Neural network forecasting in prediction Sharpe ratio: Evidence from EU debt market

Vuković, Darko; Vyklyuk, Yaroslav; Matsiuk, Natalia; Maiti, Moinak

doi:10.1016/j.physa.2019.123331

Cited by 30 publications

(18 citation statements)

References 37 publications

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“…For the normal returns' estimation in terms of event study analysis a large choice of models exists starting from the simplest one of average stock returns to complex multiple‐factor market models. Every model has its advantages and disadvantages related to estimation accuracy and biases of results what plays an important role in the findings' reliability (Maiti, Krakovich, Shams, & Vukovic, 2020; Vukovic et al, 2020,c).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…Higher liquidity makes it easier to trade and frequently shows the threshold level of entering the market for ordinary investors (Vukovic, Vyklyuk, Matsiuk, & Maiti, 2020). It seems evident that the lower this threshold, the more investors participate, and this is what makes the market more transparent and somehow allocates the valuable information between the traders.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

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Sell‐side analysts' recommendations a value or noise

Vuković

Ugolnikov²,

Maiti

2020

Int. J Fin Econ

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The main objective of the paper is to investigate the analysts’ recommendations’ value and to determine on which market the analysts have more predictive power that can be defined as an extent of a stock price’s reaction around a particular recommendation what leads to abnormal returns of the security. Such recommendations are significant in decision‐making whether to buy or to sell a particular stock. We observed 1,881 events from 168 companies traded at the London Stock Exchange and the New York Stock Exchange in a period between January 1, 2016, and April 31, 2019. We used an event study analysis and classical one‐factor market model to determine expected returns for a particular stock in an estimation window. It was found that both American and European Union markets are feasible to be outperformed by the analysts but it is impossible to highlight any of the markets as they behave almost identically around positive, neutral and negative recommendations.

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Section: Theoretical Backgroundmentioning

confidence: 99%

Section: Theoretical Backgroundmentioning

confidence: 99%

Sell‐side analysts' recommendations a value or noise

Vuković

Ugolnikov²,

Maiti

2020

Int. J Fin Econ

Self Cite

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“…Quantitative forecasting method uses quantitative knowledge and mathematical model to conduct quantitative measure on the future economic phenomena. This kind of method mainly includes time series prediction method, regression analysis prediction method and tendency curve model prediction method [17] [18].…”

Section: Function Analysismentioning

confidence: 99%

Study of Economic Management Forecast and Optimized Resource Allocation Based on Cloud Computing and Neural Network

He¹

2020

Preprint

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As various factors which affect the development of global market economy become increasingly uncertain, economy and commodity will become more and more fluctuating in economic operation. With its strong non-linear mapping capacity, artificial neural network has already been applied in many fields, time series analysis and trend prediction, for instance.Cloud computing can interact fast with service provider at the minimum management cost. This paper proposes an economic forecast and optimized resource allocation model based on cloud computing and BP neural network. Its main goal is to break down a complex prediction task into several sub-tasks, effectively reduce the workload of a single computer and enhance the operating efficiency. Meanwhile, this method can also choose the optimal neural network prediction model at an adaptive learning rate so as to make the prediction and analysis result more accurate.

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“…The topic of government obligations and macro factors has been in particular interest in the financial sphere, especially due to a couple of the severe financial crisis (Aguiar and Gopinath, 2004). In many studies, researchers test the methods of (Vukovic et al, 2020b the interest rates and the yield curve forecasting, what makes the interest rates to be one of the key factors in the bond returns (Diebold and Li, 2006). Interest rates have a major effect on the bond yields, which capture an extra return for the interest rate risk and that can be a good factor in forecasting the bond returns (Ferson and Harvey, 1991).…”

Section: Literature Reviewmentioning

confidence: 99%

A study on the factors that governs US and EU YTM

Vuković

Prosin

Maiti

2020

CyA

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This paper analyzes the factors that contribute to the government obligations yield to maturity on the EU and US markets. Both, the bond characteristics and macroeconomic factors are taken into account, and the magnitude of each of the factor is provided which compose the average yield to maturity. Due to a severe financial crisis in the past years, economies are still recovering from the effects what makes investors to look for the stable investment instruments. Results of this study are a good fundamental for private investors that desire a stable return with a low-risk exposure. The factors and obtained coefficients included in the paper, can be used by investors, both private and institutional, to understand the magnitudes of the premiums that they can take on by varying the bond characteristics which account to the bond yield to maturity. Investors can decide at which premiums they are willing to focus, to obtain the desired expected returns.

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Neural network forecasting in prediction Sharpe ratio: Evidence from EU debt market

Cited by 30 publications

References 37 publications

Sell‐side analysts' recommendations a value or noise

Sell‐side analysts' recommendations a value or noise

Study of Economic Management Forecast and Optimized Resource Allocation Based on Cloud Computing and Neural Network

A study on the factors that governs US and EU YTM

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