Liquidity risk is always present in our financial system and has in the last years been a major contribution to the financial crisis. Market liquidity risk has an effect on for example security prices, risk management, and the speed of arbitrage. The banks and their funding liquidity drives the market liquidity risk. Liquidity crisis arises through losses, increasing margins, tightened risk management, and increased volatility. When this happens the traditional liquidity providers becomes liquidity demanders which affect prices in a negative way. To get a sound understanding of liquidity risk we have to specify and describe liquidity. Market liquidity and funding liquidity are two kinds of liquidity. Market liquidity can be described as good when a security is easy to trade. Easy to trade is defined as small bid ask spread, small price impact and high resilience. If a bank or investor have good funding liquidity they have good availability of funds by their own capital or from loans. The main objective in this paper is to show if liquidity risk has a significant impact on option price and depends on a real supply curve.

Derivatives in financial market play an important and useful role in hedging and managing risk. Derivative securities, when used correctly, can help investors increase their expected returns and minimize their exposure to risk. Options offer leverage and insurance for risk-averse investors. For the risk-alike investors, they can be ways of speculation. However, the values of option depend on a number of different variables in addition to the underlying asset, which makes them hard to value. This book explored some commonly used pricing models and compared their accuracy for the valuation. In the last section, it introduced a new numerical scheme --- the Radial Basis Function Method (RBF), particularly Hardy’s multiquadric (MQ) as a spatial approximation for the numerical solution of the option value and its derivatives.

This monograph focuses on the liquidity risk of commercial banks in the Visegrad countries in the period from 2000 to 2011. This risk is comprehensively evaluated with several different methods: six liquidity ratios, panel data regression analysis with fixed effects, probit model and scenario analysis. The liquidity position, net position on the interbank market and strategy of liquidity risk management differ significantly in individual Visegrad countries. The capital adequacy is the most important determinant of bank liquidity. However, some other factors such as size of the bank, credit portfolio quality or macroeconomic development are significant as well. All three tested stress scenarios would have a negative influence on bank liquidity. A run on the bank would have most serious impact on the bank liquidity in all Visegrad countries. The use of committed loans is the second most severe scenario for Czech and Slovak banks and a crisis confidence in the interbank market for Hungarian and Polish banks.

The recent turmoil on financial markets has made evident the importance of efficient liquidity risk management for the stability of banks. The measurement and management of liquidity risk must take into account economic factors such as the impact area, the timeframe of the analysis, the origin and the economic scenario in which the risk becomes manifest. Basel III, among other things, has introduced harmonized international minimum requirements and has developed global liquidity standards and supervisory monitoring procedures. The short book analyses the economic impact of the new regulation on profitability, on assets composition and business mix, on liabilities structure and replacement effects on banking and financial products.a??

The book will give the reader a path of how to use Black-Scholes option pricing model to get a forecast of falling market price of a stock exchange. I applied the method in two different time windows to Dhaka Stock Exchange and found appropriate result. I hope this method will work properly . This book is very helpful for the readers who are willing to know about the market changes of stock exchange.

The text is designed to cater to the need of the students, as well as the research people of financial management, by giving a good understanding of the subject and its applications. This new edition seeks to enhance the coverage of the book and update it by including new statistical techniques.It makes the book more comprehensive and incorporates the changes that have incurred in the field of finance and management in India as well as the world. The purpose of this book is to clarify concepts in Liquidity, Profitability and Risk management of the particular industry and at the same time relate them to those examples which rendered the text meaningful to the reader. The book has been written for the student as well as the researcher in the field of finance and management, both of whom need to have good understanding of the subject and its applications.

A new element of risk, the liquidity risk, has flourished along this time taking importance and playing a key role in risk management tools. This has attracted the attention of the scientific community and financial experts. Therefore, this book provides a theoretical introduction and a state of the art of the key elements needed to understand the complexity of the dealt issue. Mainly it gives a study over liquidy risk and its application in market risk (being included in VaR measure). It also explores a relatively new alternative approach to model the liquidity risk using artificial neural networks, which has been oriented in focused delay and recurrent neural networks due to their capability to work with time series. That analysis should help shed some light on this new environment and should be useful to professionals in finance.

