robench-2024b
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48 items • Updated
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It is relatively easy to check that 𝒜ϱKsubscript𝒜superscriptitalic-ϱ𝐾\mathcal{A}_{\varrho^{K}}caligraphic_A start_POSTSUBSCRIPT italic_ϱ start_POSTSUPERSCRIPT italic_K end_POSTSUPERSCRIPT end_POSTSUBSCRIPT is a convex set if ϱKsuperscriptitalic-ϱ𝐾\varrho^{K}italic_ϱ start_POSTSUPERSCRIPT italic_K end_POSTSUPERSCRIP... | Now, the dual representation of p(⋅)𝑝⋅p(\cdot)italic_p ( ⋅ )-convex risk measures is provided and which will be used in the proof of p(⋅)𝑝⋅p(\cdot)italic_p ( ⋅ )-dynamic risk measures in Sect. 5. | A special example of p(⋅)𝑝⋅p(\cdot)italic_p ( ⋅ )-convex risk measures which is so called OCE, is discussed in the next section. Finally, in Sect. 5, the p(⋅)𝑝⋅p(\cdot)italic_p ( ⋅ )-convex risk measures are used to study the dual representation of the p(⋅)𝑝⋅p(\cdot)italic_p ( ⋅ )-dynamic risk measures. | In this section, a special class of p(⋅)𝑝⋅p(\cdot)italic_p ( ⋅ )-convex risk measures that is the Optimized Certainty Equivalent (OCE) is studied and it will be used as an example of dynamic risk measures in Sect. 5. | Now, with the definition and dual representation, we consider the time consistency of dynamic p(⋅)𝑝⋅p(\cdot)italic_p ( ⋅ )-convex risk measures. | A |
These asymptotic results were based on the idea that an underlying process (St)t≥0subscriptsubscript𝑆𝑡𝑡0(S_{t})_{t\geq 0}( italic_S start_POSTSUBSCRIPT italic_t end_POSTSUBSCRIPT ) start_POSTSUBSCRIPT italic_t ≥ 0 end_POSTSUBSCRIPT under the local volatility model can be approximated by some suitable Gaussian proces... | For comparison with the Asian option, we examined the short-maturity behavior of the European option. In contrast to the Asian volatility, we proved that at short maturity T,𝑇T\,,italic_T , the European option is expressed by the European volatility. In terms of these volatilities, we observed the resemblance between ... | This paper described the short-maturity asymptotic analysis of the Asian option having an arbitrary Hölder continuous payoff in the local volatility model. We were mainly interested in the Asian option price and the Asian option delta value. The short-maturity behaviors of the option price and the delta value were both... | which we refer to as the European volatility, in the formulas for the Asian option prices and delta values. With regard to σA(T)subscript𝜎𝐴𝑇\sigma_{A}(T)italic_σ start_POSTSUBSCRIPT italic_A end_POSTSUBSCRIPT ( italic_T ) and σE(T),subscript𝜎𝐸𝑇\sigma_{E}(T)\,,italic_σ start_POSTSUBSCRIPT italic_E end_POSTSUBSCR... | In Section 4, short-maturity asymptotic formulas for the delta values will be presented in terms of the Asian volatility and the European volatility. | A |
Var(ϵ~(t))=Var(2ϵ(t)).𝑉𝑎𝑟~italic-ϵ𝑡𝑉𝑎𝑟2italic-ϵ𝑡\displaystyle Var(\tilde{\epsilon}(t))=Var(2\epsilon(t)).italic_V italic_a italic_r ( over~ start_ARG italic_ϵ end_ARG ( italic_t ) ) = italic_V italic_a italic_r ( 2 italic_ϵ ( italic_t ) ) . | Joint estimation and testing for the model in eq. 30 can be performed by using the techniques presented in [1]. Let us assume we have run a computer experiment composed of N𝑁Nitalic_N runs, for which we observe δny(t),t∈T,n=1,…,Nformulae-sequencesubscript𝛿𝑛𝑦𝑡𝑡𝑇𝑛1…𝑁\delta_{n}y(t),t\in T,n=1,\ldots,Nitalic_δ s... | To estimate the FCSI from data, let us define a generic contrast between two model runs as δy(t)𝛿𝑦𝑡\delta y(t)italic_δ italic_y ( italic_t ). We can so write, using Eq. 26: | For each t∈T𝑡𝑇t\in Titalic_t ∈ italic_T, the generic Δft,…Δsubscript𝑓𝑡…\Delta f_{t,\ldots}roman_Δ italic_f start_POSTSUBSCRIPT italic_t , … end_POSTSUBSCRIPT is a scalar value. We can so define | Building from [4] and [28], let us define the input-output (I/O) relationship of a given simulation model with a real response varying over an interval as | B |
Under NRA(Θ)𝑁𝑅𝐴ΘNRA(\Theta)italic_N italic_R italic_A ( roman_Θ ), the market is complete if and only if |𝒬|=1𝒬1|\mathcal{Q}|=1| caligraphic_Q | = 1. Furthermore, if NA({θ})𝑁𝐴𝜃NA(\{\theta\})italic_N italic_A ( { italic_θ } ) holds for some θ∈Θ𝜃Θ\theta\in\Thetaitalic_θ ∈ roman_Θ, then Θ={θ}Θ𝜃\Theta=\{\the... | The robust pricing systems are used to compute the robust superhedging price of 𝐟𝐟\mathbf{f}bold_f as follows | the set of robust pricing systems for the model θ𝜃\thetaitalic_θ and by 𝒬=⋃θ∈Θ𝒬θ𝒬subscript𝜃Θsuperscript𝒬𝜃\mathcal{Q}=\bigcup_{\theta\in\Theta}\mathcal{Q}^{\theta}caligraphic_Q = ⋃ start_POSTSUBSCRIPT italic_θ ∈ roman_Θ end_POSTSUBSCRIPT caligraphic_Q start_POSTSUPERSCRIPT italic_θ end_POSTSUPERSCRIPT the set of ... | Usually, information from the market data, for example available option prices, are used in calibration to select models that fit real data. We show in this section that this fitting procedure helps to reduce the set of robust pricing systems, and hence superhedging prices. | two prices are equal. In [8], the authors explained the two conflicting results by showing the differences in the information used by the hedger and Nature: in [6] the hedger and Nature have the same information while Nature has access to more information in [40]. Another explanation was given in [39], where the author... | C |
Now consider any ε𝜀\varepsilonitalic_ε-neighborhood of the set of Bayes-plausible distributions supported on stationary beliefs, call it (ΦS)εsuperscriptsuperscriptΦ𝑆𝜀(\Phi^{S})^{\varepsilon}( roman_Φ start_POSTSUPERSCRIPT italic_S end_POSTSUPERSCRIPT ) start_POSTSUPERSCRIPT italic_ε end_POSTSUPERSCRIPT. If an agent... | We can then apply an improvement principle. The idea is as follows, where we consider deterministic networks for simplicity. | Sadler (2015) introduce a notion of “information diffusion” and use the improvement principle to establish information diffusion even when learning fails. | Consider deterministic networks and assume that society can be covered by finitely many subsequences such that in each subsequence agent nksubscript𝑛𝑘n_{k}italic_n start_POSTSUBSCRIPT italic_k end_POSTSUBSCRIPT observes nk−1subscript𝑛𝑘1n_{k-1}italic_n start_POSTSUBSCRIPT italic_k - 1 end_POSTSUBSCRIPT. Then, denoti... | Sørensen (2020) consider “unordered” random sampling models that also only allow for binary states and actions. We believe ours is the first paper to consider the canonical sequential social learning problem with general observational networks and general state and action spaces. At a methodological level, we develop a... | A |
\frac{C(G)}{G}\right)\right\},\quad\forall g\in\{1,\dots,G\},italic_r start_POSTSUBSCRIPT italic_g end_POSTSUBSCRIPT start_POSTSUPERSCRIPT italic_t end_POSTSUPERSCRIPT ( italic_X ; italic_G ) = 1 { divide start_ARG italic_X start_POSTSUBSCRIPT italic_g end_POSTSUBSCRIPT end_ARG start_ARG square-root start_ARG roman_Σ s... | A natural approach for choosing optimal hypothesis testing protocols would be to set λ=0𝜆0\lambda=0italic_λ = 0 and choose maximin protocols that uniformly dominate all other maximin protocols, as Tetenov (2016) does in the J=1𝐽1J=1italic_J = 1 case. This corresponds to looking for uniformly most powerful (UMP) tests... | As an alternative to the approach above, one could examine a worst-case approach with respect to the identity of the implementing policymaker. This model leads to very conservative hypothesis testing protocols. When the researcher’s payoff is linear, threshold crossing protocols such as t𝑡titalic_t-tests are not maxim... | et al. (2002, Table 1) tested for effects in more than one subgroup. In economics, 27 of 124 field experiments published in “top-5” journals between 2007 and 2017 feature factorial designs with more than one treatment (Muralidharan et al., 2020).—these assumptions rationalize separate hypothesis tests based on threshol... | Which (if any) hypothesis testing protocols are globally (and maximin) optimal? The answer to this question depends on the functional form of the researcher’s payoff function, the functional form of welfare, and the distribution of X𝑋Xitalic_X. In this section, we consider settings with a linear researcher payoff (Ass... | B |
