scholarly journals Federal Reserve Transparency and Financial Market Forecasts of Short-Term Interest Rates

2004 ◽  
Author(s):  
Eric T. Swanson
Keyword(s):  
Interest Rates ◽  
Financial Market ◽  
Federal Reserve ◽  
Short Term

scholarly journals Importance Of Money And Credit

2011 ◽  
Vol 8 (1) ◽  
Author(s):  
Michael Cosgrove ◽  
Daniel Marsh
Keyword(s):  
Monetary Policy ◽  
Interest Rates ◽  
Federal Reserve ◽  
Rapid Growth ◽  
Credit Crisis ◽  
Short Term ◽  
Demand For Money ◽  
The Stability

The thesis of this paper is that the Federal Reserve could better achieve their goals if they paid more attention to quantity targets of both money and credit. The rapid growth in credit that ended in the credit crisis of 2007 and 2008 might have been avoided had the Federal Reserve attempted to incorporate quantitative credit measures in assessing policy. But their focus on short-term interest rates in conducting monetary policy to the exclusion of credit measures led to inaction on their part. The stability of the demand for money and credit determined by this analysis suggests the Federal Reserve could have taken policy steps early in this cycle jawboning, quantitative and regulatory to temper the credit bubble and potentially avoid the credit crisis.

scholarly journals Why The Quantity Of Money Still Matters

2011 ◽  
Vol 3 (2) ◽  
Author(s):  
Michael Cosgrove ◽  
Daniel Marsh
Keyword(s):  
Interest Rates ◽  
Federal Reserve ◽  
Price Level ◽  
Theory Model ◽  
Conventional Wisdom ◽  
Real Output ◽  
Font Size ◽  
Short Term ◽  
Federal Funds ◽  
Federal Funds Rate

<p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="font-size: 10pt;"><span style="font-family: Times New Roman;">The operating procedure of Federal Reserve policy focuses almost exclusively on interest rates, in particular short term rates such as the federal funds rate. Conventional wisdom today interprets a low federal funds rate as an indicator of an expansionary monetary policy, and a high federal funds rate as indicative of a contractionary policy.</span></span></p><p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="font-size: 10pt;"><span style="font-family: Times New Roman;">&nbsp;</span></span></p><p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="font-size: 10pt;"><span style="font-family: Times New Roman;">Our thesis is that this conventional wisdom is flawed. We develop a quantity theory model to illustrate how changes in the real money supply can impact both the price level and real output. We present data showing that when the Fed slows the rate of growth of the monetary base to approximately the growth rate of GDP, that this slowdown also impacts real variables. However, according to comments, the Federal Reserve pays little attention to the quantity of money.</span></span></p><p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="font-size: 10pt;"><span style="font-family: Times New Roman;">&nbsp;</span></span></p><p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="font-size: 10pt;"><span style="font-family: Times New Roman;">Finally we asked: Since the Federal Reserve pays little attention to the quantity of money, what variables does the FOMC likely consider in deciding to alter the federal funds rate? The answer, perhaps not surprisingly, appears to be variables readily measured and easily related to by the general public &ndash; prices and capacity.</span></span></p>

scholarly journals A Partial Equilibrium Analysis of Current US Monetary Policy with a Prediction

2018 ◽  
Author(s):  
Elliott Middleton
Keyword(s):  
Monetary Policy ◽  
Interest Rates ◽  
Federal Reserve ◽  
Equilibrium Analysis ◽  
Partial Equilibrium ◽  
Postwar Period ◽  
Short Term ◽  
The Us ◽  
Partial Equilibrium Analysis ◽  
Current Mechanism

A partial equilibrium analysis of US credit markets reveals that the Federal Reserve System’s current mechanism for raising short-term interest rates has placed the US short-term markets in a position that is far from apparent equilibria achieved over the postwar period.

Information Uncertainty and Volatility in Financial Stock Markets

2017 ◽  
pp. 207-219
Author(s):  
Jose J Haspa DeLarosiere ◽  
Soren Nielsen
Keyword(s):  
Business Cycles ◽  
Interest Rates ◽  
Financial Market ◽  
Federal Reserve ◽  
Commodity Prices ◽  
Information Uncertainty ◽  
Financial Shocks ◽  
Entire Volume ◽  
Advanced Economies ◽  
The Impact

Rising oil prices, steel prices - as well as the stronger dollar certainly impacted the financial markets during the latter part of May 2016. So also, the expected announcement of higher interest rates in June 2016 by the Federal Reserve. As well as illustrating the impact of financial shocks for emerging economies, this chapter also illustrates the impact of financial shocks for smaller – as well as more advanced economies. Having highlighted through the entire volume, the macroeconomic consequences of the changes and fluctuations of commodity prices – as reflected through the recent global financial market volatilities. This chapter will also focus on the main channels through which commodities price fluctuations affect business cycles in EMEs.

