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Economic forecasting is the process of making predictions about the economy. Forecasts can be carried out at a high level of aggregation—for example for GDP, inflation, unemployment or the fiscal deficit—or at a more disaggregated level, for specific sectors of the economy or even specific firms.
Financial modeling is the task of building an abstract representation (a model) of a real world financial situation. [1] This is a mathematical model designed to represent (a simplified version of) the performance of a financial asset or portfolio of a business, project, or any other investment.
The 2014 AP Chemistry exam was the first administration of a redesigned test as a result of a redesigning of the AP Chemistry course. The exam format is now different from the previous years, with 60 multiple choice questions (now with only four answer choices per question), 3 long free response questions, and 4 short free response questions.
Major topics include measurement of economic performance, national income and price determination, fiscal and monetary policy, and international economics and growth. AP Macroeconomics is frequently taught in conjunction with (and, in some cases, in the same year as) AP Microeconomics as part of a comprehensive AP Economics curriculum, although ...
Blue Chip Economic Indicators is a monthly survey and associated publication by Wolters Kluwer collecting macroeconomic forecasts related to the economy of the United States. [1] The survey polls America's top business economists, collecting their forecasts of U.S. economic growth, inflation, interest rates, and a host of other critical ...
The Taylor rule is a monetary policy targeting rule. The rule was proposed in 1992 by American economist John B. Taylor [1] for central banks to use to stabilize economic activity by appropriately setting short-term interest rates. [2]
The Conference Board Leading Economic Index is an American economic leading indicator intended to forecast future economic activity. It is calculated by The Conference Board , a non-governmental organization , which determines the value of the index from the values of ten key variables .
Temporal difference (TD) learning refers to a class of model-free reinforcement learning methods which learn by bootstrapping from the current estimate of the value function. These methods sample from the environment, like Monte Carlo methods , and perform updates based on current estimates, like dynamic programming methods.