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That is, it is the risk of the actual return being below the expected return, or the uncertainty about the magnitude of that difference. [1] [2] Risk measures typically quantify the downside risk, whereas the standard deviation (an example of a deviation risk measure) measures both the upside and downside risk
Risk is the lack of certainty about the outcome of making a particular choice. Statistically, the level of downside risk can be calculated as the product of the probability that harm occurs (e.g., that an accident happens) multiplied by the severity of that harm (i.e., the average amount of harm or more conservatively the maximum credible amount of harm).
In particular, control self-assessment may understate risk by not identifying extreme downside risk. An extreme downside risk is a highly improbable event that would have catastrophic consequences if it occurred. These risks should have a high overall risk score (generally calculated as a product of the probability of a risk occurring and the ...
The covariance matrix can be used to compute portfolio variance. RiskMetrics assumes that the market is driven by risk factors with observable covariance. The risk factors are represented by time series of prices or levels of stocks, currencies, commodities, and interest rates.
The Sortino ratio measures the risk-adjusted return of an investment asset, portfolio, or strategy. [1] It is a modification of the Sharpe ratio but penalizes only those returns falling below a user-specified target or required rate of return, while the Sharpe ratio penalizes both upside and downside volatility equally.
The apportioning risk perspective can also be used to as a factor in the transition of employment status, only if the strength of downside risk aversion exceeds the strength of risk aversion. [33] If using the behavioural approach to model an individual’s decision on their employment status there must be more variables than risk aversion and ...
The comparison of upside to downside risk is necessary because “modern portfolio theory measures risk in terms of standard deviation of asset returns, which treats both positive and negative deviations from expected returns as risk.” [1] In other words, regular beta measures both upside and downside risk.
The goal is to maximize expected returns while ensuring that the portfolio's risk (e.g., variance or downside risk) stays within acceptable levels with a certain probability. This approach allows investors to consider the uncertainty in asset returns and make more informed investment decisions. [3]