Dr Gita Persand

'Dr Gita Persand

Dr Gita Persand

  • Lecturer in Finance

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Profile & Expertise

Gita Persand is a Lecturer in Finance and currently teaches on the undergraduate degree programmes, having previously taught at the Universities of Bristol and Southampton. She is the module convenor for Financial Modelling and for Introductory Finance. Gita holds a PhD in Risk Management from the ICMA Centre. Her research is in the areas of financial risk management and financial econometrics, and she has published in various journals including the Journal of Business, Journal of Empirical Finance, Journal of Banking and Finance, Financial Analyst Journal, Journal of Applied Econometrics, andInternational Journal of Forecasting.

Specialisms

  • Financial risk management
  • Financial econometrics

Key publications, books, research & papers

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Article

Autoregressive conditional kurtosis

Brooks, C. , Burke, S. P. , Heravi, S. and Persand, G. (2005) Autoregressive conditional kurtosis. Journal of Financial Econometrics, 3 (3). pp. 399-421. ISSN 1479-8417 doi: https://doi.org/10.1093/jjfinec/nbi018

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This article proposes a new model for autoregressive conditional heteroscedasticity and kurtosis. Via a time-varying degrees of freedom parameter, the conditional variance and conditional kurtosis are permitted to evolve separately. The model uses only the standard Student’s t-density and consequently can be estimated simply using maximum likelihood. The method is applied to a set of four daily financial asset return series comprising U.S. and U.K. stocks and bonds, and significant evidence in favor of the presence of autoregressive conditional kurtosis is observed. Various extensions to the basic model are proposed, and we show that the response of kurtosis to good and bad news is not significantly asymmetric.

Professor Chris Brooks

Professor Chris Brooks

Henley Business School Director of Research, Deputy Head of Department

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Dr Gita Persand

Dr Gita Persand

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Article

A comparison of extreme value theory approaches for determining value at risk

Brooks, C. , Clare, A. D., Dalle Molle, J. W. and Persand, G. (2005) A comparison of extreme value theory approaches for determining value at risk. Journal of Empirical Finance, 12 (2). pp. 339-352. ISSN 0927-5398 doi: https://doi.org/10.1016/j.jempfin.2004.01.004

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This paper compares a number of different extreme value models for determining the value at risk (VaR) of three LIFFE futures contracts. A semi-nonparametric approach is also proposed, where the tail events are modeled using the generalised Pareto distribution, and normal market conditions are captured by the empirical distribution function. The value at risk estimates from this approach are compared with those of standard nonparametric extreme value tail estimation approaches, with a small sample bias-corrected extreme value approach, and with those calculated from bootstrapping the unconditional density and bootstrapping from a GARCH(1,1) model. The results indicate that, for a holdout sample, the proposed semi-nonparametric extreme value approach yields superior results to other methods, but the small sample tail index technique is also accurate.

Professor Chris Brooks

Professor Chris Brooks

Henley Business School Director of Research, Deputy Head of Department

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Dr Gita Persand

Dr Gita Persand

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Article

Volatility forecasting for risk management

Brooks, C. and Persand, G. (2003) Volatility forecasting for risk management. Journal of Forecasting, 22 (1). pp. 1-22. ISSN 1099-131X doi: https://doi.org/10.1002/for.841

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Recent research has suggested that forecast evaluation on the basis of standard statistical loss functions could prefer models which are sub-optimal when used in a practical setting. This paper explores a number of statistical models for predicting the daily volatility of several key UK financial time series. The out-of-sample forecasting performance of various linear and GARCH-type models of volatility are compared with forecasts derived from a multivariate approach. The forecasts are evaluated using traditional metrics, such as mean squared error, and also by how adequately they perform in a modern risk management setting. We find that the relative accuracies of the various methods are highly sensitive to the measure used to evaluate them. Such results have implications for any econometric time series forecasts which are subsequently employed in financial decisionmaking.

Professor Chris Brooks

Professor Chris Brooks

Henley Business School Director of Research, Deputy Head of Department

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Dr Gita Persand

Dr Gita Persand

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Article

The effect of asymmetries on stock index return value-at-risk estimates

Brooks, C. and Persand, G. (2003) The effect of asymmetries on stock index return value-at-risk estimates. Journal of Risk Finance, 4 (2). pp. 29-42. ISSN 1526-5943 doi: https://doi.org/10.1108/eb022959

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It is widely accepted that equity return volatility increases more following negative shocks rather than positive shocks. However, much of value-at-risk (VaR) analysis relies on the assumption that returns are normally distributed (a symmetric distribution). This article considers the effect of asymmetries on the evaluation and accuracy of VaR by comparing estimates based on various models.

