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Microsoft (MSFT) Augusto Pucci
Overview ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Microsoft Campus
Microsoft: Company Overview
Financial Highlights ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],William Henry Gates III   (Seattle, 10/28/1955)
Financial Highlights ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Steven Anthony Ballmer   (Detroit, 03/24/1956)
Important Dates ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Important Dates [2] ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
MSFT – Return Analysis
Adj_Close from 03/13/1986 to 02/05/2009 9/11 Win95 Win98 monopoly accuse European antitrust action 5,000 emp. layoffs
RT from 03/13/1986 to 02/05/2009 9/11 Win95 Win98 monopoly accuse European antitrust action 5,000 emp. layoffs
Windows 95 & Windows 98 Win95 Win98
Windows 95 & Windows 98 Win95 Win98
Dot.Com Bubble & 9/11 9/11 monopoly accuse
Dot.Com Bubble & 9/11 9/11 monopoly accuse
European antitrust accuse & massive layoffs European antitrust action 5,000 emp. layoffs
European antitrust accuse & massive layoffs European antitrust action 5,000 emp. layoffs
RT - Histogram
Windows 95 & Windows 98
Dot.Com Bubble & 9/11
RT Synth - Histogram
RT Vs. RT Synth 5776 5776 Observations 9143113. 9136709. Sum Sq. Dev. 8686.960 8147.096 Sum 0.000000 0.066684 Probability 51406.45 5.415586 Jarque-Bera 17.56243   3.076041 Kurtosis -0.619675 -0.064653 Skewness   39.78974   39.77580 Std. Dev. -602.4211 -154.1308 Minimum 283.3044    143.1277 Maximum   0.000000   1.712924 Median   1.503975   1.410508 Mean RT RT_SYNTH
RT Synth
RT Vs. RT Synth [2]
RT Vs. RT Synth [3]
RT - Correlogram Sign. Level (5%) =  ± 0.025
RT 2  - Correlogram Sign. Level (5%) =  ± 0.025
abs(RT) - Correlogram Sign. Level (5%) =  ± 0.025
RT 2
RT 2  - Histogram
abs(RT)
abs(RT) - Histogram
RT – AR(2) model
RTF - AR(2) Static Forecast
RT Vs. RTF AR(2) Static Forecast
RTF - AR(2) Dynamic Forecast
RT AR(2) – Residual Plot
RT AR(2) – Residual Plot [2]
RT AR(2) – Residual Histogram
RT AR(2) – Residual Correlogram Sign. Level (5%) =  ± 0.025
RT AR(2) – Residual ARCH Test
RT – AR(2) – ARCH(1) model
RT – AR(2) – ARCH(1) model σ 2  = 1,618.1026 σ   =  40.225647
RT – ARCH(1) Residual Plot
RT – ARCH(1) Conditional Variance Plot
RT – ARCH(1) Residual Vs. Conditional Variance Plot
RT – ARCH(1) Std. Residual Plot
RT – ARCH(1) Residuals Vs. Std. Residuals Plot
RT – ARCH(1) Std. Residuals Vs. Residuals
RT – ARCH(1) Conditional Variance Vs. Std. Residuals
RT – ARCH(1) Residual Histogram
RT – ARCH(1) Std. Residual Correlogram Sign. Level (5%) =  ± 0.025
RT – ARCH(1) Squared Std. Residual Correlogram Sign. Level (5%) =  ± 0.025
RT ARCH(1) – Residual ARCH Test
RT – AR(2) – ARCH(2) model
RT – AR(2) – ARCH(2) model σ 2  = 1,635.1865 σ   =  40.437440
RT – ARCH(2) Residual Plot
RT – ARCH(2) Conditional Variance Plot
RT – ARCH(2) Residual Vs. Conditional Variance Plot
RT – ARCH(2) Std. Residual Plot
RT – ARCH(2) Residuals Vs. Std. Residuals Plot
RT – ARCH(2) Std. Residuals Vs. Residuals
RT – ARCH(2) Conditional Variance Vs. Std. Residuals
RT – ARCH(2) Residual Histogram
RT – ARCH(2) Std. Residual Correlogram Sign. Level (5%) =  ± 0.025
RT – ARCH(2) Squared Std. Residual Correlogram Sign. Level (5%) =  ± 0.025
RT ARCH(2) – Residual ARCH Test
RT – AR(2) – GARCH(1,1) model
RT – AR(2) – GARCH(1,1) model σ 2  = 2,391.1118 σ   =  48.898996
RT – GARCH(1,1) Residual Plot