This thesis seeks to provide an overview on the use of Mellin transforms in Option pricing and to explain related issues. After introducing some basic concepts of Stochastic analysis and Option pricing, we use Mellin transforms as a tool to uncover formulas for pricing of different types of financial derivatives, such as European vanilla and power options, or the American options. Most of this content can be regarded as a summary of existing results on the use of Mellin transforms in option pricing. The main added value of the thesis is the deeper mathematical analysis which most of the preceding studies were lacking. In fact, although Mellin transforms offer an exceedingly convenient tool under the operational (optimistic) approach, the detailed analysis of its use is rather nontrivial.

It is now known that long memory stochastic volatility models can capture the well-documented evidence of volatility persistence. However, due to the complex structures of the long memory processes, the analytical formulas for option prices are not available yet. In this book, we propose two fractional continuous time stochastic volatility models which are built on the popular short memory stochastic volatility models. Using the tools from stochastic calculus, fractional calculus and Fourier transform, we derive the (approximate) analytical solutions for option prices. We also numerically study the effects of long memory on option prices. We show that the fractional integration parameter has the opposite effect to that of volatility of volatility parameter. We also find that long memory models can accommodate the short term options and the decay of volatility skew better than the corresponding short memory models. These findings would appeal to the researchers and practitioners in the areas of quantitative finance.

The main two areas of financial mathematics areportfolio optimization and option pricing. Portfoliooptimization deals with the determination of the bestinvestment strategy under certain constraints (e.g.risk, liquidity or budget constraints). Optionpricing is concerned with valuation of derivativecontracts with complex payoffs, dependent on tradableassets. The first part of the book deals with realisticproblems of portfolio optimization. Thereby, theexpected outcome of a utility function underconstraints is maximised. For instance, the portfoliois optimized with fixed income and consumptionconstraints. The borrower rates of an investor dependon his debt-ratio, but usually they are assumed to bedebt-independent. The author shows, how debt-ratiodependent borrower rates can be incorporated intoportfolio optimization and how they affect theoptimal trading strategy. In the second part of thebook, some efficient methods to price Asian andaverage options are introduced. This book is adressed to quantitative researchers andportfolio managers in insurance companies andinvestment banks, as well as students of economicsand financial mathematics.

The recent market turmoil caused by the sub-prime crisis highlighted how several key factors can strongly affect the banks’ capability to preserve their financial equilibrium under stress. Current liquidity risk models demonstrated to undervalue extreme events affecting funding and market risk in global scenarios. There was not an integrated measurement tool able to cover all the dimensions of liquidity risk and commonly adopted by the majority of institutions. This work, therefore, intends to highlight the most significant features to consider in order to implement an effective liquidity risk measurement and management.

The study tests the significance of multiple risk factors in determination of stock returns in Pakistan using KSE as the benchmark. Pakistan’s market has shown an upward trend as KSE100 improved from 11348 to 16905 points in 2012. The market is also subject to a strong degree of volatility. Individual monthly stock returns from 2006 – 2010 have been used in the study. It will contribute to investor’s understanding of the market and assist research analysts. The study is based on competing Fama-Macbeth models and incorporates equity risk premium, size and value premiums, liquidity premium and momentum premium. The results suggest that in Pakistan, market risk and momentum premiums are strong estimators of equity returns whereas liquidity premium and company specific fundamental factors like size and value premiums do not hold in the country’s equity markets. The limitation is the lack of cross country diversification.

This study verifies quantitatively a systematic character of default risk and statistical quality of the competing three- and four-factor asset pricing models. The experimental design applied to this study is premised on the three-factor model of Fama and French enhanced by default risk factor. The study utilizes the factor mimicking portfolio technique for modeling the risks underlying size, value and default risk factors. Distance-to-default estimate, deduced from the option-based model, is adopted by this study as a proxy for default risk. The augmentation of the three-factor model with default risk factor improves the performance of a conventional asset pricing specification on average. The factor loadings of the portfolios of size, value and default risk factors exhibit properties of risk factor sensitivities for stocks. The size and value factors are found to be common in equity returns, but at the same time not being proxies for default related information.

