Similar documents
untitled

,,,17,,, ( ),, E Q [S T F t ] < S t, t [, T ],,,,,,,,

mf.dvi

II Brown Brown

[1][2] [3] *1 Defnton 1.1. W () = σ 2 dt [2] Defnton 1.2. W (t ) Defnton 1.3. W () = E[W (t)] = Cov[W (t), W (s)] = E[W (t)w (s)] = σ 2 mn{s, t} Propo

Green

Chap11.dvi

F S S S S S S S 32 S S S 32: S S rot F ds = F d l (63) S S S 0 F rot F ds = 0 S (63) S rot F S S S S S rot F F (63)

08-Note2-web

,. Black-Scholes u t t, x c u 0 t, x x u t t, x c u t, x x u t t, x + σ x u t, x + rx ut, x rux, t 0 x x,,.,. Step 3, 7,,, Step 6., Step 4,. Step 5,,.

Black-Scholes 1 ( )

1 No.1 5 C 1 I III F 1 F 2 F 1 F 2 2 Φ 2 (t) = Φ 1 (t) Φ 1 (t t). = Φ 1(t) t = ( 1.5e 0.5t 2.4e 4t 2e 10t ) τ < 0 t > τ Φ 2 (t) < 0 lim t Φ 2 (t) = 0

1 1.1 ( ). z = a + bi, a, b R 0 a, b 0 a 2 + b 2 0 z = a + bi = ( ) a 2 + b 2 a a 2 + b + b 2 a 2 + b i 2 r = a 2 + b 2 θ cos θ = a a 2 + b 2, sin θ =

() x + y + y + x dy dx = 0 () dy + xy = x dx y + x y ( 5) ( s55906) 0.7. (). 5 (). ( 6) ( s6590) 0.8 m n. 0.9 n n A. ( 6) ( s6590) f A (λ) = det(a λi)

( ) Loewner SLE 13 February

(3) (2),,. ( 20) ( s200103) 0.7 x C,, x 2 + y 2 + ax = 0 a.. D,. D, y C, C (x, y) (y 0) C m. (2) D y = y(x) (x ± y 0), (x, y) D, m, m = 1., D. (x 2 y

III III 2010 PART I 1 Definition 1.1 (, σ-),,,, Borel( ),, (σ-) (M, F, µ), (R, B(R)), (C, B(C)) Borel Definition 1.2 (µ-a.e.), (in µ), (in L 1 (µ)). T

Feynman Encounter with Mathematics 52, [1] N. Kumano-go, Feynman path integrals as analysis on path space by time slicing approximation. Bull

v er.1/ c /(21)

Grushin 2MA16039T

() Remrk I = [0, ] [x i, x i ]. (x : ) f(x) = 0 (x : ) ξ i, (f) = f(ξ i )(x i x i ) = (x i x i ) = ξ i, (f) = f(ξ i )(x i x i ) = 0 (f) 0.

S I. dy fx x fx y fx + C 3 C vt dy fx 4 x, y dy yt gt + Ct + C dt v e kt xt v e kt + C k x v k + C C xt v k 3 r r + dr e kt S Sr πr dt d v } dt k e kt

( ) ( )

K E N Z OU

201711grade1ouyou.pdf

A (1) = 4 A( 1, 4) 1 A 4 () = tan A(0, 0) π A π

B [ 0.1 ] x > 0 x 6= 1 f(x) µ 1 1 xn 1 + sin sin x 1 x 1 f(x) := lim. n x n (1) lim inf f(x) (2) lim sup f(x) x 1 0 x 1 0 (


x (x, ) x y (, y) iy x y z = x + iy (x, y) (r, θ) r = x + y, θ = tan ( y ), π < θ π x r = z, θ = arg z z = x + iy = r cos θ + ir sin θ = r(cos θ + i s

d (K + U) = v [ma F(r)] = (2.4.4) t = t r(t ) = r t 1 r(t 1 ) = r 1 U(r 1 ) U(r ) = t1 t du t1 = t F(r(t)) dr(t) r1 = F dr (2.4.5) r F 2 F ( F) r A r

