Conditional variance forecasts for long-term stock returns

In this paper, we apply machine learning to forecast the conditional variance of long-term stock returns measured in excess of different benchmarks, considering the short- and long-term interest rate, the earnings-by-price ratio, and the inflation rate. In particular, we apply in a two-step procedure a fully nonparametric local-linear smoother and choose the set of covariates as well as the smoothing parameters via cross-validation. We find that volatility forecastability is much less important at longer horizons regardless of the chosen model and that the homoscedastic historical average of the squared return prediction errors gives an adequate approximation of the unobserved realised conditional variance for both the one-year and five-year horizon

Ranking Risks

Dr. Fischhoff considers the role of government in helping citizens manage risks. He then offers a general procedure for risk ranking and concludes by discussing what can be done with a list of risks

Perceived Risks Versus Actual Risks: Managing Hazards through Negotiation

The author describes what she calls the Expert-Judgment Strategy , finding that, because it discounts lay perceptions of Risk, it interferes with the acceptance of important but Risky technologies

Special Issue “Machine Learning in Insurance”

Learning in Insurance”, which represents a compilation of ten high-quality articles discussing avant-garde developments or introducing new theoretical or practical advances in this field

Comparing Risks Thoughtfully

Dr. Finkel argues that comparing risks is neither impossible nor immoral - but is nonetheless very difficult. He then discusses two major pitfalls of making such comparisons, one commonly cited and one routinely ignored, before sketching a framework for improving them

Credit derivatives, macro risks, and systemic risks

This paper explores some bigger-picture risks associated with credit derivatives. Drawing a distinction between the market's perception of credit and "real credit" as reflected in the formal definition of a credit event, the author examines the well-documented macro drivers of credit generally. ; The author next enumerates frequently cited concerns with credit derivatives: the exceedingly large notional trade in credit default swaps relative to outstanding debt, the increasing involvement of hedge funds in these products, and operational concerns that have surfaced in the past year or two. ; The paper then considers the possibilities of associated systemic risk, looking at the issues of modeling and proper hedging, risk management, and valuation of new and sometimes complex credit derivative instruments. ; Despite the inherent risks involved in credit derivatives, the market for these instruments continues to grow rapidly as people find them practical and beneficial for hedging risk, generating income, and distributing credit risk among a broader institutional base. Evolving market practices and safeguards should help establish a more efficient, transparent marketplace. Whether credit risk is best allocated outside of the traditional financial intermediaries remains an open question.Credit derivatives ; Risk

Risks for Peripheral Arterial Disease in the Elderly with Type 2 Diabetes Mellitus : Their Correlation with High Sensitivity C-reactive Protein and Ankle-brachial Index

The Indonesian elderly population has been projected to increase up to about four-fold inthree decades (1990-2020). As a consequence of this population trend, the increased prevalence ofdegenerative diseases would be inevitable; this would include the prevalence of peripheral arterialdisease.This study aims to identify the correlation of diverse risk factors, either traditional or nontraditional,with the ankle-brachial index scores, and the correlation of novel non-traditional riskfactor, e.i. high sensitive C-reactive protein with the prevalence of perioheral arterial disease in theelderly, age 60-80 years old, with type 2 diabetes mellitus.Among the 146 elderly patients with type 2 diabetes mellitus, and based on measurement ofthe ABI score, approximately 30.9% of them had PAD. Some traditional and non-traditional riskfactors having a significant correlation with the ankle-brachial index score, were age (r = -0.396, p <0.001 for right ABI; r = -0.509, p < 0.001 for left ABI), supine systolic blood pressure (r= -0.268, p =0.012 for right ABI; r = -0.267, p = 0.013 for left ABI), 2-hour post-prandial blood glucose (r= -0.252, p = 0.018 for right ABI), and hsCRP (r = -0.280, p = 0.011 for right ABI; r = -0.402, p <0.001 for left ABI); whereas other risk factors like obesity based on waist circumference and BMI,non-supine systolic blood pressure, fasting blood glucose, HbA1C, duration of diabetes, plasma lipidsdid not show statistically significant different odd ratios. After linear regression test for risk factorshaving significant correlations with ABI, age and hsCRP were found to influence the ABI scores.Based on a case-control study, risk factors which, to some extent, had statistically significant valuesas risk factors, include older age (? 70 years old; OR = 7.737 [CI = 2.515-23.805]; p < 0.001),relatively high supine diastolic blood pressure (? 90 mmHg; OR = 6.882 [CI = 0.789-60.060]; p =0.048), and high concentration of hsCRP (> 3 mg/L; OR = 4.420 [CI = 1.287-15.181]; p = 0.013).Among these statistically significant risk factors, after logistic regression test analysis, only the age ofthe patient appeared to have significant influence on the prevalence of PAD.In conclusion, this study demonstrates a negative correlation between hsCRP and ABI score;and high levels of hsCRP appeared to be a risk factor for PAD. The age of the patient, however,appeared to be the strongest risk factor for PAD

GSE Risks

This article was originally presented as a speech to the St. Louis Society of Financial Analysts, St. Louis, Missouri, January 13, 2005.Government-sponsored enterprises ; Risk