金融时间序列分析2077192236.docx

Chapter 1: Financial Time Series and Their CharacteristicsData used in the text:(1) Daily log returns of IBM (62/7/3 to97/12): d-ibmln.dat(2) Dailysimple returns of value-weighted and equal-weighted indexes: d-vwew.dat(3) Dailysimple returns of Intel stock: d-intc.dat(4) Daily simple returns of 3M stock: d-mmm.dat(5) Daily simple returns of Microsoft stock: d-msft.dat(6) Daily simple returns of Citi-group stock: d-citi.dat(7) Monthly bond returns (30 yrs, 20 yrs, ., 1 yr): m-bnd.dat(8) Monthly Treasury rates (10 yrs, 5 yrs, ., 1 yr): m-gs.dat(9) Weekly Treasury Bill rates: w-tb3ms.dat & w-tb6ms.dat Data setsfor Exercises: 1.Log returns of Alcoa stock: d-aa9099.dat Log returns of American Express stock: d-axp9099.dat Log returns of Disney stock: d-dis9099.dat Log returns of Chicago Tribune stock: d-trb9099.dat Log returns of Tyco International stock: d-tyc9099.dat2. Monthly log stock returns of five U.S. companies: Alcoa: m-aa6299.dat American Express: m-axp7399.datDisney: m-dis6299.dat General Motors: m-gm6299.dat Hershey Foods: m-hsy6299.dat Mellon Financial Co.: m-mel7399.dat3. See Alcoa stock returns in Problem 2.4. See American Express stock returns in Problem 2.5. See American Express stock returns in Problem 1.6. Exchange rates of Canadian Dollar, German Mark, United Kingdom Pound,Japanese Yen, and French Francversus U.S. Dollar: forex-c.datChapter 2: Linear Time Series Analysis and Its ApplicationsData sets used in the chapter:(1) U.S. quarterly growth rates of GNP: q-gnp.dat(2) Monthly value-weighted index returns: m-vw.dat(3) Monthly equal-weighted index returns: m-ew.dat(4) Monthly log returns of 3M stock: m-3m4699.dat(5) Quarterly earnings per share of Johnson & Johnson: jnj.dat(6) Weekly U.S. Treasury 1-y and 3-y constant maturity rates: w-gs1yr.dat and w-gs3yr.datData sets for Exercises: 3. Simple returns on monthly U.S. bonds: m-bnd.dat 4. Daily log returns of Alcoa stock: d-aa9099.dat 5. Daily log returns of Hewlett-Packard, value-weighted, equal-weighted and SP500 index: d-hwp3dx8099.dat6. Monthly log returns of equal-weighted index: m-ew6299.dat7. See Problem 5.8. Daily log returns of equal-weighted index: see Problem 5. Calendar of 1980 on (yr,mm,dd,date): day80on.dat Dummy variables (M,T,W,R,yr,mm,dd,days): wkdays8099.dat9. Log prices of futures and spot of SP500: sp5may.dat10. U.S. quarterly unemployment rates: q-unemrate.dat11. Quarterly GDP implicit price deflator: gdpipd.datChapter 3: Conditional Heteroscedastic ModelsData sets used in the text:(1) Monthly simple returns of Intel stock: m-intc.dat RATS program for an ARCH(3) model: m-intc.rats(2) 10-m log returns of FX (Mark-US): exch-perc.dat(3) Excess returns of S&P500: sp500.dat RATS programs for variousvolatility models: (a) AR(3)-GARCH(1,1):m-sp-ar-garch11.rats (b) GARCH(1,1):m-sp-garch11.rats (c) GARCH(1,1) with t_5:t5-garch11.rats (d) GARCH(1,1) with t:garch11-t.rats (e) IGARCH(1,1):m-sp-igarch.rats (f) GARCH(1,1)-M model: m-sp-garchm.rats (g) CHARMA model: sp-charma.rats(4) Monthly log returns of IBM stock:m-ibmln.dat RATS program for EGARCH(1,0): ibm-egarch10.rats (5) Daily log returns of SP500 index: see d-hwp3dx8099.dat in Chapter 2.(6) Monthly log returns of IBM stock& SP500: m-ibmspln.dat Data set for Example 3.5:m-ibmsplnsu.dat RATS program without summer effect:summer.rats RATS program with summer effect:summer1.rats RATS program for Example 3.6: charmax.rats Data setsfor exercises:5. Monthly log returns of Intel stock: m-intc.dat 6. Monthly simple returns of Merck stock: m-mrk.dat (The file contains the simple returns in Column 1. The sample period is from 1946/6 to 1999/12.)7. Monthly simple returns of 3M stock: m-mmm.dat 8. Monthly log returns of GM stock & Sp500: m-gmsp5099.dat 9. See problem 8.10. Daily log returns of IBM stock: d-ibmln.dat Chapter 4: Nonlinear Models and Their ApplicationsData sets used in the text:(1) Monthly simple returns of equal-weighted index: m-ew.dat(2) Daily log returns of IBM stock: d-ibmln99.dat RATS program for TAR-GARCH model: ibm-ar-tar.rats (3) Monthly simple