(1) D = [0, 1] [1, 2], (2x y)dxdy = D = = (2) D = [1, 2] [2, 3], (x 2 y + y 2 )dxdy = D = = (3) D = [0, 1] [ 1, 2], 1 {

n=1 1 n 2 = π = π f(z) f(z) 2 f(z) = u(z) + iv(z) *1 f (z) u(x, y), v(x, y) f(z) f (z) = f/ x u x = v y, u y = v x

i 18 2H 2 + O 2 2H 2 + ( ) 3K

DVIOUT


S I. dy fx x fx y fx + C 3 C dy fx 4 x, y dy v C xt y C v e kt k > xt yt gt [ v dt dt v e kt xt v e kt + C k x v + C C k xt v k 3 r r + dr e kt S dt d

II (10 4 ) 1. p (x, y) (a, b) ε(x, y; a, b) 0 f (x, y) f (a, b) A, B (6.5) y = b f (x, b) f (a, b) x a = A + ε(x, b; a, b) x a 2 x a 0 A = f x (


1 I 1.1 ± e = = - = C C MKSA [m], [Kg] [s] [A] 1C 1A 1 MKSA 1C 1C +q q +q q 1

x i [, b], (i 0, 1, 2,, n),, [, b], [, b] [x 0, x 1 ] [x 1, x 2 ] [x n 1, x n ] ( 2 ). x 0 x 1 x 2 x 3 x n 1 x n b 2: [, b].,, (1) x 0, x 1, x 2,, x n

Z: Q: R: C: sin 6 5 ζ a, b

振動と波動

Stoch. Integral & SDE (S. Hiraba) 1 1 (Definition of Stochastic Processes),, t, X t = X t (ω)., 1, 2,, n = 1, 2,..., X n = X n (ω).,., ω Ω,,.,,

2 2 L 5 2. L L L L k.....

1 (Berry,1975) 2-6 p (S πr 2 )p πr 2 p 2πRγ p p = 2γ R (2.5).1-1 : : : : ( ).2 α, β α, β () X S = X X α X β (.1) 1 2

1 nakayama/print/ Def (Definition ) Thm (Theorem ) Prop (Proposition ) Lem (Lemma ) Cor (Corollary ) 1. (1) A, B (2) ABC

( ) sin 1 x, cos 1 x, tan 1 x sin x, cos x, tan x, arcsin x, arccos x, arctan x. π 2 sin 1 x π 2, 0 cos 1 x π, π 2 < tan 1 x < π 2 1 (1) (


Fubini

grad φ(p ) φ P grad φ(p ) p P p φ P p l t φ l t = 0 g (0) g (0) (31) grad φ(p ) p grad φ φ (P, φ(p )) xy (x, y) = (ξ(t), η(t)) ( )

(1) (2) (3) (4) HB B ( ) (5) (6) (7) 40 (8) (9) (10)

II A A441 : October 02, 2014 Version : Kawahira, Tomoki TA (Kondo, Hirotaka )

( ) 2.1. C. (1) x 4 dx = 1 5 x5 + C 1 (2) x dx = x 2 dx = x 1 + C = 1 2 x + C xdx (3) = x dx = 3 x C (4) (x + 1) 3 dx = (x 3 + 3x 2 + 3x +

Gmech08.dvi



December 28, 2018

mugensho.dvi

untitled

16 7 5

18 I ( ) (1) I-1,I-2,I-3 (2) (3) I-1 ( ) (100 ) θ ϕ θ ϕ m m l l θ ϕ θ ϕ 2 g (1) (2) 0 (3) θ ϕ (4) (3) θ(t) = A 1 cos(ω 1 t + α 1 ) + A 2 cos(ω 2 t + α


( ) ) ) ) 5) 1 J = σe 2 6) ) 9) 1955 Statistical-Mechanical Theory of Irreversible Processes )

pdf

KENZOU

(Bessel) (Legendre).. (Hankel). (Laplace) V = (x, y, z) n (r, θ, ϕ) r n f n (θ, ϕ). f n (θ, ϕ) n f n (θ, ϕ) z = cos θ z θ ϕ n ν. P ν (z), Q ν (z) (Fou

Part () () Γ Part ,

f(x) = f(x ) + α(x)(x x ) α(x) x = x. x = f (y), x = f (y ) y = f f (y) = f f (y ) + α(f (y))(f (y) f (y )) f (y) = f (y ) + α(f (y)) (y y ) ( (2) ) f

