Miracle-dz/UniFAR-FTUs huggingface dataset:
Can Kelly Gambling Explain Equity Risk Premia?

Standard finance theory has long identified equity investment with aggregate consumption and equity investors with average consumers, while treating most growth risks as iid. The combination makes it impossible to reconcile high equity risk premia with low risk aversion. Reinterpreting equity markets as gambling casinos with unstable risks cuts a Gordian knot. Enrichment-seeking gamblers pursuing fractional Kelly strategies need a risk premium to maintain net long positions in equities. In simulations that use GDP disaster risks to proxy dividend trends, rational learning induces enough volatile excess volatility to account for risk premia of hundreds of basis points.
Effektivt stöd för FoU, innovationer och företagande (Efficient Support to R&D, Innovations and Entrepreneurship)

<b>Swedish Abstract:</b> De senaste 20 åren har svenska regeringar genomfört många förändringar när det gäller satsningar på FoU/innovationer och företagande – i synnerhet inom det sistnämnda området. I denna rapport har förändringarna diskuterats med utgångspunkt från den nationalekonomiska forskningslitteraturen. Det visar sig att flera satsningar inte har varit optimala och att många åtgärder är dåligt utvärderade. Nedan följer en sammanfattning vad som har gjorts och i punktform förslag på vad som behöver göras. <br><br><b>English Abstract:</b> In the last 20 years, Swedish governments have implemented many changes in terms of investments in R&amp;D / innovation and entrepreneurship . In this report, the changes are analyzed on the basis of the economic research literature. It turns out that several policy changes have not been optimal and that many programs are poorly evaluated. Below is a summary of what has been done and in point form suggestions of what needs to be done.
Explaining Algorithmic Decisions

Algorithmic systems are increasingly instrumental to how private and public actors make real world decisions. Often, the internal reasonings underlying these systems are opaque to the humans who use them. This Article gives a broad technical overview of how algorithms work and what tools exist to interrogate how they come to decisions. It is aimed at a non-technical audience and builds off of technical and ontological scholarship from the nascent field of explainable artificial intelligence (XAI). Part II defines and contextualizes the terms "algorithm" and "explanation. " Part III proposes a hypothetical machine learning algorithm and explores how feature engineering and dimensionality affect the capacity for humans to understand how it works. Part IV looks at the unique explainability problems posed by systems that combine multiple opaque algorithms and the latest tools developed to address them.
Relevance of Capital Asset Pricing Model – A Review

Though it is commonly said that higher the risk higher would be the returns, the questions that remain are, what type of risks are awarded and what is risk premium per unit of risk. A few equilibrium asset-pricing models attempted to answer these questions. Out of these, Capital Asset Pricing Model (CAPM) is the most popular and widely used model. It was independently developed by Sharpe (1964), Lintner (1965), and Mossin (1966). Fama (1968), Black, Jensen and Scholes (1972), Fama and Mac Beth (1973), and Fama and French (1992) and others proposed further refinements. The CAPM provides a precise prediction of the relationship between the risk of an asset and its expected return. In the Indian stock market the empirical studies on CAPM showed mixed results. Roll’s critique has attracted attention of many researchers and resulted in popular articles such as “Is Beta Dead? ” “Is Beta Dead or Alive? ” “Are Reports of Beta’s Death Premature? “Is Beta Dead Again? ” that effectively reduced the popularity of CAPM in the world of finance in 1992. The debate regarding superiority of Asset Pricing Theory (APT) to CAPM is continuing. The empirical testing of APT is still in its early stage and concrete results in favour of APT or against CAPM do not exist. Till then, CAPM is expected to dominate the capital market as a measure to ascertain expected returns of risky securities.
Convergence in Motion: A Review of Fair Value Levels' Relevance