Matsuyama (1992) constructs a model of the Industrial Revolution that incorporates the above two characteristics. His model interprets that the Industrial Revolution was caused by an increase in agricultural (labor) productivity, which reallocated labor from agriculture to manufacturing and facilitated learning-by-doin... | However, his model does not explain why the Great Divergence occurred, that is, why agricultural (labor) productivity increased in Britain, but not in China. | To understand why the Industrial Revolution occurred in Britain in the 18th century, researchers need to identify factors that caused what he refers to as the Great Divergence–the divergence in economic growth between Europe and China since the 19th century. These factors should have been present in Britain but absent ... | Interestingly, even if the agricultural productivity level in China is higher than that in Britain, it does not contribute to escaping the stagnant Malthusian state in our model. | argues that the relief of land constraints is the reason why the Industrial Revolution did not occur in China but in Britain. | A |
Contribution decisions and link decisions in isolation may not capture the true dynamic of behavior. This is because both variables together determine the cost of sharing—the marginal return on a player’s contribution in this purely congestive game decreases as they share with more other players. For each observed acti... | Individual costs of sharing are significantly higher in the treatment condition than in the baseline, although they exhibit a similar downward trend over time in both conditions. | Reciprocity is significantly higher in the treatment condition than in the baseline condition. Moreover, it increases over time in the treatment, while it decreases over time in the baseline. | Contributions and average degree (number of links) are both significantly higher in the treatment condition than in the baseline condition. | Contribution decisions and link decisions in isolation may not capture the true dynamic of behavior. This is because both variables together determine the cost of sharing—the marginal return on a player’s contribution in this purely congestive game decreases as they share with more other players. For each observed acti... | A |
\mathbb{X},\mathcal{B}(\mathbb{X}))( italic_J start_POSTSUPERSCRIPT fraktur_p end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_t , ∞ end_POSTSUBSCRIPT ) start_POSTSUBSCRIPT italic_t ∈ blackboard_N end_POSTSUBSCRIPT ∈ roman_ℓ start_POSTSUPERSCRIPT ∞ end_POSTSUPERSCRIPT ( blackboard_N ; blackboard_X , caligraphic_B ( black... | Here, we focus on the risk-averse MDPs framework proposed in [55]. While a plethora of studies exist on conditional risk measures (CRMs) and dynamic risk measures (DRMs), the problem of risk-averse MDPs and their corresponding DPP cannot be straightforwardly inferred from the established properties of these risk measur... | We are now in position to present the DPP for the infinite horizon optimization in (P). We recall the definition of Stsubscript𝑆𝑡S_{t}italic_S start_POSTSUBSCRIPT italic_t end_POSTSUBSCRIPT from (27). | To establish the infinite horizon DPP, we define the infinite horizon version of the optimal value function as | To establish an infinite horizon DPP for (P), we first study the value functions associated with a Markovian policy 𝔭𝔭\mathfrak{p}fraktur_p. Recall the definitions of Gt,Ht𝔭subscript𝐺𝑡subscriptsuperscript𝐻𝔭𝑡G_{t},H^{\mathfrak{p}}_{t}italic_G start_POSTSUBSCRIPT italic_t end_POSTSUBSCRIPT , italic_H start_POSTSU... | C |
This paper attempts to support inventory management decisions of a real-world e-grocery retailer. While the more general characterisation of e-grocery retailing in Section 2.3 also holds for the company under consideration, we will introduce its specific requirements and characteristics in this section. | On the other hand, while there are opportunities resulting from the control the retailer exerts over the fulfilment process, picking and delivery increase the time between the instance a replenishment order for an SKU is placed and the final availability to the customer. This longer delivery time reduces the forecastin... | The assortment of the retailer covers several thousand SKUs from different areas such as fruits, vegetables and meat. The outward distribution process covers two phases. First, at each day there is a supply from national distribution warehouses to local fulfilment centres. In the following, we refer to these warehouses... | As our demand data is uncensored, it does not depend on the inventory level (see the characteristics on e-grocery retailing in Section 2.3). Therefore, we are able to evaluate the lookahead policy according to the true demand which in particular is not limited by the demand fulfilled under the policy of the retailer. H... | We evaluate four SKUs within six fulfilment centres. Due to missing data for the SKU lettuce in two fulfilment centres, we are able to evaluate 22 SKU/fulfilment centre combinations in total. Table 6 illustrates relative changes in the resulting average costs, i.e. relative savings, when using our lookahead policy inst... | B |
Low (24): Benin, Cameroon, Congo, Dem. Rep., Cote d’Ivoire, Ethiopia, Gambia, Ghana, Kenya, Mozambique, Niger, Nigeria, Senegal, Sudan, Tanzania, Togo, Zambia, Bangladesh, Cambodia, Myanmar, Nepal, Pakistan, Sri Lanka, Tajikistan, Haiti. | Medium (26): Congo, Egypt, Eswatini, Lesotho, Morocco, Yemen, Zimbabwe, Armenia, Fiji, India, Indonesia, Kyrgyzstan, Philippines, Vietnam, Albania, Belize, Bolivia, Brazil, Colombia, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, Paraguay, Peru. | Latin America and the Caribbean (20): Argentina, Belize, Bolivia, Brazil, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Venezuela. | Medium (26): Congo, Egypt, Eswatini, Lesotho, Morocco, Yemen, Zimbabwe, Armenia, Fiji, India, Indonesia, Kyrgyzstan, Philippines, Vietnam, Albania, Belize, Bolivia, Brazil, Colombia, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, Paraguay, Peru. | Latin America and the Caribbean (20): Argentina, Belize, Bolivia, Brazil, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Venezuela. | A |
The numerical computation of the signature is performed using the iisignature Python package (version 0.24) of Reizenstein and Graham (2020). The signatory Python package of Kidger and Lyons (2020) could also be used for faster computations. Because the signature is an infinite object, we compute in practice only the t... | The present article is organized as follows: as a preliminary, we introduce in Section 2 the Maximum Mean Distance and the signature before describing the statistical test proposed by Chevyrev and Oberhauser (2022). This test is based on these two notions and allows to assess whether two stochastic processes have the s... | We propose a new approach for the validation of real-world economic scenarios motivated by insurance applications. This approach relies on the formulation of the problem of validating real-world economic scenarios as a two-sample hypothesis testing problem where the first sample consists of historical paths, the second... | Our contribution is to study more deeply this statistical test from a numerical point of view on a variety of stochastic models and to show its practical interest for the validation of real-world stochastic scenarios when this validation is specified as an hypothesis testing problem. First, we present a numerical analy... | In this subsection, we apply the signature-based validation on simulated data, i.e. the two samples of stochastic processes are numerically simulated. Keeping in mind insurance applications, the two-sample test is structured as follows: | D |
