A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
The study uses historical revenue data to forecast music catalog cashflows and multipliers.
The study assesses music as an investment asset class using discounted cashflow models.
This paper provides intuition on the relationship of accrual and mark-to-market valuation for cash and forward interest rate trades. Discounted cashflow valuation is compared to spread-based valuation for forward trades, which explains the trader's view on valuation. This is followed by Taylor series approximation for …
Geometric Arbitrage Theory reformulates a generic asset model possibly allowing for arbitrage by packaging all assets and their forwards dynamics into a stochastic principal fibre bundle, with a connection whose parallel transport encodes discounting and portfolio rebalancing, and whose curvature measures, in this geom…
The abstract reviews Markov models in life insurance surplus.
This paper studies the problem of optimal investment in incomplete markets, robust with respect to stopping times. We work on a Brownian motion framework and the stopping times are adapted to the Brownian filtration. Robustness can only be achieved for logartihmic utility, otherwise a cashflow should be added to the in…
The paper addresses pricing interest rate derivatives in markets with volatility uncertainty.
From SA-CCR to RSA-CCR: making SA-CCR self-consistent and appropriately risk-sensitive by cashflow decomposition in a 3-Factor Gaussian Market Model
We introduce a generic model for spouse's pensions. The generic model allows for the modeling of various types of spouse's pensions with payments commencing at the death of the insured. We derive abstract formulas for cashflows and liabilities corresponding to common types of spouse's pensions. We show how the standard…
Deep learning approximates Bermudan option exposures and future values.
In this paper, we study the dual representation for generalized multiple stopping problems, hence the pricing problem of general multiple exercise options. We derive a dual representation which allows for cashflows which are subject to volume constraints modeled by integer valued adapted processes and refraction period…
Paper develops a discounted algorithm for online convex optimization that adapts to unknown discount factors.
Paper introduces non-linear discounting models for default compensation and climate valuation.
Study analyzes how discounts affect train ticket purchases and rescheduling in Switzerland.
We demonstrate a limitation of discounted expected utility, a standard approach for representing the preference to risk when future cost is discounted. Specifically, we provide an example of the preference of a decision maker that appears to be rational but cannot be represented with any discounted expected utility. A …
Proves lower discount rates are needed for future losses.
We consider the valuation of contingent claims with delayed dynamics in a Black&Scholes complete market model. We find a pricing formula that can be decomposed into terms reflecting the market values of the past and the present, showing how the valuation of future cashflows cannot abstract away from the contribution of…
Reinforcement learning (RL) typically defines a discount factor as part of the Markov Decision Process. The discount factor values future rewards by an exponential scheme that leads to theoretical convergence guarantees of the Bellman equation. However, evidence from psychology, economics and neuroscience suggests that…
There is an observed basis between repo discounting, implied from market repo rates, and bond discounting, stripped from the market prices of the underlying bonds. Here, this basis is explained as a convexity effect arising from the decorrelation between the discount rates for derivatives and bonds. Using a Hull-White …
Proposes a new framework for discount models.
Revises derivative pricing post financial crisis by defining a discount rate.
This paper shows how forward rate interpolations are equivalent to discount factor interpolations in yield curve construction.
New RL approach handles non-exponential discounting for sequential decisions.
The valuation process that economic agents undergo for investments with uncertain payoff typically depends on their statistical views on possible future outcomes, their attitudes toward risk, and, of course, the payoff structure itself. Yields vary across different investment opportunities and their interrelations are …
We optimize discounts to maximize influence spread in social networks.
Study optimal portfolio strategies with time-varying discount rates.
The study uses reproducing kernels to model bond discount curves.
A new two-step LSMC method improves game option pricing accuracy.
We show that different rates should be used for borrowing and discount rates, and that the risk-free rate should be used for discounting when assessing and comparing the cost of energy accross diffferent producers and technologies, on the example of photovoltaics. Recent quantitative models using the same rate for borr…
We consider a discounted reward control problem in continuous time stochastic environment where the discount rate might be an unbounded function of the control process. We provide a set of general assumptions to ensure that there exists a smooth classical solution to the corresponding HJB equation. Moreover, some verif…
Framework for pricing waterfall structures using simulation and uncertainty modeling.
New findings reveal discount regularization can be seen as a strong prior, leading to poor performance in unevenly sampled data.
New RL difficulty shown for discounted settings.
UCBVI-γ algorithm minimizes regret in discounted MDPs.
The policy gradient theorem is defined based on an objective with respect to the initial distribution over states. In the discounted case, this results in policies that are optimal for one distribution over initial states, but may not be uniformly optimal for others, no matter where the agent starts from. Furthermore, …
Lower discount factors act as a regularizer in RL, improving performance.
Asset prices contain information about the probability distribution of future states and the stochastic discounting of those states as used by investors. To better understand the challenge in distinguishing investors' beliefs from risk-adjusted discounting, we use Perron-Frobenius Theory to isolate a positive martingal…
In this paper, we study the dividend strategies for a shareholder with non-constant discount rate in a diffusion risk model. We assume that the dividends can only be paid at a bounded rate and restrict ourselves to the Markov strategies. This is a time inconsistent control problem. The extended HJB equation is given an…
Paper proposes a machine learning method to predict sale efficacy.
In this paper we extend the existing literature on xVA along three directions. First, we enhance current BSDE-based xVA frameworks to include initial margin in presence of defaults. Next, we solve the consistency problem that arises when the front-office desk of the bank uses trade-specific discount curves (CSA discoun…
Study improves dividend discount model using VAR process.
Study optimal stopping for group with diverse discount rates using an attitude function.
Study optimal stopping times for multi-dimensional processes with non-exponential discounting.
The paper analyzes optimal dividend and capital injection strategies under time-inconsistent preferences.
Proposes a new method for determining LGD discount rates based on cost of capital.
Paper tackles time inconsistency in portfolio management with stochastic volatility and power utility.
This paper considers the problem of consumption and investment in a financial market within a continuous time stochastic economy. The investor exhibits a change in the discount rate. The investment opportunities are a stock and a riskless account. The market coefficients and discount factor switch according to a finite…
Optimal online linear regression in dynamic environments using discounted Vovk-Azoury-Warmuth forecaster.