1 SHAREX: A MULTIPERIOD PORTFOLIO MANAGEMENT MODEL.

Slides:

Advertisements

Similar presentations

Sequential learning in dynamic graphical model Hao Wang, Craig Reeson Department of Statistical Science, Duke University Carlos Carvalho Booth School of.

Advertisements

Fuzzy Reasoning in Computer Go Opening Stage Strategy P.Lekhavat and C.J.Hinde.

Neural Networks in Financial Analysis

1 A MULTIPERIOD FIRM MODEL by Ralf Östermark. 2 Firm plan model – Key elements Input: Decision variables Sales volume Production volume New debt etc.

Quantsmile: Quantitative Portfolio Management Quantsmile: Quantitative Portfolio Management.

1 Market Efficiency in the Emerging Securitized Real Estate Markets Felix Schindler Centre for European Economic Research (ZEW) Milan, 26 th of June 2010.

1 CHAPTER FOURTEEN FINANCIAL ANALYSIS OF COMMON STOCKS.

CAS 1999 Dynamic Financial Analysis Seminar Chicago, Illinois July 19, 1999 Calibrating Stochastic Models for DFA John M. Mulvey - Princeton University.

FIN 685: Risk Management Topic 5: Simulation Larry Schrenk, Instructor.

Collaborative Filtering in iCAMP Max Welling Professor of Computer Science & Statistics.

Efficient Portfolios MGT 4850 Spring 2008 University of Lethbridge.

SpaeSoft Managerial risk assessment services. Software SpaeSoft delivers high precision software for strategic firm planning and risk assessment, investment.

CHAPTER TWENTY-TWO FINANCIAL ANALYSIS. n WHAT IS FINANCIAL ANALYSIS? DEFINITION: the activity of providing inputs to the portfolio management process.

MARKET IN TRAFFIC LIGHTS Designed for the next Users Private Investors Professional investors in Broker companies Run mode: Real Time combined with the.

1 Limits to Diversification Assume w i =1/N,  i 2 =  2 and  ij = C  p 2 =N(1/N) 2  2 + (1/N) 2 C(N 2 - N)  p 2 =(1/N)  2 + C - (1/N)C as N  

FINANCIAL ECONOMETRICS FALL 2000 Rob Engle. OUTLINE DATA MOMENTS FORECASTING RETURNS EFFICIENT MARKET HYPOTHESIS FOR THE ECONOMETRICIAN TRADING RULES.

Estimation Error and Portfolio Optimization Global Asset Allocation and Stock Selection Campbell R. Harvey Duke University, Durham, NC USA National Bureau.

Asset Allocation and the Efficient Frontier: Optimizing a portfolio’s risk/return profile J.P. Morgan Investment Academy SM FOR INSTITUTIONAL USE ONLY.

Expected Utility, Mean-Variance and Risk Aversion Lecture VII.

The Weighted Cost of Capital. Objectives n Define the concept of cost of capital. n Use the concept of cost of capital to link the investment decisions.

Yale School of Management The Dow Theory William Peter Hamilton’s Track Record Re-Considered Stephen J. Brown (NYU Stern School) William N. Goetzmann (Yale.

Portfolio Management Grenoble Ecole de Management.

Instruments of Financial Markets at Studienzentrum Genrzensee Switzerland. August 30-September 17, 2004 Course attended by: Muhammad Arif Senior Joint.

1 Optimal Risky Portfolio, CAPM, and APT Diversification Portfolio of Two Risky Assets Asset Allocation with Risky and Risk-free Assets Markowitz Portfolio.

Investments, 8 th edition Bodie, Kane and Marcus Slides by Susan Hine McGraw-Hill/Irwin Copyright © 2009 by The McGraw-Hill Companies, Inc. All rights.

1 Forecasting BET Index Volatility MSc.: Răzvan Ghelmeci Supervisor: Prof. Moisă Altăr.

McGraw-Hill/Irwin © 2008 The McGraw-Hill Companies, Inc., All Rights Reserved. Capital Asset Pricing and Arbitrage Pricing Theory CHAPTER 7.

The Security Market Line (SML) aka The Capital Asset Pricing Model (CAPM) The Capital Asset Price Model is E(R A ) = R f + [E(R M ) - R f ] x A Expected.

Operations Research Models

Optimal Risky Portfolio, CAPM, and APT

MBAD/F 619: Risk Analysis and Financial Modeling Instructor: Linda Leon Fall 2014

Dr. Anton Fokin The Svedberg Laboratory, Sweden. Outline R-Quant is a software toolbox, which provides a financial researcher or quantitative investor.

Cost of Capital Professor Ronald Miolla. Agenda 1) What is Cost of Capital? 2) How to compute Cost of Capital. 3) Cost of debt. 4) Cost of equity.

7/2/2013Copyright R. Douglas Martin1 5. TRANSACTION COSTS AND MIP 5.1 Transaction costs constraints in MVO 5.2 Transaction costs penalty in quadratic utility.

Investment and portfolio management MGT 531.  MGT 531   Lecture # 16.

19 October 2015All rights reserved, Edward Tsang & Serafin Martinez jaramillo CHASM Co-evolutionary Heterogeneous Artificial Stock Markets Serafín Martínez.

FYP Briefing. Project #56 Is R&D a Priced Factor in APT Market Model for Capital Asset Pricing Model (CAPM) –R i = a i + b i R mt + ε i Where Ri = expected.

