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arXiv research

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.

168,694 papers · 148 categories

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48 results for fund replication

Study cash-flow forecasting for derivatives, aligning with replication strategy and addressing timing frictions.

problem Inconsistencies in cash-flow forecasting under different measures and stochastic payment times.
method Use discounting sensitivities (funding-curve hedge ratios) for replication and propose a liquidity valuation adjustment.
result Aligns forecasting with replication strategy and avoids measure-mixing issues.

In this note we sketch an initial tentative approach to funding costs analysis and management for contracts with bilateral counterparty risk in a simplified setting. We depart from the existing literature by analyzing the issue of funding costs and benefits under the assumption that the associated risks cannot be hedge…

2014-10-08abs ↗pdf ↗

The paper explores perpetual contracts in a financial market without arbitrage.

problem Modeling perpetual contracts in a continuous-time financial market.
method Derive model-free and semi-robust expressions for perpetual contracts' funding and discount rates.
result Explicit replication strategies for perpetual contracts are derived, relating them to traditional financial instruments.

We develop a framework for computing the total valuation adjustment (XVA) of a European claim accounting for funding costs, counterparty credit risk, and collateralization. Based on no-arbitrage arguments, we derive backward stochastic differential equations (BSDEs) associated with the replicating portfolios of long an…

2016-08-09abs ↗pdf ↗

In this article, we combine replication pricing with expectation pricing for derivative trades that are partially collateralized by cash. The derivatives are replicated by underlying assets and cash, using repurchasing agreement (repo) and margining, which incur funding costs. We derive a partial differential equation …

2013-02-03abs ↗pdf ↗

Study optimizes funding rates for cryptocurrency perpetual futures to maintain price alignment.

problem Maintaining alignment between perpetual future prices and target values in cryptocurrency markets.
method Developed replicating portfolios and path-dependent funding rates using path-dependent infinite-horizon BSDEs and arbitrage pricing theory.
result Appropriate funding rate design can keep perpetual future prices aligned with target values.

The Mutual Fund Theorem (MFT) is considered in a general semimartingale financial market S with a finite time horizon T, where agents maximize expected utility of terminal wealth. It is established that: 1) Let N be the wealth process of the numéraire portfolio (i.e. the optimal portfolio for the log utility). If any p…

2007-10-10abs ↗pdf ↗

This paper investigates market-consistent valuation of insurance liabilities in the context of, for instance, Solvency II and to some extent IFRS 4. We propose an explicit and consistent framework for the valuation of insurance liabilities which incorporates the Solvency II approach as a special case. The proposed fram…

2010-12-30abs ↗pdf ↗

FedSight AI predicts federal funds rate using LLMs and multi-agent reasoning.

problem Predicting Federal Open Market Committee's decisions on federal funds rate.
method Multi-agent framework with large language models, structured and unstructured inputs, and CoD extension for efficient reasoning.
result Achieved 93.75% accuracy and 93.33% stability in predicting FOMC outcomes.

Credit (CVA), Debit (DVA) and Funding Valuation Adjustments (FVA) are now familiar valuation adjustments made to the value of a portfolio of derivatives to account for credit risks and funding costs. However, recent changes in the regulatory regime and the increases in regulatory capital requirements has led many banks…

2014-05-02abs ↗pdf ↗

Derives pricing formulas for perpetual futures contracts.

problem Ensuring fair pricing of perpetual futures contracts without expiration.
method Explicit expressions derived for various types of perpetual contracts, including linear, inverse, and quantos futures.
result Futures price is the risk-neutral expectation of the spot price sampled at a random time reflecting funding payments.

The paper prices and replicates various financial contracts on a risky asset with stochastic volatility and jumps.

problem Pricing and replicating financial contracts on assets with stochastic volatility and jumps.
method Develops pricing and hedging formulas for various financial contracts, independent of the volatility process dynamics.
result Pricing and hedging formulas for financial contracts are derived without dependence on the volatility process dynamics.

We discuss and clarify the XVA modelling framework specified in the paper "MVA by replication and regression" (Risk Magazine, May 2015) for including bilateral credit risk and funding costs in derivative pricing, and in doing so we rectify two key errors in the valuation adjustments accounting for costs of capital and …

2018-07-28abs ↗pdf ↗

The paper prices long-term options with a reflecting barrier model.

problem Pricing long-term options with asset price limits.
method Model asset price as geometric Brownian motion with a lower reflecting barrier, pricing options using compound options.
result Option prices can be determined using standard risk-neutral arguments, and hedging strategies are available.

