scholarly journals Do Cryptocurrency Prices Camouflage Latent Economic Effects? A Bayesian Hidden Markov Approach

2020 ◽  
Vol 12 (3) ◽  
pp. 59
Author(s):  
Constandina Koki ◽  
Stefanos Leonardos ◽  
Georgios Piliouras
Keyword(s):  
Logistic Model ◽  
Transition Probabilities ◽  
Hidden Markov ◽  
Economic Effects ◽  
Financial Assets ◽  
Policy Makers ◽  
Price Series ◽  
Financial Perspective ◽  
Layer Analysis ◽  
Extreme Variability

We study the Bitcoin and Ether price series under a financial perspective. Specifically, we use two econometric models to perform a two-layer analysis to study the correlation and prediction of Bitcoin and Ether price series with traditional assets. In the first part of this study, we model the probability of positive returns via a Bayesian logistic model. Even though the fitting performance of the logistic model is poor, we find that traditional assets can explain some of the variability of the price returns. Along with the fact that standard models fail to capture the statistic and econometric attributes—such as extreme variability and heteroskedasticity—of cryptocurrencies, this motivates us to apply a novel Non-Homogeneous Hidden Markov model to these series. In particular, we model Bitcoin and Ether prices via the non-homogeneous Pólya-Gamma Hidden Markov (NHPG) model, since it has been shown that it outperforms its counterparts in conventional financial data. The transition probabilities of the underlying hidden process are modeled via a logistic link whereas the observed series follow a mixture of normal regressions conditionally on the hidden process. Our results show that the NHPG algorithm has good in-sample performance and captures the heteroskedasticity of both series. It identifies frequent changes between the two states of the underlying Markov process. In what constitutes the most important implication of our study, we show that there exist linear correlations between the covariates and the ETH and BTC series. However, only the ETH series are affected non-linearly by a subset of the accounted covariates. Finally, we conclude that the large number of significant predictors along with the weak degree of predictability performance of the algorithm back up earlier findings that cryptocurrencies are unlike any other financial assets and predicting the cryptocurrency price series is still a challenging task. These findings can be useful to investors, policy makers, traders for portfolio allocation, risk management and trading strategies.

scholarly journals Do Cryptocurrency Prices Camouflage Latent Economic Effects? A Bayesian Hidden Markov Approach

Proceedings ◽  
2019 ◽  
Vol 28 (1) ◽  
pp. 5 ◽  
Author(s):  
Constandina Koki ◽  
Stefanos Leonardos ◽  
Georgios Piliouras
Keyword(s):  
Hidden Markov ◽  
Current Approach ◽  
Economic Effects ◽  
Unexpected Result ◽  
Price Series ◽  
Out Of Sample ◽  
Extreme Variability ◽  
Linear Effects ◽  
Time Limitations

With Bitcoin, Ether and more than 2000 cryptocurrencies already forming a multi-billion dollar market, a proper understanding of their statistical and financial properties still remains elusive. Traditional economic theories do not explain their characteristics and standard financial models fail to capture their statistic and econometric attributes such as their extreme variability and heteroskedasticity. Motivated by these findings, we study Bitcoin and Ether prices via a Non-Homogeneous Pólya Gamma Hidden Markov (NHPG) model that has been shown to outperform its counterparts in conventional financial data. The NHPG algorithm has good in-sample performance and identifies both linear and non-linear effects of the predictors. Our results indicate that all price series are heteroskedastic with frequent changes between the two states of the underlying Markov process. In a somewhat unexpected result, the Bitcoin and Ether prices, although correlated, are significantly affected by different variables. We compare long term to short term Bitcoin data and find that significant covariates may change over time. Limitations of the current approach—as expressed by the large number of significant predictors and the poor out-of-sample predictions—back earlier findings that cryptocurrencies are unlike any other financial asset and hence, that their understanding requires novel tools and ideas.

scholarly journals Evaluating smoking control policies in the e-cigarette era: a modelling study

2019 ◽  
pp. tobaccocontrol-2019-054951 ◽  
Author(s):  
Thi Thanh Tra Doan ◽  
Ken Wei Tan ◽  
Borame Sue Lee Dickens ◽  
Yin Ai Lean ◽  
Qianyu Yang ◽  
...  
Keyword(s):  
Smoking Prevalence ◽  
Transition Probabilities ◽  
Electronic Cigarettes ◽  
Tobacco Consumption ◽  
Quality Adjusted Life Year ◽  
Control Policies ◽  
Policy Makers ◽  
The Usa ◽  
Laissez Faire ◽  
The Uk

