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Financial Modelling by Joerg Kienitz

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1Post-Keynesian Monetary Economics : New Approaches To Financial Modelling

“Post-Keynesian Monetary Economics : New Approaches To Financial Modelling” Metadata:

  • Title: ➤  Post-Keynesian Monetary Economics : New Approaches To Financial Modelling
  • Language: English

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2Financial Modelling With Jump Processes

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“Financial Modelling With Jump Processes” Metadata:

  • Title: ➤  Financial Modelling With Jump Processes
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3Modelling Fluctuations Of Financial Time Series: From Cascade Process To Stochastic Volatility Model

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In this paper, we provide a simple, ``generic'' interpretation of multifractal scaling laws and multiplicative cascade process paradigms in terms of volatility correlations. We show that in this context 1/f power spectra, as observed recently by Bonanno et al., naturally emerge. We then propose a simple solvable ``stochastic volatility'' model for return fluctuations. This model is able to reproduce most of recent empirical findings concerning financial time series: no correlation between price variations, long-range volatility correlations and multifractal statistics. Moreover, its extension to a multivariate context, in order to model portfolio behavior, is very natural. Comparisons to real data and other models proposed elsewhere are provided.

“Modelling Fluctuations Of Financial Time Series: From Cascade Process To Stochastic Volatility Model” Metadata:

  • Title: ➤  Modelling Fluctuations Of Financial Time Series: From Cascade Process To Stochastic Volatility Model
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  • Language: English

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4Financial Modelling For Business Decisions

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In this paper, we provide a simple, ``generic'' interpretation of multifractal scaling laws and multiplicative cascade process paradigms in terms of volatility correlations. We show that in this context 1/f power spectra, as observed recently by Bonanno et al., naturally emerge. We then propose a simple solvable ``stochastic volatility'' model for return fluctuations. This model is able to reproduce most of recent empirical findings concerning financial time series: no correlation between price variations, long-range volatility correlations and multifractal statistics. Moreover, its extension to a multivariate context, in order to model portfolio behavior, is very natural. Comparisons to real data and other models proposed elsewhere are provided.

“Financial Modelling For Business Decisions” Metadata:

  • Title: ➤  Financial Modelling For Business Decisions
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  • Language: English

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5BFN 3304 - Financial And Valuation Modelling

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Trimester 1 2018/2019

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  • Title: ➤  BFN 3304 - Financial And Valuation Modelling
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The book is available for download in "texts" format, the size of the file-s is: 9.10 Mbs, the file-s for this book were downloaded 17 times, the file-s went public at Sun May 05 2024.

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6BFN 3174 - Financial Modelling

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Trimester 2 2019/2020

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  • Title: BFN 3174 - Financial Modelling
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  • Language: English

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7Optimal Design, Financial And Risk Modelling With Stochastic Processes Having Semicontinuous Covariances

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A.N. Kolmogorov proposed several problems on stochastic processes, which has been rarely addressed later on. One of the open problems are stochastic processes with discontinuous covariance function. For example, semicontinuous covariance functions have been used in regression and kriging by many authors in statistics recently. In this paper we introduce purely topologically defined regularity conditions on covariance kernels which are still applicable for increasing and infill domain asymptotics for regression problems, kriging and finance. These conditions are related to semicontinuous maps of Ornstein Uhlenbeck (OU) processes. Beside this new regularity conditions relax the continuity of covariance function by consideration of semicontinuous covariance. We provide several novel applications of the introduced class for optimal design of random fields, random walks in finance and probabilities of ruins related to shocks, e.g. by earthquakes. In particular we construct a random walk model with semicontinuous covariance.