This book describes a new methodology that allows the Banks to evaluate the loans using a risk neutral approach. More in detail it illustrates the methodological framework behind the definition of the risk neutral default probabilities used to estimate the loans credit spreads. These risk neutral probabilities are calculated using a contingent-claims approach conceptually similar to the Black-Scholes and Merton framework for modeling corporate liabilities. The proposed risk neutral approach is suitable at producing estimates, in a fair value computation context, that are as close as possible to the exit price as mandated by IFRS 13 with a lower dependency on internal parameters. The methodology is compatible with the income approach, usually adopted for the loans evaluation, and is coherent with the discounted cashflows methodologies used for the pricing of securities subject to default risk.

Revision with unchanged content. This collection contributes to the fields of asset pricing and financial market microstructure. Two essays study the continuous double auction (CDA), the operating mode of all major stock exchanges. Agent based modelling techniques are used to observe institutional characteristics of CDA markets. Agent based modelling is a novel computational approach, increasingly being applied to financial and economic research. The agent based markets in this work are isolated from artefacts of trader behaviour by employing naive agents, called zero intelligence agents. Such primitive markets possess actual features of real markets pertaining to efficiency, convergence to equilibrium, liquidity effects, and time series properties of price and return. In the second essay price formation in CDA markets with a passive market maker is analysed, and a price density function developed. The third piece empirically investigates the structure of equity returns autocorrelation and presents two stylised facts that reveal anomalous behaviour. These facts are justified by turning to market liquidity as an explanatory factor. An implication is that return reversals deliver profits to traders who undertake the purveyance of liquidity services when opportune; in support of this, a liquidity based trading strategy that delivers significant profits is presented.

## option pricing in the presence of liquidity risk в наличии / купить интернет-магазине

## Option Pricing in the Presence of Liquidity Risk

Liquidity risk is always present in our financial system and has in the last years been a major contribution to the financial crisis. Market liquidity risk has an effect on for example security prices, risk management, and the speed of arbitrage. The banks and their funding liquidity drives the market liquidity risk. Liquidity crisis arises through losses, increasing margins, tightened risk management, and increased volatility. When this happens the traditional liquidity providers becomes liquidity demanders which affect prices in a negative way. To get a sound understanding of liquidity risk we have to specify and describe liquidity. Market liquidity and funding liquidity are two kinds of liquidity. Market liquidity can be described as good when a security is easy to trade. Easy to trade is defined as small bid ask spread, small price impact and high resilience. If a bank or investor have good funding liquidity they have good availability of funds by their own capital or from loans. The main objective in this paper is to show if liquidity risk has a significant impact on option price and depends on a real supply curve.

## Evaluation of Various Numerical Methods of Option Pricing

Derivatives in financial market play an important and useful role in hedging and managing risk. Derivative securities, when used correctly, can help investors increase their expected returns and minimize their exposure to risk. Options offer leverage and insurance for risk-averse investors. For the risk-alike investors, they can be ways of speculation. However, the values of option depend on a number of different variables in addition to the underlying asset, which makes them hard to value. This book explored some commonly used pricing models and compared their accuracy for the valuation. In the last section, it introduced a new numerical scheme --- the Radial Basis Function Method (RBF), particularly Hardy’s multiquadric (MQ) as a spatial approximation for the numerical solution of the option value and its derivatives.

## Liquidity risk of banks in the Visegrad countries

This monograph focuses on the liquidity risk of commercial banks in the Visegrad countries in the period from 2000 to 2011. This risk is comprehensively evaluated with several different methods: six liquidity ratios, panel data regression analysis with fixed effects, probit model and scenario analysis. The liquidity position, net position on the interbank market and strategy of liquidity risk management differ significantly in individual Visegrad countries. The capital adequacy is the most important determinant of bank liquidity. However, some other factors such as size of the bank, credit portfolio quality or macroeconomic development are significant as well. All three tested stress scenarios would have a negative influence on bank liquidity. A run on the bank would have most serious impact on the bank liquidity in all Visegrad countries. The use of committed loans is the second most severe scenario for Czech and Slovak banks and a crisis confidence in the interbank market for Hungarian and Polish banks.