The IFRS 13 post-implementation review by the IASB motivates our investigation on the value relevance of fair value (FV) measurement hierarchy (i.e. level 1, level 2, and level 3). First, using a meta-analysis, which allows us to summarize inconsistent empirical findings, we synthesize studies on the value relevance of the FV hierarchy. Overall, value relevance is lower for level 3 than for levels 1 and 2, but it increases over time. In non-U.S. studies, we note lower value relevance across all levels of FV assets. Underlying asset fundamentals, model risk, and measurement process complexity may contribute to this value relevance gap. Second, from interviews with professionals from financial institutions, we note that, in practice, there has been extensive learning about FV accounting since the 2007‒9 Financial Crisis and a formalization of the valuation process that the academic literature has yet to fully recognize. We thus highlight conceptual and methodological issues and areas for research with practical implications.
What is the value of the cross-sectional approach to deep reinforcement learning?

Reinforcement learning (RL) for dynamic asset allocation is an emerging field of study. Total return, the common performance metric, is useful for comparing algorithms but does not help us determine how close an RL algorithm is to an optimal solution. In real-world financial applications, a bad decision could prove to be fatal. One of the key ideas of our work is to combine the two paradigms of the mean-variance optimization approach (Markowitz criteria) and the optimal capital growth approach (Kelly criteria) via the actor-critic approach. By using an actor-critic approach, we can balance optimization of risk and growth by configuring the actor to optimize the mean-variance while the critic is configured to maximize growth. We propose a Geometric Policy Score used by the critic to assess the quality of the actions taken by the actor. This could allow portfolio manager practitioners to better understand the investment RL policy. We present an extensive and in-depth study of RL algorithms for use in portfolio management (PM). We studied eight published policy-based RL algorithms which are preferred over value-based RL because they are better suited for continuous action spaces and are considered to be state of the art, Deterministic Policy Gradient (DPG), Stochastic Policy Gradients (SPG), Deep Deterministic Policy Gradient (DDPG), Trust Region Policy Optimization (TRPO), Proximal Policy Optimization (PPO), Twin Delayed Deep Deterministic Policy Gradient (TD3), Soft Actor Critic (SAC), and Evolution Strategies (ES) for Policy Optimization. We implemented all eight and we were able to modify all of them for PM but our initial testing determined that their performance was not satisfactory. Most algorithms showed difficulty converging during the training process due to the non-stationary and noisy nature of financial environments, along with other challenges. We selected the four most promising algorithms DPG, SPG, DDPG, PPO for further improvements. The modification of RL algorithms to finance required unconventional changes. We have developed a novel approach for encoding multi-type financial data in a way that is compatible with RL. We use a multi-channel convolutional neural network (CNN-RL) framework, where each channel corresponds to a specific type of data such as high-low-open-close prices and volumes. We also designed a reward function based on concepts such as alpha, beta, and diversification that are financially meaningful while still being learnable by RL. In addition, portfolio managers will typically use a blend of time series analysis and cross-sectional analysis before making a decision. We extend our approach to incorporate, for the first time, cross-sectional deep RL in addition to time series RL. Finally, we demonstrate the performance of the RL agents and benchmark them against commonly used passive and active trading strategies, such as the uniform buy-and-hold (UBAH) index and the dynamical multi-period Mean-Variance-Optimization (MVO) model.
A Replicating Portfolio Approach to Valuing American Options in Closed-Form

I derive closed-form expressions for the value of American call and put options (on an asset with continuous yield) using the Feynman-Kac formula, modelling the size of early exercise premium as a function of the strike, dividend yield and time to maturity. Strategies involving European options and binary options on forwards on the asset replicate an American option exactly. Violations of Put-Call parity for American options is also explored in this framework.
The Role of Banks in the Circular Economy

The circular economy concept has received considerable attention both in the business sector and in academia. In this paper, we highlight the role of banks in the circular economy. We propose that banks need to: develop a common understanding of the circular economy; issue widely accepted and recognized guidelines on circular economy finance; adapt existing finance models to fit into a circular economy model; offer credit lines to circular businesses; create a green bank; train bank staff; promote a strong culture of waste reduction and material re-use; ensure that the board risk committee is competent in circular risk management and control. Overall, banks have an important role to play both as a leader in circular economy finance and as a lender to companies in the circular economy.
Monetary Policy and the Wage Inflation-Unemployment Tradeoff