For the human component of my experiment, I explored using Amazon GroundTruth and Prolific (prolific.co) to recruit participants. For the automated component of my experiment, I explored Meta AI’s BlenderBot and GPT-3, a large language model (LLM) developed by OpenAI that is the largest LLM publicly available through a... | After investigating GroundTruth and Prolific.co, I opted to use Prolific.co to survey human subjects due to its high quality of responses and ease of use. Prolific is a platform for on-demand data collection focused on survey studies and experiments involving paid human subjects. It has over 130,000 vetted participants... | Since determining what wage to offer to employees is a complex judgement, employers may use the minimum wage as a convenient reference point upon which to base their offers. Due to the difficulty of conducting controlled experiments with employers, I seek to answer a related question: does the minimum wage function as ... | I test human subjects through the crowdsourcing service Prolific.co as well as AI Bots such as BlenderBot | Prolific automates the selection of subjects based on an initial survey. I limited participation to residents of the United States without restriction to demographic characteristics, and I collected information about age, sex, ethnicity, country of birth, country of residence, nationality, language, student status, and... | A |
Unlike Bitcoin, which prefers a peer-to-peer electronic cash system, Ethereum is a platform for decentralized applications and allows anyone to create and execute smart contracts. | Blockchain [1] is a peer-to-peer network system based on technologies such as cryptography [2] and consensus mechanisms [3] to create and store huge transaction information. At present, the biggest application scenario of blockchain is cryptocurrency. For example, the initial “Bitcoin” [4] also represents the birth of ... | The code of a smart contract defines the functionality of the contract account, enabling analysis to determine whether it is a Ponzi account. | As cryptocurrencies continue to evolve, smart contracts [5] bring blockchain 2.0, also known as Ethereum [6]. | The smart contract [7], accompanying Ethereum, is understood as a program on the blockchain that operates when the starting conditions are met. | D |
Three regulatory paradigms govern firms’ announcements about the success and failure of drug candidates throughout the development process.666Although most announcements in our sample are made in the U.S., firms also market drugs elsewhere, such as in the E.U. and Canada. We include announcements from all “western” cou... | The results of this sensitivity analysis are presented in Table 5, under the row labeled “Drugs with Complete Path.” When considering the middle 90% and bottom 95% samples, which exclude outlier firms based on market capitalization, we find that the estimated values for the 29 drugs with complete paths are $1.89 billio... | Given the pronounced right skewness in the firm size distribution, we estimate the value of drugs after removing outlier firms to ensure that extreme cases do not drive our results. This decision is motivated by our discussion of the market capitalization distribution in Section 3.3, which suggests that large and small... | Three regulatory paradigms govern firms’ announcements about the success and failure of drug candidates throughout the development process.666Although most announcements in our sample are made in the U.S., firms also market drugs elsewhere, such as in the E.U. and Canada. We include announcements from all “western” cou... | These regulations incentivize firms to inform the market and the general public correctly and promptly. However, companies retain some discretion in determining what is considered “material” and “not misleading.” This ambiguity is more pronounced when the results from clinical trials are small or when large companies a... | D |
15 voters in all, with 3 experts: N=15𝑁15N=15italic_N = 15, K=3𝐾3K=3italic_K = 3. The two treatments | Table 2: p=0.7𝑝0.7p=0.7italic_p = 0.7, F(q)𝐹𝑞F(q)italic_F ( italic_q ) Uniform over [0.5,0.7]0.50.7[0.5,0.7][ 0.5 , 0.7 ] | Table 1: p=0.7𝑝0.7p=0.7italic_p = 0.7, F(q)𝐹𝑞F(q)italic_F ( italic_q ) Uniform over [0.5,0.7]0.50.7[0.5,0.7][ 0.5 , 0.7 ] | With p=0.7𝑝0.7p=0.7italic_p = 0.7 and q𝑞qitalic_q uniform over [0.5,[0.5,[ 0.5 ,0.7], we have verified | In all experiments, we set π=0.5𝜋0.5\pi=0.5italic_π = 0.5, p=0.7𝑝0.7p=0.7italic_p = 0.7, and F(q)𝐹𝑞F(q)italic_F ( italic_q ) Uniform | B |
In Section 3 we present our numerical simulations in one and two space dimensions as well as discuss their potential extension to higher dimensions. | In this paper, we propose a quantum Monte Carlo algorithm to solve high-dimensional Black-Scholes PDEs with correlation and general payoff function which is continuous and piece-wise affine (CPWA), enabling to price most relevant payoff functions used in finance (see also Section 2.1.2). Our algorithm follows the idea ... | In Section 4, we introduce and analyze all relevant quantum circuits we need in our quantum Monte Carlo algorithm. | In Section 5, we provide a detailed error analysis of the steps of our algorithm outlined in Section 2.4.1. | In this section, we first present our quantum Monte Carlo algorithm named Algorithm 1 to solve Black-Scholes PDEs (1) with corresponding CPWA payoff function (8). Moreover, we then outline Algorithm 1 and present our main result in Theorem 1, namely a convergence and complexity analysis of our algorithm. | B |
\theta^{*},c^{*}}))]blackboard_E [ ∫ start_POSTSUBSCRIPT 0 end_POSTSUBSCRIPT start_POSTSUPERSCRIPT ∞ end_POSTSUPERSCRIPT italic_e start_POSTSUPERSCRIPT - italic_ρ italic_t end_POSTSUPERSCRIPT italic_d ( 0 ∨ roman_sup start_POSTSUBSCRIPT italic_s ≤ italic_t end_POSTSUBSCRIPT ( italic_M start_POSTSUBSCRIPT italic_s end_P... | In solving the stochastic control problem (1.6) with a running maximum cost, we introduce two auxiliary state processes with reflections and study an auxiliary stochastic control problem, which gives rise to the HJB equation with two Neumann boundary conditions. By applying the dual transform and stochastic flow analys... | Theorem 3.1 provides a probabilistic presentation of the classical solution to the PDE (2) with Neumann boundary conditions (2.10) and (2.11). Our method in the proof of Theorem 3.1 is completely from a probabilistic perspective. More precisely, we start with the proof of the smoothness of the function v𝑣vitalic_v by ... | The rest of the paper is organized as follows. In Section 2, we introduce the auxiliary state processes with reflections and derive the associated HJB equation with two Neumann boundary conditions for the auxiliary stochastic control problem. In Section 3, we address the solvability of the dual PDE problem by verifying... | Next, we propose a homogenization method of Neumann boundary conditions to study the smoothness of the last term in the probabilistic representation (3) together with the application of the result obtained in Lemma 3.3. | A |
This results in only a gradual increase of expected job and output loss in the beginning, but fails to anticipate the effects of a systemically very important firm which triggers widespread job and output losses. 102 firms need to be closed in this strategy to reach the benchmark. | (B) In the ‘Remove least-employees firms first’ strategy, firms are closed according to their ascending numbers of employees. | ‘Remove least-risky firms first (employment)’ strategy that tries to lose the least number of jobs per firm closed, including network effects, and the | The ‘Remove least-risky firms first (employment)’ strategy that focuses on minimum expected job loss in the total economy per firm removed, as seen in Fig. 3C, produces a cumulative emission savings curve that approximately increases linearly for the first 100 firms. The expected job loss increases slowly, as expected,... | (C) In the ‘Remove least-risky firms first (employment)’ strategy, firms are removed according to their ascending risk of triggering job loss, i.e., EW-ESRI; firms that are considered least systemically relevant for the production network are removed first. | D |