Black-Scholes [1] Nelson [2] Schrödinger 1 Black Scholes [1] Black-Scholes Nelson [2][3][4] Schrödinger Nelson Parisi Wu [5] Nelson Parisi-W

第5章 偏微分方程式の境界値問題

1 1. x 1 (1) x 2 + 2x + 5 dx d dx (x2 + 2x + 5) = 2(x + 1) x 1 x 2 + 2x + 5 = x + 1 x 2 + 2x x 2 + 2x + 5 y = x 2 + 2x + 5 dy = 2(x + 1)dx x + 1

x () g(x) = f(t) dt f(x), F (x) 3x () g(x) g (x) f(x), F (x) (3) h(x) = x 3x tf(t) dt.9 = {(x, y) ; x, y, x + y } f(x, y) = xy( x y). h (x) f(x), F (x

1 X X A, B X = A B A B A B X 1.1 R R I I a, b(a < b) I a x b = x I 1.2 R A 1.3 X : (1)X (2)X X (3)X A, B X = A B A B = 1.4 f : X Y X Y ( ) A Y A Y A f

2011de.dvi

I 1

i

xia2.dvi

No δs δs = r + δr r = δr (3) δs δs = r r = δr + u(r + δr, t) u(r, t) (4) δr = (δx, δy, δz) u i (r + δr, t) u i (r, t) = u i x j δx j (5) δs 2


III Kepler ( )

x,, z v = (, b, c) v v 2 + b 2 + c 2 x,, z 1 i = (1, 0, 0), j = (0, 1, 0), k = (0, 0, 1) v 1 = ( 1, b 1, c 1 ), v 2 = ( 2, b 2, c 2 ) v

y π π O π x 9 s94.5 y dy dx. y = x + 3 y = x logx + 9 s9.6 z z x, z y. z = xy + y 3 z = sinx y 9 s x dx π x cos xdx 9 s93.8 a, fx = e x ax,. a =

微分積分 サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます. このサンプルページの内容は, 初版 1 刷発行時のものです.

Untitled

変 位 変位とは 物体中のある点が変形後に 別の点に異動したときの位置の変化で あり ベクトル量である 変位には 物体の変形の他に剛体運動 剛体変位 が含まれている 剛体変位 P(x, y, z) 平行移動と回転 P! (x + u, y + v, z + w) Q(x + d x, y + dy,

1 filename=mathformula tex 1 ax 2 + bx + c = 0, x = b ± b 2 4ac, (1.1) 2a x 1 + x 2 = b a, x 1x 2 = c a, (1.2) ax 2 + 2b x + c = 0, x = b ± b 2

³ÎΨÏÀ

(2 X Poisso P (λ ϕ X (t = E[e itx ] = k= itk λk e k! e λ = (e it λ k e λ = e eitλ e λ = e λ(eit 1. k! k= 6.7 X N(, 1 ϕ X (t = e 1 2 t2 : Cauchy ϕ X (t

I, II 1, A = A 4 : 6 = max{ A, } A A 10 10%

1 1 sin cos P (primary) S (secondly) 2 P S A sin(ω2πt + α) A ω 1 ω α V T m T m 1 100Hz m 2 36km 500Hz. 36km 1

2 1 x 2 x 2 = RT 3πηaN A t (1.2) R/N A N A N A = N A m n(z) = n exp ( ) m gz k B T (1.3) z n z = m = m ρgv k B = erg K 1 R =

(1.2) T D = 0 T = D = 30 kn 1.2 (1.4) 2F W = 0 F = W/2 = 300 kn/2 = 150 kn 1.3 (1.9) R = W 1 + W 2 = = 1100 N. (1.9) W 2 b W 1 a = 0


W u = u(x, t) u tt = a 2 u xx, a > 0 (1) D := {(x, t) : 0 x l, t 0} u (0, t) = 0, u (l, t) = 0, t 0 (2)

untitled

2

24 I ( ) 1. R 3 (i) C : x 2 + y 2 1 = 0 (ii) C : y = ± 1 x 2 ( 1 x 1) (iii) C : x = cos t, y = sin t (0 t 2π) 1.1. γ : [a, b] R n ; t γ(t) = (x

A B P (A B) = P (A)P (B) (3) A B A B P (B A) A B A B P (A B) = P (B A)P (A) (4) P (B A) = P (A B) P (A) (5) P (A B) P (B A) P (A B) A B P

st.dvi

構造と連続体の力学基礎

Transcription:

43433 8 3

. Stochastic exponentials...................................... 3. Girsanov s theorem......................................... 4 On the martingale property of stochastic exponentials 5. Gronwall s inequality........................................ 5. The Martingale property...................................... 6 3 Applications and examples 7 3. A classical example........................................ 7 3. Feller s test for exposion and McKean s claim.......................... 3.3 A counterexample to McKean.................................. 5 5

3 3 3. 3. Feller s test McKean 3.3 McKean

Definition.. {F t Ω, F F σ {F t ; t F s F t F s < t < Definition.. {F t Ω, F T {T F t t Definition.3. t A BR d {s, ω; s t, ω Ω, X s ω A σ B[, t] F t s, ω X s ω : [, t] Ω, B[, t] F t R d, BR d t X {F t Definition.4. Wiener Xt t Wiener Wiener process Brownian motion process X = Xt t t < t < < t k < Xt Xt Xt 3 Xt 3 s < t Xt Xs, σ t s 4 Xt sample path Definition.5. X = {X t, F t t < s < t < P EX t F s X s EX t F s X s {X t, F t t < Definition.6. X = {X t, F t t < {F t {T n n= {X n t X t Tn, F t t < n P lim n T n = = X

. Stochastic exponentials Definition.7. Ω, F, P t [, T ] d Wiener {W t {F t { Z X t = exp Xu dw u Z X =, Xu du Xt R d F t,. Z X t M X t E[Z X T ] = Xu du τ M X τ M X = lim τ M X. t τ M X = inf t R + Xu du inf = τ M X {F t τ M X t T Xt = Xτ M X =,, τ M X Xu dw u t [, τ M X Xu dw u Lemma.8. {Xt d F t T P Xt dt C = C. Z X t [ Kallianpur 98, Section 7. ] 3

. Girsanov s theorem Theorem.9.. Z X t W = { W t, F t ; t < W t = W t Xsds t < T [, { W t, F t ; t < T Ω, F T, P T d Brown [ I. Karatzas and S. E. Shreve, Section 3.5 ] 4

On the martingale property of stochastic exponentials. Gronwall s inequality Lemma.. αt, βt [a, b] Lebesgue H αt βt + H αt βt + H a αsds t [a, b] a e Ht s βsds At = αsds a gt = Ate Ht [a, b] g t d dt gt = αte Ht HAte Ht a.e. [a, b] g t βte Ht gt ga = g sds a a a.e., βse Hs ds t [a, b]. gt ga = Ate Ht Aa e Ha βse Hs ds {{ a = At e Ht βse Hs ds = βse Ht s ds a a αt βt + H αsds a {{ =At αt βt + HAt βt + H a βse Ht s ds βt B a e Ht s ds = e Ht a αt B + BH a e Ht s ds [ e Hs ds = e Ht ] t H e Hs = a H e Ht a αt B B e Ht a = Be Ht a 5

. The Martingale property Theorem.. b C R b R Wiener {W t ; t X t = bx s ds + W t, X = a.s., F W t τ b [τ b > a.s.] [t, ω : t < τ b ω] X t ω τ b, X. X t ω = bx sωds + W t ω, t τ b ω a.s.. a.a. ω, t X t ω [, τ b ω t [, t] [ω; τ b ω > t] X B[, t] Ft W 3. lim sup t τ b ω X t ω = {ω Ω τ b ω < =,, 3, b C R X t, ω b = b on [, ] b = on, ] [ +, ξ t = b ξ s ds + W t τ = inf {t Xt = τ F t W σ = τ τ + X + t σ = = X t σ = I [,σ ]txt σ + Xt σ = I [,σ ]t I [,σ ]sb + Xs + ds + W t σ I [,σ ]sbx + s ds + W t σ I [,σ ]sbx s ds + W t σ I [,σ ]s[bxs + bxs ]ds E I [,σ ]t Xt σ + Xt σ = E I [,σ ]t t I [,σ ]s[bxs + bxs ]ds 6