Initial margin requirements are becoming an increasingly common feature of derivative markets. However, while the valuation of derivatives under collateralisation (Piterbarg 2010, Piterbarg2012), under counterparty risk with unsecured funding costs (FVA) (Burgard2011, Burgard2011, Burgard2013) and in the presence of re…

2014-05-02abs ↗pdf ↗

Quantum optimization for portfolios with risk and diversification constraints.

problem Implementing complex constraints in portfolio optimization for financial applications.
method Transformed portfolio optimization into a quadratic binary optimization problem suitable for quantum annealers.
result Demonstrated practical implementation of daily constraints in real data using quantum processors.

We present an approach to market-consistent multi-period valuation of insurance liability cash flows based on a two-stage valuation procedure. First, a portfolio of traded financial instrument aimed at replicating the liability cash flow is fixed. Then the residual cash flow is managed by repeated one-period replicatio…

2016-07-14abs ↗pdf ↗

Study uses deep learning for pairs trading in Polish equities, achieving profits in 2017-2019.

problem Statistical arbitrage in Polish equities market using traditional methods.
method Deep learning (LSTMs) for asset replication, PCA for risk factor analysis, Ornstein Uhlenbeck process for residual modeling.
result Deep learning methods, especially LSTMs, show promise for profitable trading in Polish equities.

Complex contagion model explains financial fire sales through continuous asset prices.

problem Modeling financial fire sales with a continuum of asset prices.
method Developed a threshold model of continuous-state cascades using real values for asset prices.
result Discretization approach accurately replicates the distribution of defaulted banks and asset prices.
Ponzi Fundsq-fin.GN

Funds inflate their returns due to price pressure, leading to wealth reallocation and market crashes.

problem Funds inflate their returns due to price pressure, leading to wealth reallocation and market crashes.
method Decomposed fund returns into price pressure and fundamental components, and identified the impact of price chasing on fund flows.
result Funds' self-inflated returns lead to wealth reallocation and market crashes, and can be predicted by fund illiquidity.

This report was originally written as an industry white paper on Hedge Funds. This paper gives an overview to Hedge Funds, with a focus on risk management issues. We define and explain the general characteristics of Hedge Funds, their main investment strategies and the risk models employed. We address the problems in H…

2009-04-17abs ↗pdf ↗

Deep learning models predict mutual funds' performance better than traditional methods.

problem Predicting mutual funds' performance accurately.
method Deep learning models (LSTM, GRUs) trained with Bayesian optimization and ensemble methods.
result Ensemble method of LSTM and GRUs achieves the highest accuracy in forecasting mutual funds' Sharpe ratios.

This paper optimizes perpetual contract liquidity by accounting for funding rates.

problem Optimal liquidity provision for perpetual contracts with stochastic funding rates.
method Formulated a control problem, solved with a HJB scheme, and calibrated on real data.
result Funding-aware market making improves performance and reduces inventory risk.

Study finds Indian mutual funds adjust cash holdings based on inflows, impacting stock purchases.

problem Active liquidity management by mutual funds in India.
method Examined cash holdings and stock purchases of Indian equity mutual funds.
result Funds with active liquidity choices outperform, highlighting the importance of this strategy.

Blockchain protocol improves traditional mutual funds with performance fees and investor protection.

problem Operational issues and performance fees in traditional mutual funds.
method Developed a blockchain protocol that integrates features of mutual funds and hedge funds.
result Blockchain can simplify performance fee calculations and protect investors.

Study uses machine learning and PolyModel to improve hedge fund performance.

problem Improving hedge fund investment performance with machine learning.
method Integration of machine learning techniques, PolyModel feature selection, and analysis of fund size.
result Machine learning enhances cumulative returns but increases annual volatility.

In this paper we investigate the relationship between Funding Value Adjustment (FVA) and Net Stable Funding Ratio (NSFR). FVA is defined in a consistent way with NSFR such that the new framework of FVA monitors the costs due to keeping NSFR at an acceptable level, as well. In addition, the problem of choosing the optim…

2017-01-01abs ↗pdf ↗

Study examines Indian equity mutual funds' investment style and risk-shifting.

problem Understanding how Indian equity mutual funds' investment styles affect their returns.
method Estimating size and style beta coefficients, identifying breakpoints, analyzing investment styles, and assessing risk-shifting intensity.
result Funds can enhance returns by shifting to high-return styles like Small Value and Small Blend.

Sparse portfolio strategy from mutual funds' favorite stocks in China A share market.

problem Building a sparse portfolio from mutual funds' favorite stocks in a market with limited fund information.
method Analyzed mutual fund favorite stocks, used portfolio optimizer with constraints, and compared different methods.
result Sparse portfolios consistently outperform the benchmark index 930950.CSI.