How the Federal Funds Rate Affects 10 Year Treasury Bond Yields

2005 ◽  
Author(s):  
Kane Snyder
Keyword(s):  
Bond Yields ◽  
Federal Funds ◽  
Federal Funds Rate ◽  
Treasury Bond

scholarly journals The US Stock Market Leads the Federal Funds Rate and Treasury Bond Yields

PLoS ONE ◽  
2011 ◽  
Vol 6 (8) ◽  
pp. e22794 ◽  
Author(s):  
Kun Guo ◽  
Wei-Xing Zhou ◽  
Si-Wei Cheng ◽  
Didier Sornette
Keyword(s):  
Stock Market ◽  
Bond Yields ◽  
Federal Funds ◽  
Federal Funds Rate ◽  
The Us ◽  
Treasury Bond

scholarly journals The US Stock Market Leads the Federal Funds Rate and Treasury Bond Yields

2011 ◽  
Author(s):  
Kun Guo ◽  
Wei-Xing Zhou ◽  
Si-Wei Cheng ◽  
Didier Sornette
Keyword(s):  
Stock Market ◽  
Bond Yields ◽  
Federal Funds ◽  
Federal Funds Rate ◽  
The Us ◽  
Treasury Bond

Interest-rate causality between the federal funds rate and long-run market interest rates

2019 ◽  
Vol 7 (3) ◽  
pp. 388-401
Author(s):  
Hongkil Kim
Keyword(s):  
Interest Rates ◽  
Causality Test ◽  
Federal Funds ◽  
Federal Funds Rate ◽  
Vector Error Correction ◽  
Long Run ◽  
Empirical Relations ◽  
Treasury Bond ◽  
Short Run ◽  
Error Correction Modeling

This paper investigates empirical relations between the federal funds rate/federal funds future rate and long-run market interest rates, employing a cointegration technique, vector error-correction modeling, and the Granger causality test developed by Toda and Yamamoto (1995). As a result, stable long-run relationships between the federal funds rate and Treasury bond rates are identified in the form of bidirectional causalities that are supportive of the Structuralist position, while the findings indicate unidirectional causalities from the federal funds rate to the Treasury bond rates in the short run. Empirical evidence in this paper also rejects the Horizontalist view that the expected future federal funds rate is relevant to current movements of the long-run interest rates, demonstrating Moore (1991) and his followers’ reverse interpretation on the causality from market rates to the federal funds rate to be inaccurate. An implication of such findings is that the current and the expected future federal funds rate do not have as much exogenous power on long-run market rates as claimed by Horizontalists, and the federal funds rate is, rather, endogenous to market rates for the 2004:2–2008:8 period.

scholarly journals A mixture autoregressive model based on Gaussian and Student’s t-distributions

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Savi Virolainen
Keyword(s):  
Interest Rate ◽  
Autoregressive Model ◽  
Autoregressive Models ◽  
Federal Funds ◽  
Treasury Bill ◽  
Federal Funds Rate ◽  
Empirical Application ◽  
Model Based ◽  
Interest Rate Spread ◽  
Student’S T

Abstract We introduce a new mixture autoregressive model which combines Gaussian and Student’s t mixture components. The model has very attractive properties analogous to the Gaussian and Student’s t mixture autoregressive models, but it is more flexible as it enables to model series which consist of both conditionally homoscedastic Gaussian regimes and conditionally heteroscedastic Student’s t regimes. The usefulness of our model is demonstrated in an empirical application to the monthly U.S. interest rate spread between the 3-month Treasury bill rate and the effective federal funds rate.

Federal-funds-rate volatility and the reserve-maintenance period

1995 ◽  
Vol 4 (2) ◽  
pp. 157-170 ◽  
Author(s):  
David Eagle
Keyword(s):  
Maintenance Period ◽  
Federal Funds ◽  
Federal Funds Rate

scholarly journals Co-integration with score-driven models: an application to US real GDP growth, US inflation rate, and effective federal funds rate

2021 ◽  
pp. 1-21
Author(s):  
Szabolcs Blazsek ◽  
Alvaro Escribano ◽  
Adrian Licht
Keyword(s):  
Inflation Rate ◽  
Predictive Accuracy ◽  
Moving Average ◽  
Impulse Response Functions ◽  
Federal Funds ◽  
Federal Funds Rate ◽  
Vector Autoregressive ◽  
Autoregressive Moving Average Model ◽  
Long Run ◽  
The Us

Abstract Nonlinear co-integration is studied for score-driven models, using a new multivariate dynamic conditional score/generalized autoregressive score model. The model is named t-QVARMA (quasi-vector autoregressive moving average model), which is a location model for the multivariate t-distribution. In t-QVARMA, I(0) and co-integrated I(1) components of the dependent variables are included. For t-QVARMA, the conditions of the maximum likelihood estimator and impulse response functions (IRFs) are presented. A limiting special case of t-QVARMA, named Gaussian-QVARMA, is a Gaussian-VARMA specification with I(0) and I(1) components. As an empirical application, the US real gross domestic product growth, US inflation rate, and effective federal funds rate are studied for the period of 1954 Q3 to 2020 Q2. Statistical performance and predictive accuracy of t-QVARMA are superior to those of Gaussian-VAR. Estimates of the short-run IRF, long-run IRF, and total IRF impacts for the US data are reported.

scholarly journals VARIABEL-VARIABEL PENGGERAK INDEKS HARGA SAHAM SEKTOR PERTANIAN

2020 ◽  
Vol 2019 (1) ◽  
pp. 720-725
Author(s):  
Muhammad Febrian Rizky Ramadhan ◽  
Gama Putra Danu Sohibien
Keyword(s):  
Federal Funds ◽  
Federal Funds Rate ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag

Indeks harga saham sektor pertanian di Indonesia cenderung menurun dari tahun 2009 – 2018 dengan rata-rata pertumbuhan sebesar -0,76 persen per tahun. Apabila tidak terjadi pemulihan harga, penurunan yang terjadi berpotensi menimbulkan sentimen buruk terhadap sektor pertanian dan menurunkan aliran modal masuk terhadap perusahaan-perusahaan yang tercakup dalam sektor tersebut. Dalam upaya memecahkan permasalahan tersebut, dilakukan identifikasi variabel-variabel yang mempengaruhi harga saham sektor pertanian. Adapun variabel yang diduga memiliki pengaruh terhadap harga saham sektor tersebut, yakni nilai tukar rupiah terhadap dolar Amerika Serikat, federal funds rate, harga minyak kelapa sawit, dan volume transaksi saham sektor pertanian. Dengan pemodelan Autoregressive Distributed-lag disimpulkan bahwa, keempat variabel tersebut memiliki pengaruh yang signifikan terhadap indeks harga saham sektor pertanian. Federal Funds Rate dan nilai tukar rupiah memiliki pengaruh negatif terhadap indeks harga saham sektor pertanian, sedangkan variabel lainnya memiliki pengaruh positif. Hasil penelitian ini diharapkan mampu memberikan informasi ke penggiat saham dan pemerintah, agar tidak terjadi kerugian yang besar di periode-periode selanjutnya.

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