Relevant bibliographies by topics / Shifted Lognormal Forward Rates

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Academic literature on the topic 'Shifted Lognormal Forward Rates'

Author: Grafiati
Published: 10 September 2021
Last updated: 11 February 2022

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Journal articles on the topic "Shifted Lognormal Forward Rates"

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DECAMPS, MARC, MARC GOOVAERTS, and WIM SCHOUTENS. "SELF EXCITING THRESHOLD INTEREST RATES MODELS." International Journal of Theoretical and Applied Finance 09, no. 07 (November 2006): 1093–122. http://dx.doi.org/10.1142/s0219024906003937.

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In this paper, we study a new class of tractable diffusions suitable for model's primitives of interest rates. We consider scalar diffusions with scale s′(x) and speed m(x) densities discontinuous at the level x*. We call that family of processes Self Exciting Threshold (SET) diffusions. Following Gorovoi and Linetsky [18], we obtain semi-analytical expressions for the transition density of SET (killed) diffusions. We propose several applications to interest rates modeling. We show that SET short rate processes do not generate arbitrage possibilities and we adapt the HJM procedure to forward rates with discontinuous scale density. We also extend the CEV and the shifted-lognormal LIBOR market models. Finally, the models are calibrated to the US market. SET diffusions can also be used to model stock price, stochastic volatility, credit spread, etc.
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MERCURIO, FABIO. "MODERN LIBOR MARKET MODELS: USING DIFFERENT CURVES FOR PROJECTING RATES AND FOR DISCOUNTING." International Journal of Theoretical and Applied Finance 13, no. 01 (February 2010): 113–37. http://dx.doi.org/10.1142/s021902491000570x.

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We introduce an extended LIBOR market model that is compatible with the current market practice of building different yield curves for different tenors and for discounting. The new paradigm is based on modeling the joint evolution of FRA rates and forward rates belonging to the discount curve. We will start by analyzing the basic lognormal case, then we will add stochastic volatility. The dynamics of FRA rates under different measures will be obtained and closed form formulas for caplets and swaptions derived in the lognormal and Heston (1993) cases.
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DUN, TIM, GEOFF BARTON, and ERIK SCHLÖGL. "SIMULATED SWAPTION DELTA–HEDGING IN THE LOGNORMAL FORWARD LIBOR MODEL." International Journal of Theoretical and Applied Finance 04, no. 04 (August 2001): 677–709. http://dx.doi.org/10.1142/s0219024901001127.

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Alternative approaches to hedging swaptions are explored and tested by simulation. Hedging methods implied by the Black swaption formula are compared with a lognormal forward LIBOR model approach encompassing all the relevant forward rates. The simulation is undertaken within the LIBOR model framework for a range of swaptions and volatility structures. Despite incompatibilities with the model assumptions, the Black method performs equally well as the LIBOR method, yielding very similar distributions for the hedging profit and loss — even at high rehedging frequencies. This result demonstrates the robustness of the Black hedging technique and implies that — being simpler and generally better understood by financial practitioners — it would be the preferred method in practice.
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Goldys, Beniamin. "A note on pricing interest rate derivatives when forward LIBOR rates are lognormal." Finance and Stochastics 1, no. 4 (September 1, 1997): 345–52. http://dx.doi.org/10.1007/s007800050028.

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VAN APPEL, JACQUES, and THOMAS A. MCWALTER. "EFFICIENT LONG-DATED SWAPTION VOLATILITY APPROXIMATION IN THE FORWARD-LIBOR MODEL." International Journal of Theoretical and Applied Finance 21, no. 04 (June 2018): 1850020. http://dx.doi.org/10.1142/s0219024918500206.

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We provide efficient swaption volatility approximations for longer maturities and tenors under the lognormal forward-LIBOR model (LFM). In particular, we approximate the swaption volatility with a mean update of the spanning forward rates. Since the joint distribution of the forward rates is not known under a typical pricing measure, we resort to numerical discretization techniques. More specifically, we approximate the mean forward rates with a multi-dimensional weak order 2.0 Itō–Taylor scheme. The higher-order terms allow us to more accurately capture the state dependence in the drift terms and compute conditional expectations with second-order accuracy. We test our approximations for longer maturities and tenors using a quasi-Monte Carlo (QMC) study and find them to be substantially more effective when compared to the existing approximations, particularly for calibration purposes.
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VAN APPEL, JACQUES, and THOMAS A. MCWALTER. "MOMENT APPROXIMATIONS OF DISPLACED FORWARD-LIBOR RATES WITH APPLICATION TO SWAPTIONS." International Journal of Theoretical and Applied Finance 23, no. 07 (November 2020): 2050046. http://dx.doi.org/10.1142/s0219024920500466.

