Time-varying window length for correlation forecasts

10.32920/14636631 ◽

2021 ◽

Author(s):

Yoontae Jeon ◽

Thomas H. McCurdy

Keyword(s):

Risk Management ◽

Model Uncertainty ◽

Regime Switching ◽

Structural Breaks ◽

Historical Data ◽

Time Varying ◽

Window Length ◽

Past Data ◽

Asset Classes ◽

Predictive Content

Forecasting correlations between stocks and commodities is important for diversification across asset classes and other risk management decisions. Correlation forecasts are affected by model uncertainty, the sources of which can include uncertainty about changing fundamentals and associated parameters (model instability), structural breaks and nonlinearities due, for example, to regime switching. We use approaches that weight historical data according to their predictive content. Specifically, we estimate two alternative models, ‘time-varying weights’ and ‘time-varying window’, in order to maximize the value of past data for forecasting. Our empirical analyses reveal that these approaches provide superior forecasts to several benchmark models for forecasting correlations. Keywords: model uncertainty; variance and correlation forecasts; time-varying window length

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Pension Schemes and Fixed Income Investment

British Actuarial Journal ◽

10.1017/s1357321700002853 ◽

2004 ◽

Vol 10 (2) ◽

pp. 353-402

Author(s):

P. J. Sweeting

Keyword(s):

Historical Data ◽

Asset Returns ◽

Pension Scheme ◽

Decision Making Process ◽

Fixed Income ◽

Fixed Income Securities ◽

Pension Schemes ◽

Past Data ◽

Asset Classes ◽

Over Time

ABSTRACTThe purpose of this paper is to investigate the role that fixed income securities should play in pension scheme investment. In this paper I look at the investment characteristics of the various bond asset classes, including the nature of the income streams produced. I also look at the relationships between the various asset classes and their stability over time. I then look at the usefulness of the asset classes in the context of a pensioner portfolio, considering both capital values and income streams. I look at skew and excess kurtosis in the distributions of asset returns and consider the effect of their existence on the decision making process. Given that most asset models are calibrated using historical data, I do not carry out any modelling and instead analyse past data. Finally, I discuss practical issues that need to be considered, particularly in a United Kingdom context.

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Has tourism driven house prices in Germany? Time-varying evidence since 1870

Tourism Economics ◽

10.1177/13548166211008832 ◽

2021 ◽

pp. 135481662110088

Author(s):

Sefa Awaworyi Churchill ◽

John Inekwe ◽

Kris Ivanovski

Keyword(s):

World War Ii ◽

Historical Data ◽

House Prices ◽

Housing Prices ◽

Time Varying ◽

Data Set ◽

Time Series Modelling ◽

The Impact ◽

Tourism Flows ◽

Non Parametric

Using a historical data set and recent advances in non-parametric time series modelling, we investigate the nexus between tourism flows and house prices in Germany over nearly 150 years. We use time-varying non-parametric techniques given that historical data tend to exhibit abrupt changes and other forms of non-linearities. Our findings show evidence of a time-varying effect of tourism flows on house prices, although with mixed effects. The pre-World War II time-varying estimates of tourism show both positive and negative effects on house prices. While changes in tourism flows contribute to increasing housing prices over the post-1950 period, this is short-lived, and the effect declines until the mid-1990s. However, we find a positive and significant relationship after 2000, where the impact of tourism on house prices becomes more pronounced in recent years.

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Time Varying Trade Intensities and the Deutsche Telekom IPO / Zeitvariable Handelsintensitaten und die Deutsche Telekom IPO

Jahrbücher für Nationalökonomie und Statistik ◽

10.1515/jbnst-2000-0606 ◽

2000 ◽

Vol 220 (6) ◽

Author(s):

Reinhard Hujer ◽

Joachim Grammig ◽

Stefan Kokot

Keyword(s):

Initial Public Offering ◽

Structural Breaks ◽

Duration Model ◽

Time Varying ◽

Threshold Autoregressive ◽

Public Offering ◽

Autoregressive Conditional Duration ◽

Autoregressive Conditional Duration Model

SummaryWe apply the Threshold Autoregressive Conditional Duration Model (TACD) as proposed by Zhang, Russell, and Tsay (1999) to model the after market trading duration process associated with the initial public offering of the Deutsche Telekom AG share in November of 1996. Special emphasis is devoted to the empirical specification of intra-day seasonality and to the detection of non-stationarity and structural breaks in the trading process.

