 months. The measure considers both price risk and volume risk (e.g. due to uncertainty in electricity generation volumes or consumer demand). Mathematically, the PaR is the quantile of the profit distribution of a portfolio. Since weather related volume risk drivers can be represented in the form of historical weather records over many years, a Monte-Carlo simulation approach is often used. Example If the confidence interval for evaluating the PaR is 95%, there is a 5% probabilit ...
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Price Risk
Market risk is the risk of losses in positions arising from movements in market variables like prices and volatility. There is no unique classification as each classification may refer to different aspects of market risk. Nevertheless, the most commonly used types of market risk are: * '' Equity risk'', the risk that stock or stock indices (e.g. Euro Stoxx 50, etc.) prices or their implied volatility will change. * ''Interest rate risk'', the risk that interest rates (e.g. Libor, Euribor, etc.) or their implied volatility will change. * '' Currency risk'', the risk that foreign exchange rates (e.g. EUR/USD, EUR/GBP, etc.) or their implied volatility will change. * '' Commodity risk'', the risk that commodity prices (e.g. corn, crude oil) or their implied volatility will change. * ''Margining risk'' results from uncertain future cash outflows due to margin calls covering adverse value changes of a given position. * '' Shape risk'' * ''Holding period risk'' * '' Basis risk ...
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Volume Risk
Volume risk is a commodity risk which refers to the fact that a player in the commodity market has uncertain quantities of consumption or sourcing, i.e. production of the respective commodity. Examples of other circumstances which can cause large deviations from a volume forecast are weather (e.g. temperature-changes for gas consumption), the plant-availability, the collective customer outrage, but also regulatory interventions. Another relevant cause of volatility risk in volumes and (or) prices of commodities is the financial investment in options or future contracts related to a commodity, which is achieved with the purpose of speculating, rather than hedging in order to reduce the risk of adverse price movements in assets. Example An electricity retailer cannot accurately predict the demand of all house holds for a given time which is why the producer cannot forecast the precise time that a power plant will provide more electricity that consumed, even if the plant always de ...
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Monte-Carlo Simulation
Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. The underlying concept is to use randomness to solve problems that might be deterministic system, deterministic in principle. They are often used in physics, physical and mathematics, mathematical problems and are most useful when it is difficult or impossible to use other approaches. Monte Carlo methods are mainly used in three problem classes: optimization, numerical integration, and generating draws from a probability distribution. In physics-related problems, Monte Carlo methods are useful for simulating systems with many coupling (physics), coupled degrees of freedom, such as fluids, disordered materials, strongly coupled solids, and cellular structures (see cellular Potts model, interacting particle systems, McKean–Vlasov processes, kinetic theory of gases, kinetic models of gases). Other examples include modeling ...
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Electricity Market
In a broad sense, an electricity market is a system that facilitates the exchange of electricity-related goods and services. During more than a century of evolution of the electric power industry, the economics of the electricity markets had undergone enormous changes for reasons ranging from the technological advances on supply and demand sides to politics and ideology. A restructuring of electric power industry at the turn of the 21st century involved replacing the vertically integrated and tightly regulated "traditional" electricity market with multiple competitive markets for electricity generation, transmission, distribution, and retailing. The traditional and competitive market approaches loosely correspond to two visions of industry: the deregulation was transforming electricity from a public service (like sewerage) into a tradable good (like crude oil). As of 2020s, the traditional markets are still common in some regions, including large parts of the United Stat ...
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Value At Risk
Value at risk (VaR) is a measure of the risk of loss for investments. It estimates how much a set of investments might lose (with a given probability), given normal market conditions, in a set time period such as a day. VaR is typically used by firms and regulators in the financial industry to gauge the amount of assets needed to cover possible losses. For a given portfolio, time horizon, and probability ''p'', the ''p'' VaR can be defined informally as the maximum possible loss during that time after excluding all worse outcomes whose combined probability is at most ''p''. This assumes mark-to-market pricing, and no trading in the portfolio. For example, if a portfolio of stocks has a one-day 95% VaR of $1 million, that means that there is a 0.05 probability that the portfolio will fall in value by more than $1 million over a one-day period if there is no trading. Informally, a loss of $1 million or more on this portfolio is expected on 1 day out of 20 days (because of 5% proba ...