RT – GARCH(1,1) Conditional Variance Plot
RT – GARCH(1,1) Residual Vs. Conditional Variance Plot
RT – GARCH(1,1) Std. Residual Plot
RT – GARCH(1,1) Residuals Vs. Std. Residuals Plot
RT – GARCH(1,1) Std. Residuals Vs. Residuals
RT – GARCH(1,1) Conditional Variance Vs. Std. Residuals
RT – GARCH(1,1) Residual Histogram
RT – GARCH(1,1) Std. Residual Correlogram Sign. Level (5%) =  ± 0.025
RT – GARCH(1,1) Squared Std. Residual Correlogram Sign. Level (5%) =  ± 0.025
RT GARCH(1,1) – Residual ARCH Test
RT GARCH(1,1) - Sign Bias Test
RT GARCH(1,1) – Negative Size Bias Test
RT – AR(2) – TGARCH(1,1) model
RT – AR(2) – TGARCH(1,1) model σ 2  = 2,656.5854 σ   =  51.542074
RT – TGARCH(1,1) Residual Plot
RT – TGARCH(1,1) Conditional Variance Plot
RT – TGARCH(1,1) Residual Vs. Conditional Variance Plot
RT – TGARCH(1,1) Std. Residual Plot
RT – TGARCH(1,1) Residuals Vs. Std. Residuals Plot
RT – TGARCH(1,1) Std. Residuals Vs. Residuals
RT – TGARCH(1,1) Conditional Variance Vs. Std. Residuals
RT – TGARCH(1,1) Residual Histogram
RT – TGARCH(1,1) Std. Residual Correlogram Sign. Level (5%) =  ± 0.025
RT – TGARCH(1,1) Squared Std. Residual Correlogram Sign. Level (5%) =  ± 0.025
RT TGARCH(1,1) – Residual ARCH Test
Range & Range 2 ,[object Object],[object Object]
Range 2  model
E[ Range 2 t  | I (t-1)  ] (from Range MEM)
Range 2 t   Vs. E[ Range 2 t  | I (t-1)  ]
abs(RT) model -> RT 2  model
RT 2  model
E[ RT 2 t  | I (t-1)  ] (from abs(RT) MEM)
RT 2 t   Vs. E[ RT 2 t  | I (t-1)  ]
RT – GARCH(1,1) model Extended…
RT – GARCH(1,1) eXt. model
RT – GARCH(1,1) eXt.   Residual Plot
RT – GARCH(1,1) eXt. Conditional Variance Plot
RT – GARCH(1,1) eXt. Residual Vs. Conditional Variance Plot
RT – GARCH(1,1) eXt. Std. Residual Plot
RT – GARCH(1,1) eXt. Residuals Vs. Std. Residuals Plot
RT – GARCH(1,1) eXt. Std. Residuals Vs. Residuals
RT – GARCH(1,1) eXt. Conditional Variance Vs. Std. Residuals
RT – GARCH(1,1) eXt. Residual Histogram
RT – GARCH(1,1) eXt. Std. Residual Correlogram Sign. Level (5%) =  ± 0.025
RT – GARCH(1,1) eXt. Squared Std. Residual Correlogram Sign. Level (5%) =  ± 0.025
RT - GARCH(1,1) eXt – Residual ARCH Test
RT – GARCH(1,1) model Extended 2…
RT – GARCH(1,1) eXt.2 model
RT – GARCH(1,1) eXt.2   Residual Plot
RT – GARCH(1,1) eXt.2 Conditional Variance Plot
RT – GARCH(1,1) eXt.2 Residual Vs. Conditional Variance Plot
RT – GARCH(1,1) eXt.2 Std. Residual Plot
RT – GARCH(1,1) eXt.2 Residuals Vs. Std. Residuals Plot
RT – GARCH(1,1) eXt.2 Std. Residuals Vs. Residuals
RT – GARCH(1,1) eXt.2 Conditional Variance Vs. Std. Residuals
RT – GARCH(1,1) eXt.2 Residual Histogram
RT – GARCH(1,1) eXt.2 Std. Residual Correlogram Sign. Level (5%) =  ± 0.025
RT – GARCH(1,1) eXt.2 Squared Std. Residual Correlogram Sign. Level (5%) =  ± 0.025
RT - GARCH(1,1) eXt.2 – Residual ARCH Test
RT – AR(2) – TGARCH(1,1) ShortFall
RT Vs. Expected Loss [ -1.000*sqr(GARCH) ] Z α  = 1.000
Shortfall  [ min{rt-loss_hat,0}] Z α  = 1.000
Shortfall Histogram  [12.1406 %] Z α  = 1.000 [12.1406 %]
RT Vs. Expected Loss [ -2.000*sqr(GARCH) ] Z α  = 2.000
Shortfall  [ min{rt-loss_hat,0}] Z α  = 2.000
Shortfall Histogram  [1.9050 %] Z α  = 2.000 [1.9050 %]
RT Vs. Expected Loss [ -2.250*sqr(GARCH) ] Z α  = 2.250
Shortfall  [ min{rt-loss_hat,0}] Z α  = 2.250
Shortfall Histogram  [1.3508 %] Z α  = 2.250 [1.3508 %]
RT Vs. Expected Loss [ -2.250*sqr(GARCH) ] Z α  = 2.426
Shortfall  [ min{rt-loss_hat,0}] Z α  = 2.426
Shortfall Histogram  [1.0737 %] Z α  = 2.426 [1.0737 %]
