Refinance Loans Home Equity Refinance Loans Home Equity Refinance Loans Home Equity

Www Refinanceloanshomeequity C Refinance Szh Donghuapian 3635 Mingzhentankenan Refinance Loans Home Equity ²ÆÎñ½ðÈÚ½¨Ä£¡ªÍ¼±í(39xls) £­ÔªÃîÆóÒµ¹ÜÀíÍø

Www Refinanceloanshomeequity C Refinance Szh Donghuapian 3635 Mingzhentankenan Refinance Loans Home Equity

.00 2.00 3.00 4.00 5.00 6.00 7.00 -1150.00 234.00 257.40 283.14 311.45 342.60 376.86 414.55 101.46 .18 .00 101.46 .18 .00 -176.46 .10 .05 -47.82 .14 .10 101.46 .18 .15 274.35 .2¡­¡­¡­¡­
Szh a 3635 e Refinanceloanshomeequity 24 Www c Refinance a Refinanceloanshomeequity t Refinance £searchÖ Donghuapian Îsearch£search a Donghuapian e2 Refinance 4 Www c Mingzhentankenan asearcht Www P Refinance g Refinanceloanshomeequity Refinanceloanshomeequity 3 Refinanceloanshomeequity - Refinanceloanshomeequity 3 Www Szh ÖÐÎsearch) Mingzhentankenan Psearchg Mingzhentankenan 3 Mingzhentankenan - Www 3 Donghuapian searchasearche 2 Mingzhentankenan 3search(searchÐ Refinance Ä Szh Www ag Mingzhentankenan Mingzhentankenan 3 Donghuapian %C3%F9%C8%CB%C7%BF%BC%E9%D0%A1%D3%A3%D0%A1%D3%CE%CF%B7a Refinance esearch2 Www 1search Donghuapian ÖÐ Donghuapian Ä) 3635 P Mingzhentankenan g Donghuapian search3bsearchPa Szh e2 3635 1(ÖÎ Www )P Donghuapian gsearch Mingzhentankenan 3 Refinanceloanshomeequity ( 3635 Ð Refinanceloanshomeequity Ä Refinance Pa Refinanceloanshomeequity e Refinance 30 Donghuapian Pgesearch2search8 Www 22search ( Szh ÐsearchÄ Refinanceloanshomeequity V Refinance Af Www nsearcht Www on, Refinance p Szh .192 Refinanceloanshomeequity 0 Refinance Refinanceloanshomeequity 03 Donghuapian Pag Szh 2 Www 8- Mingzhentankenan 29 searchal C Szh ll searchasearchlO Refinanceloanshomeequity t Refinanceloanshomeequity o 3635 Refinance asearchlVolatsearchlity isearchpl Refinanceloanshomeequity e0_searchasearchl_ Donghuapian o Donghuapian ati Refinanceloanshomeequity isearchysearchi Donghuapian p Www iesearch_ca Refinance l_volatility interest interest PutOption r_ r_ S S sigma sigma solver_adj solver_adj solver_adj solver_cvg 1.00E-04 solver_cvg 1.00E-04 solver_cvg 1.00E-04 solver_drv 1.00 solver_drv 1.00 solver_drv 1.00 solver_est 1.00 solver_est 1.00 solver_est 1.00 solver_itr 100.00 solver_itr 100.00 solver_itr 100.00 solver_lin 2.00 solver_lin 2.00 solver_lin 2.00 solver_neg 2.00 solver_neg 2.00 solver_neg 2.00 solver_num .00 solver_num .00 solver_num .00 solver_nwt 1.00 solver_nwt 1.00 solver_nwt 1.00 solver_opt solver_opt solver_opt solver_pre 1.00E-06 solver_pre 1.00E-06 solver_pre 1.00E-06 solver_scl 2.00 solver_scl 2.00 solver_scl 2.00 solver_sho 2.00 solver_sho 2.00 solver_sho 2.00 solver_tim 100.00 solver_tim 100.00 solver_tim 100.00 solver_tol .05 solver_tol .05 solver_tol .05 solver_typ 3.00 solver_typ 3.00 solver_typ 3.00 solver_val 4.00 solver_val 4.00 solver_val 4.00 T T target_call_price target_call_pri¡­¡­¡­¡­