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Earnings At Risk
Earnings at risk (EaR) and the related cash flow at risk (CFaR) Earnings at Risk
bloomsburycollections.com are measures reflecting the potential impact of market risk on the income statement and cash flow statement respectively, and hence the risk to the institution's return on assets and, ultimately,
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Liquidity At Risk
The Liquidity-at-Risk (short: LaR) is a measure of the liquidity risk Liquidity risk is a financial risk that for a certain period of time a given financial asset, security or commodity cannot be traded quickly enough in the market without impacting the market price. Types Market liquidity – An asset cannot be so ... exposure of a financial portfolio. It may be defined as the net liquidity drain which can occur in the portfolio in a given risk scenario. If the Liquidity at Risk is greater than the portfolio's current liquidity position then the portfolio may face a liquidity shortfall. Liquidity at Risk is different from other measures of risk based on total loss, as it is based on an estimate of cash losses, or liquidity outflows, as opposed to total loss. Definition The Liquidity-at-Risk of a financial portfolio associated with a stress scenario is the net liquidity outflow resulting from this stress scenario: The liquidity shortfall in a stress scenario is thus g ...
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Margin At Risk
The Margin-at-Risk (MaR) is a quantity used to manage short-term liquidity risks due to variation of margin requirements, i.e. it is a financial risk occurring when trading commodities. It is similar to the Value-at-Risk (VaR), but instead of simulating EBIT it returns a quantile of the (expected) cash flow distribution. To do so, MaR requires (1) a currency, (2) a confidence level (e.g. 90%) and (3) a holding period (e.g. 3 days). The idea is that a given portfolio loss will be compensated by a margin call by the same amount. The MaR quantifies the "worst case" margin-call and is only driven by market prices. See also * Liquidity at risk * Value at risk * Profit at risk * Earnings at risk Earnings at risk (EaR) and the related cash flow at risk (CFaR) Earnings at Ris ...
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Algorithmic Trading
Algorithmic trading is a method of executing orders using automated pre-programmed trading instructions accounting for variables such as time, price, and volume. This type of trading attempts to leverage the speed and computational resources of computers relative to human traders. In the twenty-first century, algorithmic trading has been gaining traction with both retail and institutional traders. It is widely used by investment banks, pension funds, mutual funds, and hedge funds that may need to spread out the execution of a larger order or perform trades too fast for human traders to react to. A study in 2019 showed that around 92% of trading in the Forex market was performed by trading algorithms rather than humans. The term algorithmic trading is often used synonymously with automated trading system. These encompass a variety of trading strategies, some of which are based on formulas and results from mathematical finance, and often rely on specialized software. Examples o ...
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Value At Risk
Value at risk (VaR) is a measure of the risk of loss for investments. It estimates how much a set of investments might lose (with a given probability), given normal market conditions, in a set time period such as a day. VaR is typically used by firms and regulators in the financial industry to gauge the amount of assets needed to cover possible losses. For a given portfolio, time horizon, and probability ''p'', the ''p'' VaR can be defined informally as the maximum possible loss during that time after excluding all worse outcomes whose combined probability is at most ''p''. This assumes mark-to-market pricing, and no trading in the portfolio. For example, if a portfolio of stocks has a one-day 95% VaR of $1 million, that means that there is a 0.05 probability that the portfolio will fall in value by more than $1 million over a one-day period if there is no trading. Informally, a loss of $1 million or more on this portfolio is expected on 1 day out of 20 days (because of 5% proba ...
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Mathematical Finance
Mathematical finance, also known as quantitative finance and financial mathematics, is a field of applied mathematics, concerned with mathematical modeling of financial markets. In general, there exist two separate branches of finance that require advanced quantitative techniques: derivatives pricing on the one hand, and risk and portfolio management on the other. Mathematical finance overlaps heavily with the fields of computational finance and financial engineering. The latter focuses on applications and modeling, often by help of stochastic asset models, while the former focuses, in addition to analysis, on building tools of implementation for the models. Also related is quantitative investing, which relies on statistical and numerical models (and lately machine learning) as opposed to traditional fundamental analysis when managing portfolios. French mathematician Louis Bachelier's doctoral thesis, defended in 1900, is considered the first scholarly work on mathematical fina ...
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