“Optimal Design, Financial And Risk Modelling With Stochastic Processes Having Semicontinuous Covariances” Metadata:

  • Title: ➤  Optimal Design, Financial And Risk Modelling With Stochastic Processes Having Semicontinuous Covariances
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8Practical Financial Modelling : A Guide To Current Practice

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A.N. Kolmogorov proposed several problems on stochastic processes, which has been rarely addressed later on. One of the open problems are stochastic processes with discontinuous covariance function. For example, semicontinuous covariance functions have been used in regression and kriging by many authors in statistics recently. In this paper we introduce purely topologically defined regularity conditions on covariance kernels which are still applicable for increasing and infill domain asymptotics for regression problems, kriging and finance. These conditions are related to semicontinuous maps of Ornstein Uhlenbeck (OU) processes. Beside this new regularity conditions relax the continuity of covariance function by consideration of semicontinuous covariance. We provide several novel applications of the introduced class for optimal design of random fields, random walks in finance and probabilities of ruins related to shocks, e.g. by earthquakes. In particular we construct a random walk model with semicontinuous covariance.

“Practical Financial Modelling : A Guide To Current Practice” Metadata:

  • Title: ➤  Practical Financial Modelling : A Guide To Current Practice
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  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 584.75 Mbs, the file-s for this book were downloaded 75 times, the file-s went public at Thu Dec 23 2021.

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9BFN 3304 -Financial And Valuation Modelling

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Trimester 2 - 2017/2018

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10Martingale Methods In Financial Modelling

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Trimester 2 - 2017/2018

“Martingale Methods In Financial Modelling” Metadata:

  • Title: ➤  Martingale Methods In Financial Modelling
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  • Language: English

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11Modelling The Survival Of Financial And Industrial Enterprises : Advantages, Challenges, And Problems With The Internal Ratings-based (IRB) Method

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Trimester 2 - 2017/2018

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12BFN 3304 - Financial And Valuation Modelling

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Trimester 2 2018/2019

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13Modelling Financial Time Series

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Trimester 2 2018/2019

“Modelling Financial Time Series” Metadata:

  • Title: ➤  Modelling Financial Time Series
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  • Language: English

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14Introduction To Financial Modelling( 720p)

1st

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  • Title: ➤  Introduction To Financial Modelling( 720p)

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15Modelling Techniques For Financial Markets And Bank Management

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“Modelling Techniques For Financial Markets And Bank Management” Metadata:

  • Title: ➤  Modelling Techniques For Financial Markets And Bank Management
  • Language: English

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16Modelling The Survival Of Financial And Industrial Enterprises : Advantages, Challenges, And Problems With The Internal Ratings-based (IRB) Method

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1st

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17The Econometric Modelling Of Financial Time Series

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“The Econometric Modelling Of Financial Time Series” Metadata:

  • Title: ➤  The Econometric Modelling Of Financial Time Series
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18BFN 3174 - Financial Modelling

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Trimester 2 2016/2017

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19Financial Management : A Modelling Approach Using Spreadsheets

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Trimester 2 2016/2017

“Financial Management : A Modelling Approach Using Spreadsheets” Metadata:

  • Title: ➤  Financial Management : A Modelling Approach Using Spreadsheets
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The book is available for download in "texts" format, the size of the file-s is: 1473.47 Mbs, the file-s for this book were downloaded 68 times, the file-s went public at Sat Nov 21 2020.

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20Empirical Finance : Modelling And Analysis Of Emerging Financial And Stock Markets

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Trimester 2 2016/2017

“Empirical Finance : Modelling And Analysis Of Emerging Financial And Stock Markets” Metadata:

  • Title: ➤  Empirical Finance : Modelling And Analysis Of Emerging Financial And Stock Markets
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The book is available for download in "texts" format, the size of the file-s is: 552.44 Mbs, the file-s for this book were downloaded 23 times, the file-s went public at Wed Jul 12 2023.

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21Modelling The Linkages Between Financial Development, Economic Growth, Energy Use, Globalization And Carbon Dioxide Emissions Evidence From BRICS Countries