BackgroundIn jurisdictions in which electronic cigarettes are currently prohibited, policy makers must weigh the potentially lower risk compared with conventional cigarettes against the risk of initiation of e-cigarettes among non-smokers.MethodsWe simulated a synthetic population over a 50-year time horizon with an open cohort model using data from Singapore, a country where e-cigarettes are currently prohibited, and data from the USA, the UK and Japan. Using the smoking prevalence and the quality-adjusted life year gained calculated, we compared tobacco control policies without e-cigarettes—namely, raising the minimum legal age (MLA), introducing a smoke-free generation (SFG) and tax rises on tobacco consumption—with policies legalising e-cigarettes, either taking a laissez-faire approach or under some form of restriction. We also evaluated combinations of these policies.ResultsRegardless of the country informing the transition probabilities to and from e-cigarette use in Singapore, a laissez-faire e-cigarette policy could reduce the smoking prevalence in the short term, but it is not as effective as other policies in the long term. The most effective single policies evaluated were SFG and aggressive tax rises; the most effective combination of policies considered was MLA plus moderate tax rises and e-cigarettes on prescription.ConclusionPolicy makers in jurisdictions in which e-cigarettes are not yet established may be advised not to prioritise e-cigarettes in their tobacco end-game strategy, unless their use can be restricted to current smokers seeking to quit.

The Economic Effects of Industrial Relations Legislation Since 1979

1990 ◽  
Vol 131 ◽  
pp. 57-70 ◽  
Author(s):  
William Brown ◽  
Sushil Wadhwani
Keyword(s):  
Economic Performance ◽  
Trade Unions ◽  
Alternative Explanation ◽  
Labour Productivity ◽  
Industrial Relations ◽  
Economic Effects ◽  
Economic Consequences ◽  
Policy Makers ◽  
Actual Impact ◽  
Wage Effects

This is the fourth article from members of the CLARE Group to appear in the Review. Future articles will normally appear about twice a year. The Review is pleased to give hospitality to the deliberations of the CLARE Group but is not necessarily in agreement with the views expressed. Members of the CLARE Group are M.J. Artis, A.J.C. Britton, W.A. Brown, C.H. Feinstein, C.A.E. Goodhart, D.A. Hay, J.A. Kay, R.C.O. Matthews, M.H. Miller, P.M. Oppenheimer, M.V. Posner, W.B. Reddaway, J.R. Sargent, M.F-G. Scott, Z.A. Silberston, J.H.B. Tew, J.S. Vickers, S. Wadhwani.The industrial relations legislation of the 1980s has been widely credited with having made a major contribution to Britain's economic performance. This study evaluates its actual impact. The costs to trade unions of strike action have increased, but the legislation has had some perverse effects, not least in encouraging unions to tighten up their own organisation. The economic consequences predicted by the policy makers are investigated by means of a number of econometric studies. They suggest that the expected employment and wage effects did not occur. They also failed to provide improvements in labour productivity. The study offers an alternative explanation of these findings.

Intellectual Property and Economic Development

2020 ◽  
Keyword(s):  
Intellectual Property ◽  
Economic Effects ◽  
Research Review ◽  
Policy Makers ◽  
Technology Markets ◽  
Considerable Debate ◽  
Recognition And Enforcement ◽  
The Subject ◽  
National Economies

The economic impact of intellectual property rights has been the subject of considerable debate and research. This engaging research review discusses literature by distinguished scholars who have addressed, from different perspectives and in different contexts, how such rights help to shape goods and technology markets. The economic effects of intellectual property vary depending on the sectors involved, the level of development of the countries where they apply, and the policies implemented to govern their recognition and enforcement. Written by an expert in the field, this review is essential reading for academics, students, professionals and policy makers interested in understanding the role of intellectual property in national economies as well as in an international dimension.

Extending hidden Markov models to allow conditioning on previous observations

2018 ◽  
Vol 16 (05) ◽  
pp. 1850019 ◽  
Author(s):  
Ioannis A. Tamposis ◽  
Margarita C. Theodoropoulou ◽  
Konstantinos D. Tsirigos ◽  
Pantelis G. Bagos
Keyword(s):  
Hidden Markov Models ◽  
Probabilistic Models ◽  
Markov Models ◽  
Transition Probabilities ◽  
Hidden Markov ◽  
Simple Extension ◽  
Computational Molecular Biology ◽  
Current State ◽  
Observation Sequence ◽  
Hidden States

Hidden Markov Models (HMMs) are probabilistic models widely used in computational molecular biology. However, the Markovian assumption regarding transition probabilities which dictates that the observed symbol depends only on the current state may not be sufficient for some biological problems. In order to overcome the limitations of the first order HMM, a number of extensions have been proposed in the literature to incorporate past information in HMMs conditioning either on the hidden states, or on the observations, or both. Here, we implement a simple extension of the standard HMM in which the current observed symbol (amino acid residue) depends both on the current state and on a series of observed previous symbols. The major advantage of the method is the simplicity in the implementation, which is achieved by properly transforming the observation sequence, using an extended alphabet. Thus, it can utilize all the available algorithms for the training and decoding of HMMs. We investigated the use of several encoding schemes and performed tests in a number of important biological problems previously studied by our team (prediction of transmembrane proteins and prediction of signal peptides). The evaluation shows that, when enough data are available, the performance increased by 1.8%–8.2% and the existing prediction methods may improve using this approach. The methods, for which the improvement was significant (PRED-TMBB2, PRED-TAT and HMM-TM), are available as web-servers freely accessible to academic users at www.compgen.org/tools/ .

