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Biblioteca

MARC Lista (tabellare)
Allgemeines statistisches Archiv
Allgemeines statistisches Archiv
Pubbl/distr/stampa [New York], : Physica-Verlag, -2006
Disciplina 310
Soggetto topico Statistics
Méthode statistique
Statistique
Soggetto genere / forma Periodicals.
Ressource Internet (Descripteur de forme)
Périodique électronique (Descripteur de forme)
ISSN 1614-0176
Formato Materiale a stampa
Livello bibliografico Periodico
Lingua di pubblicazione ger
Record Nr. UNISA-996218752703316
[New York], : Physica-Verlag, -2006
Materiale a stampa
Lo trovi qui: Univ. di Salerno
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Alphanumeric : the journal of operations research, statistics, econometrics and management information systems
Alphanumeric : the journal of operations research, statistics, econometrics and management information systems
Pubbl/distr/stampa Istanbul, Turkey : , : School of Transportation and Logistics, Istanbul University, , 2013-
Descrizione fisica 1 online resource
Soggetto topico Operations research
Statistics
Econometrics
Management information systems
Soggetto genere / forma Periodicals.
ISSN 2148-2225
Formato Materiale a stampa
Livello bibliografico Periodico
Lingua di pubblicazione eng
Altri titoli varianti Alphanumeric journal
Record Nr. UNINA-9910265954403321
Istanbul, Turkey : , : School of Transportation and Logistics, Istanbul University, , 2013-
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Alphanumeric : the journal of operations research, statistics, econometrics and management information systems
Alphanumeric : the journal of operations research, statistics, econometrics and management information systems
Pubbl/distr/stampa Istanbul, Turkey : , : School of Transportation and Logistics, Istanbul University, , 2013-
Descrizione fisica 1 online resource
Soggetto topico Operations research
Statistics
Econometrics
Management information systems
Soggetto genere / forma Periodicals.
ISSN 2148-2225
Formato Materiale a stampa
Livello bibliografico Periodico
Lingua di pubblicazione eng
Altri titoli varianti Alphanumeric journal
Record Nr. UNISA-996321583903316
Istanbul, Turkey : , : School of Transportation and Logistics, Istanbul University, , 2013-
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
The American statistician
The American statistician
Pubbl/distr/stampa Washington, DC, : American Statistical Association
Disciplina 310
Soggetto topico Statistics
Soggetto genere / forma Periodicals.
ISSN 1537-2731
Formato Materiale a stampa
Livello bibliografico Periodico
Lingua di pubblicazione eng
Record Nr. UNISA-996215970603316
Washington, DC, : American Statistical Association
Materiale a stampa
Lo trovi qui: Univ. di Salerno
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The American statistician
The American statistician
Pubbl/distr/stampa Washington, DC, : American Statistical Association
Disciplina 310
Soggetto topico Statistics
Soggetto genere / forma Periodicals.
ISSN 1537-2731
Formato Materiale a stampa
Livello bibliografico Periodico
Lingua di pubblicazione eng
Record Nr. UNINA-9910134146203321
Washington, DC, : American Statistical Association
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Analysis of Categorical Data from Historical Perspectives [[electronic resource] ] : Essays in Honour of Shizuhiko Nishisato / / edited by Eric J. Beh, Rosaria Lombardo, Jose G. Clavel
Analysis of Categorical Data from Historical Perspectives [[electronic resource] ] : Essays in Honour of Shizuhiko Nishisato / / edited by Eric J. Beh, Rosaria Lombardo, Jose G. Clavel
Autore Beh Eric J
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (0 pages)
Disciplina 519
Altri autori (Persone) LombardoRosaria
ClavelJose G
Collana Behaviormetrics: Quantitative Approaches to Human Behavior
Soggetto topico Statistics
Social sciences - Statistical methods
Quantitative research
Psychometrics
Applied Statistics
Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy
Statistical Theory and Methods
Data Analysis and Big Data
ISBN 981-9953-29-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Gratitude: A Life Relived -- Nishisato’s Psychometric World -- My Recollections of People in the World of Data Science -- A Straightforward Approach to Chi-Squared Analysis of Associations in Contingency Tables -- Contrasts for Neyman’s Modified Chi-Square Statistic in One-Way Contingency Tables.
