The expectation hypothesis of the term structure of very short-term rates: Statistical tests and economic value☆

Corte, Pasquale Della; Sarno, Lucio; Thornton, Daniel L.

doi:10.1016/j.jfineco.2007.08.002

Cited by 94 publications

(27 citation statements)

References 51 publications

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“…Thus we prefer to deal directly with transaction costs setting a realistic value for it, and keeping portfolio weights and bonds as updated as possible by rebalancing them on a monthly basis. For that purpose, we follow Della Corte, Sarno, and Thornton (2008) and Thornton and Valente (2012), and compute the excess return net of transaction costs (rx net t ). This calculation is performed as follows:…”

Section: Economic Measures Of Performancementioning

confidence: 99%

Yield curve forecast combinations based on bond portfolio performance

Caldeira

Moura

Santos

2017

Journal of Forecasting

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We propose an economically motivated forecast combination strategy in which model weights are related to portfolio returns obtained by a given forecast model. An empirical application based on an optimal mean-variance bond portfolio problem is used to highlight the advantages of the proposed approach with respect to combination methods based on statistical measures of forecast accuracy. We compute average net excess returns, standard deviation, and the Sharpe ratio of bond portfolios obtained with nine alternative yield curve specifications, as well as with 12 different forecast combination strategies. Return-based forecast combination schemes clearly outperformed approaches based on statistical measures of forecast accuracy in terms of economic criteria. Moreover, return-based approaches that dynamically select only the model with highest weight each period and discard all other models delivered even better results, evidencing not only the advantages of trimming forecast combinations but also the ability of the proposed approach to detect best-performing models. To analyze the robustness of our results, different levels of risk aversion and a different dataset are considered.

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Section: Economic Measures Of Performancementioning

confidence: 99%

Yield curve forecast combinations based on bond portfolio performance

Caldeira

Moura

Santos

2017

Journal of Forecasting

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“…Fleming, Kirby, and Ostdiek (2001) investigate volatility timing in equity markets. Della-Corte, Sarno, and Thornton (2008) and DellaCorte, Sarno, and Tsiakas (2009) apply the approach to short-term interest rates and predictability in the foreign exchange market. Thornton and Valente (2012) investigate the economic value of long-term forward interest rate information to predict bond returns.…”

Section: However It Is Unclearmentioning

confidence: 99%

Economic Valuation of Liquidity Timing

Karstanje

Sojli²,

Tham

et al. 2013

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract This paper conducts a horse-race of different liquidity proxies using dynamic asset allocation strategies to evaluate the short-horizon predictive ability of liquidity on monthly stock returns. We assess the economic value of the out-of-sample power of empirical models based on different liquidity measures and find three key results: liquidity timing leads to tangible economic gains; a risk-averse investor will pay a high performance fee to switch from a dynamic portfolio strategy based on various liquidity measures to one that conditions on the Zeros measure (Lesmond, Ogden, and Trzcinka, 1999); the Zeros measure outperforms other liquidity measures because of its robustness in extreme market conditions. These findings are stable over time and robust to controlling for existing market return predictors or considering risk-adjusted returns. Terms of use: Documents inJEL classification: G11; G12; G17.

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“…The risk premium compensates investors for the higher degree of market risk associated with holding longer-term assets. The empirical evidence against the EH is overwhelming (e.g., Campbell and Shiller, 1991;Sarno, et al, 2007, andDella Corte, et al, 2008, and the references cited therein). 13 As was the case with inflation targeting, the Reserve bank of New Zealand took the lead.…”

Section: Conventional Wisdom Sees Central Banks Influencing Longer-tementioning

confidence: 99%

How Did We Get to Inflation Targeting and Where Do We Go Now? A Perspective from the U.S. Experience

Thornton

2009

SSRN Journal

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This paper advances the hypothesis that the transition from there-is-little-central-banks-can-do-tocontrol-inflation to inflation targeting occurred because central banks, especially the Federal Reserve, demonstrated that central banks can control inflation rather than a consequence of marked improvement in the professions understanding of how monetary policy controls inflation. As consequence, monetary theorists and central bankers have returned to a Phillips curve framework for formulating and evaluating the monetary policy. I suggest that the return to the Phillips curve framework endangers the continued effectiveness, and perhaps even viability, of inflation targeting, recommend three steps that inflation-targeting central banks should take to preserve and strengthen inflation targeting. JEL Codes: E52, E58

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The expectation hypothesis of the term structure of very short-term rates: Statistical tests and economic value☆

Cited by 94 publications

References 51 publications

Yield curve forecast combinations based on bond portfolio performance

Yield curve forecast combinations based on bond portfolio performance

Economic Valuation of Liquidity Timing

How Did We Get to Inflation Targeting and Where Do We Go Now? A Perspective from the U.S. Experience

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