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Registered Representative

A registered representative (RR) is a person who works for a client-facing financial firm such as a brokerage company and serves as a representative for clients who are trading investment products and securities. Registered representatives may be employed as brokers, financial advisors, or portfolio managers.Registered representatives must pass licensing tests and are regulated by the Financial Industry Regulatory Authority (FINRA) and the Securities and Exchange Commission (SEC). RRs must furthermore adhere to the suitability standard. An investment must meet the suitability requirements outlined in FINRA Rule 2111 prior to being recommended by a firm to an investor. The following question must be answered affirmatively: "Is this investment appropriate for my client?"

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Active Management

The term active management means that an investor, a professional money manager, or a team of professionals is tracking the performance of an investment portfolio and making buy, hold, and sell decisions about the assets in it. The goal of any investment manager is to outperform a designated benchmark while simultaneously accomplishing one or more additional goals such as managing risk, limiting tax consequences, or adhering to environmental, social, and governance (ESG) standards for investing. Active managers may differ from other is how they accomplish some of these goals.For example, active managers may rely on investment analysis, research, and forecasts, which can include quantitative tools, as well as their own judgment and experience in making decisions on which assets to buy and sell. Their approach may be strictly algorithmic, entirely discretionary, or somewhere in between.By contrast, passive management, sometimes known as indexing, follows simple rules that try to track an index or other benchmark by replicating it.

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Confidence Interval

A confidence interval, in statistics, refers to the probability that a population parameter will fall between a set of values for a certain proportion of times. Analysts often use confidence intervals that contain either 95% or 99% of expected observations. Thus, if a point estimate is generated from a statistical model of 10.00 with a 95% confidence interval of 9.50 - 10.50, it can be inferred that there is a 95% probability that the true value falls within that range.Statisticians and other analysts use confidence intervals to understand the statistical significance of their estimations, inferences, or predictions. If a confidence interval contains the value of zero (or some other null hypothesis), then one cannot satisfactorily claim that a result from data generated by testing or experimentation is to be attributable to a specific cause rather than chance.