activity
20132026
most citedStochastic Modelling with Randomised Markov Bridges

6 citations · 6 across the 6 of their papers we have counts for

collaborators

6 papers

q-fin.MF2026

Minimizing Benchmark-Relative Drawdown Duration via Occupation Time Penalization

Jun Sekine, Marcus Wunsch

We study a continuous-time portfolio optimization problem in which an investor is evaluated relative to a non-replicable benchmark and seeks to control the persistence of benchmark…

math.PR2023

Backward stochastic difference equations on lattices with application to market equilibrium analysis

Masaaki Fukasawa, Takashi Sato, Jun Sekine

We study backward stochastic difference equations (BSΔE) driven by a d-dimensional stochastic process on a lattice whose increments have only d + 1 possible values that generates t…

q-fin.MF2020

Notes on Backward Stochastic Differential Equations for Computing XVA

Jun Sekine, Akihiro Tanaka

The X-valuation adjustment (XVA) problem, which is a recent topic in mathematical finance, is considered and analyzed. First, the basic properties of backward stochastic differenti…

math.PR2014★ 6 cited

Stochastic Modelling with Randomised Markov Bridges

Andrea Macrina, Jun Sekine

We consider the filtering problem of estimating a hidden random variable by noisy observations. The noisy observation process is constructed by a randomised Markov bridge (RMB)…

q-fin.PR2014

A One-Factor Conditionally Linear Commodity Pricing Model under Partial Information

Takashi Kato, Jun Sekine, Hiromitsu Yamamoto

A one-factor asset pricing model with an Ornstein--Uhlenbeck process as its state variable is studied under partial information: the mean-reverting level and the mean-reverting spe…

q-fin.CP2013

Order Estimates for the Exact Lugannani-Rice Expansion

Takashi Kato, Jun Sekine, Kenichi Yoshikawa

The Lugannani-Rice formula is a saddlepoint approximation method for estimating the tail probability distribution function, which was originally studied for the sum of independent…