Over the last years, many have been questioning the importance of the Phillips curve arguing that it has flatten out of favour. Thus, a lot of attention has been given to understand why its slope is flatter and how can central bankers still explore it. Building on this current debate, I estimate historical wage Phillips curves by using newly assembled data on wages and unemployment rates for a set of 17 advanced economies starting in 1870. I show that the wage Phillips curve has always been alive and well but, similarly to recent times, it was flatter during the Gold Standard. The collected data suggest that a low price inflation environment promotes this disconnect, which is aligned with the New Keynesian model predictions. In such an environment, wages and prices are adjusted by firms less often and thus, the relationship between unemployment and wage inflation becomes weaker.
The Economic Burden of Pension Shortfalls: Evidence from House Prices

U.S. state pensions are underfunded by trillions of dollars, but their economic burden is unclear. In a model of inefficient taxation, real estate fully reflects the cost of pension shortfalls when it is the only form of immobile capital. We study the effect of pension shortfalls on real estate values at state borders, where labor and physical capital could more easily relocate to a state with a smaller shortfall. Using plausibly exogenous variation driven by pension asset returns, we find that one dollar of pension underfunding reduces house prices near state borders by approximately two dollars. Our estimates imply a deadweight loss associated with addressing pension shortfalls that is consistent with prior research in settings with high returns to public spending and costs of taxation.
THE RISE OF FUND MANAGERS IN FOREIGN EXCHANGE 519

INTERNATIONAL fund managers seem to increasingly dominate foreign exchange (FX) markets. Although they do not match FX dealers in terms of turnover, they do outweigh them when it comes to holding positions. Whereas FX dealers usually close positions on a daily basis, international fund managers typically hold positions over longer periods of time. Therefore, one might expect that fund managers tend to be closer to the fundamentalist role-model. Are foreign exchange markets therefore increasingly driven by fundamentalist strategies? This is the basic question of our paper. This study is the first to analyse the differences between groups of market participants by means of survey evidence, based on questionnaires sent out to both international fund managers and FX dealers. The emerging picture of a major change in foreign exchange due to the rise of fund managers – that are more fundamentally oriented than FX dealers – is restricted in two ways, however: first, the fundamental stance of fund managers is weak when assessed from an absolute point of view. Second, fund managers’ behaviour has changed over time. The underlying survey is the only one in foreign exchange that can be directly compared with an older questionnaire survey. We find that fund managers behave increasingly more like conventional FX dealers, i.e. they increasingly show a preference for non-fundamental behaviour. Thus, foreign exchange markets will stay imperfect, being influenced by individual rationality and behavioural elements that do not always bring about efficient markets.
#Flattenthecurve

In this paper I adapt a common model used in economics to study the diffusion of innovations to model the transmission of a virus Emphasis is placed on the evolution of the number of new infections and the cumulative total number of infections over time and how they might be influenced by different policies Although the model is very simple it does yield some useful implications for public policy
Public Budgeting & Finance

Though the fiscal slack literature has advanced over the past decade, more research is needed for a systematic understanding of the determinants and uses of fiscal reserves at the local level. This paper reviews theory and empirical evidence on the determinants of municipal fiscal reserves offers a conceptual framework for analyzing fiscal reserves accumulation and tests a series of hypotheses using a panel of 2007–2012 financial data for 145 U.S. cities from 21 states. Generalized least squares models show that unassigned general fund balances and unrestricted net assets are positively associated with general fund surpluses in the previous year and with local household incomes, while not being related to measures of fiscal risk, revenue effort, and voter characteristics. Overall, the findings suggest a relatively stronger influence of the capacity to save than the need to save on local fiscal reserves.
The Important Role of Time Limits when Consumers Choose their Time in Service

