Browsing NHH Brage by Author "Andersson, Jonas"

A likelihood ratio and Markov Chain based method to evaluate density forecasting

Li, Yushu; Andersson, Jonas (Discussion paper;12/14, Working paper, 2014-03)

In this paper, we propose a likelihood ratio and Markov chain based method to evaluate density forecasting. This method can jointly evaluate the unconditional forecasted distribution and dependence of the outcomes. This ...

A maximum entropy approach to the newsvendor problem with partial information

Andersson, Jonas; Jörnsten, Kurt; Nonås, Sigrid Lise; Sandal, Leif Kristoffer; Ubøe, Jan (Journal article; Peer reviewed, 2013)

In this paper, we consider the newsvendor model under partial information, i.e., where the demand distribution D is partly unknown. We focus on the classical case where the retailer only knows the expectation and variance ...

A maximum entropy approach to the newsvendor problem with partial information

Andersson, Jonas; Jörnsten, Kurt; Nonås, Sigrid Lise; Sandal, Leif Kristoffer; Ubøe, Jan (Discussion paper;2011:14, Working paper, 2011-08)

In this paper, we consider the newsvendor model under partial information, i.e., where the demand distribution D is partly unknown. We focus on the classical case where the retailer only knows the expectation and variance ...

Analyse av faktorer som påvirker Oslo Børs : en analyse av hvordan utviklingen på Oslo Børs kan forklares av endringer i verdensøkonomi og oljepris

Fosby, Jesper; Dahl, Ole Marius (Master thesis, 2016-09-02)

Formålet med oppgaven er å undersøke hvordan endringer i verdensmarkedene og oljeprisen har påvirket Oslo Børs med underliggende sektorer i perioden 1996-2015. Regresjonsresultatene viser at oljeprisen leder Oslo Børs ...

Analyzing learning effects in the newsvendor model by probabilistic methods

Andersson, Jonas; Jörnsten, Kurt; Lillestøl, Jostein; Ubøe, Jan (Discussion paper;13/19, Working paper, 2019-10-11)

In this paper, we use probabilistic methods to analyze learning effects in a behavioral experiment on the newsvendor model. We argue why we should believe that suggested orders follow a multinomial logit distribution, and ...

Demand forecasting of antarctic krill meal : an automatic model for comparison of time series methods

Takseth, Miriam Slagnes; Newermann, Tove Fotland (Master thesis, 2019)

The world’s population is growing faster than ever. As a consequence, it is challenging to maintain a sustainable food production to satisfy all needs. In recent years, krill has emerged as a viable and effective supplement, ...

Electricity Prices, Large-Scale Renewable Integration, and Policy Implications

Kyritsis, Evangelos; Andersson, Jonas; Serletis, Apostolos (Discussion paper;18/16, Working paper, 2016-11-22)

This paper investigates the effects of intermittent solar and wind power generation on electricity price formation in Germany. We use daily data from 2010 to 2015, a period with profound modifications in the German electricity ...

Empirical comparison of time series forecasting strategies : forecasting the Baltic p1a spot price using gradient boosting and different strategies for multi-step time series

Aae, Joachim; Dovran, Anders (Master thesis, 2019)

This NHH master thesis researches methodologies for forecasting a financial time series, the Baltic Dry P1A spot price, one week and one month ahead. The methods researched are four different strategies for time series ...

Forecasting GDP growth : a comprehensive comparison of employing machine learning algorithms and time series regression models

Premraj, Pirasant (Master thesis, 2019)

In this paper, we do a comprehensive comparison of forecasting Gross Domestic Product (GDP) growth using Machine Learning algorithms and traditional time series regression models on the following economies: Australia, ...

Fraud detection by a multinomial model: Separating honesty from unobserved fraud

Andersson, Jonas; Olden, Andreas; Rusina, Aija (Discussion paper;15/20, Working paper, 2020-12-31)

In this paper we investigate the EM-estimator of the model by Caudill et al. (2005). The purpose of the model is to identify items, e.g. individuals or companies, that are wrongly classified as honest; an example of this ...

Good days ahead : forecasting ticket sales for Go Fjords using weather data

Svendsen, Christian Slåen (Master thesis, 2020)

The purpose of this study is to evaluate whether public weather data from MET Norway can be used to improve ticket sales forecasts for the travel company Go Fjords, and to demonstrate how such a forecasting model can be ...

The historical relation between banking, insurance and economic

Adams, Mike; Andersson, Jonas; Andersson, Lars-Fredrik; Lindmark, Magnus (Discussion paper, Working paper, 2005)

We examine empirically the dynamic historical relation between banking, insurance economic (income) growth in Sweden using time-series data from 1830 to 1998. We examine long-run historical trends in the data using ...

Hva vet vi om dem som skjuler inntekt og formue i skatteparadis?

Andersson, Jonas; Lillestøl, Jostein; Støve, Bård; Schjelderup, Guttorm (Journal article; Peer reviewed, 2013)

I denne artikkelen presenteres resultater fra et prosjekt utført for SNF (Samfunns- og Næringslivsforskning) på oppdrag av Skattedirektoratet (SKD). Hensikten med prosjektet var å finne kjennetegn ved personlige skattytere ...

Kjennetegnsanalyser av skattytere som unndrar skatt ved å skjule formuer og inntekter i utlandet

Andersson, Jonas; Lillestøl, Jostein; Støve, Bård (Rapport;2012:10, Research report, 2012-09)

I denne rapporten presenteres resultatet av et prosjekt utført for Skattedirektoratet (SKD). Hensikten har vært å finne kjennetegn ved personlige skattytere som har unndratt skatt gjennom å skjule formuer og/eller inntekt ...

Konkursprediksjon med termindata : en empirisk studie av prediksjonsevnen til termindata fra skatteetaten

Sævig, Mats; Vonen, Guri Husom (Master thesis, 2017)

I denne oppgaven undersøker vi i hvilken grad termindata fra Skatteetaten kan brukes for å forbedre eksisterende regnskapsbaserte konkursprediksjonsmodeller. Konkursprediksjonsmodeller benyttes blant annet av banker, ...

Machine learning as a tool for improved housing price prediction : the applicability of machine learning in housing price prediction and the economic implications of improvement to prediction accuracy

Wolstad, Henrik I W.; Dewan, Didrik (Master thesis, 2020)

This thesis investigates whether non-linear machine learning algorithms can produce more accurate predictions of Norwegian housing prices compared to linear regression models. We find that the non-linear XGBoost algorithm ...

Machine learning in default Prediction : the incremental power of machine learning techniques in mortgage default prediction

Marte, Arvin (Master thesis, 2019)

In this thesis, alternative machine learning techniques have been used to test if these perform better than a Logistic Regression in predicting default on retail mortgages. It is found that the ROC AUC statistic is ...