RT Vs. Expected Loss [ -3.000*sqr(GARCH) ] Z α  = 3.000
Shortfall  [ min{rt-loss_hat,0}] Z α  = 3.000
Shortfall Histogram  [0.5542 %] Z α  = 3.000 0.5542 %]
RT Vs. Expected Loss [ -4.000*sqr(GARCH) ] Z α  = 4.000
Shortfall  [ min{rt-loss_hat,0}] Z α  = 4.000
Shortfall Histogram  [0.1383 %] Z α  = 4.000 [0.1383 %]
Volatility Forecasting from: TGARCH(1,1) model
TGARCH(1,1) - Plot RT  ± 2  σ
TGARCH(1,1) – Variance Dynamic Forecast (out of the sample) 02/06/2009  - 02/06/2010
TGARCH(1,1) - Plot RT  ± 2  σ   Variance Dynamic Forecast (out of the sample)
TGARCH(1,1) – Variance Dynamic Forecast (in the sample) Training Set:  03/13/1986 - 12/31/2007 Test Set:  01/01/2008 - 02/05/2009
TGARCH(1,1) - Plot RT  ± 2  σ   Variance Dynamic Forecast (in the sample)
TGARCH(1,1) – Variance Static Forecast (in the sample) Training Set:  03/13/1986 - 12/31/2007 Test Set:  01/01/2008 - 02/05/2009
TGARCH(1,1) - Plot RT  ± 2  σ   Variance Static Forecast (in the sample)
Volatility Forecasting from: Range 2  model
Range 2  - Plot RT  ± 2  σ
Range 2  – Variance Dynamic Forecast (in the sample) Training Set:  03/13/1986 - 12/31/2007 Test Set:  01/01/2008 - 02/05/2009
Range 2  - Plot RT  ± 2  σ   Variance Dynamic Forecast (in the sample)
Range 2  – Variance Static Forecast (in the sample) Training Set:  03/13/1986 - 12/31/2007 Test Set:  01/01/2008 - 02/05/2009
Range 2  - Plot RT  ± 2  σ   Variance Static Forecast (in the sample)
Volatility Forecasting from: GARCH(1,1) eXt. model
GARCH(1,1) eXt.2   - Plot RT  ± 2  σ
GARCH(1,1) eXt.2 – Variance Dynamic Forecast (in the sample) Training Set:  03/13/1986 - 12/31/2007 Test Set:  01/01/2008 - 02/05/2009
GARCH(1,1) eXt.2 - Plot RT  ± 2  σ   Variance Dynamic Forecast (in the sample)
GARCH(1,1) eXt.2 –  Variance Static Forecast (in the sample) Training Set:  03/13/1986 - 12/31/2007 Test Set:  01/01/2008 - 02/05/2009
GARCH(1,1) eXt.2 - Plot RT  ± 2  σ   Variance Static Forecast (in the sample)
Conditional Variance Comparisons
Extra Stuff…
S&P 500
RT MSFT Vs. RM S&P500
RX = RT - RM 9/11 Win95 Win98 monopoly accuse European antitrust action 5,000 emp. layoffs
RX - Histogram
RX - Correlogram Sign. Level (5%) =  ± 0.025
RX 2  - Correlogram Sign. Level (5%) =  ± 0.025
RX – AR(2) model
RXF - AR(2) Static Forecast
RX Vs. RXF AR(2) Static Forecast
RXF - AR(2) Dynamic Forecast
RX AR(2) – Residual Plot
RX AR(2) – Residual Plot [2]
RX AR(2) – Residual Histogram
RX AR(2) – Residual Correlogram Sign. Level (5%) =  ± 0.025
RX AR(2) – Squared Residual Correlogram Sign. Level (5%) =  ± 0.025
RX AR(2) – Residual ARCH Test
RX – AR(2) – GARCH(1,1) model
RX – AR(2) – GARCH(1,1) model σ 2  = 1,055.5790 σ   =  32.489675
RX – AR(2) - GARCH(1,1) Residual Plot
RX – AR(2) - GARCH(1,1) Conditional Variance Plot
RX – AR(2) – GARCH(1,1) Residual Vs. Conditional Variance Plot
RX – AR(2) -GARCH(1,1) Std. Residual Plot
RX – AR(2) - GARCH(1,1) Residuals Vs. Std. Residuals Plot
RX – AR(2) - GARCH(1,1) Std. Residuals Vs. Residuals
RX – AR(2) - GARCH(1,1) Conditional Variance Vs. Std. Residuals
RX – AR(2) - GARCH(1,1) Residual Histogram
RX – AR(2) - GARCH(1,1) Std. Residual Correlogram Sign. Level (5%) =  ± 0.025
RX – AR(2) - GARCH(1,1) Squared Std. Residual Correlogram Sign. Level (5%) =  ± 0.025
RX - AR(2) - GARCH(1,1) – Residual ARCH Test
RX - AR(2) - GARCH(1,1) – Variance Dynamic Forecast
Grazie dell’Attenzione !!!

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Microsoft - Volatility modeling and analysis