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This research empirically investigates the relationship between financial development, economic growth, energy consumption, globalization and carbon emissions in Brazil, Russia, India, China, and South Africa (BRICS countries). The study utilizes annual panel data retrieved from World Bank, Swiss Economic Institute, and International Energy Agency for the period 1990-2022. A range of econometric techniques robust to heterogeneity and cross-sectional dependence is employed in the analysis. The empirical estimation methods employed in the analysis include Breusch and Pesaran cross-sectional dependence tests, the Pesaran panel unit root test, and the Pooled Mean Group (PMG)/ Auto-Regressive Distributed Lag (ARDL) model, developed by Pesaran and Smith . The findings reveal that economic growth, energy consumption, and economic globalization have a long-run positive and significant relationship with CO 2 emissions. In contrast, a long-run negative and significant relationship between political globalization, social globalization and CO2 emissions is observed. Moreover, the financial development is negatively co-integrated with CO 2 emissions in the long run. These results suggest that the economic and political aspects of globalization have a profound impact on the environment. Therefore, governments and policymakers in BRICS countries should formulate environmentally sustainable policies that carefully consider the effects of globalization on carbon emissions. 

“Modelling The Linkages Between Financial Development, Economic Growth, Energy Use, Globalization And Carbon Dioxide Emissions Evidence From BRICS Countries” Metadata:

  • Title: ➤  Modelling The Linkages Between Financial Development, Economic Growth, Energy Use, Globalization And Carbon Dioxide Emissions Evidence From BRICS Countries
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  • Language: English

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22Financial Modelling : A Practical Guide

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This research empirically investigates the relationship between financial development, economic growth, energy consumption, globalization and carbon emissions in Brazil, Russia, India, China, and South Africa (BRICS countries). The study utilizes annual panel data retrieved from World Bank, Swiss Economic Institute, and International Energy Agency for the period 1990-2022. A range of econometric techniques robust to heterogeneity and cross-sectional dependence is employed in the analysis. The empirical estimation methods employed in the analysis include Breusch and Pesaran cross-sectional dependence tests, the Pesaran panel unit root test, and the Pooled Mean Group (PMG)/ Auto-Regressive Distributed Lag (ARDL) model, developed by Pesaran and Smith . The findings reveal that economic growth, energy consumption, and economic globalization have a long-run positive and significant relationship with CO 2 emissions. In contrast, a long-run negative and significant relationship between political globalization, social globalization and CO2 emissions is observed. Moreover, the financial development is negatively co-integrated with CO 2 emissions in the long run. These results suggest that the economic and political aspects of globalization have a profound impact on the environment. Therefore, governments and policymakers in BRICS countries should formulate environmentally sustainable policies that carefully consider the effects of globalization on carbon emissions. 

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  • Title: ➤  Financial Modelling : A Practical Guide
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  • Language: English

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23Financial Modelling - BFN 3174

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Trimester 2 2015/2016

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  • Title: Financial Modelling - BFN 3174
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The book is available for download in "texts" format, the size of the file-s is: 1.36 Mbs, the file-s for this book were downloaded 21 times, the file-s went public at Sun May 05 2024.

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24Mastering Financial Modelling : A Practitioner's Guide To Applied Corporate Finance

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Trimester 2 2015/2016

“Mastering Financial Modelling : A Practitioner's Guide To Applied Corporate Finance” Metadata:

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25Modelling For Financial Decisions : Proceedings Of The 5th Meeting Of The EURO Working Group On "Financial Modelling" Held In Catania, 20-21 April, 1989

Trimester 2 2015/2016

“Modelling For Financial Decisions : Proceedings Of The 5th Meeting Of The EURO Working Group On "Financial Modelling" Held In Catania, 20-21 April, 1989” Metadata:

  • Title: ➤  Modelling For Financial Decisions : Proceedings Of The 5th Meeting Of The EURO Working Group On "Financial Modelling" Held In Catania, 20-21 April, 1989
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26Neural Networks For Economic And Financial Modelling

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Trimester 2 2015/2016

“Neural Networks For Economic And Financial Modelling” Metadata:

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27Financial Modelling And Project Finance

Financial Modelling And Project Finance

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28The Econometric Modelling Of Financial Time Series

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Financial Modelling And Project Finance

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29Financial Modelling In Corporate Management

Financial Modelling And Project Finance

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30Modelling Returns And Volatilities During Financial Crises: A Time Varying Coefficient Approach