Table 4 presents the summary regarding the compositions of the input parameter values that have the strongest and the weakest effect on each of the output factors (VRE share in the generation mix, total welfare and generation amount). Additionally, it provides the relative values indicating the improvement of the corre... | Table 4 presents the summary regarding the compositions of the input parameter values that have the strongest and the weakest effect on each of the output factors (VRE share in the generation mix, total welfare and generation amount). Additionally, it provides the relative values indicating the improvement of the corre... | Table 4: Nordics case study: summary. Percentage values (%) are calculated relative to the baseline case. | Lastly, we present a sensitivity analysis for the carbon tax. Similarly to the case of the other input parameters, we fix the values of incentives and TEB budget to 0% and €10M, respectively, while assuming the GEB to take values from Table 2. Here, we have also omitted the cases in which GenCos have a €1M capacity exp... | Next, the VRE generation-capacity subsidies are varied. Similarly to the previous subsection, we consider the values of the remaining parameters to be fixed. In particular, we assume the carbon tax to remain at 0 € / MWh, the TEB at €10M while considering the GEB values as defined in Table 2 but excluding the case wher... | B |
Let fVGsubscript𝑓VGf_{\text{VG}}italic_f start_POSTSUBSCRIPT VG end_POSTSUBSCRIPT denote the density of the log-returns in the | VG model at maturity T>0𝑇0T>0italic_T > 0 with parameters σ>0𝜎0\sigma>0italic_σ > 0, θ∈ℝ𝜃ℝ\theta\in\mathbb{R}italic_θ ∈ blackboard_R | The FMLS model with parameters σ>0𝜎0\sigma>0italic_σ > 0 and α∈(1,2)𝛼12\alpha\in(1,2)italic_α ∈ ( 1 , 2 ) describes | σ>0𝜎0\sigma>0italic_σ > 0 and maturity T𝑇Titalic_T by the smallest natural number NFsubscript𝑁𝐹N_{F}italic_N start_POSTSUBSCRIPT italic_F end_POSTSUBSCRIPT | skewness β∈[−1,1]𝛽11\beta\in[-1,1]italic_β ∈ [ - 1 , 1 ], scale c>0𝑐0c>0italic_c > 0 and location θ∈ℝ𝜃ℝ\theta\in\mathbb{R}italic_θ ∈ blackboard_R | A |
}}{n}\sum_{j\neq i}\pi^{j}\Big{)}^{2}.italic_a ↦ ( italic_a - divide start_ARG italic_θ start_POSTSUBSCRIPT italic_i end_POSTSUBSCRIPT end_ARG start_ARG italic_n end_ARG ∑ start_POSTSUBSCRIPT italic_j ≠ italic_i end_POSTSUBSCRIPT italic_π start_POSTSUPERSCRIPT italic_j end_POSTSUPERSCRIPT ) ( italic_μ + over~ start_ARG... | Due to our assumption on g𝑔gitalic_g, a maximum point a*superscript𝑎a^{*}italic_a start_POSTSUPERSCRIPT * end_POSTSUPERSCRIPT exists and is finite. Then we obtain the following result. | Then we can prove that there exists an optimal strategy for (4.3). In order to do so, let a*superscript𝑎a^{*}italic_a start_POSTSUPERSCRIPT * end_POSTSUPERSCRIPT be a maximum point of | [Y^{a^{*}}]blackboard_E start_POSTSUBSCRIPT blackboard_Q end_POSTSUBSCRIPT [ italic_Y start_POSTSUPERSCRIPT italic_π start_POSTSUPERSCRIPT italic_i end_POSTSUPERSCRIPT end_POSTSUPERSCRIPT ] ≤ italic_Y start_POSTSUPERSCRIPT italic_a start_POSTSUPERSCRIPT * end_POSTSUPERSCRIPT end_POSTSUPERSCRIPT = blackboard_E start_POS... | If limx→±∞g(x)x=0subscriptnormal-→𝑥plus-or-minus𝑔𝑥𝑥0\lim_{x\to\pm\infty}\frac{g(x)}{x}=0roman_lim start_POSTSUBSCRIPT italic_x → ± ∞ end_POSTSUBSCRIPT divide start_ARG italic_g ( italic_x ) end_ARG start_ARG italic_x end_ARG = 0, an optimal strategy for (4.3) is given by πti≡a*superscriptsubscript𝜋𝑡𝑖superscript... | A |
Traditionally, the flow of resources is discussed within the framework of a material flows approach \citep[see][]flow_ayres,soc_ec_systems, where the amount of a specific material is measured or approximated when it is transferred between systems. Examples are the transition of phosphates (in the following abbreviated ... | or as country-wise exceedence footprints \citepp_exceed. With these approaches it is possible to cover most of the countries in the world, however, for the analysis of flows that happen before the production of biomass, the resolution of input-output data cannot deliver satisfactory results, since mineral resources, fe... | Our approach to P flows therefore aims to use much more detailed trade data as the basis of the analysis \citep[see also][]chen_p_net. The novelty of our approach is that we transform and connect these data to other sources in such a way that we receive results that can again be interpreted in terms of the material flo... | Traditionally, the flow of resources is discussed within the framework of a material flows approach \citep[see][]flow_ayres,soc_ec_systems, where the amount of a specific material is measured or approximated when it is transferred between systems. Examples are the transition of phosphates (in the following abbreviated ... | A related approach is to employ data from sector- or product-based input-output tables and to calculate the flows implied by these relationships, for example with a focus on biomass \citep[in particular agricultural and food products, see][]fabio, | D |
Table 3: Fair premium dependence on fee rate f2subscript𝑓2f_{2}italic_f start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT | When comparing buffer EPSs with floor EPSs, we observe that the hedging costs for buffer EPSs are higher than for floor EPSs. In order to explain this feature, we focus on their respective structures and we note that the fee legs for the buffer EPS and floor EPS shown in Table 1 are identical but their protection legs ... | Let us introduce two most practically relevant forms of an EPS, which are called the buffer EPS and the floor EPS. Notice that the proposed terminology for a generic EPS is referring directly to the protection leg, rather than the fee leg for which the choice of a buffer | We first define the buffer EPS where, incidentally, the concept of a buffer leg is applied to both the protection and fee legs and thus it could also be called a double-buffer EPS or a buffer/buffer EPS. | The so-called floor EPS, which can also be called floor/buffer EPS, is obtained by setting p2=0,p1∈(0,1],f1=0formulae-sequencesubscript𝑝20formulae-sequencesubscript𝑝101subscript𝑓10p_{2}=0,p_{1}\in(0,1],f_{1}=0italic_p start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT = 0 , italic_p start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT ∈ ( ... | A |
We find that the defaulters on larger amounts or with a subsequent harsh default have substantially higher penalties in terms of income and location, they move to lower median home values areas and to zip codes of lower economic activity. | We find that the defaulters on larger amounts or with a subsequent harsh default have substantially higher penalties in terms of income and location, they move to lower median home values areas and to zip codes of lower economic activity. | What seems to be happening is that there are consumers who are delinquent on smaller amounts, possibly because of uninsurable shocks, who suffer the consequences of such defaults, but substantially less than those who default on larger amounts and seek bankruptcy and other legal reliefs. The latter appear to have overe... | What seems to be happening is that there are individuals who are delinquent on smaller amounts, possibly because of uninsurable shocks, who suffer the consequences of such defaults, but substantially less than those who default on larger amounts and seek bankruptcy and other legal reliefs. The latter appear to have ove... | We show that the recovery is slow, painful, and in many respects only partial. In particular, after several years, up to 10, credit scores are still lower by 16 points, incomes never recover and appear to be substantially lower (by about 7,000USD or 14% of the 2010 mean), the defaulters live in lower “quality” neighbor... | C |
_{jk}\right)∑ start_POSTSUBSCRIPT italic_j end_POSTSUBSCRIPT ( italic_q ⋅ italic_s start_POSTSUBSCRIPT italic_j end_POSTSUBSCRIPT italic_f start_POSTSUBSCRIPT italic_j end_POSTSUBSCRIPT + ∑ start_POSTSUBSCRIPT italic_k end_POSTSUBSCRIPT sign ( italic_s start_POSTSUBSCRIPT italic_j end_POSTSUBSCRIPT - italic_s start_POS... | Minimax: Vote sincerely222222While a viability-aware strategy was included for Minimax in Wolk et al. (2023), | to Minimax. As with IRV, each ballot is a ranking of some or all of the candidates.101010While it is often recommended that equal rankings be allowed under | Block Approval: Voters vote for any number of candidates.272727We use the same sincere strategy as for single-winner Approval Voting. | Approval: Vote for all candidates with uj≥EVsubscript𝑢𝑗𝐸𝑉u_{j}\geq EVitalic_u start_POSTSUBSCRIPT italic_j end_POSTSUBSCRIPT ≥ italic_E italic_V. | A |
