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First Derivative Test: Problem Solving01:25

First Derivative Test: Problem Solving

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Imagine an asset price that crashes to a low point, rebounds sharply as bargain-hunters step in, and then gradually declines. Such behavior can be modeled with a smooth function whose turning points represent locally overvalued and undervalued regions. A convenient example that captures rebound followed by decay is:The high and low points of this curve are identified using the first derivative test, which determines where the function changes from increasing to decreasing or vice versa. To...
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The most common and easiest way to display the relationship between two variables, x and y, is a scatter plot. A scatter plot shows the direction of a relationship between the variables. A clear direction happens when there is either:
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In statistics, two variables are said to be correlated if the values of one variable are associated with the other variable. Depending on the relationship between two variables, correlation can be of three types– positive correlation, negative correlation, and zero correlation.
Two variables, for example, a and b, are said to be positively correlated if both variables move in the same direction. In other words, a positive correlation exists between two variables, a and b, if:
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A close look at earthquakes provides evidence for the conditions appropriate for resonance, standing waves, and constructive and destructive interference. A building may vibrate for several seconds with a driving frequency matching the building's natural frequency of vibration; this produces a resonance that results in one building collapsing while the neighboring buildings do not. Often, buildings of a certain height are devastated, while other taller buildings remain intact. This...
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Statistical tests can calculate whether there is a relationship, or correlation, between independent and dependent variables. An indirect relationship of the variables signifies a correlation, while a direct relationship shows causation. If it is determined that no connection exists between the variables, then the correlation is a coincidence.
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Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
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Do Earthquakes Shake Stock Markets?

Susana Ferreira1, Berna Karali1

  • 1Department of Agricultural and Applied Economics, The University of Georgia, Athens, Georgia, United States of America.

Plos One
|July 22, 2015
PubMed
Summary

Major earthquakes rarely disrupt global stock markets, showing resilience to financial shocks. While some factors can mediate effects, no consistent pattern emerges across markets.

Area of Science:

  • * Financial Economics
  • * Natural Disaster Impact Studies

Background:

  • * Stock markets are sensitive to various global events.
  • * Understanding the impact of natural disasters on financial markets is crucial.

Purpose of the Study:

  • * To investigate the effect of major earthquakes on stock market returns and volatility.
  • * To identify macroeconomic and earthquake-specific factors influencing these effects across 35 financial markets.

Main Methods:

  • * Analysis of aggregate stock market indices over the past twenty years.
  • * Examination of earthquake characteristics (magnitude, fatalities, tsunami) and macroeconomic variables (GDP per capita, trade openness).

Main Results:

  • * Global financial markets demonstrate resilience to earthquake-related shocks.

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  • * Macroeconomic and earthquake variables can mediate impacts, but effects are market-specific with no systematic global pattern.
  • * Stock market volatility remains largely unaffected, with Japan as a notable exception.

    • Conclusions:

    • * Financial markets are generally robust to earthquake events.
    • * Market-specific factors, not global patterns, determine the nuanced impact of earthquakes on stock returns.
    • * Earthquake impacts on stock market volatility are minimal, except in highly exposed markets like Japan.