Record Nr. UNINA-9910806195503321
Beh Eric J  
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Analysis of variance [e-book] / ed. by P. R. Krishnaiah
Analysis of variance [e-book] / ed. by P. R. Krishnaiah
Pubbl/distr/stampa Amsterdam : North-Holland, 1980
Descrizione fisica xvi, 1002 p. ; 25 cm
Disciplina 519.5952
Altri autori (Persone) Krishnaiah, Paruchuri R.
Collana Handbook of statistics, 0169-7161 ; 1
Soggetto topico Statistics
ISBN 0444853359
Classificazione AMS 62-02
LC QA279.A524
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISALENTO-991002545979707536
Amsterdam : North-Holland, 1980
Materiale a stampa
Lo trovi qui: Univ. del Salento
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Analysis of variance / ed. by P. R. Krishnaiah
Analysis of variance / ed. by P. R. Krishnaiah
Pubbl/distr/stampa Amsterdam : North-Holland, 1980
Descrizione fisica xvi, 1002 p. ; 25 cm
Disciplina 519.5952
Altri autori (Persone) Krishnaiah, Paruchuri R.
Collana Handbook of statistics, 0169-7161 ; 1
Soggetto topico Statistics
ISBN 0444853359
Classificazione AMS 62-02
AMS 62-XX
LC QA279.A524
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISALENTO-991000680809707536
Amsterdam : North-Holland, 1980
Materiale a stampa
Lo trovi qui: Univ. del Salento
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Analyzing financial data and implementing financial models using R / / Clifford S. Ang
Analyzing financial data and implementing financial models using R / / Clifford S. Ang
Autore Ang Clifford S.
Edizione [2nd ed.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (476 pages)
Disciplina 332
Collana Springer Texts in Business and Economics
Soggetto topico Risk management
Economics, Mathematical
Statistics
R (Computer program language)
ISBN 3-030-64155-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Acknowledgments -- Contents -- 1 Prices -- 1.1 Price Versus Value -- 1.2 Importing Price Data from Yahoo Finance -- 1.3 Checking the Data -- 1.3.1 Check the Start and End Data -- 1.3.2 Plotting the Data -- 1.3.3 Checking the Dimension -- 1.3.4 Outputting Summary Statistics -- 1.3.5 Checking the Ticker Symbol -- 1.4 Basic Data Manipulation Techniques -- 1.4.1 Keeping and Deleting One Row -- 1.4.2 Keeping First and Last Rows -- 1.4.3 Keeping Contiguous Rows -- 1.4.4 Keeping One Column -- 1.4.5 Deleting One Column -- 1.4.6 Keeping Non-Contiguous Columns -- 1.4.7 Keeping Contiguous Columns -- 1.4.8 Keeping Contiguous and Non-Contiguous Columns -- 1.4.9 Keeping Rows and Columns -- 1.4.10 Subsetting Time Series Data Using Dates -- 1.4.11 Converting to Weekly Prices -- 1.4.12 Converting to Monthly Prices -- 1.5 Comparing Capital Gains Between Securities -- 1.5.1 Alternative 1-Using xts-Style Chart -- 1.5.2 Alternative 2-Plotting Four Mini-Charts -- 1.5.3 Alternative 3-Using ggplot to Plot FourMini-Charts -- 1.6 Simple and Exponential Moving Averages -- 1.7 Volume-Weighted Average Price -- 1.8 Plotting a Candlestick Chart -- 1.9 2-Axis Price and Volume Chart -- 1.10 Further Reading -- References -- 2 Individual Security Returns -- 2.1 Price Returns -- 2.2 Total Returns -- 2.3 Logarithmic Total Returns -- 2.4 Winsorization and Truncation -- 2.5 Cumulating Multi-Day Returns -- 2.5.1 Cumulating Arithmetic Returns -- 2.5.2 Cumulating Logarithmic Returns -- 2.5.3 Comparing Price Return and Total Return -- 2.6 Weekly Returns -- 2.7 Monthly Returns -- 2.8 Comparing Performance of Multiple Securities -- 2.8.1 Using Normalized Prices -- 2.8.2 Using Cumulative Returns -- 3 Portfolio Returns -- 3.1 Portfolio Returns the Long Way -- 3.2 Portfolio Returns Using Matrix Algebra -- 3.3 Constructing Benchmark Portfolio Returns.