Professor Chris Brooks

Professor Chris Brooks

Henley Business School Director of Research, Deputy Head of Department

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Dr Gita Persand

Dr Gita Persand

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Article

The effect of asymmetries on optimal hedge ratios

Brooks, C. , Henry, O.T. and Persand, G. (2002) The effect of asymmetries on optimal hedge ratios. Journal of Business, 75 (2). pp. 333-352. ISSN 0740-9168

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There is widespread evidence that the volatility of stock returns displays an asymmetric response to good and bad news. This article considers the impact of asymmetry on time-varying hedges for financial futures. An asymmetric model that allows forecasts of cash and futures return volatility to respond differently to positive and negative return innovations gives superior in-sample hedging performance. However, the simpler symmetric model is not inferior in a hold-out sample. A method for evaluating the models in a modern risk-management framework is presented, highlighting the importance of allowing optimal hedge ratios to be both time-varying and asymmetric.

Professor Chris Brooks

Professor Chris Brooks

Henley Business School Director of Research, Deputy Head of Department

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Dr Gita Persand

Dr Gita Persand

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Article

Model choice and value-at-risk performance

Brooks, C. and Persand, G. (2002) Model choice and value-at-risk performance. Financial Analysts Journal, 58 (5). pp. 87-97. doi: https://doi.org/10.2469/faj.v58.n5.2471

Professor Chris Brooks

Professor Chris Brooks

Henley Business School Director of Research, Deputy Head of Department

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Dr Gita Persand

Dr Gita Persand

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Article

An extreme value theory approach to calculating minimum capital risk requirements

Brooks, C. , Clare, A.D. and Persand, G. (2002) An extreme value theory approach to calculating minimum capital risk requirements. Journal of Risk Finance, 3 (2). pp. 22-33. ISSN 1526-5943 doi: https://doi.org/10.1108/eb043485

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This paper investigates the frequency of extreme events for three LIFFE futures contracts for the calculation of minimum capital risk requirements (MCRRs). We propose a semiparametric approach where the tails are modelled by the Generalized Pareto Distribution and smaller risks are captured by the empirical distribution function. We compare the capital requirements form this approach with those calculated from the unconditional density and from a conditional density – a GARCH(1,1) model. Our primary finding is that both in-sample and for a hold-out sample, our extreme value approach yields superior results than either of the other two models which do not explicitly model the tails of the return distribution. Since the use of these internal models will be permitted under the EC-CAD II, they could be widely adopted in the near future for determining capital adequacies. Hence, close scrutiny of competing models is required to avoid a potentially costly misallocation capital resources while at the same time ensuring the safety of the financial system.

Professor Chris Brooks

Professor Chris Brooks

Henley Business School Director of Research, Deputy Head of Department

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Dr Gita Persand

Dr Gita Persand

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Article

A note on estimating market–based minimum capital risk requirements: a multivariate GARCH approach

Brooks, C. , Clare, A.D. and Persand, G. (2002) A note on estimating market–based minimum capital risk requirements: a multivariate GARCH approach. The Manchester School, 70 (5). pp. 666-681. ISSN 1467-9957 doi: https://doi.org/10.1111/1467-9957.00319

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Internal risk management models of the kind popularized by J. P. Morgan are now used widely by the world’s most sophisticated financial institutions as a means of measuring risk. Using the returns on three of the most popular futures contracts on the London International Financial Futures Exchange, in this paper we investigate the possibility of using multivariate generalized autoregressive conditional heteroscedasticity (GARCH) models for the calculation of minimum capital risk requirements (MCRRs). We propose a method for the estimation of the value at risk of a portfolio based on a multivariate GARCH model. We find that the consideration of the correlation between the contracts can lead to more accurate, and therefore more appropriate, MCRRs compared with the values obtained from a univariate approach to the problem.

Professor Chris Brooks

Professor Chris Brooks

Henley Business School Director of Research, Deputy Head of Department

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Dr Gita Persand

Dr Gita Persand

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Article

The trading profitability of forecasts of the gilt–equity yield ratio

Brooks, C. and Persand, G. (2001) The trading profitability of forecasts of the gilt–equity yield ratio. International Journal of Forecasting, 17 (1). pp. 11-29. ISSN 0169-2070 doi: https://doi.org/10.1016/S0169-2070(00)00060-1

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Research has highlighted the usefulness of the Gilt–Equity Yield Ratio (GEYR) as a predictor of UK stock returns. This paper extends recent studies by endogenising the threshold at which the GEYR switches from being low to being high or vice versa, thus improving the arbitrary nature of the determination of the threshold employed in the extant literature. It is observed that a decision rule for investing in equities or bonds, based on the forecasts from a regime switching model, yields higher average returns with lower variability than a static portfolio containing any combinations of equities and bonds. A closer inspection of the results reveals that the model has power to forecast when investors should steer clear of equities, although the trading profits generated are insufficient to outweigh the associated transaction costs.

