option value
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Author(s):  
Tumellano Sebehela

The interdependence of options is common among compound options. Moreover, this interconnectedness is synonymous with probability theory-how a set of axioms are treated. The conditionality, where one option value is dependent on another option, has spilled over to option pricing, especially exchange options. However, it seems that no study has explored whether that simultaneous occurrence of two options is conditional or not. This study uses conditional approaches (Radon–Nikodým derivative and probability theory) to illustrate conditionality in an exchange option. Furthermore, hedging strategy is derived based on straddles. The results show that due to conditionality another exotic option, tri-conditional option (also known as triple option) is derived. The hedging of a triple option encompasses both dynamic and static techniques.


2021 ◽  
pp. 1-31
Author(s):  
Germain Lefebvre ◽  
Christopher Summerfield ◽  
Rafal Bogacz

Abstract Reinforcement learning involves updating estimates of the value of states and actions on the basis of experience. Previous work has shown that in humans, reinforcement learning exhibits a confirmatory bias: when the value of a chosen option is being updated, estimates are revised more radically following positive than negative reward prediction errors, but the converse is observed when updating the unchosen option value estimate. Here, we simulate performance on a multi-arm bandit task to examine the consequences of a confirmatory bias for reward harvesting. We report a paradoxical finding: that confirmatory biases allow the agent to maximize reward relative to an unbiased updating rule. This principle holds over a wide range of experimental settings and is most influential when decisions are corrupted by noise. We show that this occurs because on average, confirmatory biases lead to overestimating the value of more valuable bandits and underestimating the value of less valuable bandits, rendering decisions overall more robust in the face of noise. Our results show how apparently suboptimal learning rules can in fact be reward maximizing if decisions are made with finite computational precision.


Author(s):  
CHARLES SIMS ◽  
SARAH E. NULL ◽  
JOSUE MEDELLIN-AZUARA ◽  
AUGUSTINA ODAME

Adaptation gaps arise when observed adaptation to climate change is slower than perceived adaptation potential. Two common explanations for adaptation gaps are (1) private parties failing to recognize that the climate is changing and (2) the cost of adaptation is higher than commonly believed. This paper shows how these two explanations are linked and that the likelihood and duration of adaptation gaps depend on whether climate change is characterized by stationary or non-stationary dynamics. Using an investment in water-saving irrigation in California’s Central Valley as an illustrative example, we find little evidence that failing to account for climate change would explain adaptation gaps. A more likely explanation for adaptation gaps is a failure to account for the adaptation option value that arises due to the possibility of maladaptation.


2021 ◽  
Author(s):  
Woojung Lee ◽  
Meng Li ◽  
William B. Wong ◽  
Tu My To ◽  
Louis P. Garrison ◽  
...  

Author(s):  
William B Wong ◽  
Tu My To ◽  
Meng Li ◽  
Woojung Lee ◽  
David L Veenstra ◽  
...  

Author(s):  
John M. Clapp ◽  
Jeffrey P. Cohen ◽  
Thies Lindenthal

AbstractSeparating urban land and structure values is important for national accounts and for analysis of real estate risk over time. A large part of the literature on urban land valuation uses the land residual method, which relies on the assumption that structures are easily replaced. But urban land value depends on accessibility to nearby land uses, implying that infrastructure and the slowly changing built environment are the most important components of land value. Investments in structures are only slowly reversible, implying that land and structure function as a bundled good whereas land residual theory severs the connection between land value and structure value over time. We develop a simple theoretical model that includes option value and compare to a nested land residual model before and after a shock to values. Cross-sectionally our model shows that land residual theory overestimates structure value. Over time almost all of any change in property value is allocated to land residuals. Data from Maricopa county, AZ, 2012–2018 strongly support option value models when nested within a general model that also includes land residuals. FHFA estimates use entirely different cost estimation methods: our analysis of FHA data suggest that our conclusions generalize to the U.S. as a whole, and that high and rising land value ratios over 50 years (the “hockey stick” pattern found in the literature) are likely an artifact of the residual model.


2021 ◽  
Author(s):  
Hatice Düzakın ◽  
Süreyya Yılmaz

The real option method, which emerged in the 1980s and is based on financial options, has been heavily involved in the literature since the early 2000s. Calculated by adding option value to investments in real assets, this method offers managers opportunities to evaluate the investment project. While the traditional capital budgeting method cannot be changed during the decision project process taken when evaluating the investment project, the real option method can be changed throughout the project process. The reason for this situation is that the real option method does not ignore the managerial flexibility. The reason for this situation is that the real option method does not ignore the managerial flexibility. In this study, these two methods in the literature are examined according to the types of projects.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Adama Sanou ◽  
Issouf Soumaré

Abstract This paper proposes a stochastic multi-period pricing model based on the default option value with insurance cycle to examine the interactions among pricing, surplus allocation and solvency for a multiline insurer. The proposed innovative model captures the dynamic aspects of capitalization and the impact of dynamic premium setting on the insurer’s solvency and risk management. We derived the equilibrium premium for different insurance contract designs. Our results show that the allocation of surplus per line affects the default of the other lines and depends on the correlation between the solvency ratio and the loss ratio of the line. The presence of the insurance cycle can boost solvency provided that the insurer adopts the right underwriting strategy. Based on the correlation between the solvency ratio and the loss ratio of the line, the insurer can make strategic decision about fair pricing. This makes it possible to reconcile the objectives of pricing with the insurer’s solvency and its strategic decision-making in a long-term perspective.


2021 ◽  
Author(s):  
Uyen (Wendy) Nguyen

Considerable effort has been devoted to indicate the critical determinants of acquisition premiums. However, the determinants of mergers and acquisitions (M&A) premiums are not yet fully understood. This research paper empirically examines the effect of stock return volatility on mergers and acquisitions premiums through real options value of bidder and target firms. With a sample of 2,559 completed M&A deals in the US during 1986-2016, we find that bidder firms tend to pay more premiums for the targets that have more future real option value and higher risk. To be more specific, when targets have more real options measured as high Research and Development (R&D) to market value, high sales growth rate, and low leverage ratio, the relationship between target return volatility and acquisition premiums is stronger. This study contributes not only to the literature regarding the determinants of mergers and acquisitions premiums but also to the literature of real options value. Keywords: Mergers and acquisition premiums, acquisition premiums, stock return volatility, real options, growth options


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