Pldt Case Study

Presented at the DLSU Research Congress 2014

De La Salle University, Manila, Philippines

March 6-8, 2014

Dynamics of PLDT Stock Price

Roseanne Kaw1,* and Robert Roleda1

1

Physics Department, De La Salle University, 2401 Taft Avenue, Manila

*Corresponding Author: raly_anne_kaw@yahoo.com

Abstract: Investing in stocks is commonly held to be a risky enterprise because of the

unpredictable nature of the market. While it may be true that forecasting the exact

value of stock price at some time in the future is impossible, it is believed that one

can at least calculate the probability that a certain price occurs. Calculation of

probabilities is generally based on past prices. This study evaluates the dynamics of

PLDT stock prices by looking at the evolution of the probability density function that

describes the stock price return over a period of 24 years, divided into 30-day

segments with 15-day overlaps. Gaussian distribution is assumed and the mean and

standard deviation (sigma) for each segment are determined. Graphical analysis of

the mean, sigma, increment mean, increment sigma, and time showed that only

sigma has a deterministic characteristic, with a curve-fit sine-square time

dependence. With a time-dependent sigma, it is then shown that the evolution of the

probability density function follows the Fokker-Planck equation. Comparison with

the Feynman-Kac equation indicates that the dynamics can be described by a sigmadependent potential, which has an oscillatory characteristic.

Key Words: stock market; probability density function; Fokker-Planck equation

1. INTRODUCTION

Stock market investments are risky because

of the unpredictability of the market. Risks can

however be managed if one has some level of

understanding of dynamical behaviour of the market.

While one may not be able to predict exactly what

price a stock would have at any given time as one

would expect from a completely deterministic system,

stochastic analysis can at least provide some

information...