Explanations of "Gold" investment-related terms A to Z

A reversal is a change in the direction in which an asset is going. Reversals can be extremely important for gold and silver investors and traders s they might signify a change in the current trend. At the same time, the analysis of reversals is not limited to price itself. The reversals can take the form of a shooting star candlestick, but there are also other ways in which the price can reverse. Most of them, however, are confirmed by high volume readings.

The term “risk premium” refers to the difference between the higher interest rates that riskier investments must pay to attract investors and the interest rate of the risk-free investment. Thus, it is the return in excess of the risk-free rate of return than an investment is expected to yield. It is a compensation for investors to bear more risk and hold the risky asset rather than the risk-free asset. The risk premium is positive, since people are generally risk averse, i.e. they dislike risk. The risk premium explains why, for example, stocks have higher expected returns than a bank account or Treasury bonds.

The Relative Strength Index (RSI) is one of the most popular technical indicators that can help you determine overbought and oversold price levels as well as generate buy and sell signals. The RSI Indicator has proven to be quite useful to gold traders and investors. It could potentially help to identify local tops and bottoms.

R-squared is a statistical measure of how well a statistical model (it may be just a line) fits the data. It is also known as the coefficient of determination, and denoted as R2 or r2. To be more specific, R-squared is the percentage of the variability of the data that is explained by the model (i.e., it is the explained variation divided by the total variation). In simple words, R2 shows how much of the changes in one thing (like the prices of gold stocks) can be explained by changes in another thing (like the price of gold). R-squared is always between 0 and 100 percent, where the higher the-R squared, the better the model fits the data. An R2 of 1 indicates that the model (it may be a simple regression line) perfectly fits the data, while an R2 of 0 means that the model does not fit the data at all.