APPENDIX D
... data is such that a cost of equity estimate produced by any asset pricing model -- whether the traditional CAPM or their three-factor CAPM -- is subject to wide error: “We do not take a stance on which is the right asset pricing model. Instead we use both the CAPM and our three-factor model to estim ...
... data is such that a cost of equity estimate produced by any asset pricing model -- whether the traditional CAPM or their three-factor CAPM -- is subject to wide error: “We do not take a stance on which is the right asset pricing model. Instead we use both the CAPM and our three-factor model to estim ...
Binary Search Tree
... after the initial call of Inorder_Tree_Walk the following is true: for each of the (n -1) “not-NIL” nodes of the tree there are exactly two calls of Inorder_Tree_Walk – one for its left child and one for its right child (for details see [Corman]) ...
... after the initial call of Inorder_Tree_Walk the following is true: for each of the (n -1) “not-NIL” nodes of the tree there are exactly two calls of Inorder_Tree_Walk – one for its left child and one for its right child (for details see [Corman]) ...
Victory CEMP US 500 Enhanced Volatility Wtd Index Fund
... Conversely, if rates fall, the value of the fixed income securities generally increases. The Fund is not actively managed and does not, therefore, seek returns in excess of the Index. The Fund’s return may not match the return of the Index. The value of the equity securities in which the Fund invest ...
... Conversely, if rates fall, the value of the fixed income securities generally increases. The Fund is not actively managed and does not, therefore, seek returns in excess of the Index. The Fund’s return may not match the return of the Index. The value of the equity securities in which the Fund invest ...
PowerPoint
... Insertion into a full node causes a split into two nodes which may propagate to higher tree levels Note: if there are n search-key values to be split, put the first ( (n1)/2 in the existing node & the remaining in a new node ...
... Insertion into a full node causes a split into two nodes which may propagate to higher tree levels Note: if there are n search-key values to be split, put the first ( (n1)/2 in the existing node & the remaining in a new node ...
2. Basics of Options
... The seller of a call option is said to write a call, and he receives the options price called a premium. He has an obligation to deliver the underlying asset on the expiration date (European), for the exercise price which may be lower than the market value of the asset. The payoff of a short call po ...
... The seller of a call option is said to write a call, and he receives the options price called a premium. He has an obligation to deliver the underlying asset on the expiration date (European), for the exercise price which may be lower than the market value of the asset. The payoff of a short call po ...
Chapter 20
... • Visit order: left subtree, right subtree, node • We must indicate to the node whether the left and right subtrees have been visited − Solution: other than saving a pointer to the node, save an integer value of 1 before moving to the left subtree and value of 2 before moving to the right subtree − ...
... • Visit order: left subtree, right subtree, node • We must indicate to the node whether the left and right subtrees have been visited − Solution: other than saving a pointer to the node, save an integer value of 1 before moving to the left subtree and value of 2 before moving to the right subtree − ...
U1S09_Su10_Lesson_04 - U1S09-2010
... Small companies who are within the first three levels of selling abroad (Domestic, Intermittent and Export) may avoid exchange rate volatility by simply requiring payment in their own local currency. ...
... Small companies who are within the first three levels of selling abroad (Domestic, Intermittent and Export) may avoid exchange rate volatility by simply requiring payment in their own local currency. ...
CS2007Ch13B
... paths from each of these nodes to its neighbors, and so on Nodes that have been visited but not explored are kept in a (ready) queue, so that when we are ready to move to a node adjacent to the current node, we will be able to return to another node adjacent to the old current node after our move ...
... paths from each of these nodes to its neighbors, and so on Nodes that have been visited but not explored are kept in a (ready) queue, so that when we are ready to move to a node adjacent to the current node, we will be able to return to another node adjacent to the old current node after our move ...
data structure
... A stack is a data-structure in which elements are stored and retrieved by: a. FIFO method b.LIFO method c. FCFS method d. None of the above Q3. The different types of arrays are: a. One & Multi-dimensional b. int and float c. int,char,float d. One & Two dimensional Q4. An array is passed into a func ...
... A stack is a data-structure in which elements are stored and retrieved by: a. FIFO method b.LIFO method c. FCFS method d. None of the above Q3. The different types of arrays are: a. One & Multi-dimensional b. int and float c. int,char,float d. One & Two dimensional Q4. An array is passed into a func ...
Range and multidimensional searches
... Nearest(Neighbor(Search( • Steps:( – 1.(Start(with(root(node(and(use(depth3first(search(to( find(where(you(would(insert(the(node(if(you(were( inser8ng(it.(Save(this(as(current(best( – 2.(Go(up(one(node.(If(it’s(befer(than(closest(best,(it( becomes(closest(best.(( – 3.(Check(whether(there(could(be ...
... Nearest(Neighbor(Search( • Steps:( – 1.(Start(with(root(node(and(use(depth3first(search(to( find(where(you(would(insert(the(node(if(you(were( inser8ng(it.(Save(this(as(current(best( – 2.(Go(up(one(node.(If(it’s(befer(than(closest(best,(it( becomes(closest(best.(( – 3.(Check(whether(there(could(be ...
