scholarly journals Covariance Principle for Capital Allocation: A Time-Varying Approach

Mathematics ◽  
2021 ◽  
Vol 9 (16) ◽  
pp. 2005
Author(s):  
Jilber Urbina ◽  
Miguel Santolino ◽  
Montserrat Guillen
Keyword(s):  
Capital Allocation ◽  
Investment Risk ◽  
Time Varying ◽  
Conditional Correlation ◽  
Risk Capital ◽  
Change Over Time ◽  
Covariance Principle ◽  
Static Approach ◽  
Stock Portfolio ◽  
Over Time

The covariance allocation principle is one of the most widely used capital allocation principles in practice. Risks change over time, so capital risk allocations should be time-dependent. In this paper, we propose a dynamic covariance capital allocation principle based on the variance-covariance of risks that change over time. The conditional correlation of risks is modeled by means of a dynamic conditional correlation (DCC) model. Unlike the static approach, we show that in our dynamic capital allocation setting, the distribution of risk capital allocations can be estimated, and the expected future allocations of capital can be predicted, providing a deeper understanding of the stochastic multivariate behavior of risks. The methodology presented in the paper is illustrated with an example involving the investment risk in a stock portfolio.

Flexible Design of Systems Considering Time-Dependent Reliability

2015 ◽  
Author(s):  
Vijitashwa Pandey ◽  
Zissimos P. Mourelatos ◽  
Annette Skowronska
Keyword(s):  
Time Dependent ◽  
Time Varying ◽  
Repairable Systems ◽  
Flexible Design ◽  
Change Over Time ◽  
New Approach ◽  
Hydrokinetic Turbine ◽  
The Future ◽  
Over Time

Many repairable systems degrade with time and are subjected to time-varying loads. Their characteristics may change over time considerably, making the assessment of their performance and hence their design difficult. To address this issue, we introduce in this paper the concept of flexible design of repairable systems under time-dependent reliability considerations. In flexible design, the system can be modified in the future to accommodate uncertain events. As a result, regardless of how uncertainty resolves itself, a modification is available that will keep the system close to optimal provided failure events have been properly characterized. We discuss how flexible design of repairable systems requires a fundamentally new approach and demonstrate its advantages using the design of a hydrokinetic turbine. Our results show that long-term metrics are improved when time-dependent characteristics and flexibility are considered together.

scholarly journals Capital Allocation in Decentralized Businesses

2018 ◽  
Vol 11 (4) ◽  
pp. 82 ◽  
Author(s):  
Stuart Turnbull
Keyword(s):  
Performance Measurement ◽  
Business Performance ◽  
Investment Decisions ◽  
Capital Allocation ◽  
Time Varying ◽  
Present Value ◽  
Risk Capital ◽  
Adjusted Present Value

This paper described a theory of capital allocation for decentralized businesses, taking into account the costs associated with risk capital. We derive an adjusted present value expression for making investment decisions, that incorporates the time varying profile of risk capital. We discuss the implications for business performance measurement.

scholarly journals Inspecting gradual and abrupt changes in emotion dynamics with the time-varying change point autoregressive model

2020 ◽  
Author(s):  
Casper J Albers ◽  
Laura Francina Bringmann
Keyword(s):  
Negative Affect ◽  
Positive Affect ◽  
Change Point ◽  
A Priori ◽  
Ar Model ◽  
Time Varying ◽  
Change Over Time ◽  
Abrupt Changes ◽  
Emotion Dynamics ◽  
Over Time

Recent studies have shown that emotion dynamics such as inertia (i.e., autocorrelation) can change over time. Importantly, current methods can only detect either gradual or abrupt changes in inertia. This means that researchers have to choose a priori whether they expect the change in inertia to be gradual or abrupt. This will leave researchers in the dark regarding when and how the change in inertia occurred. Therefore in this article we use a new model: the time-varying change point autoregressive (TVCP-AR) model. The TVCP-AR model can detect both gradual and abrupt changes in emotion dynamics. More specifically, we show that the inertia of positive affect and negative affect measured in one individual differ qualitativelyin how they change over time. Whereas the inertia of positive affect increased only gradually over time, negative affect changed both in a gradual and abrupt fashion over time. This illustrates the necessity of being able to model both gradual and abrupt changes in order to detect meaningful quantitative and qualitative differences in temporal emotion dynamics.

scholarly journals Estimation of time-varying decision thresholds from the choice and reaction times with no assumption on the shape

2016 ◽  
Author(s):  
Yul Hyoung Ryul Kang
Keyword(s):  
Heuristic Algorithm ◽  
Reaction Times ◽  
Time Varying ◽  
Change Over Time ◽  
Best Estimate ◽  
Conventional Methods ◽  
Estimation Of Time ◽  
Over Time

AbstractWhen a decision is made based on a series of samples of evidence, the threshold for decision may change over time. Here we propose a fast heuristic algorithm that estimates the time-varying thresholds without making an assumption on their shape. The algorithm gives an approximate best estimate of the time-varying thresholds for all time considered when all other parameters are fixed. The algorithm outperforms conventional methods that gradually adjust the threshold estimates during fitting, when fitting time is limited.

scholarly journals DYNAMIC VOLATILITY AND SHOCK INTERACTIONS BETWEEN OIL AND THE U.S. ECONOMIC SECTORS

2019 ◽  
Vol 1 (1) ◽  
pp. 1-1 ◽  
Author(s):  
Geoffrey Ngene ◽  
Jennifer Brodmann ◽  
M. Kabir Hassan
Keyword(s):  
Mutual Funds ◽  
Capital Allocation ◽  
Time Varying ◽  
Conditional Correlation ◽  
Economic Sectors ◽  
Shock Interactions ◽  
Oil Market ◽  
Risk Parity ◽  
Shock Transmission ◽  
Optimal Capital

his study examines (i) the dynamic shocks and volatility interactions between each of the eleven U.S. economic sectors and the oil market; (ii) riskminimizing optimal capital allocations between each sector and oil; and (iii) the hedging effectiveness resulting from the inclusion of oil in each sector portfolio. Using weekly data spanning the period June 1994 through February 2016, we document the following regularities: (i) the conditional correlation between each sector and the oil market is time-varying and slowly decaying; (ii) there is either volatility or shock transmission from oil to each sector but not the reverse; and (iii) investors can minimize and hedge risk by allocating a portion of their wealth to oil commodities and forming a portfolio consisting of sector stocks and oil commodities. however, they will need to overweight their investment in sector stocks. Our findings indicate that oil commodities offer diversification potential to U.S. investors holding sector portfolios such as sector ETFs and mutual funds. Further, the risk parity portfolio weights significantly differ from the capital allocation weights.

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