## Stochastic equation for stock price

6.4 The Stock Price as a Stochastic Process Stock prices are stochastic processes in discrete time which take only discrete values due to the limited measurement scale. Nevertheless, stochastic processes in continuous time are used as models since they are analytically easier to handle than discrete models, e.g. the binomial or trinomial process. George C. Lane, in an intellectual epiphany, developed the stochastic oscillator in the late 50s. This important technical indicator calculates the momentum of stock price changes, and is defined by these equations (courtesy of Wikipedia). \(\% K = \frac{(C – L)} {(H – L)} \times 100\) where. C is the current closing price A typical model used for stock price dynamics is the following stochastic differential equation: where is the stock price, is the drift coefficient, is the diffusion coefficient, and is the Brownian Motion. STOCHASTIC MODELING OF STOCK PRICES Sorin R. Straja, Ph.D., FRM Montgomery Investment Technology, Inc. 200 Federal Street Camden, NJ 08103 Phone: (610) 688-8111 sorin.straja@fintools.com www.fintools.com ABSTRACT The geometric Brownian motion model is widely used to explain the stock price time series. The A bearish divergence can be confirmed with a support break on the price chart or a Stochastic Oscillator break below 50, which is the centerline. A bullish divergence can be confirmed with a resistance break on the price chart or a Stochastic Oscillator break above 50. 50 is an important level to watch. A stochastic differential equation (SDE) is a differential equation in which one or more of the terms is a stochastic process, resulting in a solution which is also a stochastic process. SDEs are used to model various phenomena such as unstable stock prices or physical systems subject to thermal fluctuations. Geometric Brownian motion is used to model stock prices in the Black–Scholes model and is the most widely used model of stock price behavior. Some of the arguments for using GBM to model stock prices are: The expected returns of GBM are independent of the value of the process (stock price), which agrees with what we would expect in reality.

## Stochastic Oscillator: The stochastic oscillator is a momentum indicator comparing the closing price of a security to the range of its prices over a certain period of time. The sensitivity of the

In the Black-Scholes model, the stock price S is a geometric Brownian motion described by the following stochastic differential equation (SDE). dSt. St. = µdt + σ 15 Jan 2020 concerned with any “prediction” of stock price behaviors that belong other merical solution of PDEs and stochastic differential equations, Asymptotic analysis of stochastic stock price models is the central topic of the in finite time for solutions of certain auxiliary stochastic differential equations. These include the time-varying instantaneous volatility of stock prices and the Among the three stochastic volatility models investigated, the Heston model and The integrated volatility proxy formula is calculated through equation (1) and In the modeling of financial market, especially stock market, Brownian Motion play In general, the process above is of solving a stochastic differential equation,

### In the most common example of derivatives pricing, the Black-Scholes model for stock options is a stochastic partial differential equation that rests on the

Stochastics is a favored technical indicator because it is easy to understand and has a high degree of accuracy. Stochastics is used to show when a stock has moved into an overbought or oversold

### Assume the stock does not pay dividends and the price process of the stock is given by The Itô process Xt satisfies a stochastic differential equation. dXt = µ(t

term intervals because stock prices are able to reproduce the leptokurtic Partial differential equations and probability and stochastic processes are the two Keywords: Futures, Kalman Filter, Stochastic Process, Theoretical Pricing. 1. exchange rates, commodity price and stock prices. partial differential equation ( PDE) was derived for the value of the asset dependent on these two factors. A. 18 Sep 2007 If the underlying stock price follows geometric Brownian motion with a nonlinear drift and constant volatility Consider the stochastic equation. 3 Jun 2010 Investors purchase stocks and bonds in the financial market, putting their derivative equations, while maintaining its real world applications. 16 Jul 2014 Though one must consider the model of stock prices following giving stochastic equations for the log price An external file that holds a picture 23 Mar 2012 Solving the sums of risk hedging The stochastic differential equation that As long as the stock and bond prices move obey the model, the

## stock prices, because the price of each stock affects each other. Keywords: Stochastic Differential Equation, Multidimensional Geometric Brownian Motion,.

The Stochastic technical analysis indicator might be helpful in detecting price divergences and confirming trend. This is discussed on the next page. The information above is for informational and entertainment purposes only and does not constitute trading advice or a solicitation to buy or sell any stock, option, future, commodity, or forex STOCHASTIC MODELING OF STOCK PRICES Sorin R. Straja, Ph.D., FRM Montgomery Investment Technology, Inc. 200 Federal Street Camden, NJ 08103 Phone: (610) 688-8111 sorin.straja@fintools.com www.fintools.com ABSTRACT The geometric Brownian motion model is widely used to explain the stock price time series. The A stochastic differential equation (SDE) is a differential equation where one or more of the terms is a stochastic process, resulting in a solution, which is itself a stochastic process. SDEs are used to model phenomena such as fluctuating stock prices and interest rates. It is defined by the following stochastic differential equation. Equation 1 Equation 2 S t is the stock price at time t, dt is the time step, μ is the drift, σ is the volatility, W t is a Weiner process, and ε is a normal distribution with a mean of zero and standard deviation of one. Substituting Equation 2 into Equation 1 gives

The Stochastic Oscillator (STOCH) was developed by George Lane in the 1950's. Lane believed that his indicator was a good way to measure momentum which is important because changes in momentum precede change in price. In a 2007 interview he was quoted as saying "Stochastics measures the momentum of price. Once you have the differential equation, you use a stochastic integral to solve for the value. I was introduced to the concept through a finance class, so let’s look at an example from the stock market. The above equation describes the price of a stock. St is the price of the stock. dSt is the change in the stock price. dt is the change in time. The Stochastic technical analysis indicator might be helpful in detecting price divergences and confirming trend. This is discussed on the next page. The information above is for informational and entertainment purposes only and does not constitute trading advice or a solicitation to buy or sell any stock, option, future, commodity, or forex STOCHASTIC MODELING OF STOCK PRICES Sorin R. Straja, Ph.D., FRM Montgomery Investment Technology, Inc. 200 Federal Street Camden, NJ 08103 Phone: (610) 688-8111 sorin.straja@fintools.com www.fintools.com ABSTRACT The geometric Brownian motion model is widely used to explain the stock price time series. The A stochastic differential equation (SDE) is a differential equation where one or more of the terms is a stochastic process, resulting in a solution, which is itself a stochastic process. SDEs are used to model phenomena such as fluctuating stock prices and interest rates.