Data Structures So Far
... remove(e): Remove from P and return entry e. replaceKey(e,k): Replace with k and return the old key; an error condition occurs if k is invalid (that is, k cannot be compared with other keys). replaceValue(e,x): Replace with x and return the old ...
... remove(e): Remove from P and return entry e. replaceKey(e,k): Replace with k and return the old key; an error condition occurs if k is invalid (that is, k cannot be compared with other keys). replaceValue(e,x): Replace with x and return the old ...
08 Managing Financial Risk
... Commodity risk is the uncertainty about the value of widely used commodities such as gold, silver, etc. Equity risk is the uncertainty about the value of the ownership stakes, a firm has in other companies, real estate, etc. Market risk is typically measured using Value at Risk (VaR) which quantifie ...
... Commodity risk is the uncertainty about the value of widely used commodities such as gold, silver, etc. Equity risk is the uncertainty about the value of the ownership stakes, a firm has in other companies, real estate, etc. Market risk is typically measured using Value at Risk (VaR) which quantifie ...
Getting familiar with global portfolio hedging
... Currency forward contracts: The most common way to manage currency risk is with shortterm currency forward contracts. Currency forwards are agreements between two parties to buy and sell a currency pair at an agreed upon price on an agreed upon date in the future. Investors can manage currency risk ...
... Currency forward contracts: The most common way to manage currency risk is with shortterm currency forward contracts. Currency forwards are agreements between two parties to buy and sell a currency pair at an agreed upon price on an agreed upon date in the future. Investors can manage currency risk ...
Document
... • Self-adjusting trees get reorganized over time as nodes are accessed › Tree adjusts after insert, delete, or find ...
... • Self-adjusting trees get reorganized over time as nodes are accessed › Tree adjusts after insert, delete, or find ...
Lecture Notes on Optimal Control
... Moreover, when V t ( p) - p > - c , equation (2.1) tells us that b ò V t + 1( p + x )dF (x ) > p - c and it is not optimal to exercise the option. Thus, there exists a strike price, pt* , such that for any ...
... Moreover, when V t ( p) - p > - c , equation (2.1) tells us that b ò V t + 1( p + x )dF (x ) > p - c and it is not optimal to exercise the option. Thus, there exists a strike price, pt* , such that for any ...
Technical Prep
... value for the firm. The equity value divided by the number of diluted shares outstanding is the per share value. (Whew!!!) DCF results should be presented as a RANGE of estimated values, not a single estimate. DCF tends to be overvalued because of projections by management. Trading Comparables (Comp ...
... value for the firm. The equity value divided by the number of diluted shares outstanding is the per share value. (Whew!!!) DCF results should be presented as a RANGE of estimated values, not a single estimate. DCF tends to be overvalued because of projections by management. Trading Comparables (Comp ...
Chapter 2--Basic Data Structures
... – recursive method returning the value of a subtree – when visiting an internal node, combine the values of the subtrees ...
... – recursive method returning the value of a subtree – when visiting an internal node, combine the values of the subtrees ...
The NESTOR Framework: How to Handle Hierarchical
... models in conjunction with OAI-PMH overcomes many of these issues. The paper is organized as follows: Section 2 briefly defines the tree data structure. Section 3 defines the two proposed set data models and presents the mapping functions between the tree data structure and the set data models. Section ...
... models in conjunction with OAI-PMH overcomes many of these issues. The paper is organized as follows: Section 2 briefly defines the tree data structure. Section 3 defines the two proposed set data models and presents the mapping functions between the tree data structure and the set data models. Section ...
chap11
... Binary Search Tree Analysis • Theorem: Let T be a binary search tree with n nodes, where n > 0.The average number of nodes visited in a search of T is approximately 1.39 log2n • Number of comparisons required to determine whether x is in T is one more than the number of comparisons required to inse ...
... Binary Search Tree Analysis • Theorem: Let T be a binary search tree with n nodes, where n > 0.The average number of nodes visited in a search of T is approximately 1.39 log2n • Number of comparisons required to determine whether x is in T is one more than the number of comparisons required to inse ...
Performance Evaluation
... is split into two: half is modeled as being paid at the beginning (and thus needs to be compounded forward at the rate R), while the other half is modeled as being paid at the end and thus does not need any compounding since its "spot on the timeline" is the same as the final portfolio value P1. ...