3.3.1 Quarterly Returns the Long Way -- 3.3.2 Quarterly Returns the Shorter Way -- 3.3.3 Equal-Weighted Portfolio -- 3.3.4 Value-Weighted Portfolio -- 3.3.5 Daily Portfolio Returns -- 3.4 Time-Weighted Rate of Return -- 3.5 Money-Weighted Rate of Return -- 3.6 Further Reading -- Reference -- 4 Risk -- 4.1 Risk-Return Trade-Off -- 4.2 Individual Security Risk -- 4.2.1 Standard Deviation and Variance -- 4.3 Portfolio Risk -- 4.3.1 Two Assets Using Manual Approach -- 4.3.2 Two Assets Using Matrix Algebra -- 4.3.3 Multiple Assets -- 4.4 Value-at-Risk -- 4.4.1 Gaussian VaR -- 4.4.2 Historical VaR -- 4.5 Expected Shortfall -- 4.5.1 Gaussian ES -- 4.5.2 Historical ES -- 4.5.3 Comparing VaR and ES -- 4.6 Alternative Risk Measures -- 4.6.1 Parkinson -- 4.6.2 Garman-Klass -- 4.6.3 Rogers, Satchell, and Yoon -- 4.6.4 Yang and Zhang -- 4.6.5 Comparing the Risk Measures -- 4.7 Further Reading -- References -- 5 Factor Models -- 5.1 CAPM -- 5.2 Market Model -- 5.3 Rolling Window Regressions -- 5.4 Betas on Different Reference Days -- 5.5 Fama-French Three Factor Model -- 5.6 Testing for Heteroskedasticity -- 5.7 Testing for Non-Normality -- 5.8 Testing for Autocorrelation -- 5.9 Event Studies -- 5.9.1 Example: Drop in Tesla Stock After 1Q 2019 Earnings Release on April 24, 2019 -- 5.9.2 Single Step Event Study -- 5.9.3 Two Stage Event Study -- 5.9.4 Sample Quantiles/Non-Parametric -- 5.10 Selecting Best Regression Variables -- 5.10.1 Create Dataset of Returns -- 5.10.2 Forward Step Approach -- 5.10.3 Backward Step Approach -- 5.10.4 Suppressing Steps in Output -- 5.11 Further Reading -- References -- 6 Risk-Adjusted Portfolio Performance Measures -- 6.1 Portfolio and Benchmark Data -- 6.2 Sharpe Ratio -- 6.3 Roy's Safety First Ratio -- 6.4 Treynor Ratio -- 6.5 Sortino Ratio -- 6.6 Information Ratio -- 6.7 Combining Results -- 6.8 Further Reading -- References.
