Mathematical or statistical models are used to analyze and predict the behavior of financial markets, specifically the stock market and derivatives markets, which include options, futures, and other financial instruments derived from underlying assets such as stocks, bonds, or commodities.
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- The Black-Scholes model is used to calculate the theoretical value of European call and put options. The model takes into account factors such as the current stock price, the option’s strike price, time to expiration, risk-free interest rate, and the option’s implied volatility.
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- The Binomial Options Pricing Model is a numerical method used to value American-style options. The model assumes that the price of the underlying asset can either increase or decrease in each time period.
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- Monte Carlo Simulation is a statistical method used to estimate the value of a financial instrument. The model uses random sampling to generate multiple possible outcomes, which can be used to predict the probability of different outcomes.
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- Capital Asset Pricing Model (CAPM). The CAPM model is used to estimate the expected return on an investment based on its risk. The model takes into account the expected return of the market, the risk-free rate of return, and the investment’s beta (a measure of its volatility relative to the market).
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- The GARCH (Generalized Autoregressive Conditional Heteroscedasticity) model is used to model volatility in financial markets. The model assumes that volatility is not constant over time and can be influenced by past volatility and other factors.
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- The Random Walk Model assumes that stock prices follow a random walk and that future prices cannot be predicted based on past prices. The model is based on the efficient market hypothesis, which states that financial markets are always efficient and that stock prices always reflect all available information.