We did not include weekend effects in our seasonality function, since especially for the extremely volatile crisis data, these effects are negligible. | In order to take into account the change of the mean level in the data after the beginning of the crisis, the linear part of the seasonal function was calibrated piecewise for three different time periods. This is important since for the next step of the calibration, we assume that the deseasonalized data has mean leve... | This leads to the conclusion that the rapid up- and downward movements in the desaisonalized data in this time period are not Gaussian any more but are rather modeled by a succession of exponentially distributed jumps of large size. The adequacy of these calibration results are confirmed by the relatively high p𝑝pital... | We point out that even in the 4444-factor model, the inference performed by the MCMC algorithm is still exact at the level of distributions, since there is no discretization involved in the update of the second Gaussian component. The two models are then calibrated to EEX spot price data within different time periods a... | In this section, we compare the fit of the 3333-factor and 4444-factor model for three different time periods namely the pre-crisis period 2018-2021, the crisis 2021-23 and the whole interval 2018-2023. The EEX data we use for our studies starts at 30.9.2018 and ends at 10.1.2023. When we separate our data to investiga... | A |
In this work, we propose DoubleAdapt, a meta-learning approach to incremental learning for stock trend forecasting. | The upper level includes the data adapter and the model adapter as two meta-learners that are optimized to minimize the forecast error on the adapted test data. | We introduce two meta-learners, namely data adapter and model adapter, which adapt data towards a locally stationary distribution and equip the model with task-specific parameters that have quickly adapted to the incremental data and still generalize well on the test data. | Confronted with this challenge, it is noteworthy that the incremental updates stem from two factors: the incremental data and the initial parameters. Conventional IL blindly inherits the parameters learned in the previous task as initial parameter weights and conducts one-sided model adaptation on raw incremental data.... | (i) in the lower-level optimization, the parameters of the forecast model are initialized by the model adapter and fine-tuned on the adapted incremental data; | B |
My main contribution is to literature studying IPO returns. Some studies have examined the influence of institutional investors on IPO returns. For instance, Jiang and Li (2013) employed over-subscription rates for IPOs in Hong Kong to highlight the role that institutional investors play in determining IPO returns. On ... | Refining my focus on the qualitative nuances of investor communication, I observe that messages rich in financial insights and those that reinforce existing information have a marked influence on stock returns. Further, I explore the continuity of pre-IPO enthusiasm at the individual investor level. The data indicates ... | Closest to my setting, Tsukioka et al. (2018) uses investor sentiment extracted from Yahoo! Japan Finance message boards on 654 Japanese IPOs from 2001 to 2010, and shows that increased investor attention and optimism lead to higher IPO offer prices and initial returns, offering insight into the typical initial high re... | I examine how changes in emotion affect stock returns and demonstrate that elevated investor enthusiasm, as reflected in social media data, can induce buying pressure, leading to a temporary increase in stock prices. Subsequently, I show that these stocks, after their initial surge driven by this enthusiasm, tend to un... | My main contribution is to literature studying IPO returns. Some studies have examined the influence of institutional investors on IPO returns. For instance, Jiang and Li (2013) employed over-subscription rates for IPOs in Hong Kong to highlight the role that institutional investors play in determining IPO returns. On ... | B |
The dataset contains a large number of missing values, which motivated the experimentation of different imputation techniques such as zero-filling, round-robin imputation (implemented in the Python package scikit-learn), and MICE [43]. The best results were achieved with round-robin imputation using scikit-learn’s Iter... | The first quantum neural network architecture, named OrthoResNN, uses an 8×8888\times 88 × 8 orthogonal experimental layer implemented with a semi-diagonal loader and X𝑋Xitalic_X circuit. Note that the final output of the layer is provided by measurements. We add a skip connection by adding the input of the orthogonal... | Our second architecture, ExpResNN, replaces the experimental layer with an 8×8888\times 88 × 8 Expectation-per-subspace compound layer. We use the the H𝐻Hitalic_H-loader to encode our data. The layer is again followed by a tanh\tanhroman_tanh activation function. Fig. 18 illustrates the ExpResNN architecture. | To compare the performance of the orthogonal and compound layers to the classical baseline, we designed three neural network architectures. Each architecture had three layers: an encoding layer, an experimental layer, and a classification head. The encoding layer was a standard linear layer of size 32×832832\times 832 ... | In our experimental setup, we consider the fully connected residual layer (ResNN) as the classical benchmark. We performed the same experiment with an orthogonal layer using the semi-diagonal loader and the X circuit (OrthoResNN). Finally, we tried the expectation-per-subspace compound layer with the Hadamard loader an... | D |
Since it is based on actual trades, realized volatility (RV) is the ultimate measure of market volatility, although the latter is more often associated with the implied volatility, most commonly measured by the VIX index cboevix ; cboevixhistoric – the so called market ”fear index” – that tries to predict RV of the S&... | While the standard search for Dragon Kings involves performing a linear fit of the tails of the distribution pisarenko2012robust ; janczura2012black , here we tried to broaden our analysis by also fitting the entire distribution using mGB (7) and GB2 (11) – the two members of the Generalized Beta family of distribution... | The main result of this paper is that the largest values of RV are in fact nDK. We find that daily returns are the closest to the BS behavior. However, with the increase of n𝑛nitalic_n we observe the development of ”potential” DK with statistically significant deviations upward from the straight line. This trend termi... | We fit CCDF of the full RV distribution – for the entire time span discussed in Sec. 2 – using mGB (7) and GB2 (11). The fits are shown on the log-log scale in Figs. 4 – 13, together with the linear fit (LF) of the tails with RV>40𝑅𝑉40RV>40italic_R italic_V > 40. LF excludes the end points, as prescribed in pisarenk... | It should be emphasized that RV is agnostic with respect to gains or losses in stock returns. Nonetheless, it has been habitual that large gains and losses occur at around the same time. Here we wish to address the question of whether the largest values of RV fall on the power-law tail of the RV distribution. As is wel... | D |