7 Markowitz Mean-Variance Optimization -- 7.1 Two Assets the Long Way -- 7.2 Two Assets Using Quadratic Programming -- 7.3 Multiple Assets Using Quadratic Programming -- 7.4 Effect of Allowing Short Selling -- 7.5 Further Reading -- References -- 8 Equities -- 8.1 Company Financials -- 8.2 Projections -- 8.2.1 Projecting Based on Historical Trends -- 8.2.2 Analyzing Projections Prepared by Third Parties -- 8.2.3 Analyzing Growth Rates Embedded in Projections -- 8.2.4 Analyzing Projections Using Regression Analysis -- 8.3 Equity Risk Premium -- 8.4 Unlevering Betas -- 8.5 Sensitivity Analysis -- 8.6 Relative Valuation Using Regression Analysis -- 8.7 Identifying Significant Shifts in Stock Returns -- 8.7.1 t-Test: Testing Difference in Average Returns -- 8.7.2 Identifying Breakpoints -- 8.7.3 Chow Test -- 8.7.4 Test Equality of Two Betas -- 8.8 Further Reading -- References -- 9 Fixed Income -- 9.1 Economic Analysis -- 9.1.1 Real GDP -- 9.1.2 Unemployment Rate -- 9.1.3 Inflation Rate -- 9.2 US Treasuries -- 9.2.1 Shape of the US Treasury Yield Curve -- 9.2.2 Slope of the US Treasury Yield Curve -- 9.2.3 Real Yields on US Treasuries -- 9.2.4 Expected Inflation Rates -- 9.2.5 Mean Reversion -- 9.3 Principal Components Analysis -- 9.4 Investment Grade Bond Spreads -- 9.4.1 Time Series of Spreads -- 9.4.2 Spreads and Real GDP Growth -- 9.5 Bond Valuation -- 9.5.1 Valuing Bonds with Known Yield to Maturity -- 9.5.2 Bond Valuation Function -- 9.5.3 Finding the Yield to Maturity -- 9.6 Duration and Convexity -- 9.6.1 Calculating Duration and Convexity -- 9.6.2 Duration and Convexity Functions -- 9.6.3 Comparing Estimates of Value to Full Valuation -- 9.7 Short Rate Models -- 9.7.1 Vasicek -- 9.7.2 Cox, Ingersoll, and Ross -- 9.8 Further Reading -- References -- 10 Options -- 10.1 Obtaining Options Chain Data -- 10.2 Black-Scholes-Merton Options Pricing Model.
10.2.1 BSM Function -- 10.2.2 Put-Call Parity -- 10.2.3 The Greeks -- 10.3 Implied Volatility -- 10.3.1 Implied Volatility Function -- 10.3.2 Volatility Smile -- 10.3.3 Gauging Market Risk -- 10.4 The Cox, Ross, and Rubinstein Binomial OPM -- 10.4.1 CRR: The Long Way -- 10.4.2 CRR Function -- 10.5 American Option Pricing -- 10.5.1 CRR Binomial Tree -- 10.5.2 Bjerksund-Stensland Approximation -- 10.6 Further Reading -- References -- 11 Simulation -- 11.1 Simulating Stock Prices Using Geometric Brownian Motion -- 11.1.1 Simulating Multiple Ending Stock Price Paths -- 11.1.2 Comparing Theoretical to Empirical Distributions -- 11.2 Simulating Stock Prices with and Without Dividends -- 11.3 Simulating Stocks with Correlated Prices -- 11.4 Value-at-Risk Using Simulation -- 11.5 Monte Carlo Pricing of European Options -- 11.6 Monte Carlo Option Pricing Using Antithetic Variables -- 11.7 Exotic Option Valuation -- 11.7.1 Asian Options -- 11.7.2 Lookback Options -- 11.7.3 Barrier Options -- 11.8 Further Reading -- References -- 12 Trading Strategies -- 12.1 Efficient Markets Hypothesis -- 12.1.1 Autocorrelation Test -- 12.1.2 Variance Ratio Test -- 12.1.3 Runs Test -- 12.2 Technical Analysis -- 12.2.1 Trend: Simple Moving Average Crossover -- 12.2.2 Volatility: Bollinger Bands -- 12.2.3 Momentum: Relative Strength Index -- 12.3 Building a Simple Trading Strategy -- 12.4 Machine Learning Techniques -- 12.4.1 General Steps to Apply ML -- 12.4.2 k-Nearest Neighbor Algorithm -- 12.4.3 Regression and k-Fold Cross Validation -- 12.4.4 Artificial Neural Networks -- 12.5 Further Reading -- References -- A Getting Started with R -- A.1 Installing R -- A.2 The R Working Directory -- A.3 R Console Output -- A.4 R Editor -- A.5 Packages -- A.6 Basic Commands -- A.7 The R Workspace -- A.8 Vectors -- A.9 Combining Vectors -- A.10 Matrices -- A.11 data.frame.
