While taking a random walk, an object stays close to its origin and probability of it moving away from origin diminishes as per the normal distribution centered at origin. Random walks are everywhere around us and plays important roles in modelling/studying the behavior of objects/system/instruments in field of Finance and Science. What we are interested in is the outcome (position) of such random walks, that is the position this object will take after a certain number of steps. Given the starting position at number 0 and with an equal probability of that object moving in left or right directions in this line (which can be implemented by simply adding -1 or +1 to starting number), object can perform random walk. one can now start imagining a graph (or bidirected graph if movement is allowed in both direction) taking shape with neighboring nodes as allowed moves and edges as steps).Ī simple example of random walk is a bidirectional walk on an integer number line. Given these four values an object can take N number of steps in different directions (following probabilities) and perform a random walk.
An object can do a random walk provided it has a few directions to move, some probabilities of object moving into those directions, distance an object will move in one step and the number of steps. Random walk is a process of moving (taking steps) in random directions from a starting point.
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