returns of 3M stock: m-mmm.dat RATS program for smooth TAR: star.rats (4) Quarterly growth rates of U.S. gnp: q-gnp.dat (5) Monthly log returns of IBM stock: m-ibmln99.dat(6) Quarterly unemployment rates: q-unemrate.dat To run neural networks on S-Plus or R, visit the Modapplstat at the S-Archive on Statlib for free softwareR and S commands for Example 4.5 are innnet-ibm.sor and thedata set is m-ibmln99.dat.Data setsfor exercises: 1. Monthly log returns of GE stock: m-ge2699.dat 5. Weekly U.S. interest rates: (a) Treasury 1-year constant maturity rates: wgs1yr.dat (b) Treasury 3-year constant maturity rates: wgs3yr.dat Chapter 5: High-Frequency Data Analysis and MarketMicrostructureData stes used in the text: (1) IBM transactions data (11/1/90-1/31/91): The columns are date/time, volume, bid quote, ask quote, and transaction price: ibm.txt (large)(2) IBM transactions data of December 1999. (day. time, price): ibm9912-tp.dat (large)(3) Adjusted time durations between trades (11/01/90- 1/31/91). Positive durations only: ibmdurad.dat(4) Adjusted durations in (3) for the first 5 trading days: ibm1to5-dur.dat (5) Data for Example 5.2 (files are relatively large) (a) The ADS file:ibm91-ads.dat (b) The explanatory variables as defined: ibm91-adsx.dat (6) Transactions data of IBM stock on November 21, 1990 (a) original data:day15-ori.dat (b) data for PCD models:day15.dat data descriptions in file day15.txt RATS programs for estimating duration models:The data file used is ibm1to5-dur.dat.(a) EACD model: eacd.rats(b) WACD model: wacd.rats(c) GACD model: gacd.rats(d) Threshold-WACD model: tar-wacd.rats.Data sets for exercises:3. Adjusted durations of IBM stock (11/2/90): ibm-d2-dur.dat5. Transactions data of 3M (12/99): mmm9912-dtp.dat(large)6. Adjusted durations of 3M (12/99): mmm9912-adur.datChapter 6: Continuous-Time Models and Their ApplicationsData sets used in the text:(1) Daily simple returns of IBM stock in 1998: ibmy98.dat(2) Daily log returns of Cisco stock in 1999: d-cscoy99ln.datSource codeof a Fortran program for European call and put options based on the simple jump diffusion model discussed in the text:kou.f (You need to compile the program.)Chapter 7: Extreme Values, Quantile Estimation, and Value at RiskData sets used in the text:(1) Daily log returns of IBM stock: d-ibmln98.dat(9190 obs) The returns are in percentages.(2) RATS programs used in Example 7.3: (Note: returns used in the example are not in percentages.) (a) AR(2)-GARCH(1,1):example7-3a.rats (b) AR(2)-GARCH(1,1)-t5: example7-3b.rats (3) Daily log returns of Intel stock (Example 7.4): d-intc7297.dat(4) Data used in Subsection 7.7.6 (a) Mean-corrected daily log returns of IBM:ibmln98wm.dat (b) The explanatory variables on page 294: ibml25x.dat Data sets for exercises:1. Daily log returns (in percentages) of GE stock: d-geln.dat2. Daily log returns (in percentages) of Cisco stock: d-csco9199.dat3. See problem 2.4. Daily log returns of HP and 3 indexes: d-hwp3dx8099.datChapter 8: Multivariate Time Series Analysis and Its ApplicationsData sets used in the text:(1) Monthly log returns of IBM and SP 500:m-ibmspln.dat The SCA commands used to analyze the series:sca-ex-ch8.txt Source code of a Fortran program for multivariate Q-stat: qstat.f(2) Monthly simple returns of bond indexes: m-bnd.dat (3) Monthly U.S. interest rates of Example 8.6: m-gs1n3.dat SCA commands used: sca-ex8-6.txt(4) Log prices of SP500 index futures and shares: sp5may.dat(5) Monthly log returns of IBM, HWP, INTC, MER & MWD: m-5cln.dat Data sets for exercises:1. Monthly log returns of MRK et al.: m-mrk2vw.dat2. Monthly U.S. interest rates (1 & 10 yrs): m-gs1n10.dat3. See problem 2.4. See problem 2.Chapter 9: Multivariate Volatility Models and Their ApplicationsData sets used in the text: (1) Daily log returns of HK and Japan market index (Example 9.1): Data file (491 data pts): hkja.dat Bivariate GARCH programs: hkja-c.ratsand hkja-c1.rats(2) Monthly log returns of IBM and SP 500: m-ibmspln.dat Constant-correlation GARCH program: ibmsp-ex92.rats Time-varying correlation GARCH: ibm