Interest rates calibration with a CIR model

2019 ◽  
Vol 20 (4) ◽  
pp. 370-387 ◽  
Author(s):  
Giuseppe Orlando ◽  
Rosa Maria Mininni ◽  
Michele Bufalo
Keyword(s):  
Interest Rates ◽  
Financial Market ◽  
Short Term ◽  
New Approach ◽  
Cir Model ◽  
Market Data ◽  
Content Type ◽  
Term Structures ◽  
Negative Interest Rates ◽  
Interest Rate Dynamics

Purpose The purpose of this paper is to model interest rates from observed financial market data through a new approach to the Cox–Ingersoll–Ross (CIR) model. This model is popular among financial institutions mainly because it is a rather simple (uni-factorial) and better model than the former Vasicek framework. However, there are a number of issues in describing interest rate dynamics within the CIR framework on which focus should be placed. Therefore, a new methodology has been proposed that allows forecasting future expected interest rates from observed financial market data by preserving the structure of the original CIR model, even with negative interest rates. The performance of the new approach, tested on monthly-recorded interest rates data, provides a good fit to current data for different term structures. Design/methodology/approach To ensure a fitting close to current interest rates, the innovative step in the proposed procedure consists in partitioning the entire available market data sample, usually showing a mixture of probability distributions of the same type, in a suitable number of sub-sample having a normal/gamma distribution. An appropriate translation of market interest rates to positive values has been introduced to overcome the issue of negative/near-to-zero values. Then, the CIR model parameters have been calibrated to the shifted market interest rates and simulated the expected values of interest rates by a Monte Carlo discretization scheme. We have analysed the empirical performance of the proposed methodology for two different monthly-recorded EUR data samples in a money market and a long-term data set, respectively. Findings Better results are shown in terms of the root mean square error when a segmentation of the data sample in normally distributed sub-samples is considered. After assessing the accuracy of the proposed procedure, the implemented algorithm was applied to forecast next-month expected interest rates over a historical period of 12 months (fixed window). Through an error analysis, it was observed that our algorithm provides a better fitting of the predicted expected interest rates to market data than the exponentially weighted moving average model. A further confirmation of the efficiency of the proposed algorithm and of the quality of the calibration of the CIR parameters to the observed market interest rates is given by applying the proposed forecasting technique. Originality/value This paper has the objective of modelling interest rates from observed financial market data through a new approach to the CIR model. This model is popular among financial institutions mainly because it is a rather simple (uni-factorial) and better model than the former Vasicek model (Section 2). However, there are a number of issues in describing short-term interest rate dynamics within the CIR framework on which focus should be placed. A new methodology has been proposed that allows us to forecast future expected short-term interest rates from observed financial market data by preserving the structure of the original CIR model. The performance of the new approach, tested on monthly data, provides a good fit for different term structures. It is shown how the proposed methodology overcomes both the usual challenges (e.g. simulating regime switching, clustered volatility and skewed tails), as well as the new ones added by the current market environment (particularly the need to model a downward trend to negative interest rates).

scholarly journals Quantitative Easing and the U.S. Stock Market: A Decision Tree Analysis

2016 ◽  
Vol 7 (2) ◽  
pp. 135-156
Author(s):  
Ramaprasad Bhar ◽  
A.G. Malliaris ◽  
Mary Malliaris
Keyword(s):  
Financial Crisis ◽  
Stock Market ◽  
Interest Rates ◽  
Federal Reserve ◽  
Quantitative Easing ◽  
Short Term ◽  
Federal Funds ◽  
Monetary Policies ◽  
The U.S

The Financial Crisis of 2007-09 caused the U.S. economy to experience a relatively long recession from December 2007 to June 2009. Both the U.S. government and the Federal Reserve undertook expansive fiscal and monetary policies to minimize both the severity and length of the recession.  Most notably, the Federal Reserve initiated three rounds of unconventional monetary policies known as Quantitative Easing.  These policies were intended to reduce long-term interest rates when the short term federal funds rates had reached the zero lower bound and could not become negative. It was argued that the lowering of longer-term interest rates would help the stock market and thus the wealth of consumers.  This paper investigates this hypothesis and concludes that quantitative easing has contributed to the observed increases in the stock market’s significant recovery since its crash due to the financial crisis

Rising political risks fuel financial market anxieties

2017 ◽  
Keyword(s):  
Interest Rates ◽  
Financial Market ◽  
Federal Reserve ◽  
Donald Trump ◽  
Content Type ◽  
Political Risks ◽  
The World ◽  
Marine Le Pen ◽  
Near Term ◽  
The Impact

Subject Global reflation trade falters as markets question Trump Significance US President Donald Trump warned in a newspaper interview on April 12 that the dollar was getting too strong and said that he would prefer the Federal Reserve to keep interest rates low. His remarks were the latest challenge to the speculative bets that have underpinned surging stock markets since last November's US election. Since mid-March, the benchmark 10-year Treasury yield has fallen by 40 basis points and the dollar has weakened as confidence in Trump’s pro-business policies wanes and inflationary pressures soften across the world. Impacts Investors face greater near-term volatility in sterling assets as the June 8 UK election adds new uncertainty to the Brexit process. The recent volatility in oil prices will continue due to mounting uncertainty about the impact of production cuts by major producers. Euro-dollar volatility will heighten further if Marine Le Pen and Jean-Luc Melenchon both reach the second round of France's election.

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