A main challenge that service providers face when managing service systems is how to generate value and regulate congestion at the same time. To this end, classical queueing models suggest managers charge per-use fees and invest in capacity to speed up the service. However, in discretionary services, in which consumers value time in service and choose how long to stay, per-use fees result in suboptimal performance and speeding up does not apply. We study a queueing model of a service provider and rational consumers who are heterogenous in their requirements for service duration. Consumers incur disutility from waiting and choose whether to join and how long to spend in service. We consider time limits as a novel mechanism that may help in controlling congestion. Time limits put a cap on the maximum time that customers can spend in service. We analyze their effectiveness when combined with two price schemes: per-use fees and price rates. Time limits are effective because they reduce time in service and impact waiting times and joining behavior. Revenue maximizing firms and social planners who maximize social welfare benefit from implementing time limits in addition to price rates. Social planners who seek to maximize consumer welfare, however, focus on regulating congestion and should, therefore, offer the service for free but implement time limits if congestion levels are high. The attractiveness of time limits goes further. We show that time limits are not only a useful lever that works well when combined with simple price mechanisms, but they are in fact optimal when congestion is high. Service providers can achieve the first-best outcome and extract all customer surplus by coupling a time limit with an optimal price mechanism. The attractiveness of time limits stems from their ability to reduce not only the average time spent in service, but also its variance. This is highly effective in settings in which customers’ service times impose externalities on others’ waiting times. Thus, we conclude that providers of discretionary services should set time limits when congestion is an issue. This paper was accepted by Vishal Gaur, operations management.
Perampanel, an AMPAR antagonist, alleviates experimental intracerebral hemorrhage-induced brain injury via necroptosis and neuroinflammation

Spontaneous intracerebral hemorrhage (ICH) is a subtype of stroke with high mortality and morbidity due to the lack of effective therapies. The alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor antagonist perampanel has been reported to alleviate early brain injury following subarachnoid hemorrhage and traumatic brain injury by reducing reactive oxygen species, apoptosis, autophagy, and necroptosis. Necroptosis is a caspase-independent programmed cell death mechanism that serves a vital role in neuronal cell death following ICH. However, the precise role of necroptosis in perampanel-mediated neuroprotection following ICH has not been confirmed. The present study aimed to investigate the neuroprotective effects and potential molecular mechanisms of perampanel in ICH-induced early brain injury by regulating neural necroptosis in C57BL/6 mice and in a hemin-induced neuron damage cell culture model. Mortality, neurological score, brain water content, and neuronal death were evaluated. The results demonstrated that perampanel treatment increased the survival rate and neurological score, and increased neuron survival. In addition, perampanel treatment downregulated the protein expression levels of receptor interacting serine/threonine kinase (RIP) 1, RIP3, and mixed lineage kinase domain like pseudokinase, and of the cytokines IL-1β, IL-6, TNF-α, and NF-κB. These results indicated that perampanel-mediated inhibition of necroptosis and neuroinflammation ameliorated neuronal death in vitro and in vivo following ICH. The neuroprotective capacity of perampanel was partly dependent on the PTEN pathway. Taken together, the results of the present study demonstrated that perampanel improved neurological outcomes in mice and reduced neuronal death by protecting against neural necroptosis and neuroinflammation.
Augmented renal clearance. An unnoticed relevant event

Augmented renal clearance (ARC) is a phenomenon that can lead to a therapeutic failure of those drugs of renal clearance. The purpose of the study was to ascertain the prevalence of ARC in the critically ill patient, to study the glomerular filtration rate (GFR) throughout the follow-up and analyze the concordance between the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) estimation formula and measured GFR. Observational, prospective, multicenter study. ARC was defined as a creatinine clearance greater than 130 ml/min/1.73 m2. Eighteen hospitals were recruited. GFR measurements carried out twice weekly during a 2-month follow-up period. A total of 561 patients were included. ARC was found to have a non-negligible prevalence of 30%. More even, up to 10.7% already had ARC at intensive care unit (ICU) admission. No specific pattern of GFR was found during the follow-up. Patients in the ARC group were younger 56.5 (53.5–58.5) versus 66 (63.5–68.5) years than in the non-ARC group, p < 0.001. ICU mortality was lower in the ARC group, 6.9% versus 14.5%, p = 0.003. There was no concordance between the estimation of GFR by the CKD-EPI formula and GFR calculated from the 4-h urine. ARC is found in up to 30% of ICU patients, so renal removal drugs could be under dosed by up to 30%. And ARC is already detected on admission in 10%. It is a dynamic phenomenon without an established pattern that usually occurs in younger patients that can last for several weeks. And the CKD-EPI formula does not work to estimate the real creatinine clearance of these patients.
Polyoxometalates as Effective Nano-inhibitors of Amyloid Aggregation of Pro-inflammatory S100A9 Protein Involved in Neurodegenerative Diseases