A.12 Date Formats -- B Pre-Loaded Code -- C Constructing a Hypothetical Portfolio (Monthly Returns) -- D Constructing a Hypothetical Portfolio (Daily Returns) -- Index.
Record Nr. UNISA-996464519103316
Ang Clifford S.  
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Analyzing financial data and implementing financial models using R / / Clifford S. Ang
Analyzing financial data and implementing financial models using R / / Clifford S. Ang
Autore Ang Clifford S.
Edizione [2nd ed.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (476 pages)
Disciplina 332
Collana Springer Texts in Business and Economics
Soggetto topico Risk management
Economics, Mathematical
Statistics
R (Computer program language)
ISBN 3-030-64155-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Acknowledgments -- Contents -- 1 Prices -- 1.1 Price Versus Value -- 1.2 Importing Price Data from Yahoo Finance -- 1.3 Checking the Data -- 1.3.1 Check the Start and End Data -- 1.3.2 Plotting the Data -- 1.3.3 Checking the Dimension -- 1.3.4 Outputting Summary Statistics -- 1.3.5 Checking the Ticker Symbol -- 1.4 Basic Data Manipulation Techniques -- 1.4.1 Keeping and Deleting One Row -- 1.4.2 Keeping First and Last Rows -- 1.4.3 Keeping Contiguous Rows -- 1.4.4 Keeping One Column -- 1.4.5 Deleting One Column -- 1.4.6 Keeping Non-Contiguous Columns -- 1.4.7 Keeping Contiguous Columns -- 1.4.8 Keeping Contiguous and Non-Contiguous Columns -- 1.4.9 Keeping Rows and Columns -- 1.4.10 Subsetting Time Series Data Using Dates -- 1.4.11 Converting to Weekly Prices -- 1.4.12 Converting to Monthly Prices -- 1.5 Comparing Capital Gains Between Securities -- 1.5.1 Alternative 1-Using xts-Style Chart -- 1.5.2 Alternative 2-Plotting Four Mini-Charts -- 1.5.3 Alternative 3-Using ggplot to Plot FourMini-Charts -- 1.6 Simple and Exponential Moving Averages -- 1.7 Volume-Weighted Average Price -- 1.8 Plotting a Candlestick Chart -- 1.9 2-Axis Price and Volume Chart -- 1.10 Further Reading -- References -- 2 Individual Security Returns -- 2.1 Price Returns -- 2.2 Total Returns -- 2.3 Logarithmic Total Returns -- 2.4 Winsorization and Truncation -- 2.5 Cumulating Multi-Day Returns -- 2.5.1 Cumulating Arithmetic Returns -- 2.5.2 Cumulating Logarithmic Returns -- 2.5.3 Comparing Price Return and Total Return -- 2.6 Weekly Returns -- 2.7 Monthly Returns -- 2.8 Comparing Performance of Multiple Securities -- 2.8.1 Using Normalized Prices -- 2.8.2 Using Cumulative Returns -- 3 Portfolio Returns -- 3.1 Portfolio Returns the Long Way -- 3.2 Portfolio Returns Using Matrix Algebra -- 3.3 Constructing Benchmark Portfolio Returns.
