Hedging a derivative security with non-risk-neutral number of shares leads to portfolio profit or loss. Unlike in the Black-Scholes world, the net present value of all future cash flows till maturity is no longer deterministic, and basis risk may be present at any time. The key object of our analysis is probability distribution of future P&L conditioned on the present value of the underlying. W...

Abstract The conditional probability formula is supposed to reflect the correct updating of assignments when new information incorporated. Starting from a non-atomic measure, it proved that provides only transformed measure satisfying “minimum requirement” relational assumption. This result applies standard Bayesian parametric model.

Video streaming technique is widely used in the Internet with the development of access networks. Although some techniques such as Forward Error Correction or Content Distribution Network are effective for video streaming services, they are not sufficient in the case that streams are suffered from heavy packet loss. For this problem, we propose a novel error correction method called “ECLIPSE: E...

Estimating the cell loss probability in an ATM multiplexer is one of the most important problems concerning congestion control and bandwidth management in an ATM-based BISDN. We propose a new approach to estimating the cell loss probability in an ATM multiplexer. We use the Markov modulated deterministic process (MMDP) to approximate the actual arrival process and then model the ATM multiplexer...

This paper studies factors affecting non-life insurance demand in Lithuania. The study identified variables that are important analyzing the for and were applied estimating multivariate VAR, Classical Granger, Toda-Yamamoto causalities. Lithuania’s case showed three significant causal relationships: positive - between inflation loss probability, negative density short-term interest rate. Loss p...

Softmax GAN is a novel variant of Generative Adversarial Network (GAN). The key idea of Softmax GAN is to replace the classification loss in the original GAN with a softmax cross-entropy loss in the sample space of one single batch. In the adversarial learning of N real training samples and M generated samples, the target of discriminator training is to distribute all the probability mass to th...

The objective of this paper is to understand the drivers of consumer choice under risk. We disentangle and study the relative importance of di erent preferences in explaining the high risk premia consumers pay for actuarially unfair insurance. Empirical and behavioral research on insurance is at odds on whether diminishing returns (curvature of the utility function), or loss aversion and non-li...

Abstract Previous research on moral dilemmas has mainly focused decisions made under conditions of probabilistic certainty. We investigated the impact uncertainty preference for action (killing one individual to save five people) and inaction (saving but allowing people die) in dilemmas. reported two experimental studies that varied framing (gain vs loss), levels risk (probability gain loss) am...