Monday, September 14, 2009

On NIFTY - 1

There is now a lot of speculation regarding whether NIFTY will cross 5000 or not. As per my calculations
(a) the chance that the closing value of NIFTY on 1-Oct-2009 will exceed 5000 is 33.5% and
(b) the chance that the closing value of NIFTY on 16-Oct-2009 will exceed 5000 is 41.7%



Thursday, September 10, 2009

Deaths due to Swine Flu in India - Predictions for Sept 11 -15

The prediction of the number of deaths due to swine flu for the next five days is:

Date Forecast 95% Prediction Interval
11-Sep 154 (150, 158)
12-Sep 159 (155, 164)
13-Sep 164 (159, 169)
14-Sep 170 (164, 175)
15-Sep 175 (169, 181)

(The analysis is based on data available from http://www.swineflu-india.org/)

Saturday, September 5, 2009

Y-o-Y quarterly GDP growth of India (2009-10)

Based on the data on Year-on-Year (Y-o-Y) quarterly growth of GDP (at constant 1999-2000 prices) over the period 1997-98 to 2008-09 my predictions for the Y-o-Y quarterly growth for 2009-10 (at constant 1999-2000 prices) are as follows:
Forecast (%) 95% prediction interval
Q1 6.0 (3.1, 8.9)
Q2 6.9 (3.1, 10.7)
Q3 7.2 (3.0, 11.5)
Q4 7.8 (3.2, 12.4)


Swine Flu in India - 8

My forecasts for the number of deaths due to swine-flu for the next five days are as follows

Date Forecast 95% prediction interval
6-Sep 126 (123, 129)
7-Sep 131 (128, 134)
8-Sep 136 (132, 139)
9-Sep 141 (137, 144)
10-Sep 145 (142, 149)

The data on the statewise mortality figures given in http://www.swineflu-india.org/ continues to show remarkable heterogenity in the apparent mortality rate. Gujarat has the highest apparent mortality rate (~9%), followed by Karanataka (~6%). In contrast Delhi has an apparent mortality of 0.4% while the same for Tamil Nadu is 0.6%.

Tuesday, September 1, 2009

Swine Flu in India - 7

Here are my predictions of the cumulative number of deaths in the period 1-Sep to 5-Sep. These are based on the available data on the cumulative number of deaths between (21-Aug to 31-Aug).

Date Forecast 95% Prediction Interval
1-Sep 103 (101, 106)
2-Sep 108 (106, 111)
3-Sep 113 (111, 116)
4-Sep 118 (116, 121)
5-Sep 123 (121, 126)

There had been 37 reported deaths due to swine flu during the week 25-Aug to 31- Aug. This is almost equal to 38 deaths reported in the week 18-Aug to 24-Aug. From the predictions it appears that we will have similar number of deaths in the coming week.

The number of confirmed positive swine-flu cases in the period 25-Aug to 31 - Aug was 1077 and that for the period 18-Aug to 24-Aug is 982.


Monday, August 31, 2009

Swine-flu in India - 6

A study of the apparent death rates due to swine-flu for various states of India indicates that Gujarat has the highest rate of about 8% while Delhi has the lowest of about 0.5%. In terms of laboratory confirmed swine-flu cases Gujarat has only about 2.5% compared to about 17% of Delhi. Even in Maharashtra which has about 41% of the total confirmed swine-flu cases the death rate is only about 3.2% which though substantially higher than that of Delhi is also substantially lower than that of Gujarat. It is also interesting to see the difference in the apparent death rates of the two neighbouring states Tamil Nadu and Karnataka. While Tamil Nadu has a death rate of about 0.8% the same for Karnataka is about 5.6%. It is to be noted that both these states has similar number of confirmed cases (Tamil Nadu - 9.3%, Karnataka - 11.1%). I feel the differences in the death rates may be either due to large number of undiagnosed swine-flu cases in some states or may be due late treatment allowing onset of complications. Which one is the correct cause?

Thursday, August 27, 2009

On Swine flu in India - 5

My projections for laboratory confirmed total number of cases and new cases (based on data from 19-Jul to 26-Aug) is as follows
Date New Cases Total 95% prediction interval for Total
28 Aug 201 3664 (3443, 3899)
29 Aug 213 3877 (3572, 4208)
30 Aug 225 4102 (3705, 4543)
31 Aug 239 4341 (3841, 4906)

My projections on the cumulative number of deaths predicted on the above days are:

Date Total 95% prediction interval of no. of total deaths
28 Aug 84 (78, 89)
29 Aug 90 (84, 96)
30 Aug 96 (90, 102)
31 Aug 103 (97, 109)