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We examine how the most prevalent stochastic properties of key financial time series have been affected during the recent financial crises. In particular we focus on changes associated with the remarkable economic events of the last two decades in the mean and volatility dynamics, including the underlying volatility persistence and volatility spillovers structure. Using daily data from several key stock market indices we find that stock market returns exhibit time varying persistence in their corresponding conditional variances. Furthermore, the results of our bivariate GARCH models show the existence of time varying correlations as well as time varying shock and volatility spillovers between the returns of FTSE and DAX, and those of NIKKEI and Hang Seng, which became more prominent during the recent financial crisis. Our theoretical considerations on the time varying model which provides the platform upon which we integrate our multifaceted empirical approaches are also of independent interest. In particular, we provide the general solution for low order time varying specifications, which is a long standing research topic. This enables us to characterize these models by deriving, first, their multistep ahead predictors, second, the first two time varying unconditional moments, and third, their covariance structure.

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31Modelling Information Flows In Financial Markets

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This paper presents an overview of information-based asset pricing. In this approach, an asset is defined by its cash-flow structure. The market is assumed to have access to "partial" information about future cash flows. Each cash flow is determined by a collection of independent market factors called X-factors. The market filtration is generated by a set of information processes, each of which carries information about one of the X-factors, and eventually reveals the X-factor. Each information process has two terms, one of which contains a "signal" about the associated X-factor, and the other of which represents "market noise". The price of an asset is given by the expectation of the discounted cash flows in the risk-neutral measure, conditional on the information provided by the market. When the market noise is modelled by a Brownian bridge one is able to construct explicit formulae for asset prices, as well as semi-analytic expressions for the prices and greeks of options and derivatives. In particular, option price data can be used to determine the information flow-rate parameters implicit in the definitions of the information processes. One consequence of the modelling framework is a specific scheme of stochastic volatility and correlation processes. Instead of imposing a volatility and correlation model upon the dynamics of a set of assets, one is able to deduce the dynamics of the volatilities and correlations of the asset price movements from more primitive assumptions involving the associated cash flows. The paper concludes with an examination of situations involving asymmetric information. We present a simple model for informed traders and show how this can be used as a basis for so-called statistical arbitrage. Finally, we consider the problem of price formation in a heterogeneous market with multiple agents.

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32BFN 3304 - Financial And Valuation Modelling

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Trimester 1 2017/2018

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33BFN 3304 - Financial And Valuation Modelling

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Trimester 2 2015/2016

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34BFN 3174 - Financial Modelling

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Trimester 2 2022/20233

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35The Econometric Modelling Of Financial Time Series

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Trimester 2 2022/20233

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36Mastering Financial Modelling CD

cd included with the book "Mastering Financial Modelling"

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37BFN 3174 - Financial Modelling BFN 3304 - Financial And Valuation Modelling

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Tri 1, 2023/2023

“BFN 3174 - Financial Modelling BFN 3304 - Financial And Valuation Modelling” Metadata:

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38Modelling Financial Markets By The Multiplicative Sequence Of Trades

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We introduce the stochastic multiplicative point process modelling trading activity of financial markets. Such a model system exhibits power-law spectral density S(f) ~ 1/f**beta, scaled as power of frequency for various values of beta between 0.5 and 2. Furthermore, we analyze the relation between the power-law autocorrelations and the origin of the power-law probability distribution of the trading activity. The model reproduces the spectral properties of trading activity and explains the mechanism of power-law distribution in real markets.

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  • Title: ➤  Modelling Financial Markets By The Multiplicative Sequence Of Trades
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39Expectative Modelling For Financial Research