## Liquidity Risk Management in Banks: Economic and Regulatory Issues (SpringerBriefs in Finance)

The recent turmoil on financial markets has made evident the importance of efficient liquidity risk management for the stability of banks. The measurement and management of liquidity risk must take into account economic factors such as the impact area, the timeframe of the analysis, the origin and the economic scenario in which the risk becomes manifest. Basel III, among other things, has introduced harmonized international minimum requirements and has developed global liquidity standards and supervisory monitoring procedures. The short book analyses the economic impact of the new regulation on profitability, on assets composition and business mix, on liabilities structure and replacement effects on banking and financial products.a??

## Black-Scholes Option Pricing Model in DSE in Two Different timeWindow

The book will give the reader a path of how to use Black-Scholes option pricing model to get a forecast of falling market price of a stock exchange. I applied the method in two different time windows to Dhaka Stock Exchange and found appropriate result. I hope this method will work properly . This book is very helpful for the readers who are willing to know about the market changes of stock exchange.

## Liquidity, Profitability and Risk Analysis of E.I.D Parry Sugars Ltd

The text is designed to cater to the need of the students, as well as the research people of financial management, by giving a good understanding of the subject and its applications. This new edition seeks to enhance the coverage of the book and update it by including new statistical techniques.It makes the book more comprehensive and incorporates the changes that have incurred in the field of finance and management in India as well as the world. The purpose of this book is to clarify concepts in Liquidity, Profitability and Risk management of the particular industry and at the same time relate them to those examples which rendered the text meaningful to the reader. The book has been written for the student as well as the researcher in the field of finance and management, both of whom need to have good understanding of the subject and its applications.

## Liquidity Risk Modeling using Artificial Neural Networks

A new element of risk, the liquidity risk, has flourished along this time taking importance and playing a key role in risk management tools. This has attracted the attention of the scientific community and financial experts. Therefore, this book provides a theoretical introduction and a state of the art of the key elements needed to understand the complexity of the dealt issue. Mainly it gives a study over liquidy risk and its application in market risk (being included in VaR measure). It also explores a relatively new alternative approach to model the liquidity risk using artificial neural networks, which has been oriented in focused delay and recurrent neural networks due to their capability to work with time series. That analysis should help shed some light on this new environment and should be useful to professionals in finance.

## Option pricing theory using Mellin transforms

This thesis seeks to provide an overview on the use of Mellin transforms in Option pricing and to explain related issues. After introducing some basic concepts of Stochastic analysis and Option pricing, we use Mellin transforms as a tool to uncover formulas for pricing of different types of financial derivatives, such as European vanilla and power options, or the American options. Most of this content can be regarded as a summary of existing results on the use of Mellin transforms in option pricing. The main added value of the thesis is the deeper mathematical analysis which most of the preceding studies were lacking. In fact, although Mellin transforms offer an exceedingly convenient tool under the operational (optimistic) approach, the detailed analysis of its use is rather nontrivial.

## Option Pricing with Long Memory Stochastic Volatility Models

It is now known that long memory stochastic volatility models can capture the well-documented evidence of volatility persistence. However, due to the complex structures of the long memory processes, the analytical formulas for option prices are not available yet. In this book, we propose two fractional continuous time stochastic volatility models which are built on the popular short memory stochastic volatility models. Using the tools from stochastic calculus, fractional calculus and Fourier transform, we derive the (approximate) analytical solutions for option prices. We also numerically study the effects of long memory on option prices. We show that the fractional integration parameter has the opposite effect to that of volatility of volatility parameter. We also find that long memory models can accommodate the short term options and the decay of volatility skew better than the corresponding short memory models. These findings would appeal to the researchers and practitioners in the areas of quantitative finance.

## Portfolio Optimization and Option Pricing

The main two areas of financial mathematics areportfolio optimization and option pricing. Portfoliooptimization deals with the determination of the bestinvestment strategy under certain constraints (e.g.risk, liquidity or budget constraints). Optionpricing is concerned with valuation of derivativecontracts with complex payoffs, dependent on tradableassets. The first part of the book deals with realisticproblems of portfolio optimization. Thereby, theexpected outcome of a utility function underconstraints is maximised. For instance, the portfoliois optimized with fixed income and consumptionconstraints. The borrower rates of an investor dependon his debt-ratio, but usually they are assumed to bedebt-independent. The author shows, how debt-ratiodependent borrower rates can be incorporated intoportfolio optimization and how they affect theoptimal trading strategy. In the second part of thebook, some efficient methods to price Asian andaverage options are introduced. This book is adressed to quantitative researchers andportfolio managers in insurance companies andinvestment banks, as well as students of economicsand financial mathematics.