= E I [,σ ]t X t σ + Xt σ = E I [,σ ]t I [,σ ]s[bxs + bxs ]ds I [,σ ]t E Schwarz E ds = t E I [,σ ]s[bx + s bxs ]ds I [,σ ]s bx s + bxs ds I [,σ ]s bx s + bxs ds ϕt = E I [,σ ]t X t σ + Xt σ ϕ [, ϕt te I [,σ ]s bx s + bxs ds t [, σ ] t > σ ϕt = s [, σ ] bx s + bxs = b c X s + Xs, c + c ω sup x + b x = K [, T ] ϕt T K ϕsds Remark ϕt = t E I [,σ ]t X + t X t = X t X t + [, σ ω] X t + ω = Xt a.s. σ ω = τ ω = τ + ω = σ ω < t [, σ ω] t ω = Xt ω X + {t Xt = φ {t Xt + + = φ Xt + ω = Xt ω {t Xt + = φ τ + ω τ + ω > σ ω σ ω = τ ωa.s. ω a.a. τ ω τ + ω τ ω < τ ω < τ + ω τ τ τa.s. τ Ft W t < τ ω X t ω = X t ω X [t, ω : t < τω] τ τ b τ τ b = τ > a.s. τ > a.s. ω a.a. X t < τω t τ ω < τω X u = u b X s ds + W u 7 u τ ω

Xs b b Xs = bxs s τ ω< τω X s ω = X s ω u [, τ ω] X u = u = t u bx s ds + W u t s, ω [, t] [ω Ω τω > t] X s [, τ ω] X s = X s Xs, ωi [,t] [ω τ ω>t]s, ω = X s, ωi [,t] [ω τ ω>t]s, ω Xs, ωi [,t] [ω τ ω>t]s, ω B[, t] Ft W B[, t] Ft W - - Xs, ωi [,t] [ω τ ω>t]s, ω b 3 τω < τ ω < X τ ωω = Xτ ωω = {ω τω < lim sup t τω X t ω = τ, X 3 a.a. ω u < τ τ u X u ω u X uω η u = u bη s ds + W u u < τ τ X u = u bx sds + W u, X u = u bx sds + W u X u X u = u [bx s bx s] ds inf{u X u + X u τ = T 8

τ F t = I [,τ ]t X u τ X u τ = It u τ = u [bx s bx s] ds I [,τ ]s [bx s bx s] ds {{ = Is I u X u X u = I u X u τ X u τ u / [, τ ] u [, τ ]= u τ u τ = u = I u u I s [bx s bx s]ds It Iu = It u t E It sup X u X u = E sup It X u X u u t u t = E sup It Iu X u X u E It I t = E u t I t u t sup Iu X u X u u t E sup Iu X u X u u E sup Iu Is [bx s bx s]ds u t {{ = sup Iu u t sup u t Schwarz T u sup X u X u T E u t u Is [bx s bx s]ds u Is bx s bx s ds ds u I s bx s bx s ds I s bx s bx s ds Is bx s bx s ds Fubini σ = bx s bx s K X s X s T K E Is sup X u X u ds. u s φt = EIt sup u t X u X u It φt < φt T K 9 φsds

Lemma. t φt = I T E IT sup X u X u =. u T sup X u X u = a.s.. u T ω Λ { Λ = ω Ω I [,τ ω]t sup X u ω X uω = { ω u T sup X u ω + X uω < Λ u T {{ ω {u X u + X u =φ τ ω=t { ω sup X u ω X uω > u T { P ω sup X u ω X uω > P u T { ω { ω P Λ = = P Λ c = { P ω sup X u ω X uω > P u T { ω sup X u ω X uω = u T sup u T X u ω + X uω Λ c sup u T X u ω + X uω + P Λ c { ω { P ω sup X u ω X uω > = u T sup X u ω + X uω u T P {ω X u ω = X uω, u < τω τ ω = τω < lim sup X t ω = t τω τω = τ ω a.s. a.a. ω [, τω X t ω = X tω.