Pro-inflammatory and amyloidogenic S100A9 protein is central to the amyloid-neuroinflammatory cascade in neurodegenerative diseases. Polyoxometalates (POMs) constitute a diverse group of nanomaterials, which showed potency in amyloid inhibition. Here, we have demonstrated that two selected nanosized niobium POMs, Nb10 and TiNb9, can act as potent inhibitors of S100A9 amyloid assembly. Kinetics analysis based on ThT fluorescence experiments showed that addition of either Nb10 or TiNb9 reduces the S100A9 amyloid formation rate and amyloid quantity. Atomic force microscopy imaging demonstrated the complete absence of long S100A9 amyloid fibrils at increasing concentrations of either POM and the presence of only round-shaped and slightly elongated aggregates. Molecular dynamics simulation revealed that both Nb10 and TiNb9 bind to native S100A9 homo-dimer by forming ionic interactions with the positively charged Lys residue-rich patches on the protein surface. The acrylamide quenching of intrinsic fluorescence showed that POM binding does not perturb the Trp 88 environment. The far and near UV circular dichroism revealed no large-scale perturbation of S100A9 secondary and tertiary structures upon POM binding. These indicate that POM binding involves only local conformational changes in the binding sites. By using intrinsic and 8-anilino-1-naphthalene sulfonate fluorescence titration experiments, we found that POMs bind to S100A9 with a Kd of ca. 2.5 μM. We suggest that the region, including Lys 50 to Lys 54 and characterized by high amyloid propensity, could be the key sequences involved in S1009 amyloid self-assembly. The inhibition and complete hindering of S100A9 amyloid pathways may be used in the therapeutic applications targeting the amyloid-neuroinflammatory cascade in neurodegenerative diseases.
A Pilot Fruit and Vegetable Prescription (FVRx) Program Improves Local Fruit and Vegetable Consumption, Nutrition Knowledge, and Food Purchasing Practices

Fruit and Vegetable Prescription (FVRx) programs rely on diverse community and clinic partnerships to improve food security and fruit and vegetable consumption among medically underserved patient populations. Despite the growth in these programs, little is known about the feasibility or effectiveness of the unique partnerships developed to implement FVRx programs conducted in both community and free safety-net clinic settings. A 6-month nonrandomized controlled trial of an FVRx program was pilot tested with 54 Supplemental Nutrition Assistance Program (SNAP)–eligible adults with diet-related chronic conditions. The intervention combined monthly produce prescriptions for local produce at a farmers market, SNAP-Ed direct nutrition education, and health screenings for low-income adults. Process and outcome evaluations were conducted with respective samples using administrative program data (recruitment, retention, and prescription redemption) and self-administered pre- and postintervention surveys with validated measures on dietary intake, nutrition knowledge and behavior, and food purchasing practices. Descriptive statistical analyses were conducted. The FVRx program retained 77.3% of participants who spent nearly 90% of their prescription dollars. After the intervention, the FVRx group reported significantly increased total intake of fruits and vegetables, knowledge of fresh fruit and vegetable preparation, purchase of fresh fruits and vegetables from a farmers market, and significantly altered food purchasing practices compared with the control group. Community-based nutrition education organizations enhance the feasibility and effectiveness of community and clinic-based FVRx programs for improving low-income adults’ ability to enhance food and nutrition-related behaviors.