Investors in Target Date Funds are automatically switched from high risk to low risk assets as their retirements approach. Such funds have become very popular, but our analysis brings into question the rationale for them. Based on both a model with parameters fitted to historical returns and on bootstrap resampling, we…
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48 results for “Target Date Funds”
Target-Date Funds: A State-of-the-Art Review with Policy Applications to Chile's Pension Reformq-fin.PM
This review examines TDFs in Chile's pension reform, recommending dynamic glide paths and diversified benchmarks.
problem Chile's pension system needs to adapt to modern investment strategies.
method Comprehensive review of TDFs, highlighting challenges and opportunities for Chilean regulators and fund managers.
result Dynamic glide paths and diversified benchmarks are recommended for better retirement outcomes.
A declining CVaR glidepath framework for TDF design with Chilean pension system application
problem Designing Target-Date Funds around an explicit return objective while controlling risk
method Propose a framework for designing TDFs with a declining CVaR constraint
result Key feature: conservative evaluation of each glidepath
Investment strategies in occupational pension plans are optimized for non-tradable income risk.
problem Optimizing investment strategies for occupational pension plans in the presence of non-tradable income risk.
method Formulated as a stochastic optimization problem, analyzed in both constant and stochastic volatility environments.
result Random contributions induce the optimal glide path structure, influenced by initial wealth, contributions, and risk aversion.
The paper models SOFR and EFFR dynamics, reconciling diffusive and piecewise paths.
problem Updating interest rate models for SOFR, which is becoming a key benchmark.
method Calibrates a model to SOFR and EFFR futures prices, reconciling diffusive and piecewise paths.
result The model reflects key empirical features of SOFR dynamics and reconciles diffusive and piecewise paths.
Dynamic retirement glidepaths evolve over time based on some measure such as the retiree's funded status or current market valuations. Conversely, static glidepaths are fixed at a starting point and selected under the assumption that they will not change. In practice, new static glidepaths may be derived periodically m…
Exchange Traded Funds (ETFs) have been gaining increasing popularity in the investment community as is evidenced by the high growth both in the number of ETFs and their net assets since 2000. As ETFs are in nature similar to index mutual funds, in this paper we examined if this growing demand for ETFs can be explained …
Model predicts activist fund targets with 78.2% accuracy.
problem Predicting activist fund targets to mitigate risks and inform investments.
method Evaluated 123 model configurations using machine learning techniques.
result Best model achieved AUC-ROC of 0.782.
Reinforcement learning for optimizing retirement plans and target dated funds.
problem Optimizing financial goals through periodic investments and withdrawals.
method G-Learner and GIRL algorithms for goal-based wealth management.
result G-Learner provides a computationally tractable solution for wealth management tasks.
We develop an optimal currency hedging strategy for fund managers who own foreign assets to choose the hedge tenors that maximize their FX carry returns within a liquidity risk constraint. The strategy assumes that the offshore assets are fully hedged with FX forwards. The chosen liquidity risk metric is Cash Flow at R…
We determine the optimal investment strategy in a Black-Scholes financial market to minimize the so-called {\it probability of drawdown}, namely, the probability that the value of an investment portfolio reaches some fixed proportion of its maximum value to date. We assume that the portfolio is subject to a payout that…
Perpetual Futures Pricingq-fin.PR
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.
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.
Variable annuities (VA) are popular insurance products. VAs provides the insured with a guaranteed accumulation rate on their premium at maturity. In addition, the insured may receive extra benefit if returns of underlying funds are high enough. Here we consider a special case of VA with high-water mark feature and Gua…
Estimates growth loss in fund models and proposes a shrinkage method.
problem Estimating growth loss in fund models under frequentist and Bayesian estimation.
method Proposes a shrinkage method to target maximal growth with minimal deviation.
result Empirical evidence shows shrinkage gives a stable estimate closer to growth potential.
RL helps optimize TVS fund composition for volatility control.
problem Optimizing fund composition for target volatility strategy under uncertainty.
method Derive analytical solution for Black-Scholes model, use RL for local volatility model.
result RL agents' performance matches BS strategy in LV model.
Examines climate financing for renewable energy projects using structured funds.
problem Valuation of structured climate financing on diverse renewable energy asset pools.
method Bottom-up Gaussian copula framework with LH++ model for diversification analysis.
result Shows how the mix of indirect and direct RE investments affects the sensitivity of the senior tranche.
Quantization Under the Real-world Measure: Fast and Accurate Valuation of Long-dated Contractsq-fin.CP
This paper provides a methodology for fast and accurate pricing of the long-dated contracts that arise as the building blocks of insurance and pension fund agreements. It applies the recursive marginal quantization (RMQ) and joint recursive marginal quantization (JRMQ) algorithms outside the framework of traditional ri…
Study categorizes mutual funds using natural language processing from unstructured data.
problem Categorizing mutual funds using unstructured data for financial analysis.
method Used natural language processing models to classify mutual funds from their investment strategy descriptions.
result High accuracy in categorizing mutual funds using NLP from unstructured data.
