Profit at risk

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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). [1] 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.

Risk management Set of measures for the systematic identification, analysis, assessment, monitoring and control of risks

Risk management is the identification, evaluation, and prioritization of risks followed by coordinated and economical application of resources to minimize, monitor, and control the probability or impact of unfortunate events or to maximize the realization of opportunities.

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, the plant-availability, the collective customer outrage, but also regulatory interventions.

Contents

Example

If the confidence interval for evaluating the PaR is 95%, there is a 5% probability that due to changing commodity volumes and prices, the profit outcome for a specific period (e.g. December next year) will fall short of the expected profit result by more than the PaR value.

Note that the concept of a set 'holding period' does not apply since the period is always up until the realisation of the profit outcome through the delivery of energy. That is the holding period is different for each of the specific delivery time periods being analysed e.g. it might be six months for December and therefore seven months for January.

History

The PaR measure was originally pioneered at Norsk Hydro in Norway as part of an initiative to prepare for deregulation of the electricity market. Petter Longva and Greg Keers co-authored a paper "Risk Management in the Electricity Industry" (IAEE 17th Annual International Conference, 1994) which introduced the PaR method. This led to it being adopted as the basis for electricity market risk management at Norsk Hydro and later by most of the other electricity generating utilities in the Nordic region. The approach was based on monte-carlo simulations of paired reservoir inflow and spot price outcomes to produce a distribution of expected profit in future reporting periods. This tied directly with the focus of management reporting on profitability of operations, unlike the Value-at-Risk approach that had been pioneered by JP Morgan for banks focused on their balance sheet risks.

Critics

As is the case with Value at Risk , for risk measures like the PaR, Earnings-at-Risk (EaR), the Liquidity-at-Risk (LaR) or the Margin-at-Risk (MaR), the exact (algorithmic) implementation rule vary from firm to firm. [2]

The Liquidity-at-Risk is a quantity to measure financial risks and is the maximum net liquidity drain relative to the expected liquidity position which should not be exceeded at a given confidence level. The LaR is analog to the Value-at-Risk (VaR) where a quantile of the EBIT-distribution is considered, however it does take stochastic cash flows into account.

The Margin-at-Risk 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. Similar to the Value-at-Risk (VaR), but instead of the EBIT it is a quantile of the (expected) cash flow distribution.

Algorithmic trading is a method of executing a large order using automated pre-programmed trading instructions accounting for variables such as time, price, and volume to send small slices of the order out to the market over time. They were developed so that traders do not need to constantly watch a stock and repeatedly send those slices out manually. Popular "algos" include Percentage of Volume, Pegged, VWAP, TWAP, Implementation Shortfall, Target Close. In the twenty-first century, algorithmic trading has been gaining traction with both retail and institutional traders. Algorithmic trading is not an attempt to make a trading profit. It is simply a way to minimize the cost, market impact and risk in execution of an order. It is widely used by investment banks, pension funds, mutual funds, and hedge funds because these institutional traders need to execute large orders in markets that cannot support all of the size at once.

See also

Related Research Articles

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References

  1. "What is Profit-at-Risk (PaR)?". .arbitrage-trading.com. ART Ltd. Retrieved 8 January 2016.
  2. Burger, Markus. "Risk measures for large portfolios and their applications in energy trading" (PDF). risklab.es. EnBW Energie Baden-Württemberg AG. Retrieved 8 January 2016.