Remark ϕt = t [, T ], ϕt T K ϕt dt ϕt T K t ϕt dt ϕt T K T K.. T K n ϕt dt ϕt dt dt n ϕt n dt n dt n ϕt n dt n dt = n! ϕt n t t n n dt n ϕt T K n n! T T K n n! ϕt n t t n n dt n {{ T n = T K T K n n! n ϕt n dt n ϕt n dt n ϕt =

Theorem.3. X = X t Theorem. part T > A B T C T P X A, τ b > T = exp bw s dw s T b W s ds dp. {W A A B T C B B T C B = {x C x A, xs <, s T, [,T ] {x C xs, B T C B = A, [,T ] b Theorem. X τ P X B = = {W B T exp b W s dw s T b W s ds dp T exp bw s dw s T b W s ds dp. {W A, W s <, s T Remark. P X A, τ b > T = {X B = {X A, X s <, s T = {X A, X s <, T < τ = {X A, X s <, T < τ {W A T exp bw s dw s T b W s ds dp

ξb t = exp bw s dw s. A = C T P τ b > T = exp bw s dw s b W s ds T b W s ds = E P ξ T b.3 T P τ b > T P τ b =.3 P τ b < > T E P ξ T b < ε > M ε > s.t. T > M ε < ε < P τ b = = E P ξ T b P τ b = < ε P τ b = ε < E P ξ T b < P τ b = + ε < E P ξ T b < dp P τ b < = E P ξ T b = Remark b C R X t t [, T ] X t = bx s ds + W t Ft X = Ft W Theorem.9 X t, Ft W, P Wiener P P P Ω, FT W Radon-ikodym derivative { dp T = exp bx s dx s T b d P X s ds A B T C P X A = = {X A {W A { T exp bx s dx s { T exp bw s dw s T T b X s ds b W s ds d P dp 3

Proposition.4.. τ M X d F t Xt = ξ W, t τ M Y d F t Y t = ξ W + Y udu, t τ M Y = lim τ M Y t τ M Y = inf t R + Y u du M Y t = Y u du { M t τ X Z X t τ M X = exp [,τ M X { = exp ]u Xu = X u Xu dw u τ M X h i,τ M X u XudW u { = exp X udw u = Z X t Y u du Xu du h i,τ M X u Xu du Lemma.8 P Q A F T Q X A = E P [Z X T {X A] Theorem.9 W Q t = W t X udu.4 R d Q {t τ M X X t = ξ W Q + X udu, t P P Y t = ξ W P + τ M Y τ M Y τ M Y Y udu, t P Y t = ξ W + Y udu, t P Y t = ξ W + Y udu, t 4

Theorem. Theorem.5. Proposition.4 Xt, Y t R d F t { T Z X T = exp Xt dw t T Xt dt P τ M Y > T = E P [Z X T ] Z X T P τ M Y > T = Definition.6. P Xt candidate measure : Q C Z X t P - Q C X A = E P [ ZX T {X A ], A F T Definition.6 Corollary.7. Z X t P - Xt = ξ W QC t + t Xudu, t Q C τ M X > T = Theorem.5 E P [Z X T ] = P τ M Y > T = Q C τ M X > T Z X t E P [Z X T ] = Q C τ M X > T = 5

Xt SDE η X = lim ηx, η X = inf t R + sup i=,,d X i t X i t i =,, d Xt Corollary.8. Xt µx, t R d σx, t R d r µx, t, σx, t X dxt = µx, tdt + σx, t dw t.5 E P [Z X T ] = Q C η X > T, dxt = µx, t + σx, t Xtdt + σx, t dw QC t SDE Q C τ M X > T = Q C dw t = Xtdt + dw QC t sup X i t = t T ;i=,,d = Q C η X > T dxt = µx, tdt + σx, t dw QC t + Xtdt = µx, t + σx, t Xtdt + σx, t dw QC t 6

3 Applications and examples 3. A classical example Lemma 3. BESQ3 dzt = 3dt + ZtdW t, Z = z Ut = Zt / L Ut = Zt Bt = W t dut = Zt 3 ZtdW t = Zt dw t = Ut dw t = Ut dbt Ut Ut a.s. Ut L Bessel Zt = W t + W t + W 3 t, W t, W t, W 3 t t = W = W = W 3 = t > Ut L E[Ut ] = E[Zt ] [ ] = E W t + W t + W 3 t = t < dut = Ut dbt { Ut = U exp UsdBs λt = Ut = U Z λ t Us ds 3 7

