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eISBN : 9789812770851

Sommaire :
1 Introduction
1 .I Financial time series
1.2 About this study
1.3 The world's major financial markets
1.4 Examples of daily price series
1.5 A selective review of previous research
1.6 Daily returns
1.7 Models
1.8 Models in this book
1.9 Stochastic processes
1 .I0 Linear stochastic processes

2 Features of financial returns
2.1 Constructing financial time series
2.2 Prices studied
2.3 Average returns and risk premia
2.4 Standard deviations
2.5 Calendar effects
2.6 Skewness
2.7 Kurtosis
2.8 Plausible distributions
2.9 Autocorrelation
2.10 Non-linear structure
2.11 Summary

3 Modelling price volatility
3.1 Introduction
3.2 Elementary variance models
3.3 A general variance model
3.4 Modelling variance jumps
3.5 Modelling frequent variance changes not caused by prices
3.6 Modelling frequent variance changes caused by past prices
3.7 Modelling autocorrelation and variance changes
3.8 Parameter estimation for variance models
3.9 Parameter estimates for product processes
3.10 Parameter estimates for ARMACH processes
3.11 Summary

4 Forecasting standard deviations
4.1 Introduction
4.2 Key theoretical results
4.3 Forecasts: methodology and methods
4.4 Forecasting results
4.5 Recommended forecasts for the next day
4.6 Summary

5 The accuracy of autocorrelation estimates
5.1 Introduction
5.2 Extreme examples
5.3 A special null hypothesis
5.4 Estimates of the variances of sample autocorrelations
5.5 Some asymptotic results
5.6 Interpreting the estimates
5.7 The estimates for returns
5.8 Accurate autocorrelation estimates
5.9 Simulation results
5.10 Autocorrelations of rescaled processes
5.11 Summary

6 Testing the random walk hypothesis
6.1 Introduction
6.2 Test methodology
6.3 Distributions of sample autocorrelations
6.4 A selection of test statistics
6.5 The price-trend hypothesis
6.6 Tests for random walks versus price-trends
6.7 Consequences of data errors
6.8 Results of random walk tests
6.9 Some test results for returns
6.10 Power comparisons
6.11 Testing equilibrium models
6.12 Institutional effects
6.13 Results for subdivided series
6.14 Conclusions
6.15 Summary

7 Forecasting trends in prices
7.1 Introduction
7.2 Price-trend models
7.3 Estimating the trend parameters
7.4 Some results from simulations
7.5 Forecasting returns: theoretical results
7.6 Empirical forecasting results
7.7 Further forecasting theory
7.8 Summary

8 Evidence against the efficiency of futures markets
8.1 Introduction
8.2 The efficient market hypothesis
8.3 Problems raised by previous studies
8.4 Problems measuring risk and return
8.5 Trading conditions
8.6 Theoretical analysis
8.7 Realistic strategies and assumptions
8.8 Trading simulated contracts
8.9 Trading results for futures
8.10 Towards conclusions
8.11 Summary

9 Valuing options
9.1 Introduction
9.2 Black-Scholes option pricing formulae
9.3 Evaluating standard formulae
9.4 Call values when conditional variances change
9.5 Price trends and call values
9.6 Summary

10 Concluding remarks
10.1 Price behaviour
10.2 Advice to traders
10.3 Further research
10.4 Stationary models

Appendix : a computer program for modelling financial time series
Output produced
User-defined parameters
Optional parameters
Input requirements
About the subroutines
FORTRAN program
Computer time required
References

Langue : Anglais

Edition : 2ème

Localisation : Bibliothèque Campus de Nice

Support : Numérique

Etat : Présent

Propriétaire : Bibliothèque