Nifty 17110.15 (-0.97%)
Sensex 57276.94 (-1.00%)
Nifty Bank 37982.1 (0.73%)
Nifty IT 33475.05 (-3.55%)
Nifty Financial Services 17763.15 (-0.15%)
Adani Ports 709.10 (-0.28%)
Asian Paints 3116.95 (-0.96%)
Axis Bank 773.85 (2.88%)
B P C L 382.20 (-0.09%)
Bajaj Auto 3501.10 (0.92%)
Bajaj Finance 6837.00 (-1.82%)
Bajaj Finserv 15359.85 (-1.09%)
Bharti Airtel 707.25 (-0.65%)
Britannia Inds. 3494.15 (-1.28%)
Cipla 927.60 (2.42%)
Coal India 160.55 (-0.37%)
Divis Lab. 3939.85 (-2.70%)
Dr Reddys Labs 4256.35 (-3.33%)
Eicher Motors 2643.85 (-1.79%)
Grasim Inds 1687.05 (-1.99%)
H D F C 2503.35 (-1.08%)
HCL Technologies 1077.75 (-4.09%)
HDFC Bank 1474.95 (-0.88%)
HDFC Life Insur. 621.50 (-1.47%)
Hero Motocorp 2715.00 (-2.41%)
Hind. Unilever 2295.35 (-1.37%)
Hindalco Inds. 489.15 (0.70%)
I O C L 122.70 (1.03%)
ICICI Bank 794.65 (-0.87%)
IndusInd Bank 888.10 (0.44%)
Infosys 1678.60 (-2.53%)
ITC 214.60 (0.14%)
JSW Steel 626.10 (-0.80%)
Kotak Mah. Bank 1889.25 (1.87%)
Larsen & Toubro 1910.85 (-0.75%)
M & M 858.05 (0.42%)
Maruti Suzuki 8820.20 (2.53%)
Nestle India 18385.45 (-2.16%)
NTPC 135.00 (-0.22%)
O N G C 165.70 (0.33%)
Power Grid Corpn 214.85 (-1.83%)
Reliance Industr 2338.10 (-1.48%)
SBI Life Insuran 1211.65 (-1.33%)
Shree Cement 23961.80 (-2.19%)
St Bk of India 528.95 (2.78%)
Sun Pharma.Inds. 812.10 (0.50%)
Tata Consumer 705.95 (-0.25%)
Tata Motors 494.40 (0.78%)
Tata Steel 1088.35 (-1.87%)
TCS 3649.25 (-3.20%)
Tech Mahindra 1445.60 (-3.67%)
Titan Company 2310.05 (-2.80%)
UltraTech Cem. 7100.70 (0.03%)
UPL 771.95 (-2.43%)
Wipro 544.75 (-3.19%)

Introduction

One often witnesses heavy price fluctuations in the stocks market. The most common term used by traders to define price fluctuations is volatility.

Volatility is a statistical measure of the dispersion of returns for a given security or market index. It is measured by using variance or the square root of variance i.e. standard deviation.

Volatility is a double-edged sword; a surge in volatility could either benefit a trader or end up triggering his stop loss.

Low volatility indicates that a stock does not swing dramatically, but changes in price at a steady pace over a given period of time. In this chapter, we would cover the types of volatility, the methods to calculate them and how a trader can successfully interpret and benefit from the same

Understand through example

Let us understand the concept of volatility (Standard Deviation) better with a simple example.

Consider BCCI has to make a selection between two batsmen based on their past 10 scores.

TABLE GOES HERE

Rohit’s Average = 446/10= 44.6

Dhavan’s Average = 447/10=44.7

Both the batsmen have scored nearly the same runs and have a similar average over the course of 10 innings, which makes the selection difficult.

The parameter that can be used in such a situation is to determine the consistency of the batsmen calculated through the mathematical formula of standard deviation.

Calculate the variance

First, we calculate the variance through which the standard deviation can be easily computed.

Variance is simply the ‘sum of the squares of the deviation from the mean divided by the total number of observations'.

Variance for Rohit, who maintains an average of 44.6, is calculated a below:

Variance = [(-17.6) ^2 + (-2.6) ^2 + (2.4) ^2 + (7.4) ^2 + (-5.6) ^2 + (16.4) ^2 + (10.4) ^2 + (-10.4) ^2 + (-1.6) ^2 + (1.4) ^2] / 10

= 902.4 / 10

= 90.24

Calculate the Standard Deviation

Next, we calculate the Standard Deviation (SD)

Std deviation = √ variance

The standard deviation for Rohit’s turns out to be Square root (90.24) = 9.49

Similarly, we calculate the variance and standard deviation of Dhavan

TABLE GOES HERE

 

Lower and higher projections

Once we have obtained the standard deviation, it can be used to predict the possible/probable runs both the players are likely to score in the next match. We can arrive at lower and higher projections by adding and subtracting the S.D from the average.

TABLE GOES HERE

From this, we can estimate that in the next match Rohit is likely to score between 35 to 54 runs (rounded off), while Dhavan is likely to score between 9 to 80 (rounded off). Rohit is clearly the more consistent of the two; Dhavan could either click or get out cheaply.

From the above example, we clearly see how standard deviation and volatility estimation can be used in our day-to-day activities.

Volatility is a % number as measured by standard deviation.

School

Want to be a Pro Trader?

Start Learning Now!

Download 5paisa School App

  • Google Play Store
  • Apple APP Store

Explore all courses at www.school.5paisa.com