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5. Validation of Stock Price Prediction Models in the Conditions of Financial Crisis.

Author

Mihova, Vesela, Georgiev, Ivan, Raeva, Elitsa, Georgiev, Slavi, and Pavlov, Velizar

Subjects
FINANCIAL crises, STOCK price forecasting, PREDICTION models, STOCHASTIC processes, MOVING average process
Abstract

The distribution laws of various natural and anthropogenic processes in the world around us are stochastic in nature. The development of mathematics and, in particular, of stochastic modeling allows us to study regularities in such processes. In practice, stochastic modeling finds a huge number of applications in various fields, including finance and economics. In this work, some particular applications of stochastic processes in finance are examined in the conditions of financial crisis, aiming to provide a solid approach for stock price forecasting. More specifically, autoregressive integrated moving average (ARIMA) models and modified ordinary differential equation (ODE) models, previously developed by some of the authors to predict the asset prices of four Bulgarian companies, are validated against a time period during the crisis. Estimated rates of return are calculated from the models for one period ahead. The errors are estimated and the models are compared. The return values predicted with each of the two approaches are used to derive optimal risk portfolios based on the Markowitz model, which is the second major aim of this study. The third aim is to compare the resulting portfolios in terms of distribution (i.e., weights of the stocks), risk, and rate of return. [ABSTRACT FROM AUTHOR]

Published
2024
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6. Inflation as a factor in the chain ladder method for estimating outstanding claims reserves.

Author

Raeva, Elitsa and Pavlov, Velizar

Subjects
*PRICE inflation, *INSURANCE companies
Abstract

The Chain Ladder Method (CLM) is a widely used method from the insurance companies in order to predict different types of future payments. These important calculations are done a several times in the year because they approximately predict how much will have to be paid for some claims in the different lines of business that are yet to be reported. This paper, in their first part, presents the use of the method to predict the sum of Incurred but not reported type of claims, also known as IBNR and Reported but not settled claims, also known as RBNS. In the second part CLM has been applied to predict reserves only for IBNR. This approach allows to occur in the future and how much money should be booked by the company into a reserve for this kind of future claims. Some numerical experiments have been presented. [ABSTRACT FROM AUTHOR]

Published
2022
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8. Claim reserving estimation by using the chain ladder method.

Author

Raeva, Elitsa, Pavlov, Velizar, Georgieva, Simona, and Slavova, Angela

Subjects
*INSURANCE companies
Abstract

The Chain Ladder Method (CLM) is a widely used method from the insurance companies in order to predict different types of future payments. These important calculations are done a several times in the year because they approximately predict how much will have to be paid for some claims in the different lines of business that are yet to be reported. This paper, in their first part, presents the use of the method to predict the sum of Incurred but not reported type of claims, also known as IBNR and Reported but not settled claims, also known as RBNS. In the second part CLM has been applied to predict reserves only for IBNR. This approach allows to occur in the future and how much money should be booked by the company into a reserve for this kind of future claims. Some numerical experiments have been presented. [ABSTRACT FROM AUTHOR]

Published
2020
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10. Modeling Issues of the Claim Process and Insurance Risk

Author

Raeva, Elitsa and Pavlov, Velizar

Subjects
claim, statistical distribution, models, insurance, risk
Abstract

[Raeva Elitsa; Раева Елица]; [Pavlov Velizar; Павлов Велизар] This work presents a brief overview of some proper statistical distributions for modeling of claims and risk in general insurance. Applications of normal approximation, normal power transformation and power transformation for modeling the number and the size of claims have been considered. Some problems in terms of modern risk theory are described and their reformulation in the actuarial practice are made. There are numerical examples to determine the amount of insurance premiums in order to limit to one percent the probability of insolvency. Some comparisons were made. 2010 Mathematics Subject Classification: 62C42, 62G22.

Published
2015

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