Forecasting high-frequency excess stock returns via data analytics and machine learning

Borsa Istanbul introduced data analytics to present additional information about its market conditions. We examine whether this product can be utilized via various machine learning methods to predict intraday excess returns. Accordingly, these analytics provide significant prediction ratios above 50% with ideal profit ratios that can reach up to 33%. Among all the methods considered, XGBoost (logistic regression) performs better in predicting excess returns in the long-term analysis (short-term analysis). Results provide evidence for the benefits of both the analytics and the machine learning methods and raise further discussion on the semistrong market efficiency.     

Machine learning in individual claims reserving

Machine learning techniques make it feasible to calculate claims reserves on individual claims data. This paper illustrates how these techniques can be used by providing an explicit example in individual claims reserving.     

The Asymmetric path of Economic Long Waves

The purpose of this paper is to analyze the pattern and behavior of Economic Long Waves over time, using the long-wave chronologies of two driving economies, the USA and the UK. The statistical evidence seems in general to support the hypothesis that Long Waves are not symmetric and their regularity is based on longer periods of upwave than downwave (contraction-skewed), which implies a negative asymmetric path of these waves over time.     

Feature selection methods involving support vector machines for prediction of insolvency in non‐life insurance companies

We propose two novel approaches for feature selection and ranking tasks based on simulated annealing (SA) and Walsh analysis, which use a support vector machine as an underlying classifier. These approaches are inspired by one of the key problems in the insurance sector: predicting the insolvency of a non‐life insurance company. This prediction is based on accounting ratios, which measure the health of the companies. The approaches proposed provide a set of ratios (the SA approach) and a ranking of the ratios (the Walsh analysis ranking) that would allow a decision about the financial state of each company studied. The proposed feature selection methods are applied to the prediction the insolvency of several Spanish non‐life insurance companies, yielding state‐of‐the‐art results in the tests performed. Copyright © 2005 John Wiley & Sons, Ltd.     

Economic burden of hospital malnutrition and the cost–benefit of supplemental parenteral nutrition in critically ill patients in Latin America

Abstract

Aim: Disease-related malnutrition (DRM) is a prevalent condition that significantly increases the risk of adverse outcomes in hospitalized patients, particularly those with critical illness. Limited data is available on the economic burden of DRM and the cost–benefit of nutrition therapy in high-risk populations in Latin America. The aims of the present study were to estimate the economic burden of DRM and evaluate the cost–benefit of supplemental parenteral nutrition (SPN) in critically ill patients who fail to receive adequate nutrient intake from enteral nutrition (EN) in Latin America.

Methods: Country-specific cost and prevalence data from eight Latin American countries and clinical data from studies evaluating outcomes in patients with DRM were used to estimate the costs associated with DRM in public hospitals. A deterministic decision model based on clinical outcomes from a randomized controlled study and country-specific cost data were developed to examine the cost–benefit of administering SPN to critically ill adults who fail to reach ≥60% of the calculated energy target with EN.

Results: The estimated annual economic burden of DRM in public hospitals in Latin America is $10.19 billion (range, $8.44 billion–$11.72 billion). Critically ill patients account for a disproportionate share of the costs, with a 6.5-fold higher average cost per patient compared with those in the ward ($5488.35 vs. $839.76). Model-derived estimates for clinical outcomes and resource utilization showed that administration of SPN to critically ill patients who fail to receive the targeted energy delivery with EN would result in an annual cost reduction of $10.2 million compared with continued administration of EN alone.

Limitations: The cost calculation was limited to the average daily cost of stay and antibiotic use. The costs associated with other common complications of DRM, such as prolonged duration of mechanical ventilation or more frequent readmission, are unknown.

Conclusions: DRM imposes a substantial economic burden on Latin American countries, with critically ill patients accounting for a disproportionate share of costs. Cost–benefit analysis suggests that both improved clinical outcomes and significant cost savings can be achieved through the adoption of SPN as a therapeutic strategy in critically ill patients who fail to receive adequate nutrient intake from EN.     

Risk‐Adjusted Measures of Value Creation in Financial Institutions

Abstract Many financial institutions assess portfolio decisions using RAROC, the ratio of expected return to risk (or ‘economic’) capital. We use asset pricing theory to determine the appropriate hurdle rate, finding that this varies with the skewness of asset returns. We quantify this discrepancy under a range of assumptions showing that the RAROC hurdle rate differs substantially, being higher by a factor of five or more for equity which has a right skew compared to debt which has a pronounced left skew, and also between different qualities of debt exposure. We discuss implications for both financial institution risk management and supervision.     

Size,time-varying beta,and conditional heteroscedasticity in UK stock returns

The purpose of this study is to examine the relationship between firm size and time-varying betas of UK stocks. We extend the Schwert and Seguin (1990)(Journal of Finance 45, 1120–1155) methodology by explicitly modeling conditional heteroscedasticity in the market model residual returns. Our results show that the time-varying coefficient is not statistically significant for both small and large firm stock indexes. We also find that accounting for GARCH effects in the Schwert-Seguin market model yields beta estimates that are markedly differently from those when conditional heteroscedasticity is ignored. Event studies that ignore conditional heteroscedasticity may bias the abnormal returns of small and large firms, thereby leading to a different conclusion regarding the significance of an information event.     

Does the Welfare State Destroy the Family? Evidence from OECD Member Countries

We study the effect of the size of the welfare state on demographic trends in OECD member countries. Exploiting exogenous variation in public social spending, due to varying degrees of political fractionalization (i.e., the number of relevant parties involved in the legislative process), we show that an expansion in the welfare state increases fertility, marriage, and divorce rates with a quantitatively stronger effect on the marriage rate. We conclude that the welfare state supports family formation in the aggregate. Further, we find that the welfare state decouples marriage and fertility, and therefore alters the organization of the average family.