PROGRAM ON HOUSING AND URBAN POLICY CONFERENCE PAPER SERIES
... Modigliani 1963). But when expectations about wealth change, either because of a particularly large positive realization of a distribution of potential wealth outcomes, or because expectations change, wealth can influence consumption. We should also note that even if stock prices do not affect consu ...
... Modigliani 1963). But when expectations about wealth change, either because of a particularly large positive realization of a distribution of potential wealth outcomes, or because expectations change, wealth can influence consumption. We should also note that even if stock prices do not affect consu ...
Document
... where n! is the factorial of n. (There are n! combinations to arrange n distinct objects in a list. However n→ objects are indistinguishable and therefore the number of combinations is reduced by a factor of n→! Due to a similar reason, the number ! must be further divided by n→!.) Let’s assume that ...
... where n! is the factorial of n. (There are n! combinations to arrange n distinct objects in a list. However n→ objects are indistinguishable and therefore the number of combinations is reduced by a factor of n→! Due to a similar reason, the number ! must be further divided by n→!.) Let’s assume that ...
Tree
... deletions take at most O(logn) time Remember binary trees have a worst case of O(n) when a chain occurs. In fact it can be proven using fibonacci trees that AVL trees are at worst 44% less efficient than complete trees. Proof not required for course, but can be found in text books. CS121 © JAS 2005 ...
... deletions take at most O(logn) time Remember binary trees have a worst case of O(n) when a chain occurs. In fact it can be proven using fibonacci trees that AVL trees are at worst 44% less efficient than complete trees. Proof not required for course, but can be found in text books. CS121 © JAS 2005 ...
Lecture 11
... – Insert as in a normal binary search tree, but go back up the tree and update the balance factor of each node back towards the root. – “Go back up the tree” -> do something after the recursive call / on the “pop”. – If the balance factor becomes +2 or -2, rotate to correct it. – Four different case ...
... – Insert as in a normal binary search tree, but go back up the tree and update the balance factor of each node back towards the root. – “Go back up the tree” -> do something after the recursive call / on the “pop”. – If the balance factor becomes +2 or -2, rotate to correct it. – Four different case ...
PPT on Frac_Casc
... We are given a polygonal path P and we wish to preprocess it into a data structure so that given any query line l, we can quickly report all the intersections of P and l. The idea is based on recursive application of the following: ...
... We are given a polygonal path P and we wish to preprocess it into a data structure so that given any query line l, we can quickly report all the intersections of P and l. The idea is based on recursive application of the following: ...
Randomized Binary Search Trees
... I’ll assume from now on that all the keys and priorities are distinct. Under this assumption, we can easily prove by induction that the structure of a treap is completely determined by the search keys and priorities of its nodes. Since it’s a heap, the node v with highest priority must be the root. ...
... I’ll assume from now on that all the keys and priorities are distinct. Under this assumption, we can easily prove by induction that the structure of a treap is completely determined by the search keys and priorities of its nodes. Since it’s a heap, the node v with highest priority must be the root. ...
Derivatives pricing when one cannot borrow at the risk free rate
... • The way that derivatives are valued and risk managed is often strongly dependent on what credit risks and funding commitments are embedded in the payoffs. • We will explore these issues for uncollateralised derivatives concentrating on valuation and risk management, and show how conventional prici ...
... • The way that derivatives are valued and risk managed is often strongly dependent on what credit risks and funding commitments are embedded in the payoffs. • We will explore these issues for uncollateralised derivatives concentrating on valuation and risk management, and show how conventional prici ...
Class Notes for Week 4
... Given a node i in the heap with children l and r. Each sub-tree rooted at l and r is assumed to be a heap. The sub-tree rooted at i may violate the heap property [ key(i) > key(l) OR key(i) > key(r) ] Thus Heapify lets the value of the parent node “float” down so the sub- tree at i satisfies the hea ...
... Given a node i in the heap with children l and r. Each sub-tree rooted at l and r is assumed to be a heap. The sub-tree rooted at i may violate the heap property [ key(i) > key(l) OR key(i) > key(r) ] Thus Heapify lets the value of the parent node “float” down so the sub- tree at i satisfies the hea ...
COMP171H Notes: Hashing
... Single rotation for “outside” insertion Double rotation for “inside” insertion ...
... Single rotation for “outside” insertion Double rotation for “inside” insertion ...
Lattice model (finance)
For other meanings, see lattice model (disambiguation)In finance, a lattice model [1] is a technique applied to the valuation of derivatives, where, because of path dependence in the payoff, 1) a discretized model is required and 2) Monte Carlo methods fail to account for optimal decisions to terminate the derivative by early exercise. For equity options, a typical example would be pricing an American option, where a decision as to option exercise is required at ""all"" times (any time) before and including maturity. A continuous model, on the other hand, such as Black Scholes, would only allow for the valuation of European options, where exercise is on the option's maturity date. For interest rate derivatives lattices are additionally useful in that they address many of the issues encountered with continuous models, such as pull to par.