## Bank Liquidity Risk Management and Measurement

The recent market turmoil caused by the sub-prime crisis highlighted how several key factors can strongly affect the banks’ capability to preserve their financial equilibrium under stress. Current liquidity risk models demonstrated to undervalue extreme events affecting funding and market risk in global scenarios. There was not an integrated measurement tool able to cover all the dimensions of liquidity risk and commonly adopted by the majority of institutions. This work, therefore, intends to highlight the most significant features to consider in order to implement an effective liquidity risk measurement and management.

## Liquidity, Momentum and Expected Returns in Equity Markets of Pakistan

The study tests the significance of multiple risk factors in determination of stock returns in Pakistan using KSE as the benchmark. Pakistan’s market has shown an upward trend as KSE100 improved from 11348 to 16905 points in 2012. The market is also subject to a strong degree of volatility. Individual monthly stock returns from 2006 – 2010 have been used in the study. It will contribute to investor’s understanding of the market and assist research analysts. The study is based on competing Fama-Macbeth models and incorporates equity risk premium, size and value premiums, liquidity premium and momentum premium. The results suggest that in Pakistan, market risk and momentum premiums are strong estimators of equity returns whereas liquidity premium and company specific fundamental factors like size and value premiums do not hold in the country’s equity markets. The limitation is the lack of cross country diversification.

## Default Risk in Equity Returns

This study verifies quantitatively a systematic character of default risk and statistical quality of the competing three- and four-factor asset pricing models. The experimental design applied to this study is premised on the three-factor model of Fama and French enhanced by default risk factor. The study utilizes the factor mimicking portfolio technique for modeling the risks underlying size, value and default risk factors. Distance-to-default estimate, deduced from the option-based model, is adopted by this study as a proxy for default risk. The augmentation of the three-factor model with default risk factor improves the performance of a conventional asset pricing specification on average. The factor loadings of the portfolios of size, value and default risk factors exhibit properties of risk factor sensitivities for stocks. The size and value factors are found to be common in equity returns, but at the same time not being proxies for default related information.

## Advanced pricing of loans using the risk-neutral approach

This book describes a new methodology that allows the Banks to evaluate the loans using a risk neutral approach. More in detail it illustrates the methodological framework behind the definition of the risk neutral default probabilities used to estimate the loans credit spreads. These risk neutral probabilities are calculated using a contingent-claims approach conceptually similar to the Black-Scholes and Merton framework for modeling corporate liabilities. The proposed risk neutral approach is suitable at producing estimates, in a fair value computation context, that are as close as possible to the exit price as mandated by IFRS 13 with a lower dependency on internal parameters. The methodology is compatible with the income approach, usually adopted for the loans evaluation, and is coherent with the discounted cashflows methodologies used for the pricing of securities subject to default risk.

## Pieces on Asset Pricing and Microstructure

Revision with unchanged content. This collection contributes to the fields of asset pricing and financial market microstructure. Two essays study the continuous double auction (CDA), the operating mode of all major stock exchanges. Agent based modelling techniques are used to observe institutional characteristics of CDA markets. Agent based modelling is a novel computational approach, increasingly being applied to financial and economic research. The agent based markets in this work are isolated from artefacts of trader behaviour by employing naive agents, called zero intelligence agents. Such primitive markets possess actual features of real markets pertaining to efficiency, convergence to equilibrium, liquidity effects, and time series properties of price and return. In the second essay price formation in CDA markets with a passive market maker is analysed, and a price density function developed. The third piece empirically investigates the structure of equity returns autocorrelation and presents two stylised facts that reveal anomalous behaviour. These facts are justified by turning to market liquidity as an explanatory factor. An implication is that return reversals deliver profits to traders who undertake the purveyance of liquidity services when opportune; in support of this, a liquidity based trading strategy that delivers significant profits is presented.