The study proposes a new interest rate model that captures long-term periodicity in U.S. Treasury yields.
arXiv research
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Bayesian model predicts interest rates with short-term accuracy and long-term stability.
We introduce here for the first time the long-term swap rate, characterised as the fair rate of an overnight indexed swap with infinitely many exchanges. Furthermore we analyse the relationship between the long-term swap rate, the long-term yield, see Biagini et al. [2018], Biagini and Härtel [2014], and El Karoui et a…
The optimal strategies for a long-term static investor are studied. Given a portfolio of a stock and a bond, we derive the optimal allocation of the capitols to maximize the expected long-term growth rate of a utility function of the wealth. When the bond has constant interest rate, three models for the underlying stoc…
In this paper, we present own point of view how the unexpected fluctuations of the long-term real interest rate can be explained. We describe a macroeconomic environment by the modification of the fundamental macroeconomic equilibrium model called the IS-LM model. Last but not least, we suggest a possible cooperation b…
Empirical study on long-term discount rates using historical bond prices.
Kernel method estimates long-term effects from short-term data.
This paper analyzes the robust growth rate of leveraged ETFs under uncertain parameters.
Proposes a graph neural network for personalized news recommendation.
MRIF models dynamic user interests at multiple temporal-ranges.
A long user history inevitably reflects the transitions of personal interests over time. The analyses on the user history require the robust sequential model to anticipate the transitions and the decays of user interests. The user history is often modeled by various RNN structures, but the RNN structures in the recomme…
The well-known theorem of Dybvig, Ingersoll and Ross shows that the long zero-coupon rate can never fall. This result, which, although undoubtedly correct, has been regarded by many as surprising, stems from the implicit assumption that the long-term discount function has an exponential tail. We revisit the problem in …
New framework estimates long-term outcomes from short-term data.
Proposes a stochastic model for South African actuarial use.
We employ the Bayesian framework to define a cointegration measure aimed to represent long term relationships between time series. For visualization of these relationships we introduce a dissimilarity matrix and a map based on the Sorting Points Into Neighborhoods (SPIN) technique, which has been previously used to ana…
New ML model predicts long-term power generation at large areas.
Estimates long-term effects from short-term experiments and observational data with unobserved confounders.
This paper studies the long-term growth rate of expected utility from holding a leveraged exchanged-traded fund (LETF), which is a constant proportion portfolio of the reference asset. Working with the power utility function, we develop an analytical approach that employs martingale extraction and involves finding the …
In this paper, we assume an insure is allowed to purchase proportional reinsurance and can invest his or her wealth into the financial market where a savings account, stocks and bonds are available. Different from classical optimal investment and reinsurance problem, this paper studies the insurer's long-term investmen…
The study analyzes macroeconomic factors affecting copper futures volatility and long-term correlation with S&P 500.
The paper develops a valuation framework for GLWB-LTC contracts with Levy dynamics and stochastic interest rates.
The paper proposes a new method to estimate interest rates consistently under both risk-neutral and real-world measures.
The performance of trend following strategies can be ascribed to the difference between long-term and short-term realized variance. We revisit this general result and show that it holds for various definitions of trend strategies. This explains the positive convexity of the aggregate performance of Commodity Trading Ad…
A feature-rich Bitcoin trading assistant using reinforcement learning.
The paper models exchange rate risk premium using mean-reverting dynamics.
The paper analyzes insurance risks using stochastic models.
AIKAE enhances IKAE for long-term time series forecasting.
Certain theoretical aspects of vector autoregression (VAR) as tools to model economic time series are revised, in particular their capacity to include both short term and long term information. The VAR model, in its error correction form, is derived and the permanent-transitory decomposition of factors proposed by Gonz…
Yield curve modeling is an essential problem in finance. In this work, we explore the use of Bayesian statistical methods in conjunction with Nelson-Siegel model. We present the hierarchical Bayesian model for the parameters of the Nelson-Siegel yield function. We implement the MAP estimates via BFGS algorithm in rstan…
Estimating the long-term effects of treatments is of interest in many fields. A common challenge in estimating such treatment effects is that long-term outcomes are unobserved in the time frame needed to make policy decisions. One approach to overcome this missing data problem is to analyze treatments effects on an int…
There are more than eight hundred interest rates published in China bond market every day. Which are the benchmark interest rates that have broad influences on most interest rates is a major concern for economists. In this paper, multi-variable Granger causality test is developed and applied to construct a directed net…
Proposes a bond portfolio solution for managing interest rate risk.
Pricing extremely long-dated liabilities market consistently deals with the decline in liquidity of financial instruments on long maturities. The aim is to quantify the uncertainty of rates up to maturities of a century. We assume that the interest rates follow the affine mean-reverting Vasicek model. We model paramete…
Study examines cross-training neural networks for financial index prediction.
New framework captures long-term decision dependence in online learning.
Paper proposes methods for pricing FX-linked Bermudan options using quantization.
GEAR uses auxiliary data to estimate optimal decisions in studies with limited primary outcomes.
Proposes a new framework for resource-limited recommendation.
A novel approach predicts long-term stock price trends using 2D-convolutional encoders and semantic segmentation.
Study allocates resources to strategic agents while balancing cost and incentives.
New framework for choosing optimal proxy metrics from past experiments.
Study examines cryptocurrency behavior during and after the pandemic.
We present an arbitrage-free non-parametric yield curve prediction model which takes the full (discretized) yield curve as state variable. We believe that absence of arbitrage is an important model feature in case of highly correlated data, as it is the case for interest rates. Furthermore, the model structure allows t…
The purpose of this paper relies on the study of long term affine yield curves modeling. It is inspired by the Ramsey rule of the economic literature, that links discount rate and marginal utility of aggregate optimal consumption. For such a long maturity modelization, the possibility of adjusting preferences to new ec…
Fairness in machine learning has predominantly been studied in static classification settings without concern for how decisions change the underlying population over time. Conventional wisdom suggests that fairness criteria promote the long-term well-being of those groups they aim to protect. We study how static fairne…
TMLE improves IPM estimation for ecological population dynamics.
Model combines long-term and short-term memory using conceptors.
Credibility theory provides tools to obtain better estimates by combining individual data with sample information. We apply the Credibility theory to a Uniform distribution that is used in testing the reliability of forecasting an interest rate for long term horizons. Such empirical exercise is asked by Regulators (CRR…