Which Legislators Pay Attention to Other States’ Policies? Comparing Cosponsorship to Floor Voting in the Diffusion of Renewable Portfolio Policy

2020 ◽  
Author(s):  
Srinivas C. Parinandi ◽  
Stefani Langehennig ◽  
Mark Trautmann
Keyword(s):  
Portfolio Policy

Time consistent behavioral portfolio policy for dynamic mean–variance formulation

2017 ◽  
Vol 68 (12) ◽  
pp. 1647-1660 ◽  
Author(s):  
Xiangyu Cui ◽  
Xun Li ◽  
Duan Li ◽  
Yun Shi
Keyword(s):  
Portfolio Policy ◽  
Mean Variance

scholarly journals Relation-Aware Transformer for Portfolio Policy Learning

2020 ◽  
Author(s):  
Ke Xu ◽  
Yifan Zhang ◽  
Deheng Ye ◽  
Peilin Zhao ◽  
Mingkui Tan
Keyword(s):  
Portfolio Selection ◽  
State Of The Art ◽  
Asset Price ◽  
Sequential Patterns ◽  
Portfolio Decisions ◽  
Price Series ◽  
Crypto Currency ◽  
Key Issues ◽  
Multiple Assets ◽  
Portfolio Policy

Portfolio selection is an important yet challenging task in AI for FinTech. One of the key issues is how to represent the non-stationary price series of assets in a portfolio, which is important for portfolio decisions. The existing methods, however, fall short of capturing: 1) the complicated sequential patterns for asset price series and 2) the price correlations among multiple assets. In this paper, under a deep reinforcement learning paradigm for portfolio selection, we propose a novel Relation-aware Transformer (RAT) to handle these aspects. Specifically, being equipped with our newly developed attention modules, RAT is structurally innovated to capture both sequential patterns and asset correlations for portfolio selection. Based on the extracted sequential features, RAT is able to make profitable portfolio decisions regarding each asset via a newly devised leverage operation. Extensive experiments on real-world crypto-currency and stock datasets verify the state-of-the-art performance of RAT.

scholarly journals Convenience Yield Value of International Emission Allowance Based on Call Options

2014 ◽  
Vol 2014 ◽  
pp. 1-5
Author(s):  
Kai Chang
Keyword(s):  
Strong Correlation ◽  
Price Volatility ◽  
Portfolio Investment ◽  
Convenience Yield ◽  
Emission Allowance ◽  
Call Options ◽  
Yield Value ◽  
Information Set ◽  
Portfolio Policy ◽  
Price Spread

Convenience yield is call options; spot holders attain excess investment revenues through holding spot assets instituted futures assets. Based on the hypothesis of convenience yields, our empirical results show that monthly convenience yield of emission allowance has significant options feature; convenience yield has strong correlation with price spread between spot and futures and their price volatility. The market information set is helpful to adjust portfolio policy and improve portfolio investment revenues of emission allowances.

scholarly journals A Portfolio Policy Package to Reduce Greenhouse Gas Emissions

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 337 ◽  
Author(s):  
John Freebairn
Keyword(s):  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Low Cost ◽  
Market Failures ◽  
Gas Emissions ◽  
Policy Interventions ◽  
Production And Consumption ◽  
Reduce Emissions ◽  
The Many ◽  
Portfolio Policy

Arguments for a portfolio of price, regulation and subsidy policy interventions to reduce the production and consumption of greenhouse gas emissions are presented. The operation and effects of each intervention are described and compared. A combination of different sets of market failures across the many potential decision changes available to producers and consumers to reduce emissions and different properties of the mitigation instruments support a portfolio approach to reduce emissions at a low cost.

scholarly journals Constrained Dynamic Mean-Variance Portfolio Selection in Continuous-Time

Algorithms ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 252
Author(s):  
Weiping Wu ◽  
Lifen Wu ◽  
Ruobing Xue ◽  
Shan Pang
Keyword(s):  
Portfolio Selection ◽  
Continuous Time ◽  
Value Function ◽  
Optimal Solution ◽  
Selection Problem ◽  
Portfolio Selection Problem ◽  
Cone Constraints ◽  
Lq Optimal Control ◽  
Mean Variance Portfolio ◽  
Portfolio Policy

This paper revisits the dynamic MV portfolio selection problem with cone constraints in continuous-time. We first reformulate our constrained MV portfolio selection model into a special constrained LQ optimal control model and develop the optimal portfolio policy of our model. In addition, we provide an alternative method to resolve this dynamic MV portfolio selection problem with cone constraints. More specifically, instead of solving the correspondent HJB equation directly, we develop the optimal solution for this problem by using the special properties of value function induced from its model structure, such as the monotonicity and convexity of value function. Finally, we provide an example to illustrate how to use our solution in real application. The illustrative example demonstrates that our dynamic MV portfolio policy dominates the static MV portfolio policy.

scholarly journals Risk Taking and Fiscal Smoothing with Sovereign Wealth Funds in Advanced Economies

2019 ◽  
Vol 7 (1) ◽  
pp. 4 ◽  
Author(s):  
Snorre Lindset ◽  
Knut Anton Mork
Keyword(s):  
Interest Rates ◽  
Risk Taking ◽  
Interest Rate Risk ◽  
Sovereign Wealth Funds ◽  
Policy Makers ◽  
Risky Assets ◽  
The Government ◽  
Utility Preferences ◽  
Portfolio Policy ◽  
Over Time

In an economy with a sovereign wealth fund (SWF), the government may draw on the fund to supplement other government revenues. If the fund is invested in risky assets, this introduces a new stochastic element into the government’s budget. We analyze the interaction between the draw from and risk taking in the SWF. Using non-expected utility preferences, we distinguish between intended changes and stochastic changes in the SWF draws over time. We show that the desire for smoothness in taxes and public services translates into smoothing of SWF draws and lower risk taking. It can even lead to procyclical rebalancing of the SWF portfolio. Future interest rates are associated with interest-rate risk. We show that this risk may lead to a higher optimal equity share in the SWF portfolio. Policy makers can use the draws from the SWF to smooth over time variation in risk-free rates.

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