Page 15-16 (ÖÐÎÄ) Page 15-16 Page 12-14 (ÖÐÎÄ) Page 12-14 Page 10b (ÖÐÎÄ) Page 10b Page 10 (ÖÐÎÄ) Page 10 Page 9£¨ÖÐÎÄ£© Page 9 Page 8£¨ÖÐÎÄ£© Page 8 Page 7 (ÖÐÎÄ) Page 7 Page 5-6 (ÖÐÎÄ) Page 5-6 Page 4 (ÖÐÎÄ) Page 4 solver_adj solver_adj solver_cvg 1.00E-03 solver_cvg 1.00E-03 solver_drv 1.00 solver_drv 1.00 solver_est 1.00 solver_est 1.00 solver_itr 100.00 solver_itr 100.00 solver_lin 2.00 solver_lin 2.00 solver_neg 2.00 solver_neg 2.00 solver_num .00 solver_num .00 solver_nwt 1.00 solver_nwt 1.00 solver_opt solver_opt solver_pre 1.00E-06 solver_pre 1.00E-06 solver_scl 2.00 solver_scl 2.00 solver_sho 2.00 solver_sho 2.00 solver_tim 100.00 solver_tim 100.00 solver_tol .05 solver_tol .05 solver_typ 3.00 solver_typ 3.00 solver_val .00 solver_val .00 Discount rate Present value Cash Year flow IRR LOAN TABLE NPV Division of payment Principal Payment between interest at beginning at end and return of principal year of year Interest DATA TABLE Discount rate Identifying the two IRRs First IRR Second IRR Cost Deposit at beginning Total in account end of year Account balance beg. year earned during year <-- =D8+C8+B8 A simpler way Future value A RETIREMENT PROBLEM Annual deposit <-- =E10+D10+C10 Numerator Denom¡­¡­¡­¡­
Page 209-210 (ÖÐÎÄ) Page208 chart Page 208 (ÖÐÎÄ) Page 208 Page 207 (ÖÐÎÄ) Page 207 VBA option functions Page 201-202 Page 199-200 (ÖÐÎÄ) Page 199-200 Page 199 Page 198 (ÖÐÎÄ) Page 198 Page 196(ÖÐÎÄ) Page 195-196 (ÖÐÎÄ) Page 195-196, AmericanCall AmericanPut BSCall BSPut EurCall EurPut getformula TWO-DATE BINOMIAL OPTION PRICING Up Down Initial stock price Interest rate Exercise price Stock price Bond price Call option A B Call price State prices qu qd Solving for the portfolio parameters: A is the number of shares and B is the number of bonds. 55*A + 108*B = 5 48.5*A + 108*B = 0 or: A*stock*(1+up)+B*(1+interest)=max(stock*(1+up)-X,0) A*stock*(1+down)+B*(1+interest)=max(stock*(1+down)-X,0) The solution is: check on state prices call price state prices Call option price FIVE DATE EUROPEAN BINOMIAL OPTION PRICING up down initial stock price interest rate exercise price stock price bond price Terminal payoff * payoff of "up" of "down" price * steps of paths # paths Option value THREE DATE BINOMIAL OPTION PRICING FOR AMERICAN CALL/PUT American put option =MAX(MAX(X-S*(1+u),0),qu*put_payoffuu+qd*put_payoffud) =MAX(MAX(X-S*(1+d),0),qu*put_payoffud+qd*put_payoffdd) =MAX(MAX(X-S,0),qu*put_valueu+qd*¡­¡­¡­¡­