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We present an algorithm to approximate moments for forward rates under a displaced lognormal forward-LIBOR model (DLFM). Since the joint distribution of rates is unknown, we use a multi-dimensional full weak order 2.0 Ito–Taylor expansion in combination with a second-order Delta method. This more accurately accounts for state dependence in the drift terms, improving upon previous approaches. To verify this improvement we conduct quasi-Monte Carlo simulations. We use the new mean approximation to provide an improved swaption volatility approximation, and compare this to the approaches of Rebonato, Hull–White and Kawai, adapted to price swaptions under the DLFM. Rebonato and Hull–White are found to be the least accurate. While Kawai is the most accurate, it is computationally inefficient. Numerical results show that our approach strikes a balance between accuracy and efficiency.
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7

Scheler, Gabriele. "Logarithmic distributions prove that intrinsic learning is Hebbian." F1000Research 6 (July 25, 2017): 1222. http://dx.doi.org/10.12688/f1000research.12130.1.

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In this paper, we document lognormal distributions for spike rates, synaptic weights and intrinsic excitability (gain) for neurons in various brain areas, such as auditory or visual cortex, hippocampus, cerebellum, striatum, midbrain nuclei. We find a remarkable consistency of heavy-tailed, specifically lognormal, distributions for rates, weights and gains in all brain areas. The difference between strongly recurrent and feed-forward connectivity (cortex vs. striatum and cerebellum), neurotransmitter (GABA (striatum) or glutamate (cortex)) or the level of activation (low in cortex, high in Purkinje cells and midbrain nuclei) turns out to be irrelevant for this feature. Logarithmic scale distribution of weights and gains appears as a functional property that is present everywhere. Secondly, we created a generic neural model to show that Hebbian learning will create and maintain lognormal distributions. We could prove with the model that not only weights, but also intrinsic gains, need to have strong Hebbian learning in order to produce and maintain the experimentally attested distributions. This settles a long-standing question about the type of plasticity exhibited by intrinsic excitability.
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Scheler, Gabriele. "Logarithmic distributions prove that intrinsic learning is Hebbian." F1000Research 6 (October 11, 2017): 1222. http://dx.doi.org/10.12688/f1000research.12130.2.

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In this paper, we present data for the lognormal distributions of spike rates, synaptic weights and intrinsic excitability (gain) for neurons in various brain areas, such as auditory or visual cortex, hippocampus, cerebellum, striatum, midbrain nuclei. We find a remarkable consistency of heavy-tailed, specifically lognormal, distributions for rates, weights and gains in all brain areas examined. The difference between strongly recurrent and feed-forward connectivity (cortex vs. striatum and cerebellum), neurotransmitter (GABA (striatum) or glutamate (cortex)) or the level of activation (low in cortex, high in Purkinje cells and midbrain nuclei) turns out to be irrelevant for this feature. Logarithmic scale distribution of weights and gains appears to be a general, functional property in all cases analyzed. We then created a generic neural model to investigate adaptive learning rules that create and maintain lognormal distributions. We conclusively demonstrate that not only weights, but also intrinsic gains, need to have strong Hebbian learning in order to produce and maintain the experimentally attested distributions. This provides a solution to the long-standing question about the type of plasticity exhibited by intrinsic excitability.
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Kuznetsov, Victor P., Andery S. Skorobogatov, and Vladimir G. Gorgots. "IMPACT OF INDENTOR SLIDING VELOCITY AND LOADING REPETITION FACTOR ON SHEAR STRAIN AND STRUCTURE DISPERSION IN NANOSTRUCTURING BURNISHING." Facta Universitatis, Series: Mechanical Engineering 17, no. 2 (July 26, 2019): 161. http://dx.doi.org/10.22190/fume190330023k.

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The article probes into a relationship of the shear strain intensity and the shear strain rate in the surface layer and the sliding velocity of a spherical indentor and its loading repetition factor. It brings forward an experimental procedure to evaluate the shear strain intensity and rate by analyzing the geometrical parameters of the bulge of plastically edged metal and the thickness of the shifted layer relative to different sliding velocities and feed rates.
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Khripach, Ludmila V., T. D. Knjazeva, S. M. Yudin, S. V. German, and I. E. Zykova. "COMPARATIVE ANALYSIS OF SERUM ANTIBODY RESPONSES TO H.PYLORI AND TO RECOMBINANT CAGA IN THE COHORT OF WORKING-AGE MOSCOW ADULTS." Hygiene and sanitation 97, no. 9 (September 15, 2018): 785–90. http://dx.doi.org/10.18821/0016-9900-2018-97-9-785-790.