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Financial modelling and financial opinions are commonplace. And the media, YouTube, social media and other platforms may be having a good impact in creating confusion (possibly even motivating fear and greed) in society at large. Thus, an expectative model may be helpful in providing a more stable picture of financial performance via using a simpler approach based on descriptive statistics (namely, percentiles). This model may be even more interesting when updated in 'real time' (e.g., as a RealTime research project, https://doi.org/10.17605/OSF.IO/49A5F). Expectative modelling is eminently descriptive of past data. It was first trialled with epidemiological data (https://doi.org/10.17605/OSF.IO/MRJPB). However, the latter posed serious challenges due to the reliability and availability of such data. In comparison, financial data, especially from financial markets, is publicly available, largely reliable, and abundant. Thus, it may prove a better research environment for testing the model (even if it is not envisaged that it will provide any advantage to markets per se, other than descriptive data). Expectative modelling has very few assumptions, and the focus on percentiles allows to set the minimum and maximum bounds for our description at, say the 5th and 95th percentile (instead of at the minimum and maximum observed values). This range-based modelling has two main properties: On the one hand, to describe with Severity (Mayo), so that we may contain within the range highly informative (observed) behaviour by eliminating extreme data with a high probability of being exceptional, a fluke or a reporting error. On the other hand, to be attentive to Black Swans (Taleb), as the range itself tells us which (future) behaviours should not really surprise us (as opposed to those which fall outside the range). It is this expectative property of the approach that merits a preregistration, if only to mark a definite break between past data (already released) and current/future data (yet to be released).

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40Mesoscopic Modelling Of Financial Markets

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We derive a mesoscopic description of the behavior of a simple financial market where the agents can create their own portfolio between two investment alternatives: a stock and a bond. The model is derived starting from the Levy-Levy-Solomon microscopic model (Econ. Lett., 45, (1994), 103--111) using the methods of kinetic theory and consists of a linear Boltzmann equation for the wealth distribution of the agents coupled with an equation for the price of the stock. From this model, under a suitable scaling, we derive a Fokker-Planck equation and show that the equation admits a self-similar lognormal behavior. Several numerical examples are also reported to validate our analysis.

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41BFN 3304 - Financial And Valuation Modelling

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Trimester 2 2016/2017

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42BFN 3304 - Financial And Valuation Modelling

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Trimester 2 - 2019/2020

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43BFN 3174 - Financial Modelling

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Trimester 1 2019/2020

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44Market Practice In Financial Modelling

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Trimester 1 2019/2020

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45Martingale Methods In Financial Modelling

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Trimester 1 2019/2020

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46Financial Modelling

x, 206 pages : 21 cm

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47BFN 3174 - Financial Modelling

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Trimester 2 2017/2018

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48BFN 3174 - Financial Modelling

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Trimester 1 2016/2017

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49Modelling Of Dependence In High-dimensional Financial Time Series By Cluster-derived Canonical Vines

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We extend existing models in the financial literature by introducing a cluster-derived canonical vine (CDCV) copula model for capturing high dimensional dependence between financial time series. This model utilises a simplified market-sector vine copula framework similar to those introduced by Heinen and Valdesogo (2008) and Brechmann and Czado (2013), which can be applied by conditioning asset time series on a market-sector hierarchy of indexes. While this has been shown by the aforementioned authors to control the excessive parameterisation of vine copulas in high dimensions, their models have relied on the provision of externally sourced market and sector indexes, limiting their wider applicability due to the imposition of restrictions on the number and composition of such sectors. By implementing the CDCV model, we demonstrate that such reliance on external indexes is redundant as we can achieve equivalent or improved performance by deriving a hierarchy of indexes directly from a clustering of the asset time series, thus abstracting the modelling process from the underlying data.

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50Financial Planning : Profit Improvement Through Modelling

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We extend existing models in the financial literature by introducing a cluster-derived canonical vine (CDCV) copula model for capturing high dimensional dependence between financial time series. This model utilises a simplified market-sector vine copula framework similar to those introduced by Heinen and Valdesogo (2008) and Brechmann and Czado (2013), which can be applied by conditioning asset time series on a market-sector hierarchy of indexes. While this has been shown by the aforementioned authors to control the excessive parameterisation of vine copulas in high dimensions, their models have relied on the provision of externally sourced market and sector indexes, limiting their wider applicability due to the imposition of restrictions on the number and composition of such sectors. By implementing the CDCV model, we demonstrate that such reliance on external indexes is redundant as we can achieve equivalent or improved performance by deriving a hierarchy of indexes directly from a clustering of the asset time series, thus abstracting the modelling process from the underlying data.

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