Activists align with large fund preferences for success.
problem Aligning with large fund preferences increases activist success.
method Analyzed previous proxy voting behavior to estimate preferences and correlated them with activist success.
result Campaigns with higher alignment receive more votes and are more successful.
Paper optimizes portfolios for absolute return funds with constraints.
problem Optimizing portfolios with constraints for absolute return funds.
method Stochastic control framework with numerical solution using kernel-based collocation method.
result Leverage is necessary to achieve the target level.
Research funding agencies routinely use a proportion of their total revenues to support internal administration and marketing costs. The ratio of administration to total costs, referred to as the administration ratio, is highly variable and within any single fund depends on many factors including the number and average…
Optimizes fund portfolio updates using linear programming and heuristic search.
problem Efficiently updating mutual fund portfolios with various instruments.
method Linear programming and heuristic search approaches.
result Cost improvements over traditional methods.
In this paper we show how to hedge a zero coupon bond with a smaller amount of initial capital than required by the classical risk neutral paradigm, whose (trivial) hedging strategy does not suggest to invest in the risky assets. Long dated zero coupon bonds we derive, invest first primarily in risky securities and whe…
Funding Liquidity, Debt Tenor Structure, and Creditor's Belief: An Exogenous Dynamic Debt Run Modelq-fin.RM
We propose a unified structural credit risk model incorporating both insolvency and illiquidity risks, in order to investigate how a firm's default probability depends on the liquidity risk associated with its financing structure. We assume the firm finances its risky assets by mainly issuing short- and long-term debt.…
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.
Paper classifies institutions based on credit, debit, and funding adjustment paradigms.
problem Classifying institutions based on credit, debit, and funding adjustment paradigms.
method Mathematical framework based on the principle of invariance.
result Improved solution of principle of invariance equations for accurate metrics calculation.
Optimizes Ethena's yield strategy by controlling stETH and ETH futures positions.
problem Maximizes Ethena's yield while managing price impacts.
method Formulates and solves stochastic control problems for Ethena's yield-generating strategy.
result Explicitly determines optimal control rates for stETH and ETH futures.
This paper studies a continuous-time market where an agent, having specified an investment horizon and a targeted terminal mean return, seeks to minimize the variance of the return. The optimal portfolio of such a problem is called mean-variance efficient à la Markowitz. It is shown that, when the market coefficients a…
New pension design reduces volatility without guarantees.
problem Pension volatility and guarantees issues.
method Split premium, invest in funds, redistribute to smooth volatility.
result Maximizes total accumulated capital at retirement.
Although portfolio management didn't change much during the 40 years after the seminal works of Markowitz and Sharpe, the development of risk budgeting techniques marked an important milestone in the deepening of the relationship between risk and asset management. Risk parity then became a popular financial model of in…
Agent learns to trade currency pairs with improved risk management.
problem Improving systematic FX trading performance with online transfer learning.
method Online inductive transfer learning using feature representation from Gaussian mixture model to a reinforcement learning agent.
result Annualized portfolio information ratio of 0.52, compound return of 9.3%.
We propose a novel approach for analysis of the composition of an equity mutual fund based on the time series decomposition of the price movements of the individual stocks of the fund. The proposed scheme can be applied to check whether the style proclaimed for a mutual fund actually matches with the fund composition. …
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.
Client engineering of XVA in crisis and normality: Restructuring, Mandatory Breaks and Resetsq-fin.PR
The paper analyzes XVA reduction strategies in financial crises using Mandatory Breaks, Restructuring, and Resets.
problem Challenges in client XVA management during crises when continuous collateralization is not feasible.
method Compares multiple trade strategies including Mandatory Breaks, Restructuring, and Resets.
result Resets can be twice as effective as Mandatory Breaks/Restructuring if there is no credit recovery. When recovery is at least 1/3, Mandatory Breaks/Restructuring can be more effective.
An Introduction to Hedge Fundsq-fin.GN
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…
Dynamic-weight AMMs outperform traditional CEX rebalancing in tokenized funds, especially on L2s.
problem Improving asset allocation efficiency in decentralized finance (DeFi) protocols.
method Block-level arbitrage analysis and long-term performance benchmarks on two live pools.
result Dynamic-weight AMMs can achieve performance comparable to or better than traditional CEX rebalancing, especially on Layer 2 (L2) networks.
Study on CEF discount in Bangladesh, finds size and maturity impact, turnover negative.
problem Exploring the discount puzzle in closed-end mutual funds in Bangladesh.
method Fixed effects panel regression with diagnostic tests.
result Fund size and maturity positively impact CEF discount, turnover negatively impacts.
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.
This paper introduces an innovative Bayesian machine learning algorithm to draw interpretable inference on heterogeneous causal effects in the presence of imperfect compliance (e.g., under an irregular assignment mechanism). We show, through Monte Carlo simulations, that the proposed Bayesian Causal Forest with Instrum…
This paper examines the risk-adjusted performance and differential fund flows for socially responsible mutual funds (SRMF). The results show that SRMF rated high on ESG, perform better than lower rated ESG funds during the period of economic crisis. The findings also show that low ESG rated SRMF had higher differential…
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…
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.