“Influence of monetary information signals of the USA on the Ukrainian stock market”

The stronger the level of economic integration between countries, the greater the need to study the formation patterns of the stock market reaction to the financial information signals. This concerns the Ukrainian stock market, which is now in its infancy, and which reaction to financial information signals is sometimes ambiguous. The research aims to identify the formation patterns of return and volatility indicators of the Ukrainian stock market reaction to the US financial information signals. To assess the direct nature of US financial information signals effect on the PFTS stock index, the GARCH econometric modeling toolkit was applied. The research information base is the PFTS stock index and the Federal Reserve System financial information signals at the discount rate for 2000–2019. The fetch is divided into intervals corresponded to the ascent and decline phases of the financial cycle. It was found that an unforeseen increase in the discount rate at the financial cycle decline phase by 25 basis points decreases the PFTS stock index return, on average by 2.9%. Besides, the hypothesis about the general change stabilizing effect in the discount rate on the Ukrainian stock market volatility at the financial cycle growth phase was confirmed. Nevertheless, for investors, the most essential is the regulator’s monetary signals in the discount rate at the financial cycle decline phases rather than at the ascent phases because there is a more significant increase in the volatility level. relationship between monetary policy and stock markets is viewed along with two different directions. The first (e.g., Rigobon & Sack, 2003; Bjørnland & Jacobsen, 2013) examines the effect of the stock price dynamics on the banking regulators’ decisions regarding the parameters of the monetary policy. The second direction (e.g., Rigobon & 2004; Bernanke & Kuttner, 2005; Hau & Lai, 2016), to which this paper can also be attributed, examines the effect of the monetary decisions of central banks on stock markets. To analyze the relationship between monetary policy and stock performance, it is necessary to identify the economic transmission channels


INTRODUCTION
Among the stock market's essential functioning aspects, one can single out the specific features of its reaction to financial information signals negatively affecting the stock indices dynamics. Understanding such reaction formation patterns allows financial regulators to assess in advance the potential scale of negative consequences for the stock market development and make informed preventive management decisions.
The relationship between monetary policy and stock markets is viewed along with two different directions. The first (e.g., Rigobon  To analyze the relationship between monetary policy and stock performance, it is necessary to identify the economic transmission channels (e.g., Kozmenko  , where banking regulators decisions on crucial interest rates affect stock markets. According to Sharpe (1964), a risky asset's return is equal to a risk-free financial asset's interest rate to which the risk premium is added. Thus, when acquiring a risky financial asset (e.g., a stock or the portfolio of stocks), an investor expects excess return compared to a risk-free financial asset, i.e., the risk premium (e.g., Prat Thus, the monetary policy effect on the stock market's return occurs through the effect on the interest rate (risk-free) and/or risk premium (Ozdagli & Velikov, 2020). At the same time, the risk premium can be divided into several components, and the study can be performed to determine the channels that make monetary policy information signals have the most significant effect on the stock market return. Therefore, it is crucial to assess the average reaction of the representative Ukrainian stock market PFTS index return and volatility indicators to the US financial information signals.

LITERATURE REVIEW
Many researchers (e.g., Goodhart & Smith, 1985;Patelis, 1997;Bernanke & Kuttner, 2005;Bredin et al., 2009) reviewed the financial information signals effect of banking regulators on the stock market performance. However, most of the research data is concentrated in the US and the EU stock markets. Simultaneously, there are almost no case studies on emerging countries' stock markets, in particular Ukraine. The return of the national stock markets is usually significant and negative to the positive "surprises" of the banking regulators' monetary decisions regarding the discount rate, and vice versa (e.g., Alessi & Kerssenfischer, 2019; Jarociński & Karadi, 2020).
According to Fama (1965), stock quotes must immediately and adequately adapt to emerging information (events), including forecasts. Thus, the shift in the exchange rate at the time of information signals announcement should occur only due to the deviation of their information content, i.e., between the actual (announced) value and the corresponding forecast. In this case, the surprise effect was in question, which is significant for the stock quotes and encourages market participants to revise their investment strategies. Hence, it is necessary to distinguish between the expected and the surprise component of the information content's monetary signals.
Obtaining results that can be correctly compared with the other scientists' conclusions demands choosing a unified approach to determining the surprise component of the monetary signal information content. Krueger and Kuttner (1996)    To determine whether the overall change in the discount rate of the Federal Reserve System increases (decreases) the PFTS stock index volatility (at the ascent/decline phase), it is necessary to check whether:

