Feature learningIn machine learning, feature learning or representation learning is a set of techniques that allows a system to automatically discover the representations needed for feature detection or classification from raw data. This replaces manual feature engineering and allows a machine to both learn the features and use them to perform a specific task. Feature learning is motivated by the fact that machine learning tasks such as classification often require input that is mathematically and computationally convenient to process.
Operational riskOperational risk is the risk of losses caused by flawed or failed processes, policies, systems or events that disrupt business operations. Employee errors, criminal activity such as fraud, and physical events are among the factors that can trigger operational risk. The process to manage operational risk is known as operational risk management.
Substantia nigraThe substantia nigra (SN) is a basal ganglia structure located in the midbrain that plays an important role in reward and movement. Substantia nigra is Latin for "black substance", reflecting the fact that parts of the substantia nigra appear darker than neighboring areas due to high levels of neuromelanin in dopaminergic neurons. Parkinson's disease is characterized by the loss of dopaminergic neurons in the substantia nigra pars compacta.
Risk premiumA risk premium is a measure of excess return that is required by an individual to compensate being subjected to an increased level of risk. It is used widely in finance and economics, the general definition being the expected risky return less the risk-free return, as demonstrated by the formula below. Where is the risky expected rate of return and is the risk-free return. The inputs for each of these variables and the ultimate interpretation of the risk premium value differs depending on the application as explained in the following sections.
Value at riskValue at risk (VaR) is a measure of the risk of loss of investment/Capital. 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.
Prefrontal cortexIn mammalian brain anatomy, the prefrontal cortex (PFC) covers the front part of the frontal lobe of the cerebral cortex. The PFC contains the Brodmann areas BA8, BA9, BA10, BA11, BA12, BA13, BA14, BA24, BA25, BA32, BA44, BA45, BA46, and BA47. The basic activity of this brain region is considered to be orchestration of thoughts and actions in accordance with internal goals. Many authors have indicated an integral link between a person's will to live, personality, and the functions of the prefrontal cortex.
Foreign exchange riskForeign exchange risk (also known as FX risk, exchange rate risk or currency risk) is a financial risk that exists when a financial transaction is denominated in a currency other than the domestic currency of the company. The exchange risk arises when there is a risk of an unfavourable change in exchange rate between the domestic currency and the denominated currency before the date when the transaction is completed. Foreign exchange risk also exists when the foreign subsidiary of a firm maintains financial statements in a currency other than the domestic currency of the consolidated entity.
Functional magnetic resonance imagingFunctional magnetic resonance imaging or functional MRI (fMRI) measures brain activity by detecting changes associated with blood flow. This technique relies on the fact that cerebral blood flow and neuronal activation are coupled. When an area of the brain is in use, blood flow to that region also increases. The primary form of fMRI uses the blood-oxygen-level dependent (BOLD) contrast, discovered by Seiji Ogawa in 1990.
Least squaresThe method of least squares is a standard approach in regression analysis to approximate the solution of overdetermined systems (sets of equations in which there are more equations than unknowns) by minimizing the sum of the squares of the residuals (a residual being the difference between an observed value and the fitted value provided by a model) made in the results of each individual equation. The most important application is in data fitting.
Risk aversionIn economics and finance, risk aversion is the tendency of people to prefer outcomes with low uncertainty to those outcomes with high uncertainty, even if the average outcome of the latter is equal to or higher in monetary value than the more certain outcome. Risk aversion explains the inclination to agree to a situation with a more predictable, but possibly lower payoff, rather than another situation with a highly unpredictable, but possibly higher payoff.
