This section presents several documents relating to DEXISION and other technical topics. For example, you learn what makes DEXISION different, how to value derivatives with DEXISION in line with market quotes and how to derive Greeks even for the most complex financial products. You also learn how PYTHON can benefit you in financial modeling and engineering. In addition, you will find research papers addressing the valuation of American options via Monte Carlo simulation or the calibration of the Heston (1993) stochastic volatility model.
PYTHON TAKES A BITE
This recent cover story of the March 2010 issue of Wilmott Magazine takes a closer look at Python (www.python.org) for Financial Engineering. For this article, Yves Hilpisch, Managing Director of Visixion, has also been interviewed because DEXISION, Visixion’s valuation suite, mainly relies on Python. As the article illustrates, Python is already today an efficient framework for building powerful and fast Financial Engineering applications. Convince yourself!
DEXISION – DERIVATIVES ANALYTICS ON DEMAND
This presentation introduces our valuation suite DEXISION in a non-technical manner. The focus lies on conceptual and architectural aspects. We show how our architecture resembles the one of Google. We also illustrate how DEXISION compares to other established valuation suites. Learn how to save hundreds of hours developing financial models, how to unify and streamline valuation and risk management and how to access unlimited computing power even via a netbook.
STOCHASTIC VOLATILITY AND STOCHASTIC INTEREST RATES
The valuation of American options under both stochastic volatility and interest rates is still a challenging problem. Recently, Medvedev and Scaillet (2009) came up with approximation techniques that can be evaluated in a fraction of a second. They write in their article:
„To give an idea of the computational advantage of our method, a Matlab code implementing the algorithm of Longstaff and Schwartz (2001) takes dozens of minutes to compute a single option price while our approximation takes roughly a tenth of a second.“
In a short article, we demonstrate that valuation by Monte Carlo simulation can be accomplished in 3 seconds in their model setup with reasonable accuracy – demonstrating the capabilities of Python and Numpy (a complete Python script is provided). DEXISION is even faster and takes 1 second only per option to come up with reasonable value estimates. These computational times demonstrate that Monte Carlo simulation is competitive in terms of speed when compared with alternative approaches.
CALIBRATING HESTON’S STOCHASTIC VOLATILITY MODEL
This article analyzes in some detail the Heston (1993) stochastic volatility model and shows how to calibrate it to market data. Such a calibrated model can then be used to value and hedge more complex derviative assets. For example, model parameters from such a calibration can directly be used in DEXISION which provides Heston (1993) processes as standard underlyings. The article contains all necessary Python scripts.
PATHS VS. RUNS IN REGRESSION-BASED MONTE CARLO VALUATION
This article shows how to improve Monte Carlo value estimates for American options with complex, non-convex payoff functions from the Least Squares Monte Carlo (LSM) algorithm proposed by Longstaff and Schwartz (2001). By means of numerical examples, we illustrate that convergence of the LSM estimate may fail. As solutions we propose the use of problem-specific basis functions in combination with multiple simulation runs where each run uses a relatively small number of paths only. This approach to Monte Carlo valuation will be included in the next release of DEXISION – further improving valuation accuracy under certain circumstances.
ECONOMIC FOUNDATIONS OF REAL OPTIONS VALUATION, NET PRESENT VALUE AND SHAREHOLDER VALUE
This paper derives from scratch and explains in detail the economic foundations of the Real Options Approach. It demonstrates that you can securely use this advanced budgeting technique in practice whenever you are willing to accept the premises of the Net Present Value paradigm. In this sense, it clarifies frequent misconceptions of academics and practitioners and clears the way for its beneficial application in practical situations.
ROCKET SCIENCE AND HIGH-TECH FOR CORPORATE AND FINANCIAL MANAGEMENT
In this paper, you find an overview of the conceptual and technological building blocks of our management approach OPTIONS BASED MANAGEMENT and our analytics suite DEXISION. The paper provides complete Python scripts for American options valuation via Monte Carlo simulation.
VALUATION OF FINANCIAL CONTRACTS – ESTIMATING THE RISK-RETURN IMPACT OF VENTURE CAPITAL CONTRACTS
This research monograph concerns itself withe the modeling and valuation of financial and real options typically found in venture capital and private equity contracts. It shows in detail how payoffs can be modeled and which role interactions between single contract elements play. The insights of the Real Options Approach are applied to consistently and comprehensively address the impact of venture capital contracting on expected risks and returns.
THE IMPACT OF LIQUIDATION PREFERENCES ON THE RISK-RETURN STRUCTURE OF VENTURE CAPITAL TRANSACTIONS
In this paper, you find a Monte Carlo-simulation study on the risk and return impact of typical liquidation preferences in venture capital contracts. Liquidation preferences are studied in detail while a Python script illustrates the practical implementation of a respective valuation algorithm.
VON DER LANDKARTE ZUM NAVIGATIONSSYSTEM
(From Maps to Navigational Systems)
Dieser Artikel argumentiert, weshalb die Zeit reif ist für einen Paradigmenwechsel im finanziellen und strategischen Management hin zu OPTIONS BASED MANAGEMENT. Er zeigt auf, dass DEXISION all notwendigen Voraussetzungen bietet, um OBM in der Praxis effizient und Gewinn bringend einzusetzen.
DER FINANZIELLE WERT RECHTLICHER KLAUSELN IN BETEILIGUNGSVERTRÄGEN
(The Financial Value of Legal Clauses in Financial Contracts)
Der Artikel veranschaulicht in einer einfachen Modellwelt die Bedeutung von ökonomischen Vertragsklauseln für den Transaktionswert sowie den Einfluss von Interdependenzen zwischen Vertragsklauseln.
PYTHON – FINANCIAL MODELING 2.0
Learn how PYTHON can benefit you in financial modeling and engineering. Compare your current – often time-consuming and costly – programming and maintenance paradigms with the capabilities of PYTHON. Save time and money with our value added services.