Page 347 (ÖÐÎÄ) Page 347 Page 346 (ÖÐÎÄ) Page 346 Page 343-345 (ÖÐÎÄ) Page 343-345 Page 342, (ÖÐÎÄ) Page 342, david david jack jack simon simon terry terry x x xx xx Matrix A Matrix B Product AB Solution Matrix A of coefficients vector Y MATRICES IN EXCEL Matrix A (a row vector) Matrix D (a 4 x 3 matrix) Matrix C vector) (a column Matrix B (a square 3 x 3 matrix) MATRIX OPERATIONS Multiplication by a scalar Scalar Scalar * Matrix B <-- =D7*$B$5 Addition of matrices Sum of A + B <-- =B20+E20 Transposition of matrix Matrix E Transpose of E = ET The framed area contains To use this function: Mark off the whole area; put in the formula, then finish by pressing [Ctrl]+[Shift]+[Enter]. the array function =Transpose(A30:D32) . Multiplication of matrices <--Array contains formula =MMULT(A42:B43,D42:F43) Product BA -- this won¡®t work <-- =MMULT(D42:F43,A42:B43) MATRIX INVERSE Inverse of A: Array function Minverse(A4:D7) Verifying the inverse We multiply A*Inverse A: cells contain array function MMULT(A4:D7,F4:I7) SOLVING SIMULTANEOUS EQUATIONS Column A-1 Y Checking that the solution works Contains the array function =MMULT(A5:C7,G5:G7) EXCELÖеľØÕó ¾ØÕóA (Ò»¸öÐÐÏòÁ¿) ¾ØÕóC (Ò»¸öÁÐ ÏòÁ¿) ¾ØÕóB (Ò»¸ö3 x 3µÄ·½Õó) ¾ØÕóD (Ò»¸ö4 x¡­¡­¡­¡­
Page 150 (ÖÐÎÄ) Page 150 Page 149 (ÖÐÎÄ) Page 149 Page 148 Page 147(ÖÐÎÄ) Page 146-147 (ÖÐÎÄ) Page 146-147 Page 144,(ÖÐÎÄ) Page 144, Page 143, (ÖÐÎÄ) Page 143, AMR BS GE HR MO UK SP500 Mean Beta Intercept Slope R-squared SUMMARY OUTPUT Multiple R R Square Adjusted R Square df SS MS Coefficients t Stat X Variable 1 Regressing the means on the betas: F Significance F P-value Lower 95% Upper 95% =COVAR(B4:B13,$H$4:$H$13)/VARP($H$4:$H$13) =SLOPE(B4:B13,$H$4:$H$13) <-- =INTERCEPT(B15:G15,B16:G16) <-- =SLOPE(B15:G15,B16:G16) <-- =RSQ(B15:G15,B16:G16) THE SECURITY MARKET LINE--A SIMPLE EXAMPLE Variance-covariance matrix Means Minus Constant Calculating two efficient portfolios z x y Variance Covariance <-- =MMULT(TRANSPOSE(E17:E22),J6:J11) <-- =MMULT(MMULT(TRANSPOSE(E17:E22),C6:H11),E17:E22) <-- =SQRT(E25) <-- =MMULT(MMULT(TRANSPOSE(E17:E22),C6:H11),K17:K22) <-- =C19/SUM($C$17:$C$22) Sigma Data for SP500 returns <-- =AVERAGE(P4:P13) <-- =STDEVP(P4:P13) Calculation for a single portfolio Proportion x Proportion y <-- =D30*D24+D31*K24 <-- =D30^2*D25+D31^2*K25+2*D30*D31*D27 <-- =SQRT(D34) Portfolio proportion mean Step Cell D39 is the change in the portfolio proportion in the data table to the right. <-¡­¡­¡­¡­
Page 123-124 (ÖÐÎÄ) Page 123-124 Page 123 (ÖÐÎÄ) Page 123 Page 122£¬ (ÖÐÎÄ) Page 122£¬ Page 122 (ÖÐÎÄ) Page 122 Page 120-121 (ÖÐÎÄ) Page 120-121 Page 118£¬ (ÖÐÎÄ) Page 118£¬ junk junk varcovar RETURN DATA FOR VARIANCE-COVARIANCE CALCULATIONS AMR BS GE HR MO UK SP500 AMR American Airlines BS Bethlehem Steel GE General Electric HR International Harvester MO Philip Morris UK Union Carbide Excess return matrix Transpose of excess return matrix Beta Difference between two var-cov matrices: Product of transpose[excess return] times [excess return] / 10 