Our paper differs from the above references since it models the interaction among bidders who adopt online learning algorithms. In this sense, it is closer in spirit to the Economics literature on learning in games. In addition, unlike the present paper, the cited references assume that the winning bidder observes her ... | Finally, we mention equilibrium analyses of bidding and ad exchanges that provide results related to our simulation findings. Choi and Sayedi (2019) analyze auctions in which a new entrant’s click-through rate is not known to the publisher. Despotakis et al. (2021) demonstrates that, with competing ad exchanges, a mult... | The second branch instead takes the perspective of a single bidder who uses learning algorithms to guide her bidding process. Weed et al. (2016) focus on second-price auctions for a single good, and assume that the valuation can vary either stochastically or adversarially in each auction. In a similar environment, Bals... | To the best of our knowledge, the closest papers to our own are Kanmaz and Surer (2020), Elzayn et al. (2022), Banchio and Skrzypacz (2022), and Jeunen et al. (2022). The first reports on experiments using a multi-agent reinforcement-learning model in simple sequential (English) auctions for a single object, with a res... | As noted in §1, our contribution here is twofold. First, we demonstrate through simulations that, with multi-query targeting, different auction formats—and in particular auctions with a soft floor—can yield different revenues, even if bidder types are drawn from the same distribution. Second, restricting attention to s... | C |
In this model, individuals have to make decisions sequentially, without knowing their position in the sequence (position uncertainty), but are aware of the decisions of some of their predecessors by observing a sample of past play. In the presence of position certainty, those placed in the early positions of the sequen... | The first thing to notice is the high value of β𝛽\betaitalic_β for all treatments, ranging between 0.819 and 0.893. This parameter is always significant and different from 0.5 (β𝛽\betaitalic_β values close to 0.5 indicate random behaviour, while values close to unity indicate almost deterministic behaviour). There is... | The main intuition behind the model is that an agent who observes a sample of past decisions of immediate predecessors, without defection, would decide to contribute, hoping to influence all her successors to do so. If instead, she decides to defect, then all the successors are expected to defect as well. As there is p... | A sketch of the intuition behind this follows. Consider an agent who observes a sample of full co-operation. According to the equilibrium definition, this occurs at the equilibrium path, and the agent can therefore infer that all the previous agents in the sequence contributed. By contributing herself, she knows that a... | In this model, individuals have to make decisions sequentially, without knowing their position in the sequence (position uncertainty), but are aware of the decisions of some of their predecessors by observing a sample of past play. In the presence of position certainty, those placed in the early positions of the sequen... | B |
Further, by appropriately tuning the number of walkers, steps, and coin operator parameters, multi-SSQW can be optimized for swift convergence, thereby enhancing efficiency. It is important to note, however, that achieving efficiency necessitates a deep understanding of system dynamics and careful selection and tuning ... | Uncertainty is an inherent nature of financial markets, manifesting itself in the unpredictability of the cognitive processes of market participants, their decision-making routines, and the general macroeconomic conditions and structural dynamics of the financial market, which directly influence asset valuation. This c... | There appears to be an inherent trade-off between the quantum circuit’s complexity and the optimizer’s efficiency in the Variational Quantum Algorithms (VQA). As we increase the depth and intricacy of our quantum | The multi-SSQW framework leverages a dual-domain computational approach, involving a Parameterized Quantum Circuit (PQC) and a classical optimizer. The PQC is composed of n+1 qubits, one designated for coin space and the remainder for position space. This setup is employed to represent and emulate the distribution of s... | Figure 4: (a) Illustrates the multi-Split-Steps Quantum Walk (multi-SSQW) setup, showing the initial state and the sequence of operations modeling investors’ decision-making. The quantum state evolves iteratively to achieve a targeted distribution, analyzed by a classical optimizer. (b) Depicts the quantum circuit of ... | B |
The constant coefficient is somewhat lower (indicating a 0.32 vs 0.56 delegation rate in trivial task) | The Table shows that the median investor can potentially recoup the low (10p) cost of delegation for simple tasks, and almost recoup it for complex tasks. For high cost (100p), however, delegation is potentially cost-effective only for the very most inefficient investors in the simple task, and for no investor in the c... | Our experiment is intended to assess four different motives for delegating investment decisions to experts. To distinguish among the motives, the experiment controls for the cost of delegation and for task complexity, as well as for the available information about experts. | As elaborated below in our survey of previous literature, we identify four possible motives for delegation: | The third section lays out our laboratory procedures and experiment design, and spells out the hypotheses on delegation motives that we will test. Results are collected in the following section, beginning with an overview using descriptive summary statistics. Later subsections present inferential statistics to identify... | B |
We call g𝑔gitalic_g turbulent if there exist three points, x1subscript𝑥1x_{1}italic_x start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT, x2subscript𝑥2x_{2}italic_x start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT, and x3subscript𝑥3x_{3}italic_x start_POSTSUBSCRIPT 3 end_POSTSUBSCRIPT in I𝐼Iitalic_I such that g(x2)=g(x1)=x1𝑔subscr... | First, we clarify what we mean by a Li-Yorke chaos, a turbulence, and a topological chaos. (There are several definitions of a chaos in the literature.) The following definitions are taken from [Ruette, 2017, Def. 5.1] and [Block and Coppel, 1992, Chap. \@slowromancapii@]. Let g𝑔gitalic_g be a continuous map of a clos... | It is well-known that the existence of a period three cycle implies that of a Li-Yorke chaos (by the famous Li-Yorke theorem [Li and Yorke, 1975, Thm. 1]), and this argument has been used a lot in economic literature, see [Benhabib and Day, 1980], [Benhabib and Day, 1982], [Day and Shafer, 1985], [Nishimura and Yano, 1... | It is known that a map g𝑔gitalic_g is topologically chaotic if and only if g𝑔gitalic_g has a periodic point whose period is not a power of 2222, see [Block and Coppel, 1992, Chap. \@slowromancapii@]. This implies that a map g𝑔gitalic_g is topologically chaotic if and only if the topological entropy of g𝑔gitalic_g i... | Suppose that g𝑔gitalic_g is S𝑆Sitalic_S-unimodal, g𝑔gitalic_g has no attracting periodic orbit, and the critical point c𝑐citalic_c is non-flat. Then g𝑔gitalic_g has a unique acim ζ𝜁\zetaitalic_ζ and g𝑔gitalic_g is ergodic with respect to ζ𝜁\zetaitalic_ζ if one of the following conditions is satisfied: | C |
We also present baseline data for latency and fill-rate of transactions. Latency and fill-rate measure how quickly and reliably can traders get into their desired positions. Our dataset indicates that roughly 90% of transactions wait less than 12 seconds before their signed transactions are confirmed in a block. As we ... | Transaction costs on traditional markets. In contrast, a number of works have quantified overall trading costs on traditional markets (such as equities markets). We point to | Many works have assessed transaction costs (slippage, commission, broker fees, bid ask spreads, price impact) on traditional markets. | We compare the magnitude of the different transaction cost components: gas costs, slippage, LP fees, and the price impact of swaps. | A number of works measure the dynamics of liquidity provisioning on decentralized exchanges, sometimes through the lenses of transaction costs. [16] show that lower gas fees increase liquidity repositioning and concentration, reducing price impact for small trades. They use a notion of slippage that incorporates price ... | B |