Corollary.8 Ut dxt = Xt db QC t + Xt 3 dt Q C a.s. Bessel R t ω = B t, ω + B t, ω + B 3 t, ω dr t = dt + 3 B i tdb i t R t R t R t dr t = dt + i= 3 B i tdb i t i= drt = db t, ω + B t, ω + B 3 t, ω 3 = d B i t i= d B i t = B i tdb i t + dt 3 = B i tdb i t + 3dt Y t R t = Z t i= = R t 3 i= 3 i= B i t db i t + 3dt R t B i s db i s Bt Bt Brown R s dz t = 3dt + Z t d B t BESQ3 square of a 3-dimensional Bessel process R x + y + z dp W t,w t,w 3 tx, y, z 3 W t, W t, W 3 t dp Wt,W t,w 3tx, y, z = dp Wtx dp Wtx dp W3tx 3 = exp x πt t y t z dxdydz t 8

x = r sin θ sin ϕ, y = r sin θ cos ϕ, z = r cos θ < r <, < θ < π, < ϕ < π π π 3 r exp πt dxdydz = r sin θdrdϕdθ r r sin θdrdϕdθ = t = = t πt πt π πt πt π sin θdθ πt π dϕ exp r dr t 3 dut = Ut dbt dut Ut = UtdBt dlog Ut dlog Ut = Ut dut + Ut dut {{ =Ut 4 dt = dut Ut Ut dt = UtdBt Ut dt t dlog Ut = {{ =log Ut log U UsdBs Us ds log Ut t U = UsdBs Us ds { Ut t U = exp UsdBs { Ut = U exp UsdBs Us ds Us ds Ut 9

3. Feller s test for exposion and McKean s claim Feller s test for explosions e f C R dx t = ex t db t + fx t dt q : R R x qx = u exp x exp u fv ev dv du x fv ev dv du x < q = f/e q q = Y t = qx t dy t = ˆσY s dw s ˆσ = q q Feller s test [qx q ][q x] dx = [q qx][q x] dx = X P τ = = x > qx = q qx = x x q x = exp [q qx][q x] dx = u exp exp x x exp u fv ev dv du fv ev dv du fv ev dv = exp u x x fv ev dv dudx fv ev dv x < qx = x qx q = exp x q x = exp [qx q ][q x] dx = exp x x exp u fv ev dv du fv u ev dv fv ev dv x u du x = exp fv ev dv dudx fv ev dv

McKean s claim σ µ C R dxt = µxdt + σxdw t on Ω, F, P dxt = σxdw Q t on Ω, F, Q ± P Q Radon-ikodym Z µ/σ T = exp { T µx σx dw u T µx σx du P -.

3.3 A counterexample to McKean Proposition 3.. Brown Brown 3 Brown r < x, τ r inf{t > ; B t r d = P τ r < = d r d 3 x BESQ3 dx = 3dt + XdW t on Ω, F, P dx = XdW Q t on Ω, F, Q Feller s test dx = 3dt + XdW t x > x u exp x 3 4v dv dudx = = = = = x exp exp x x 3 x x 3 u 3 x 3 log u x u 3 dudx x dx xdx = dv dudx v dudx x < x 3 x exp u dv dudx = v = = x x x 3 x 3 = 3 exp log x u u 3 dudx x dx xdx = dudx

dx = XdW Q t x > x u exp x 4v dv dudx = = x dudx x < x x x exp u 4v dv dudx = dudx = McKean P Q Lemma 3. Xt = W t + W t + W 3 t W t, W t, W 3 t 3 Brown Proposition 3. P t > ; Xt > > dx = XdW Q t Xt > d X = X dx 4X X dx = X XdW Q t 4X X 4Xdt = dw Q t X dt t d ds t X + = dw Q s Xs ds Xt X + = W Q t Xs Xt + ds Xs = W Q t + X t > Q t > ; Xt = = P Q McKean 3

Corollary.8 P Q 3 Y t = Xt P Q P X Q { absorbing Z Y T = exp { T Y tdw t T Y t dt P - McKean McKean 4

[] BERARD WOG and C. C. HEYDE O THE MARTIGALE PROPERTY OF STOCHASTIC EXPOETIALS J. Appl. Prob. 4, 654-664 4 [] H. P. McKean Stochactic Integrals Academic Press 969 [3] I. Karatzas and S. E. Shreve Brownian Motion and Stochastic Calculus [4] Bernt Øksendal Stochactic Differential Equations An Introduction with Applications 999 [5] D. REVUZ and M. YOR Continuous Martingales and Brownian Motion,3rd edn Springer ew York 999 [6] H. Kallianpur Stochastic Filtering Theory Springer ew York 98 [7] 967 5