Convexity Contribution To Return
A bond has modified duration 7 and convexity 90. For a yield increase of 150 basis points, what is the convexity adjustment alone (the second-order term) as a percentage of price?
打开 →GLOBAL SEARCH
搜索在服务端完成,题目解析与答案不会进入搜索结果。登录后可搜索自己的收藏题单。
找到 30 个结果
中文题目A bond has modified duration 7 and convexity 90. For a yield increase of 150 basis points, what is the convexity adjustment alone (the second-order term) as a percentage of price?
打开 →The utilization cap is tighter, but the same barrier argument applies. Show that r(x) = -ln(1-3x) + 2x^2 is convex on x < 0.333333.
打开 →Show that H(w_1,w_2)=2w_1^2+5w_2^2+3(w_1+w_2)^2 is convex.
打开 →Show that ell(z)=ln(1+e^{-z}) is convex on R.
打开 →Show that ell(r)=ln cosh(r) is convex in the residual r.
打开 →A bond has current price 102, modified duration 4.3, and convexity 18. Using the duration-convexity approximation, what price do you estimate after a yield change of 0.01?
打开 →A bond has current price 98.5, modified duration 3.1, and convexity 11. Using the duration-convexity approximation, what price do you estimate after a yield change of -0.015?
打开 →A bond has current price 105.2, modified duration 5.5, and convexity 25. Using the duration-convexity approximation, what price do you estimate after a yield change of 0.02?
打开 →A bond has current price 99, modified duration 2.8, and convexity 9. Using the duration-convexity approximation, what price do you estimate after a yield change of -0.01?
打开 →Why is positive convexity generally good for a bond holder when rates move a lot in either direction?
打开 →The cost couples size and trading time through a perspective form. Show that P(x,t)=x^2/t + 3 t is convex on the domain t>0.
打开 →One stress term slopes down and the other slopes up, but the smooth envelope remains convex. Show that g(x) = ln(exp(-1x) + exp(3x + 0)) is convex on R.
打开 →The desk wants a direct curvature argument, not a vague appeal to 'it looks bowl-shaped'. Show that f(q) = 3 q^2 + 1/(1-q) is strictly convex on q<1.
打开 →Why do KKT conditions become sufficient, not just necessary, in many convex optimization problems?
打开 →Why do trading desks care whether an execution-cost model is convex rather than merely smooth?
打开 →Why does convexity of a loss function support the intuition that averaging similar predictors often cannot hurt too much?
打开 →Use dP/P ~= -D*dy + 0.5*C*dy^2. If D=6, C=80, and dy=0.01, what percentage price move is implied?
打开 →For equally spaced strikes 100, 110, 120, calls trade at 11.5, 8.4, and 5.8. How much could the middle call price rise before butterfly convexity is first violated?
打开 →For equally spaced strikes 90, 100, 110, call prices at the wings are C(90)=18.2 and C(110)=8.1. What is the largest arbitrage-free value the middle call C(100) can take under butterfly convexity?
打开 →For equally spaced strikes 80, 100, 120, call prices at the wings are C(80)=26 and C(120)=7. What is the largest arbitrage-free value the middle call C(100) can take under butterfly convexity?
打开 →For equally spaced strikes 85, 95, 105, calls trade at 20, 14.8, and 10.5. How much could the middle call price rise before butterfly convexity is first violated?
打开 →The blow-up term is steeper, but the same convexity logic should still go through. Show that f(q) = 2 q^2 + 4/(1-q) is strictly convex on q<1.
打开 →The PM wants a formal convexity check before using the function in an optimizer. Show that f(q) = 5 q^2 + 2/(1-q) is strictly convex on q<1.
打开 →The third sleeve is much more expensive on its own, but the aggregate term still preserves convexity. Prove that F(w_1,w_2,w_3) = 1w_1^2 + 4w_2^2 + 9w_3^2 + 2(w_1+w_2+w_3)^2 is convex.
打开 →Use a second-order Taylor approximation around 0 to estimate (1+3x)^(2) * (1+1x)^(-1) at x=1/40.
打开 →Both the quadratic inventory term and the capacity wall are active sources of curvature. Show that f(q) = 4 q^2 + 3/(1-q) is strictly convex on q<1.
打开 →For equally spaced strikes 95, 100, 105, calls trade at 14, 12.5, and 10. By how much must the middle call price be reduced to remove the butterfly arbitrage?
打开 →Explain complementary slackness in plain language to a PM who thinks of constraints as scarce resources.
打开 →A schedule pays a quadratic cost but also faces a blow-up term as it nears a hard capacity cap. Show that f(q) = 1 q^2 + 2/(1-q) is strictly convex on q<1.
打开 →The margin term grows smoothly but sharply as the leverage coordinate approaches its cap. Show that r(x) = -ln(1-1x) + 3x^2 is convex on x < 1.
打开 →