These companies, and other centralized cryptoasset exchanges (CEXs) like FTX, fall under the broader definition of virtual asset service providers (VASPs). They facilitate financial activity involving virtual assets (VAs), such as their exchange for other VAs or fiat currencies, their custody and transfer via cryptoass... | Figure 9: Estimation of the bitcoin holdings in Euro of VASP-5. On-chain and off-chain data are comparable only in 2015 and 2016. | As Figure 1 shows, VASPs lie at the interface of the traditional and the crypto financial ecosystems, respectively called off-chain and on-chain financial activity in jargon. | Figure 4: Comparison of traditional financial intermediaries with VASPs. Circles on the left represent VASPs, divided into groups as described in Figure 3, while on the right are traditional financial intermediaries. Links point to the financial functions offered by each financial intermediary. VASPs are most similar t... | VASPs lie at the interface of the traditional and the crypto financial ecosystems. The former encompasses financial activity with fiat currencies, i.e., legal tender money, and fiat assets, i.e., assets denominated in fiat currencies (similarly to cryptoassets being assets denominated in a cryptocurrency). It can rely ... | B |
The aim of this paper is to develop an algorithm that uses representations (5) and (6) to approximate the set of Nash equilibria of a non-cooperative game. | To do so, we will focus for the remaining part of this paper on convex games satisfying the following assumption. | Usually, when considering convex games, the focus is on providing the existence of a unique equilibrium point and developing methods for finding this particular equilibrium, see e.g. [21], where additional strong convexity conditions are assumed to guarantee uniqueness of the Nash equilibrium. In this paper, we will co... | In the following, we will make the following assumption concerning the structure of the constraint set in addition to considering convex games (Assumption 4.1). | In this paper, we will mainly focus on convex games with a shared constraint set 𝕏𝕏\mathbb{X}blackboard_X. | A |
Table 8: Parameter estimation through the CLS for French (left) and Italian (right) energy log spot price. | Third, we address the challenge of the joint temperature and log spot energy price distribution by proposing a coupled model on the dynamics. In particular, we introduce the Brownian noise of the temperature dynamics into the energy process. This allows the integration of weather information available at the time of pr... | We then turn to the goodness of fit of the estimated combined Model (ETM). Figure 11 and 12 represent χ2superscript𝜒2\chi^{2}italic_χ start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT test performed between the historical and simulated distributions on the (2-dimensional) empirical copula between temperature and electricity... | Figure 11: From top left to bottom right, χ2superscript𝜒2\chi^{2}italic_χ start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT test performed on the distributions of real (blue) and simulated (green - based on 1,000,00010000001,000,0001 , 000 , 000 simulations) ranked residuals for 4 and 25 categories for French data. | Figure 12: From top left to bottom right, chi-square test performed on the distributions of real (blue) and simulated (green - based on 1,000,00010000001,000,0001 , 000 , 000 simulations) ranked residuals for 4 and 25 categories for North Italian data. | B |
Perpetual swaps were introduced by BitMEX in 2016201620162016 [Hayes,]. They are futures contracts with no expiry. These contracts allow for high leverage with most cryptocurrency exchanges offering leverage in the range of 100100100100x–125125125125x and some recent platforms allowing up-to 1000100010001000x(!) levera... | Our datasets are comprised of tick-by-tick trades, block trades, liquidations, and open interest as reported by the APIs of the respective exchanges mentioned in Table 1. We limit our attention to Bitcoin linear perpetuals quoted in USDT (https://tether.to/en/) and inverse perpetuals quoted in USD, as these are the mos... | As stablecoins gained in popularity, inverse perpetuals ceded market dominance to the linear perpetual swap. These pay profits and losses in the quote asset and are margined by the same, which is most often some stablecoin for the US dollar. This is not unexpected, as for most people their numéraire is some form of FIA... | The other possibility is that trading volume is accurate but the reported open interest is incorrect. Market participants do observe the changes in open interest and attempt to infer how informed investors are being positioned in the market. The general heuristic is that if open interest is rising and the price is incr... | Perpetual swaps were introduced by BitMEX in 2016201620162016 [Hayes,]. They are futures contracts with no expiry. These contracts allow for high leverage with most cryptocurrency exchanges offering leverage in the range of 100100100100x–125125125125x and some recent platforms allowing up-to 1000100010001000x(!) levera... | B |
Boghosian et al. in [7] established that the Gini coefficient is monotone under the dynamics of the continuum model Eq. 2 of the classical Yard-Sale Model. This result was shown both for the master equation and the resulting non-linear partial integro-differential Fokker-Planck equation first derived in [4]. Thus the G... | We now turn to the main results of the paper: That the Gini coefficient, despite being monotonically increasing under the modified Yard-Sale Model dynamics, can have a non-trivial bound on its rate of change in time. This bound may be carried over into a bound on the value of the Gini coefficient at a future time. | The paper is organized as follows. The variant of the Yard-Sale Model on which the present paper focuses is motivated and defined in Section 2. The Gini coefficient is briefly reviewed in Section 3 with particular focus on its invariance under a normalization of the equations of motion. In Section 4 it is proven both t... | Despite the many methods of showing that wealth condensation occurs, we are not aware of any explicit bounds on the rate of increase of the Gini coefficient under models for which the Gini coefficient increases monotonically. | We introduced a variant of the Yard-Sale Model for which the Gini coefficient of economic inequality monotonically increases under the resulting continuum dynamics yet the rate of change in time of the Gini coefficient permits an upper bound. The way in which this bound holds is similar to the entropy – entropy product... | C |
A common approach to mitigate the curse of dimensionality is the regression-based Monte Carlo method, which involves simulating numerous paths and then estimating the continuation value through cross-sectional regression to obtain optimal stopping rules. [1] first used spline regression to estimate the continuation val... | Inspired by a version of Regression Monte Carlo Methods, proposed by [10], which applied GPR to estimate the continuation value within the Longstaff-Schwartz algorithm in low-dimensional cases, we aim to extend the application of GPR to the pricing of high-dimensional American options. Prior to this, there are two pote... | In this work, we will apply a deep learning approach based on Gaussian process regression (GPR) to the high-dimensional American option pricing problem. The GPR is a non-parametric Bayesian machine learning method that provides a flexible solution to regression problems. Previous studies have applied GPR to directly le... | To overcome this issue, we incorporate the Deep Kernel Learning (DKL) method, introduced by [18, 19], which employs a deep neural network to learn a non-Euclidean metric for the kernel. The second challenge is the significant computational cost associated with processing numerous simulated paths. A large training set i... | A common approach to mitigate the curse of dimensionality is the regression-based Monte Carlo method, which involves simulating numerous paths and then estimating the continuation value through cross-sectional regression to obtain optimal stopping rules. [1] first used spline regression to estimate the continuation val... | B |