Variance-covariance matrix based on return data Return data for 4 stocks (in columns) The variance-covariance matrix Mean CALCULATING THE VARIANCE-COVARIANCE MATRIX FROM EXCESS RETURNS A VBA FUNCTION FOR THE VARIANCE-COVARIANCE MATRIX My thanks go to Amir Kirsh for this suggestion. USING THE OFFSET FUNCTION TO COMPUTE THE VAR-COV MATRIX SINGLE-INDEX MODEL =COVAR(B4:B13,$H$4:$H$13)/VARP($H$4:$H$13) =SLOPE(B4:B13,$H$4:$H$13) Var(SP500) COMPUTING THE SINGLE-INDEX VARIANCE-COVARIANCE MATRIX <-- =AVERAGE(G4:G13) <-- =G12-$G$14 <-- =G13-$G$14 <-- =C$14*$B15*$C$11 My thanks go to Shay Safrir for this suggestion. ·½²îºÍЭ·½²î¼ÆËãµÄÊÕÒæÊý¾Ý ÃÀ¹úº½¿Õ¹«Ë¾ ²®Àûºã¸ÖÌú³§ ͨÓÃµçÆø¹«Ë¾ ¹ú¼ÊÊÕ¸î»ú¹«Ë¾ ·ÆÀûÆÕĪÀï˹¹«¡­¡­¡­¡­
Page 117 (ÖÐÎÄ) Page 117 Page 116 (ÖÐÎÄ) Page 116 Page 115 (ÖÐÎÄ) Page 115 Page 112, (ÖÐÎÄ) Page 112, Page 109-110 (ÖÐÎÄ) Page 109-110 Page 108 Page 107 (ÖÐÎÄ) Page 107 Page 106, graph (ÖÐÎÄ) Page 106, graph Page 104-105 (ÖÐÎÄ) Page 104-105 Stock prices Month Stock A Stock B stock A stock B Return Return-mean Product Covariance Correlation CALCULATING THE MEAN AND SIGMA OF A PORTFOLIO R A t RBt Rpt A FOUR-ASSET PORTFOLIO PROBLEM Variance-covariance Mean returns Portfolio 1 Mean Variance Portfolio 2 Transposes Calculating returns of combinations of Portfolio 1 and Portfolio 2 Proportion of Portfolio 1 Mean return Variance of return Stand. dev. of return Table of returns (uses this example and Data|Table) Proportion Stand. dev. <--the content of these cells is given below: Monthly mean Monthly variance Monthly stand. dev. Annual mean Annual variance Annual stand. dev. CALCULATING THE RETURNS Proportion of A St. dev. Sigma stock C stock D Price COVARIANCE AND VARIANCE CALCULATION <-- =MMULT(C10:F10,$G$4:$G$7) <-- =MMULT(C10:F10,MMULT(B4:E7,D21:D24)) <-- =MMULT(C9:F9,MMULT(B4:E7,D21:D24)) <-- =C16/SQRT(C14*F14) <-- =B27*C13+(1-B27)*F13 <-- =B27^2*C14+(1-B27)^2*F14+2*B27*(1-B27)*C16 <-- =SQRT(B29) <--
¡¾¼ÓÈëÊղء¿
¡¾·±ÌåÖÐÎÄ¡¿
¡¾ °ï  Öú ¡¿
  • ²ÆÎñÖÆ¶È
  • ²ÆÎñ±¨±í
  • ²ÆÎñ»á¼Æ
  • ²ÆÎñÔ¤Ëã
  • ˰Îñ¹æ»®
  • ²ÆÎñ·ÖÎö
  • ÄÚ²¿¿ØÖÆ
  • Éó¼Æ×ÊÁÏ
  • ×ʲú¹ÜÀí
  • ½ðÈÚ֪ʶ
  • ÐÅÓùÜÀí
  • Ͷ×ʹÜÀí
  • ²ÆÎñ¾­Àí
  • óÒ×
  • ²ÆÎñÕ½ÂÔ
  • ²ÆÎñ֪ʶ
  • ²ÆÎñ°¸Àý
  • ³É±¾¹ÜÀí
  • ²ÆÎñ¹ÜÀí
  • µ±Ç°Î»ÖãºÊ×Ò³ >> ²ÆÎñ¹ÜÀí >> ½ðÈÚ֪ʶ >> ²ÆÎñ½ðÈÚ½¨Ä£¡ªÍ¼±í(39xls)

    ²ÆÎñ½ðÈÚ½¨Ä£¡ªÍ¼±í(39xls)

  • ÉÏ´«Ê±¼ä£º2008-03-12
  • ÏÂÔØµãÊý£º60µã
  • Îĵµ´óС£º141.0K
  • ÎĵµÀàÐÍ£º xls
  • ÎĵµÒ³Êý£º39 Ò³
  • ×ÊÁϼò½é£¨ÓÉÔªÃîÆóÒµ¹ÜÀíÍø´ÓÔ­ÎÄÖÐËæ»úժȡµÃµ½£¬½ö¹©²Î¿¼£©

    ±¾ÎÄÏà¹ØµÄÆäËü20ƪÄÚÈÝ

  • 1981 term structure 1947 term structure term structure data __123Graph_A __123Graph_B __123Graph_C __123Graph_D __123Graph_E __123Graph_F _2D_ARRY _2D_LABX _2D_RNGA _2D_RNGB _2D_RNGC _2D_RNGD _2D_RNGE _2D_RNGF _2D_RNGG _2D_RNGH _2D_RNGI _2D_RNGJ _2D_RNGK _2D_RNGL _Fill _Regression_Int 1.00 _Regr...