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Introduction. Helicobacter pylori (Hр) is a helix-shaped bacterium adapted evolutionary to living in the mucoid of stomach. Considered usually as one of the factors in the development of gastritis, peptic ulcer and gastric cancer, but the opposite opinions were also discussed. The aim of this study was to assess levels of serum antibodies to Hp and recombinant CagA in the cohort of working-age Moscow adults. Methods. Commercial ELISA kits “IFA-Helicobacter IgG”© (ZAO EKOlab, Russia) and “HelicoBest-antibodies”© (ZAO Vector-Best, Russia) were applied for the estimation of serum antibodies to Hp and CagA, correspondingly, in the observed cohort (both gender adults, N=319). Results. 85 % of the human cohort (N=271) had positive rates of IgG-antibodies against complex Hp antigen, with lognormal distribution of IgG titers (median 1:688; Q1 - Q3 1:370 - 1:1223) and cut-off value equal to 1:100. 54 % of the human cohort (N=172) were seropositive to recombinant CagA, with the levels of total serum antibodies (IgM, IgA and IgG) from 23 to 129 elisa units (median 87,9; Q1 - Q3 56,7 - 102,5) and cut-off value equal to 18,5 EU. The distribtion of CagA antibody levels was sharply different from lognormal distribution of IgG titers to complex Hp antigen and had signs of bimodality with the main maximum shifted to the right. In the complete cohort under observation (N=319), the levels of serum antibodies to Hp and CagA were associated with a weak (R=0,217), but highly significant (p=0,00009) positive linkage; human persons, seropositive to both antigens, had no any association between the markers. Discussion. Possible reasons of differences in the shape of distributions of the studied markers are discussed. Taking into account the extraordinary genetic variability of natural Hp isolates, lognormal distribution of antibodies to complex Hp antigen can reflect combinatorial differences in the degree of proximity of Hp antigenic determinants between human persons under observation and the antigenic preparation. Bimodal distribution of antibody levels to individual protein CagA, possibly, reflect genetically determined differences in immunoreactivity inside the observed cohort.
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Dissertations / Theses on the topic "Shifted Lognormal Forward Rates"

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Lopes, Sara Bárbara Dutra. "Real World Economic Scenario Generator." Doctoral thesis, Instituto Superior de Economia e Gestão, 2020. http://hdl.handle.net/10400.5/21442.

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Doutoramento em Matemática Aplicada à Economia e Gestão
Neste trabalho apresentamos uma metodologia para simular a evolução das taxas de juros sob medida de probabilidade real. Mais precisamente, usando o modelo de mercado Shifted Lognormal LIBOR multidimensional e uma especificação do vetor do preço de mercado do risco, explicamos como realizar simulações das taxas de juro futuras, usando o método de Euler-Maruyama com preditor-corretor. A metodologia proposta permite acomodar a presença de taxas de juro negativas, tal como é observado atualmente em vários mercados. Após definir a estrutura livre de default, generalizamos os resultados para incorporar a existência de risco de crédito nos mercados financeiros e desenvolvemos um modelo LIBOR para obrigações com risco de crédito classificadas por ratings. Neste trabalho modelamos diretamente os spreads entre as classificações de ratings de acordo com uma dinâmica estocástica que garante a monotonicidade dos preços dos títulos relativamente às classificações por ratings.
In this work, we present a methodology to simulate the evolution of interest rates under real world probability measure. More precisely, using the multidimensional Shifted Lognormal LIBOR market model and a specification of the market price of risk vector process, we explain how to perform simulations of the real world forward rates in the future, using the Euler-Maruyama scheme with a predictor-corrector strategy. The proposed methodology allows for the presence of negative interest rates as currently observed in many markets. After setting the default-free framework we generalize the results to incorporate the existence of credit risk to our model and develop a LIBOR model for defaultable bonds with credit ratings. We model directly the inter-rating spreads according to a stochastic dynamic that guarantees the monotonicity of bond prices with respect to the credit ratings.
info:eu-repo/semantics/publishedVersion
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