3.3.1 Quarterly Returns the Long Way -- 3.3.2 Quarterly Returns the Shorter Way -- 3.3.3 Equal-Weighted Portfolio -- 3.3.4 Value-Weighted Portfolio -- 3.3.5 Daily Portfolio Returns -- 3.4 Time-Weighted Rate of Return -- 3.5 Money-Weighted Rate of Return -- 3.6 Further Reading -- Reference -- 4 Risk -- 4.1 Risk-Return Trade-Off -- 4.2 Individual Security Risk -- 4.2.1 Standard Deviation and Variance -- 4.3 Portfolio Risk -- 4.3.1 Two Assets Using Manual Approach -- 4.3.2 Two Assets Using Matrix Algebra -- 4.3.3 Multiple Assets -- 4.4 Value-at-Risk -- 4.4.1 Gaussian VaR -- 4.4.2 Historical VaR -- 4.5 Expected Shortfall -- 4.5.1 Gaussian ES -- 4.5.2 Historical ES -- 4.5.3 Comparing VaR and ES -- 4.6 Alternative Risk Measures -- 4.6.1 Parkinson -- 4.6.2 Garman-Klass -- 4.6.3 Rogers, Satchell, and Yoon -- 4.6.4 Yang and Zhang -- 4.6.5 Comparing the Risk Measures -- 4.7 Further Reading -- References -- 5 Factor Models -- 5.1 CAPM -- 5.2 Market Model -- 5.3 Rolling Window Regressions -- 5.4 Betas on Different Reference Days -- 5.5 Fama-French Three Factor Model -- 5.6 Testing for Heteroskedasticity -- 5.7 Testing for Non-Normality -- 5.8 Testing for Autocorrelation -- 5.9 Event Studies -- 5.9.1 Example: Drop in Tesla Stock After 1Q 2019 Earnings Release on April 24, 2019 -- 5.9.2 Single Step Event Study -- 5.9.3 Two Stage Event Study -- 5.9.4 Sample Quantiles/Non-Parametric -- 5.10 Selecting Best Regression Variables -- 5.10.1 Create Dataset of Returns -- 5.10.2 Forward Step Approach -- 5.10.3 Backward Step Approach -- 5.10.4 Suppressing Steps in Output -- 5.11 Further Reading -- References -- 6 Risk-Adjusted Portfolio Performance Measures -- 6.1 Portfolio and Benchmark Data -- 6.2 Sharpe Ratio -- 6.3 Roy's Safety First Ratio -- 6.4 Treynor Ratio -- 6.5 Sortino Ratio -- 6.6 Information Ratio -- 6.7 Combining Results -- 6.8 Further Reading -- References.
7 Markowitz Mean-Variance Optimization -- 7.1 Two Assets the Long Way -- 7.2 Two Assets Using Quadratic Programming -- 7.3 Multiple Assets Using Quadratic Programming -- 7.4 Effect of Allowing Short Selling -- 7.5 Further Reading -- References -- 8 Equities -- 8.1 Company Financials -- 8.2 Projections -- 8.2.1 Projecting Based on Historical Trends -- 8.2.2 Analyzing Projections Prepared by Third Parties -- 8.2.3 Analyzing Growth Rates Embedded in Projections -- 8.2.4 Analyzing Projections Using Regression Analysis -- 8.3 Equity Risk Premium -- 8.4 Unlevering Betas -- 8.5 Sensitivity Analysis -- 8.6 Relative Valuation Using Regression Analysis -- 8.7 Identifying Significant Shifts in Stock Returns -- 8.7.1 t-Test: Testing Difference in Average Returns -- 8.7.2 Identifying Breakpoints -- 8.7.3 Chow Test -- 8.7.4 Test Equality of Two Betas -- 8.8 Further Reading -- References -- 9 Fixed Income -- 9.1 Economic Analysis -- 9.1.1 Real GDP -- 9.1.2 Unemployment Rate -- 9.1.3 Inflation Rate -- 9.2 US Treasuries -- 9.2.1 Shape of the US Treasury Yield Curve -- 9.2.2 Slope of the US Treasury Yield Curve -- 9.2.3 Real Yields on US Treasuries -- 9.2.4 Expected Inflation Rates -- 9.2.5 Mean Reversion -- 9.3 Principal Components Analysis -- 9.4 Investment Grade Bond Spreads -- 9.4.1 Time Series of Spreads -- 9.4.2 Spreads and Real GDP Growth -- 9.5 Bond Valuation -- 9.5.1 Valuing Bonds with Known Yield to Maturity -- 9.5.2 Bond Valuation Function -- 9.5.3 Finding the Yield to Maturity -- 9.6 Duration and Convexity -- 9.6.1 Calculating Duration and Convexity -- 9.6.2 Duration and Convexity Functions -- 9.6.3 Comparing Estimates of Value to Full Valuation -- 9.7 Short Rate Models -- 9.7.1 Vasicek -- 9.7.2 Cox, Ingersoll, and Ross -- 9.8 Further Reading -- References -- 10 Options -- 10.1 Obtaining Options Chain Data -- 10.2 Black-Scholes-Merton Options Pricing Model.
