Везде
THE MACROECONOMIC ASPECTS OF NON-SYSTEMATIC SPECULATIVE INVESTMENTS
Table of contents
Annotation Estimate Publication content
References Comments
Share
QR
Metrics
THE MACROECONOMIC ASPECTS OF NON-SYSTEMATIC SPECULATIVE INVESTMENTS
Annotation
PII
S042473880000516-6-1
Publication type
Article
Status
Published
Authors
Dmitry Borodin  Leonid Krasnoschekov
Edition
Volume 53 Issue 1
Pages
128-143
Abstract

It is evident that speculative incentives to liquidity preferences decrease the economic growth rate. The growth of this incentive is motivated by the growth of non-systematic savings. This paper suggests a definition of non-systematic savings and non-classical saving distribution scheme. The economic mathematical method was developed to analyze the impact of non-classical savings distribution scheme on the US stock market. The result achieved by means of applying this method allowed to identify the growing impact of non-systematic savings on the most important parameters of the US stock market. The starting period of this impact was determined. The assumption about time of transition from the classical scheme of savings distribution to a non-classical was made based on estimate of starting point of impact non-systematic savings on the stock market. An alternative approach to the analysis of the impact of non-classical savings allocation scheme was applied to complete the achieved result. This approach is based on a well-known impact of some parameters of the stock market on statements of assets of the stockbrokers. The transition from one distribution savings scheme to another is reflected in the regression curves of aggregated statements of the stockbrokers’ assets on the stock market parameters. Two-phase two-factor model in which first phase let identify classical incentive and second phase allowed to identify non-classical incentive was written to reflect the change of regression model over time. The confidence interval for point of intersection in two-phase regression was determined. This confidence interval allowed to make alternative assessment of the time in which the regression curve of aggregated statements of the stockbrokers assets on the stock market parameters was transformed. An estimate received by means of applying of the first method is included in the confidence interval for a point of intersection in a two-phase regression proving the change in savings allocation scheme.

Keywords
savings distribution, national saving, investment, automated trading systems
Date of publication
01.01.2017
Number of purchasers
4
Views
746
Readers community rating
0.0 (0 votes)
Cite   Download pdf
1

References



Additional sources and materials

Abel A., Bernanke B. (2008). Macroeconomics. Saint Petersburg: Piter (in Russian).


Bolshev L.N., Smirnov N.V. (1983). Tables of Mathematical Statistics. Moscow: Nauka (in Russian).


Goriainov V.B., Pavlov I.V., Teskin O. I., Tsvetkova G.M. (2002). Mathematical Statistics (in Russian).


Gusev A.A., Gorunovich S.А. (2006). Household Savings: Impact on the Stock Market. Saint Petersburg: Zolotoe Secheniye (in Russian).


Hinkley D.V. (1969). Inference about the Intersection in Two-Phase Regression. Biometrica 56(3), 495–504.


Hudson D. J. (1966). Fitting Segmented Curves Whose Join Points Have to Be Estimated. Journal of the American Statistical Association 61, 1097–1129.


Krasnoshchekov L. V. (2013). Automated Trading Systems: Definition, Structure and Properties. Scientific and technological youth journal. MGTU im. N. E. Baumana 11, November. Available at: http://onxhiytvnq. mjwxg5dvfzzhk.cmle.ru/2jmj7l5rSw0yVb-vlWAYkK-YBwk=ZmlsZS9vdXQvNjM2MDQ3 (accessed: August 2016, in Russian).


Krasnoshchekov L. V. (2014). Yield of Automated Trading As Equivalent of Rate of Return on Money Assets.


Scientific and technological youth journal. MGTU im. N.E. Baumana 10, October. Available at: http://onxhiytvnq. mjwxg5dvfzzhk.cmle.ru/doc/737222.html (accessed: August 2016, in Russian). Muravyova V.S., Orlov A. I. (2007). Non-Parametric Assessment Intersection Point of the Two Regressions. Industrial


Laboratory. Materials Diagnostics 73(11), 63–67 (in Russian).


Nusratullin I.V. (2011). Theoretical Aspects of Interruption of the Steady Development of the Economics from Viewpoint of Neoclassical Economics. Economic and Law Issues 10, 61–71 (in Russian).


Orlov A. I. (2007). Applied Statistics. Moscow: Ekzamen (in Russian).


Orlov A. I. (2012). Consistent Tests for Homogeneity of Two Independent Samples. Industrial Laboratory. Materials Diagnostics 11, 66–70 (in Russian).


Seber G.A.F. (1980). Linear Regression Analysis. Moscow: Mir (in Russian).


Zar J.H. (1984). Biostatistical Analysis. Englewood Cliffs: Prentice-Hall.

Zarubina V.S., Krishchenko A.P. (eds.). Moscow: Izd. MGTU im. N.E. Baumana – BMSTU Press (in Russian).

Comments

No posts found

Write a review
Translate