Common factors, principal components analysis, and the term structure of interest rates

Juneja, Januj

doi:10.1016/j.irfa.2012.07.004

Cited by 16 publications

(6 citation statements)

References 37 publications

(66 reference statements)

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“…up to 0.9848 for Common factor 1 vs "level") to their economic intuition. These findings are line with [2] [3]. [2] find that "level" and "spread" are common factors whereas the "slope" factor is country specific.…”

Section: Yield and Model Factorssupporting

confidence: 83%

“…The economic interpretation of the factors of international term structure models as "level", "spread" and "slope" is in line with[3] [2]. find that "level" and "spread" are highly correlated across countries whereas the "slope" factor is country specific.2 See [13] [15] for literature reviews.…”

mentioning

confidence: 80%

“…[2] finds that "level", "spread" and "steepness" determine a large part of the variation in bond returns from the US, Germany and Japan. [3] studies treasury yields from the US, UK and Germany and concludes that "level" and "slope" govern the most of their variability.…”

Section: Introductionmentioning

confidence: 99%

“…A principal component analysis is applied to changes of yields of 6 months, 2, 5 and 10 years time to maturity. measures for the US and UK, respectively3 . In the absence of arbitrage, the timet prices of an US and UK zero-coupon bond that matures at t τ…”

mentioning

confidence: 99%

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Common Factors in International Bond Returns and a Joint ATSM to Match Them

Gabriel¹

2014

TEL

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The existence of common factors in international bond markets is an important cause for modelling different term structures of interest rates jointly. This paper investigates the common factors of US and UK treasury yields in the period of 1983 to 2012. A principal component analysis motivates the type of joint ATSM for modelling the yield curves of two distinct economies. In sum, two common factors explain 85% of the yield variation and the model factors have a solid economic intuition.

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Section: Yield and Model Factorssupporting

confidence: 83%

mentioning

confidence: 80%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Common Factors in International Bond Returns and a Joint ATSM to Match Them

Gabriel¹

2014

TEL

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“…Study of yield curve behavior has been an import part of financial market research as it provides us important information about the future expectation of growth, inflation, recession, etc. Modeling interest rates for the purposes of pricing of interest rate dependent cash flows and hedging the interest rate risk have been a topic of much interest to actuaries over recent decades (see for example [8], [4], [7] and [1]). These studies demonstrate both similarities and differences in international bond markets.…”

Section: Introductionmentioning

confidence: 99%

On the Risk Factors of the Yield in the Cryptocurrencies Market

Kozubík¹,

Žilina²

2018

Recent Advances in IT, Tourism, Economics, Management and Agriculture

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A cryptocurrencies are considered as digital assets that use strong cryptography to secure financial transactions, control the creation of additional units, and verify the transfer of assets. Bitcoin was released as the first and the most popular cryptocurrency in 2009. Since its release, over 4000 alternative cryptocurrencies have been released. After a period of gradual growth of the Bitcoin value, we were able to observe a dramatically increasing in its value at the beginning of this year. This was followed by a subsequent rapid decline to the value it keeps to this day. A similar development we can, however, observe with other cryptocurrencies. This paper presents the results of an empirical analysis of the nature of the factors that explain changes in yields of the ten most traded cryptocurrencies. Consistent with the analysis of the current currencies yield curves, the principal component method has shown that two or three factors are sufficient to explain most of the yield variation. These results are essential for hedging purposes.

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Empirical analysis of term structure shifts

Barber

2020

J Econ Finan

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Principal component analysis and factor analysis of term structure movements shows that between 80 and 90% of term structure shifts can be explained by a uniform shift that is roughly parallel. In contrast, our analysis of term structure data from 1986 to 2016 reveals that only 57% of the shifts have been uniform. Twist-and butterflytype shifts accounted for 28 and 10%, respectively, of all shifts. Remarkably, these frequency results are roughly the same for uniform and twist shifts determined on a daily, weekly, and monthly basis over the entire sample and over three subperiods. Based on historical data, an investor should expect a uniform shift in the term structure about 57% and a twist 28% of the time. Keywords Term structure shift • Spot rates • Principal component analysis JEL Classification G12 1 Macaulay (1938) originated the concept of duration. Bierwag et al. (1983) provided an excellent survey of the literature. 2 The prices on zero coupon bond, from which the returns were calculated, are based on spot rates implied by in prices of coupon bonds.

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Common factors, principal components analysis, and the term structure of interest rates

Cited by 16 publications

References 37 publications

Common Factors in International Bond Returns and a Joint ATSM to Match Them

Common Factors in International Bond Returns and a Joint ATSM to Match Them

On the Risk Factors of the Yield in the Cryptocurrencies Market

Empirical analysis of term structure shifts

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