Professor Chris Brooks

Professor Chris Brooks

Henley Business School Director of Research, Deputy Head of Department

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Dr Gita Persand

Dr Gita Persand

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Article

Seasonality in Southeast Asian stock markets: some new evidence on day-of-the-week effects

Brooks, C. and Persand, G. (2001) Seasonality in Southeast Asian stock markets: some new evidence on day-of-the-week effects. Applied Economics Letters, 8 (3). pp. 155-158. ISSN 1466-4291 doi: https://doi.org/10.1080/13504850150504504

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This paper examines the evidence for a day-of-the-week effect in five Southeast Asian stock markets: South Korea, Malaysia, the Philippines, Taiwan and Thailand. Findings indicate significant seasonality for three of the five markets. Market risk, proxied by the return on the FTA World Price Index, is not sufficient to explain this calendar anomaly. Although an extension of the risk-return equation to incorporate interactive seasonal dummy variables can explain some significant day-of-the-week effects, market risk alone appears insufficient to characterize this phenomenon.

Professor Chris Brooks

Professor Chris Brooks

Henley Business School Director of Research, Deputy Head of Department

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Dr Gita Persand

Dr Gita Persand

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Article

Benchmarks and the accuracy of GARCH model estimation

Brooks, C. , Burke, S. and Persand, G. (2001) Benchmarks and the accuracy of GARCH model estimation. International Journal of Forecasting, 17 (1). pp. 45-56. ISSN 0169-2070 doi: https://doi.org/10.1016/S0169-2070(00)00070-4

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This paper reviews nine software packages with particular reference to their GARCH model estimation accuracy when judged against a respected benchmark. We consider the numerical consistency of GARCH and EGARCH estimation and forecasting. Our results have a number of implications for published research and future software development. Finally, we argue that the establishment of benchmarks for other standard non-linear models is long overdue.

Professor Chris Brooks

Professor Chris Brooks

Henley Business School Director of Research, Deputy Head of Department

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Dr Gita Persand

Dr Gita Persand

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Article

A word of caution on calculating market-based minimum capital risk requirements

Brooks, C. , Clare, A. D. and Persand, G. (2000) A word of caution on calculating market-based minimum capital risk requirements. Journal of Banking & Finance, 24 (10). pp. 1557-1574. ISSN 0378-4266 doi: https://doi.org/10.1016/S0378-4266(99)00092-8

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This paper demonstrates that the use of GARCH-type models for the calculation of minimum capital risk requirements (MCRRs) may lead to the production of inaccurate and therefore inefficient capital requirements. We show that this inaccuracy stems from the fact that GARCH models typically overstate the degree of persistence in return volatility. A simple modification to the model is found to improve the accuracy of MCRR estimates in both back- and out-of-sample tests. Given that internal risk management models are currently in widespread usage in some parts of the world (most notably the USA), and will soon be permitted for EC banks and investment firms, we believe that our paper should serve as a valuable caution to risk management practitioners who are using, or intend to use this popular class of models.

Professor Chris Brooks

Professor Chris Brooks

Henley Business School Director of Research, Deputy Head of Department

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Dr Gita Persand

Dr Gita Persand

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Taught modules

Financial Modelling/CMS

Financial Modelling: Provides a rapid introduction to using MS Excel to solve a variety of practical problems related to finance. Many careers in banking and finance now require candidates to possess a strong grounding in spreadsheet modelling and a working knowledge of Visual Basic for Applications…

Financial Modelling: Provides a rapid introduction to using MS Excel to solve a variety of practical problems related to finance. Many careers in banking and finance now require candidates to possess a strong grounding in spreadsheet modelling and a working knowledge of Visual Basic for Applications…

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Introductory Finance/Trading Simulation I

Provides you with a knowledge of the key concepts that underlie the valuation of financial assets, including an examination of the pricing of stocks, bonds and options. The module also provides an introduction to modern portfolio theory, a discussion of how to measure risk and return, and an…

Provides you with a knowledge of the key concepts that underlie the valuation of financial assets, including an examination of the pricing of stocks, bonds and options. The module also provides an introduction to modern portfolio theory, a discussion of how to measure risk and return, and an…

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