This is about financial time series. Please write down in details. Thanks.

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Consider analyze the transaction data using the decomposition model for the price change. In particular, we use logistic regression to estimate the following models logit(Pi) = Bo + B1A;1 + B2 Di-1, = = logit(di) = 40 + 71 Di-1, where Pi P(A; = 1|Fi-1), di = P(D; = 1|A; = 1, Fi-1), and Fi-1 denotes the information available at the 1th transaction. The outputs are attached. (a) What is the probability pi if Ai-1 = 0? What is the probability pi if Ai-1 = 1 and Di-1 = -1? Show computations. (4 points) = -1 =- = = (b) What is the probability di when Ai-1 = Di-1 1? What is the probability P(Di -1|A; = 1, Fi-1) when Ai-1 = 1 and Di-1 computations. (4 points) = = = -1? Show N = a > m1=glm(a^am1+dm1, family=binomial) > summary (m1) Call: glm (formula am 1 + dm1, family = binomial) Coefficients: Estimate Std. Error z value Pr(>[z]) (Intercept) -0.15659 0.05636 -2.778 0.00546 ** am1 0.84506 0.07622 11.087 m2=glm (ddm1, family=binomial) > summary (m2) Call: glm (formula = d dm1, family Coefficients: = binomial) 4 (Intercept) dm 1 Estimate Std. Error z value Pr(>[z]) 0.20289 0.04980 4.074 4.61e-05 *** -0.59561 0.06204 -9.600 m1=glm(a^am1+dm1, family=binomial) > summary (m1) Call: glm (formula am 1 + dm1, family = binomial) Coefficients: Estimate Std. Error z value Pr(>[z]) (Intercept) -0.15659 0.05636 -2.778 0.00546 ** am1 0.84506 0.07622 11.087 m2=glm (ddm1, family=binomial) > summary (m2) Call: glm (formula = d dm1, family Coefficients: = binomial) 4 (Intercept) dm 1 Estimate Std. Error z value Pr(>[z]) 0.20289 0.04980 4.074 4.61e-05 *** -0.59561 0.06204 -9.600