10.2.1 BSM Function -- 10.2.2 Put-Call Parity -- 10.2.3 The Greeks -- 10.3 Implied Volatility -- 10.3.1 Implied Volatility Function -- 10.3.2 Volatility Smile -- 10.3.3 Gauging Market Risk -- 10.4 The Cox, Ross, and Rubinstein Binomial OPM -- 10.4.1 CRR: The Long Way -- 10.4.2 CRR Function -- 10.5 American Option Pricing -- 10.5.1 CRR Binomial Tree -- 10.5.2 Bjerksund-Stensland Approximation -- 10.6 Further Reading -- References -- 11 Simulation -- 11.1 Simulating Stock Prices Using Geometric Brownian Motion -- 11.1.1 Simulating Multiple Ending Stock Price Paths -- 11.1.2 Comparing Theoretical to Empirical Distributions -- 11.2 Simulating Stock Prices with and Without Dividends -- 11.3 Simulating Stocks with Correlated Prices -- 11.4 Value-at-Risk Using Simulation -- 11.5 Monte Carlo Pricing of European Options -- 11.6 Monte Carlo Option Pricing Using Antithetic Variables -- 11.7 Exotic Option Valuation -- 11.7.1 Asian Options -- 11.7.2 Lookback Options -- 11.7.3 Barrier Options -- 11.8 Further Reading -- References -- 12 Trading Strategies -- 12.1 Efficient Markets Hypothesis -- 12.1.1 Autocorrelation Test -- 12.1.2 Variance Ratio Test -- 12.1.3 Runs Test -- 12.2 Technical Analysis -- 12.2.1 Trend: Simple Moving Average Crossover -- 12.2.2 Volatility: Bollinger Bands -- 12.2.3 Momentum: Relative Strength Index -- 12.3 Building a Simple Trading Strategy -- 12.4 Machine Learning Techniques -- 12.4.1 General Steps to Apply ML -- 12.4.2 k-Nearest Neighbor Algorithm -- 12.4.3 Regression and k-Fold Cross Validation -- 12.4.4 Artificial Neural Networks -- 12.5 Further Reading -- References -- A Getting Started with R -- A.1 Installing R -- A.2 The R Working Directory -- A.3 R Console Output -- A.4 R Editor -- A.5 Packages -- A.6 Basic Commands -- A.7 The R Workspace -- A.8 Vectors -- A.9 Combining Vectors -- A.10 Matrices -- A.11 data.frame.
A.12 Date Formats -- B Pre-Loaded Code -- C Constructing a Hypothetical Portfolio (Monthly Returns) -- D Constructing a Hypothetical Portfolio (Daily Returns) -- Index.
Record Nr. UNINA-9910488695503321
Ang Clifford S.  
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui

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