  • »õ±Ò¡¢ÒøÐÐÓë¾­¼Ã
  • 2008-03-12  801Ò³
  • ¡¶»õ±Ò¡¢ÒøÐÐÓë¾­¼Ã.pdf¡·µÄ¼ò½é×ÊÁÏÔÝÎÞ
  • CHAPTER11 »õ±Ò´´Ôì ÏÖ´ú»õ±ÒµÄ´´Ôì»úÖÆ (11ÔÂ8ÈÕ¡ª11ÔÂ15ÈÕ) ÏÖ´ú»õ±ÒµÄ´´Ôì»úÖÆ ÏÖ´ú¾­¼ÃÉú»îÖеÄÐÅÓûõ±Ò ´æ¿î»õ±ÒµÄ´´Ôì ÖÐÑëÒøÐÐÌåÖÆÏµĻõ±Ò´´Ôì¹ý³Ì ¶ÔÏÖ´ú»õ±Ò¹©¸øÐγɻúÖÆµÄ×ÜÌåÆÀ¼Û Ò»¡¢ÏÖ´ú¾­¼ÃÉú»îÖеÄÐÅÓûõ±Ò £¨Ò»£©ÏÖ´úµÄÐÅÓûõ±Ò 1¡¢×îÔçµÄµäÐÍÐÎ̬ÊÇÒøÐÐȯ£»Ó²±ÒµÄ·¢ÐÐͨ³£Í³Ò»ÓÚÖÐÑëÒøÐУ¬Ò²ÊôÐÅÓûõ...
  • »õ±Ò·¢ÐÐÒµÎñºËËã
  • 2008-03-12  42Ò³
  • * * »õ±Ò·¢ÐÐÒµÎñºËËã µÚÒ»½Ú »õ±Ò·¢ÐÐÒµÎñ¸ÅÊö »õ±Ò·¢ÐÐÒµÎñÊÇÈËÃñÒøÐеÄÖØÒªÒµÎñ£¬ÆäÖ÷ÒªÄÚÈݰüÀ¨·¢Ðлù½ðµÄ±£¹Ü¡¢µ÷²¦¡¢»õ±ÒµÄ·¢ÐкͻØÁýÒÔ¼°ËðÉËÆ±±ÒµÄÏú»Ù¡£ Ò»¡¢·¢Ðлù½ðºÍ·¢Ðпâ 1¡¢ ·¢Ðлù½ð ·¢Ðлù½ðÊÇÖ¸ÖйúÈËÃñÒøÐдúÌæ¹ú¼Ò±£¹ÜµÄÉÐδ·¢ÐÐµÄÆ±±Ò£¬ÊÇΪµ÷¼ÁÊг¡»õ±ÒÁ÷ͨµÄ×¼±¸»ù½ð¡£ 2¡¢·¢Ðп⠷¢ÐпâÊÇ·¢Ðлù...
  • ¡¶»õ±ÒÊг¡Óë×ʱ¾Êг¡(Ó¢Îİæ.µÚÁù°æ).pdf¡·µÄ¼ò½é×ÊÁÏÔÝÎÞ
  • »õ±ÒÀíÂÛµÄз¢Õ¹
  • 2008-03-12  57Ò³
  • C:\Working Papers\10524.wpd NBER WORKING PAPER SERIES A SMALL CORNER OF INTERTEMPORAL PUBLIC FINANCE ? NEW DEVELOPMENTS IN MONETARY ECONOMICS: TWO GHOSTS, TWO ECCENTRICITIES, A FALLACY, A MIRAGE AND A MYTHOS Willem H. Buiter Working Paper 10524 papers/w10524 NATIONAL BUREAU O...
  • ¡¶»õ±ÒÎȶ¨·½°¸_Ã×¶û¶Ù¡¤¸¥ÀïµÂÂü.pdf¡·µÄ¼ò½é×ÊÁÏÔÝÎÞ
  • ¡¶×ʲú֤ȯ»¯²úÆ·¼°Æä½»Ò×Ñо¿.PDF¡·µÄ¼ò½é×ÊÁÏÔÝÎÞ