Hence, since the comonotonic coupling is optimal for submodular cost functions [24], the result follows. | The optimal coupling of the MK minimisation problem induced by any consistent scoring function for the entropic risk measure is the comonotonic coupling. | The comonotonic coupling is also optimal when the cost function is a score that elicits the α𝛼\alphaitalic_α-expectile. | The optimal coupling of the MK minimisation problem induced by the scoring function given in (14) is the comonotonic coupling. | The optimal coupling of the MK minimisation problem induced by the score given in (11) is the comonotonic coupling. | B |
A DF strategy (Π∗,i,C∗,i)i=1n∈𝒮nsuperscriptsubscriptsuperscriptΠ𝑖superscript𝐶𝑖𝑖1𝑛superscript𝒮𝑛\left(\Pi^{*,i},C^{*,i}\right)_{i=1}^{n}\in\mathcal{S}^{n}( roman_Π start_POSTSUPERSCRIPT ∗ , italic_i end_POSTSUPERSCRIPT , italic_C start_POSTSUPERSCRIPT ∗ , italic_i end_POSTSUPERSCRIPT ) start_POSTSUBSCRIPT italic_... | the discount function only needs to satisfy some weak conditions; see Remark 2.1 in Section 2. Meanwhile, we adopt the asset specialization framework in [23, 7] with a common noise. A lot of literature on equilibrium strategy under non-exponential discounting suggest that the investment strategy is independent of disco... | For the sake of brevity we use the name “equilibrium strategy” but it is different to “close-loop equilibrium strategies” or “subgame-perfect equilibrium strategies” discussed in the literature of time-inconsistent problems. A more appropriate name would be a “DF representation of open-loop equilibrium controls”. | The contributions of our paper are as follows: first, as far as we know, our work is the first paper to incorporate consumption into CARA portfolio game with relative performance concerns. Portfolio games under relative consumption are generally underexplored, with the exception of [22], which focuses solely on CRRA ut... | There are many important problems in mathematical finance and economics incurring time-inconsistency, for example, the mean-variance selection problem and the investment-consumption problem with non-exponential discounting. The main approaches to handle time-inconsistency are to search for, instead of optimal strategie... | B |
Importantly, the data by the relays is self-reported and thus requires some trust in the relays, as it cannot be fully verified. However, we combine our Ethereum blockchain reward data set with our PBS data set to verify that the block values reported by the relays correspond to those received by the validators. If thi... | Figure 1: PBS scheme visualization. In step \⃝raisebox{-0.9pt}{\footnotesize1}, a searcher sends (bundles of) transactions to one or many builders privately, the transactions included in the bundle can be from the public Ethereum mempool, private order flow or from the searcher itself. The builder then builds a high-va... | Note that most of trades buy ETH or BTC for a stablecoin. As we saw in Figure 4 the prices of these two cryptocurrencies rose on Binance.com, and they were thus trading for cheaper on DEXes at the beginning of the block. For example, if we look at the price at the beginning of the block, we see that the price of the ET... | Heuristic 2. The transaction is private, i.e., it did not enter the mempool before the block was propagated. | To obtain block times, i.e., the time at which a block was first seen in the network, and to identify private transactions we use Ethereum network data from the Mempool Guru project [10]. The Mempool Guru project runs geographically distributed Ethereum nodes. Each node records the timestamp at which it first saw any b... | D |
MetricsS,tsubscriptMetrics𝑆𝑡\displaystyle\text{Metrics}_{S,t}Metrics start_POSTSUBSCRIPT italic_S , italic_t end_POSTSUBSCRIPT | :Macroeconomic summary at time t.:absentMacroeconomic summary at time 𝑡\displaystyle:\text{Macroeconomic summary at time }t.: Macroeconomic summary at time italic_t . | for stock S at time t.for stock 𝑆 at time 𝑡\displaystyle\quad\text{for stock }S\text{ at time }t.for stock italic_S at time italic_t . | : Performance metrics for stock S at time t.:absent Performance metrics for stock 𝑆 at time 𝑡\displaystyle:\text{ Performance metrics for stock }S\text{ at time }t.: Performance metrics for stock italic_S at time italic_t . | at time t.umberformulae-sequence at time 𝑡𝑢𝑚𝑏𝑒𝑟\displaystyle\quad\text{ at time }t.umberat time italic_t . italic_u italic_m italic_b italic_e italic_r | C |
The outcome is a regime-switching process reminiscent of the model proposed by Buffington and Elliott (2002), enriched with randomisation features. The primary focus of this section is on deriving the characteristic function of our model, which constitutes the main result. | In the following, we model the randomised component processes without time-dependence in the coefficients and such that their conditional versions are Lévy processes, which preserves stationarity and greatly simplifies the proof given. | This construction, coupled with the assumption of independence between stochastic drivers and randomisers, establishes a valuable link between the randomised processes, with coefficients influenced by random variables ϑjsubscriptitalic-ϑ𝑗\vartheta_{j}italic_ϑ start_POSTSUBSCRIPT italic_j end_POSTSUBSCRIPT, and what we... | In addition, we define the conditional component processes Yjθ(t)subscriptsuperscript𝑌𝜃𝑗𝑡Y^{\theta}_{j}(t)italic_Y start_POSTSUPERSCRIPT italic_θ end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_j end_POSTSUBSCRIPT ( italic_t ) as the stochastic processes obtained when a realisation θj=ϑj(ω*)subscript𝜃𝑗subscripti... | In this section, we define the framework of random coefficients and switches between regimes. Randomness in the coefficients leads to what we denote as randomised processes, which are stochastic processes that incorporate an additional source of randomness, influencing both their volatility and drift coefficients. For ... | A |
We calibrate the HW model at the ATM implied volatility of a caplet with the same duration, for which we use the analytical implied volatility formula of Turfus and Romero-Bermúdez [2023]. | We also compare the 3M SOFR futures convexity of Eq. (5.8) with the 3M Eurodollar convexity, where both include the effects of option smile and skew. For more details about the calculation of the Eurodollar convexity, see Appendix D. | Finally, we show the difference between the convexity of 3M SOFR futures and the convexity of the Eurodollar future in Fig. 3. | In addition, we compare these results with the convexity calculated in the Hull-White model, which neglects the effects of market smile and skew, see Appendix E for more details. | Figure 3: Convexity of 3M-Eurodollar minus the convexity of 3M-SOFR contracts, both incorporating option smile and skew. | A |
∗ p<0.05𝑝0.05p<0.05italic_p < 0.05, ∗∗ p<0.01𝑝0.01p<0.01italic_p < 0.01, ∗∗∗ p<0.001𝑝0.001p<0.001italic_p < 0.001 | For overtreatment, we document all relevant regression analyses in the Appendix. As expected, consumers experience more overtreatment when approaching an expert with 𝐏𝐦superscript𝐏𝐦\mathbf{P^{m}}bold_P start_POSTSUPERSCRIPT bold_m end_POSTSUPERSCRIPT or 𝐏𝐞superscript𝐏𝐞\mathbf{P^{e}}bold_P start_POSTSUPERSCRIPT ... | We now look at undertreatment from the expert’s perspective. Each round, experts receive three diagnoses, and make three treatment choices. Because of diagnostic uncertainty, an expert may intent to undertreat a consumer, but does not actually do so because of a wrong diagnosis. Therefore, we define the intent-to-under... | Expert Price Setting. Figure 6 shows the share of experts choosing a specific price vector depending on type, treatment and investment. We are primarily interested in potential strategic differences between high-ability experts who invest and those who forego investments. There are two potential effects. One, an expert... | Consumer Choices. How do consumers react to undertreatment with diagnostic uncertainty? Table 7 shows that experiencing undertreatment strongly predicts consumer switching in the following round. This holds for both phases and treatments. Overtreatment appears to have no or only little effect on consumer choices. Furth... | B |
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