Community rebuilding processes in a disaster-damaged area through community currency

2017 ◽  
Vol 26 (1) ◽  
pp. 79-93 ◽  
Author(s):  
Hiromi Nakazato ◽  
Seunghoo Lim
Keyword(s):  
Social Capital ◽  
Local Community ◽  
Local Communities ◽  
Economic Effects ◽  
Policy Makers ◽  
Content Type ◽  
Community Currency ◽  
Community Rebuilding ◽  
Potential Tool

Purpose Community currency (CC) is used as a tool for reviving local communities by promoting economic growth and facilitating the formation of social capital. Although the Japanese CC movement has stagnated since mid-2005, a new experiment, Fukkou Ouen Chiiki Tsuka (CC for supporting disaster recovery), was introduced across disaster-damaged areas after the Great East Japan Earthquake and tsunami of March 2011. Previous studies assessing the role of CC in these earthquake-damaged areas are rare; the purpose of this paper is to examine the micro processes of community rebuilding that underlie the transactional networks mediated by one of the experiments, Domo, in Kamaishi. Design/methodology/approach Using transactional records capturing residents’ CC activities during the five-month pilot period before actual implementation of Domo simultaneous investigation for empirical network analysis techniques identify the network configuration dynamics representing the multiple observed forms of social capital in this disaster-affected local community. Findings This study of the five-month pilot for the Domo system revealed: intensive dependence on the coordinating role of core members (i.e. the creation of weak ties), a lack of balanced support among members and the resulting uni-directional transactions (i.e. the avoidance of generalized exchanges), and the reinforcement of previous transactional ties via reciprocation or transitive triads (i.e. the formation of strong ties). Originality/value This study provides guidance for practitioners, researchers, and policy makers on how community residents’ engagement in CC activities could function as a potential tool for generating positive socio-economic effects for local communities in disaster areas.

scholarly journals On Determining the Order of Markov Dependence of an Observed Process Governed by a Hidden Markov Model

2002 ◽  
Vol 10 (3) ◽  
pp. 241-251 ◽  
Author(s):  
R.J. Boys ◽  
D.A. Henderson
Keyword(s):  
Markov Chain ◽  
Markov Models ◽  
Transition Probabilities ◽  
Hidden Markov ◽  
Real Data ◽  
Information Criteria ◽  
Monte Carlo Algorithm ◽  
Model Parameters ◽  
Markov Dependence ◽  
Finite State

This paper describes a Bayesian approach to determining the order of a finite state Markov chain whose transition probabilities are themselves governed by a homogeneous finite state Markov chain. It extends previous work on homogeneous Markov chains to more general and applicable hidden Markov models. The method we describe uses a Markov chain Monte Carlo algorithm to obtain samples from the (posterior) distribution for both the order of Markov dependence in the observed sequence and the other governing model parameters. These samples allow coherent inferences to be made straightforwardly in contrast to those which use information criteria. The methods are illustrated by their application to both simulated and real data sets.

scholarly journals Modelling harvest of Asian elephants Elephas maximus on the basis of faulty assumptions promotes inappropriate management solutions

Oryx ◽  
2016 ◽  
Vol 51 (3) ◽  
pp. 506-512 ◽  
Author(s):  
Jean Philippe Puyravaud ◽  
Priya Davidar ◽  
Rajeev K. Srivastava ◽  
Belinda Wright
Keyword(s):  
Population Structure ◽  
Logistic Model ◽  
Transition Probabilities ◽  
Elephas Maximus ◽  
Management Tool ◽  
Tiger Reserve ◽  
Deterministic Modelling ◽  
Elephant Population ◽  
Regional Population ◽  
Harvest Regimes

AbstractA ratio-based logistic model developed to assess elephant harvest rates, based on a study at Nagarhole Tiger Reserve in India, was recommended as a management tool to control human–elephant conflict through culling. Considering this reserve among others violates an assumption of the logistic model: isolation. Nevertheless, assuming this violation was irrelevant, we re-evaluated the model, with minor modifications, for the neighbouring Mudumalai Tiger Reserve, where we used data from 13 elephant Elephas maximus population surveys to derive bootstrapped sets of population ratios, and mortality records. We generated arrays of harvest regimes and examined which ratio outputs were closest to the bootstrapped ratios. Our results indicated that (1) model outputs corresponded best with the Mudumalai population structure when harvest regimes were extreme and unlikely, (2) there were significant differences in population structure and harvest regimes between Nagarhole and Mudumalai, and (3) only 49% of adult male deaths predicted by model outputs were recorded in official governmental records. The model provides significantly different results among reserves, which invalidates it as a tool to predict change across the entire elephant population. Variability in survey data and inaccuracies in transition probabilities are sufficiently large to warrant caution when using them as a basis for deterministic modelling. Official mortality databases provide a weak means of validation because poaching incidents are poorly recorded. We conclude that the model should be based on validated transition probabilities and encompass the entire regional population.

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