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Optimal investment with time-varying transition probabilities for regime switching

Journal of Derivatives and Quantitative Studies ◽

10.1108/jdqs-12-2020-0032 ◽

2021 ◽

Vol 29 (2) ◽

pp. 102-115

Author(s):

Hyo-Chan Lee ◽

Seyoung Park ◽

Jong Mun Yoon

Keyword(s):

Regime Switching ◽

Transition Probabilities ◽

Optimal Investment ◽

Cash Flows ◽

Optimal Timing ◽

Time Varying ◽

Content Type ◽

Stochastic Nature ◽

Optimal Thresholds

Abstract This study aims to generalize the following result of McDonald and Siegel (1986) on optimal investment: it is optimal for an investor to invest when project cash flows exceed a certain threshold. This study presents other results that refine or extend this one by integrating timing flexibility and changes in cash flows with time-varying transition probabilities for regime switching. This study emphasizes that optimal thresholds are either overvalued or undervalued in the absence of time-varying transition probabilities. Accordingly, the stochastic nature of transition probabilities has important implications to the search for optimal timing of investment.

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Time Varying Transition Probabilities for Markov Regime Switching Models

SSRN Electronic Journal ◽

10.2139/ssrn.2456632 ◽

2014 ◽

Cited By ~ 4

Author(s):

Marco Bazzi ◽

Francisco Blasques ◽

Siem Jan Koopman ◽

Andre Lucas

Keyword(s):

Regime Switching ◽

Transition Probabilities ◽

Time Varying ◽

Markov Regime Switching ◽

Regime Switching Models ◽

Switching Models

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Improving Individual Risk Management Decisions: Learning from Experience and Coping with Model Uncertainty

Improving Risk Analysis - International Series in Operations Research & Management Science ◽

10.1007/978-1-4614-6058-9_2 ◽

2012 ◽

pp. 59-95

Author(s):

Louis Anthony Cox

Keyword(s):

Risk Management ◽

Model Uncertainty ◽

Individual Risk ◽

Learning From Experience ◽

Management Decisions ◽

And Coping

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A Supply Chain Vulnerability Map for the Automotive and Electronic Industries in Brazil

International Journal of Service Management and Sustainability ◽

10.24191/ijsms.v3i2.8107 ◽

2020 ◽

Vol 3 (2) ◽

pp. 83 ◽

Cited By ~ 2

Author(s):

Mauricio F. Blos ◽

Hui-Ming Wee

Keyword(s):

Risk Management ◽

Supply Chain ◽

Historical Data ◽

Methodological Approach ◽

Real Data ◽

Economic Downturn ◽

Supply Chain Risk Management ◽

Supply Chain Risk ◽

Vulnerability Map ◽

Hazard Vulnerability

This paper aims to explore various perspectives of the Supply Chain Risk Management (SCRM) as they relate to the automotive and electronic industries in Brazil based on the historical data from 2010 to 2016. The methodological approach was based on the Supply Chain Vulnerability Map (SCVM). The SCVM was tested in its totaliness and two more riskswere added to the hazard vulnerability category to form the SCVM II. The exploratory surveys were used to better understand the impacts on the automotive and electronic industries in Brazil during the study period. An interesting finding was that most of the major automotive and electronic industries are concerned with integrating risk management, governance and compliance in the supply chain. The findings of the empiricalinvestigation and SCRM historical data indicate that managers must integrate risk management, governance and compliance in the supply chain and use the proposed SCVM II. This research revealed the risks that surrounded the supply chain during the time period covered. In the study, the researchers added two more risks to the hazard vulnerability category: item 10, deficient rainfall (as seen in Manaus and São Paulo) and number 13, viral epidemics (to reflect the Zika virus around Brazil), it was named as SCVMII. Among the limitations of the research was that the study applied real data which might vary drastically due to economic downturn of the country. This might affect the performance of the investigated industries.

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