Optimizing Multi-Period DFA Systems Professor John M. Mulvey Department of OR and Financial Engineering Bendheim Center for Finance Princeton University.

Stock Price Prediction Using Reinforcement Learning

MURI: Integrated Fusion, Performance Prediction, and Sensor Management for Automatic Target Exploitation 1 Dynamic Sensor Resource Management for ATE MURI.

Tanja Magoč, François Modave, Xiaojing Wang, and Martine Ceberio Computer Science Department The University of Texas at El Paso.

Mathematical Models & Optimization?

Portfolio Management Unit – 1 Session No.3 Topic: Portfolio Management Process Unit – 1 Session No.3 Topic: Portfolio Management Process.

Financial Time Series Analysis with Wavelets Rishi Kumar Baris Temelkuran.

MSc COURSE : ASSET PRICING AND PORTFOLIO THEORY. Aims Introduce basic concepts used to price financial assets Introduce basic concepts used to price financial.

FIN 614: Financial Management Larry Schrenk, Instructor.

Soft Computing methods for High frequency tradin.

1 Event Based Financial Information Extract and analysis Student : Lee, Dah-Sheng Professor: Lee, Hahn-Ming Date: 23 July 2004.

September 28, 2000 Improved Simultaneous Data Reconciliation, Bias Detection and Identification Using Mixed Integer Optimization Methods Presented by:

Industry Analysis Shahadat Hosan Faculty, MBA Program Stamford University Bangladesh 15 June 2011.

1 FIN 408 -Hybrid Funds Hybrid Funds: Invest in both stocks and bonds, May also invest in convertible bonds and preferred stocks, Generally less risky.

Copyright © 2014 by McGraw-Hill Education (Asia). All rights reserved. 13 Aggregate Planning.

Financial Data mining and Tools CSCI 4333 Presentation Group 6 Date10th November 2003.

Water resources planning and management by use of generalized Benders decomposition method to solve large-scale MINLP problems By Prof. André A. Keller.

Prepared by Fayes Salma.  Introduction: Financial Tasks  Data Mining process  Methods in Financial Data mining o Neural Network o Decision Tree  Trading.

By Cheng F. Lee Rutgers University, USA John Lee

Capital Asset Pricing and Arbitrage Pricing Theory

The Capital Asset Pricing Model

An Investigation of Market Dynamics and Wealth Distributions

Decomposed optimization-control problem

Towards Next Generation Panel at SAINT 2002

MSc COURSE : ASSET PRICING AND PORTFOLIO THEORY

Estimation Error and Portfolio Optimization

Estimation Error and Portfolio Optimization

Estimation Error and Portfolio Optimization

Carlo A. Favero IGIER, Universita’ Bocconi

Figure 6.1 Risk as Function of Number of Stocks in Portfolio

Carrying out an Empirical Project

Financial Liquidity Management

Estimation Error and Portfolio Optimization

Presentation transcript:

1 SHAREX: A MULTIPERIOD PORTFOLIO MANAGEMENT MODEL

2 Key Features Integrated system of: 1.stock price forecasting 2.portfolio optimization 3.inventory management 4.facilities for incorporating alternative techniques

3 Key Features: the necessary financial relations included liquidity and debt, inventory, risk control transactions in discrete batch sizes fixed and variable transactions costs free specification of planning horizon forecasting and optimization combined extensive simulations for strategy specification real time management guaranteed feasibility

4 Large Scale Portfolio Management

5 Immediate research Topics: parametric search under different economic conditions mixture density forecast models for skewed markets multicomputer implementation of SHAREX connections to efficient MINLP-solvers Utilizing VMA and IMA (volume/price index moving averages) in turning point detection

6 Background Research Östermark, R. (1990): Portfolio Efficiency of Capital Asset Pricing Models. Empirical Evidence on Thin Stock Markets. Åbo Akademi University, ISBN Östermark, R. (1991): Vector forecasting and dynamic portfolio selection. European Journal of Operational Research 55, Östermark, R & Aaltonen J (1992): Recursive Portfolio Management: Large-Scale Evidence from Two Scandinavian Stock Markets. Computer Science in Economics and Management 5, Östermark, R (2000a): A Hybrid Genetic Fuzzy Neural Network Algorithm Designed for Classification Problems Involving Several Groups. Fuzzy Sets and Systems 114:2, pp Östermark, R. (2000b) A Flexible Genetic Hybrid Algorithm for Nonlinear Mixed-integer Programming Problems. Accepted in EvolutionaryOptimization.

7 Research (cont) Östermark, R., Westerlund, T. & Skrifvars, H. (2000): A Nonlinear Mixed-Integer Multiperiod Firm Model. International Journal of Production Economics 67, p Östermark, R. (2001): “Genetic modelling of multivariate EGARCHX-processes. Evidence on the international asset return signal response mechanism”. Forthcoming in Computational Statistics & Data Analysis 38/1, 2001, pp Östermark, R. (2002a): “Automatic detection of parsimony in heteroskedastic time series processes. Empirical tests on global asset returns with parallel geno-mathematical programming”. Soft Computing 6/1, pp Östermark, R. (2002b): “A Multipurpose Parallel Genetic Hybrid Algorithm for Nonlinear Non-convex Programming Problems”. Forthcoming in The European Journal of Operational Research.