A. V. Nagaev

761 total citations
53 papers, 486 citations indexed

About

A. V. Nagaev is a scholar working on Finance, Management Science and Operations Research and Mathematical Physics. According to data from OpenAlex, A. V. Nagaev has authored 53 papers receiving a total of 486 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Finance, 16 papers in Management Science and Operations Research and 14 papers in Mathematical Physics. Recurrent topics in A. V. Nagaev's work include Probability and Risk Models (15 papers), Stochastic processes and financial applications (15 papers) and Stochastic processes and statistical mechanics (9 papers). A. V. Nagaev is often cited by papers focused on Probability and Risk Models (15 papers), Stochastic processes and financial applications (15 papers) and Stochastic processes and statistical mechanics (9 papers). A. V. Nagaev collaborates with scholars based in Poland, Uzbekistan and Austria. A. V. Nagaev's co-authors include Thomas Mikosch, A. N. Startsev, Yu. I. Davydov, S.M. Shkol'nik, Г. Ш. Цициашвили, Robert M. Kunst, Adam Jakubowski, Abram Kagan and Anne Philippe and has published in prestigious journals such as Journal of Applied Probability, Journal of Multivariate Analysis and Advances in Applied Probability.

In The Last Decade

A. V. Nagaev

46 papers receiving 426 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
A. V. Nagaev Poland	10	262	231	190	144	90	53	486
Konstantin Borovkov Australia	15	243 0.9×	338 1.5×	242 1.3×	245 1.7×	100 1.1×	83	728
B. A. Rogozin Russia	17	306 1.2×	410 1.8×	283 1.5×	153 1.1×	79 0.9×	46	720
Philip S. Griffin United States	14	305 1.2×	290 1.3×	215 1.1×	179 1.2×	68 0.8×	46	511
Bengt Von Bahr Sweden	11	211 0.8×	252 1.1×	158 0.8×	250 1.7×	119 1.3×	12	663
Edward Omey Belgium	16	441 1.7×	259 1.1×	327 1.7×	302 2.1×	99 1.1×	84	852
Antónia Földes Hungary	15	144 0.5×	293 1.3×	218 1.1×	328 2.3×	127 1.4×	60	665
A. de Acosta United States	17	286 1.1×	429 1.9×	382 2.0×	255 1.8×	70 0.8×	34	801
Denis Denisov United Kingdom	9	200 0.8×	208 0.9×	114 0.6×	127 0.9×	57 0.6×	55	386
Olof Thorin Sweden	11	246 0.9×	67 0.3×	162 0.9×	189 1.3×	82 0.9×	21	408
Gerold Alsmeyer Germany	14	196 0.7×	346 1.5×	172 0.9×	162 1.1×	89 1.0×	59	482

Countries citing papers authored by A. V. Nagaev

Since Specialization

Citations

This map shows the geographic impact of A. V. Nagaev's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by A. V. Nagaev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. V. Nagaev more than expected).

Fields of papers citing papers by A. V. Nagaev

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by A. V. Nagaev. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by A. V. Nagaev. The network helps show where A. V. Nagaev may publish in the future.

Co-authorship network of co-authors of A. V. Nagaev

This figure shows the co-authorship network connecting the top 25 collaborators of A. V. Nagaev. A scholar is included among the top collaborators of A. V. Nagaev based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with A. V. Nagaev. A. V. Nagaev is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Davydov, Yu. I., A. V. Nagaev, & Anne Philippe. (2010). On the peeling procedure applied to a Poisson point process. Advances in Applied Probability. 42(3). 620–630.

Kagan, Abram & A. V. Nagaev. (2008). A Lemma on Stochastic Majorization and Properties of the Student Distribution. Theory of Probability and Its Applications. 52(1). 160–164. 1 indexed citations

Nagaev, A. V., et al.. (2005). A Diffusion Approximation for the Riskless Profit Under Selling of Discrete Time Call Options. Non-identically Distributed Jumps. Econstor (Econstor). 3 indexed citations

Nagaev, A. V., et al.. (2005). A Diffusion Approximation to the Markov Chains Model of the Financial Market and the Expected Riskless Profit Under Selling of Call and Put Options. Econstor (Econstor). 4 indexed citations

Nagaev, A. V., et al.. (2004). Local large deviation theorem for sums of i.i.d. random vectors when the Cramér condition holds in the whole space. 1 indexed citations

Davydov, Yu. I. & A. V. Nagaev. (2004). On the role played by extreme summands when a sum of independent and identically distributed random vectors is asymptotically α-stable. Journal of Applied Probability. 41(2). 437–454. 1 indexed citations

Nagaev, A. V.. (2003). Asymptotic properties of stable densities and the asymmetric large deviation problems. Statistics & Probability Letters. 61(4). 429–438. 2 indexed citations

Nagaev, A. V.. (2003). Limit theorems and testing hypotheses on Markov chains. Discrete Mathematics and Applications. 13(6). 1 indexed citations

Davydov, Yu. I. & A. V. Nagaev. (2002). On Two Aproaches to Approximation of Multidimensional Stable Laws. Journal of Multivariate Analysis. 82(1). 210–239. 11 indexed citations

10.

Nagaev, A. V.. (2002). An Asymptotic Formula for the Neyman-Pearson Risk in Discriminating Between Two Markov Chains. Journal of Mathematical Sciences. 111(3). 3582–3591. 1 indexed citations

11.

Nagaev, A. V.. (2001). An asymptotic formula for the Bayes risk in discriminating between two Markov chains. Journal of Applied Probability. 38(A). 131–141. 2 indexed citations

12.

Nagaev, A. V.. (2001). An asymptotic formula for the Bayes risk in discriminating between two Markov chains. Journal of Applied Probability. 38(A). 131–141. 1 indexed citations

13.

Nagaev, A. V.. (1999). Cramer Large Deviations when the Extreme Conjugate Distribution is Heavy-tailed. Theory of Probability and Its Applications. 43(3). 405–421. 10 indexed citations

14.

Nagaev, A. V., et al.. (1998). Multidimensional Limit Theorems Allowing Large Deviations for Densities of Regular Variation. Journal of Multivariate Analysis. 67(2). 385–397. 2 indexed citations

15.

Nagaev, A. V.. (1998). Large deviations for sums of lattice random variables under the Cramer conditions. Discrete Mathematics and Applications. 8(4). 5 indexed citations

16.

Jakubowski, Adam, et al.. (1997). Large deviation probabilities for sums of heavy-tailed dependent random vectors. Communications in Statistics Stochastic Models. 13(4). 647–660. 2 indexed citations

17.

Nagaev, A. V.. (1995). Some properties of convex hulls generated by homogeneous Poisson point processes in an unbounded convex domain. Annals of the Institute of Statistical Mathematics. 47(1). 21–29. 9 indexed citations

18.

Nagaev, A. V.. (1987). On a Boundary Problem for a Nonrecurrent Random Walk. Theory of Probability and Its Applications. 31(2). 313–317.

19.

Nagaev, A. V. & S.M. Shkol'nik. (1985). A family of probability distributions. Mathematical Notes. 37(4). 328–330. 2 indexed citations

20.

Nagaev, A. V.. (1971). Limit Distribution of the Extreme Terms of a Variational Series under Conditions of Large Deviations for the Sample Mean. Theory of Probability and Its Applications. 16(1). 126–140. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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