... is split into two: half is modeled as being paid at the beginning (and thus needs to be compounded forward at the rate R), while the other half is modeled as being paid at the end and thus does not need any compounding since its "spot on the timeline" is the same as the final portfolio value P1. ...
Performance Evaluation
... is split into two: half is modeled as being paid at the beginning (and thus needs to be compounded forward at the rate R), while the other half is modeled as being paid at the end and thus does not need any compounding since its "spot on the timeline" is the same as the final portfolio value P1. ...
... is split into two: half is modeled as being paid at the beginning (and thus needs to be compounded forward at the rate R), while the other half is modeled as being paid at the end and thus does not need any compounding since its "spot on the timeline" is the same as the final portfolio value P1. ...
Efficient Pricing of Geo-Marketing Internet Services: European vs
... Geomarketing information is information that enables the user to take better and faster decisions about marketing and sales activities. The main sources of information are geographic, demographic, and statistical data. These data are usually collected and maintained by several institutions and come ...
... Geomarketing information is information that enables the user to take better and faster decisions about marketing and sales activities. The main sources of information are geographic, demographic, and statistical data. These data are usually collected and maintained by several institutions and come ...
Multiple choice questions Answer on Scantron Form
... 19. Consider the following four statements A. For a queue, "enqueue" and "dequeue" cancel each other out: an enqueue of any value followed by a dequeue leaves the queue in exactly the state it was in initially. B. assert( true ) at any point in a program will cause that program to immediately abort. ...
... 19. Consider the following four statements A. For a queue, "enqueue" and "dequeue" cancel each other out: an enqueue of any value followed by a dequeue leaves the queue in exactly the state it was in initially. B. assert( true ) at any point in a program will cause that program to immediately abort. ...
Final - Philadelphia University Jordan
... Objective: The aim of the questioning this part is to evaluate that student can solve familiar problems with ease and can make progress toward the solution of unfamiliar problems, and can set out reasoning and explanation in clear and coherent manner. Question6 (5 marks) ...
... Objective: The aim of the questioning this part is to evaluate that student can solve familiar problems with ease and can make progress toward the solution of unfamiliar problems, and can set out reasoning and explanation in clear and coherent manner. Question6 (5 marks) ...
Lecture Note 05 EECS 4101/5101 Instructor: Andy Mirzaian SKEW
... root is a minimum key in the tree, we can carry out findmin(h) in O(1) time by returning the key at the root; returning null if the heap is empty. We perform insert and deletemin using union. To carry out insert(k , h), we make k into a one-node heap and Union it with h. To carry out deletemin(h), i ...
... root is a minimum key in the tree, we can carry out findmin(h) in O(1) time by returning the key at the root; returning null if the heap is empty. We perform insert and deletemin using union. To carry out insert(k , h), we make k into a one-node heap and Union it with h. To carry out deletemin(h), i ...
T. ROWE PRICE® ActivePlus Portfolios Methodology
... performance and correlation of these asset classes over time. Correlation refers to the tendency of sub-asset classes to perform similarly or dissimilarly during a given economic cycle. Over certain periods, for example, the performances of investment-grade bonds and small-cap stocks have moved in r ...
... performance and correlation of these asset classes over time. Correlation refers to the tendency of sub-asset classes to perform similarly or dissimilarly during a given economic cycle. Over certain periods, for example, the performances of investment-grade bonds and small-cap stocks have moved in r ...
lecture 8
... • Case 3: If x doesn’t have a right child, then its successor is x’s first ancestor such that its left child is also an ancestor of x. (This includes the case that there is no such ancestor, and then x is the maximum and the successor is null.) • Proof: To prove that a node z is the successor of x, ...
... • Case 3: If x doesn’t have a right child, then its successor is x’s first ancestor such that its left child is also an ancestor of x. (This includes the case that there is no such ancestor, and then x is the maximum and the successor is null.) • Proof: To prove that a node z is the successor of x, ...
CSC 2500 Computer Organization
... Another data structure could be used to resolve the collisions; for example, binary search trees. Why do we use linked lists instead? We define the load factor, λ, of a hash table to be the ratio of the number of elements in the table to the table size. The average length of a list is λ. The effort ...
... Another data structure could be used to resolve the collisions; for example, binary search trees. Why do we use linked lists instead? We define the load factor, λ, of a hash table to be the ratio of the number of elements in the table to the table size. The average length of a list is λ. The effort ...
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.