DATA AND METHODS
Daily quotes during 2000-2019 taken from the Datastream database and used to compute the exchange rate of the PFTS stock index return in the trading day format (excluding dividends reinvestment): where t R is the return on the stock index on the trading day , t t P is the stock index value on the trading day , t After determining computing specifics of the expected and the surprise components of the monetary signal information content on the Federal Reserve System (Bernanke & Kuttner, 2005) discount rate, it is essential to test whether the information in the bank regulators' information signals affects the PFTS stock index return and volatility. A methodological approach can be applied, which is usually used in modern scientific literature on the influence of financial information signals on stock markets. Specifically, Flannery and Protopapadakis (2002) apply an econometric model described as follows: where t R is the PFTS stock index return at time t (daily format); α is a constant; β is the autoregression coefficient; ρ is the direct effect weight coefficient of the Federal Reserve System's mone-tary information signal on the return of Ukrainian stock market; t i ∆ is the time series of financial time series, which values correspond to changes in the discount rate by the Federal Reserve System on the day the monetary information signal is announced or equal to zero on days when there is no announcement of the corresponding monetary information signals; t ε is an error, which conditional variance is heteroscedastic and follows the GARCH ( ) , q ρ process of the form: where t D is a dummy variable that equals one on day t of the Federal Reserve System financial information signal announcement and zero otherwise. It is introduced into the dispersion equation to check whether the information signals influence of the regulator's monetary policy on the Ukrainian stock market is stabilizing or destabilizing; 0 The research sample can be divided into sub-periods that correspond to the ascent or decline phases of the financial cycle to check the Ukrainian stock market's reaction to monetary policy information signals, depending on the financial cycle phase. The financial cycle is considered on the example of cyclical fluctuations of the Ukrainian representative PFTS stock index.
The model for assessing the effect on return (4) gets the following transformation: where Expansion is the financial cycle ascent phase; Recession is the financial cycle decline phase;   Table 1 represents the evaluating equations (2) and (3)  The results of testing the advanced hypotheses (     The results of testing the advanced hypotheses (      (Table 4).

EMPIRICAL RESULTS
This research relates to the entire research sample and does not consider the Ukrainian stock market's cyclical fluctuations phases (financial cycle).
The financial cycle phases are identified based on the local minimum and maximum values of the daily values time series of the PFTS stock index (Fig ure 1).
This series choice is advisable since it reflects the ascent or decline trends of such a vital component of the Ukrainian financial market as the stock market.
The sample is divided into ten intervals: five ascent phases and five decline phases ( Figure 1): 1. The first ascent phase (the conditional name of the "AB" interval) of the PFTS stock index: sub-period from January 8, 2004 to January 15, 2008.   Notes: Statistical significance levels: 1% (***); 5% (**); 10% (*). DW is Durbin-Watson statistics. LB (4) is the p-value of the Ljung-Box statistical test for the autocorrelation absence of the 4th order. LB (12) is the p-value of the Ljung-Box statistical test for the autocorrelation absence of 12th order.
The results of testing the advanced hypotheses (Table 8)   The neutral nature of the expected component effect of the Federal Reserve System's monetary information signals on the discount rate on Ukrainian stock market return at the financial cycle ascent phase can be partially explained by the fact that the forecast regarding the change in the discount rate is already reflected in the current price and, according to Fama (1965), should influence quotes.
The PFTS stock index return reaction to the  Table 7).
The results of testing the advanced hypotheses (Table 9) confirm hypothesis  The effect neutral nature of the expected component of the Federal Reserve System's financial information signals on the discount rate on Ukrainian stock market return at the financial cycle decline phase can, as in the case of the ascent phase, be partially explained by the fact that the forecast regarding the change in the discount rate is already reflected in the current price and, according to Fama (1965), should not influence quotes. Thus, there is a forecasting and predicta-   (Table 7). The results of testing the advanced hypotheses (Table 12)

Stabilizing effect
General change in discount rate i ∆

Rejected Accepted Rejected
The increase in volatility at the decline phase and the opposite effect at the ascent phase may mean that unexpected changes in monetary decisions on the Federal Reserve System discount rate at the financial cycle decline phases are perceived by the Ukrainian stock market participants more than at the ascent phases. Thus, for the Ukrainian stock market participants, the most essential is information about monetary decisions at the Federal Reserve System discount rate at the decline phases of the PFTS stock index cyclical fluctuations rather than at the ascent phases, since there is a significant increase in the level of volatility.

CONCLUSION
This study examined the effect of the Federal Reserve System's decisions on the discount rate on such main features of the Ukrainian stock market as return and volatility. The Ukrainian stock market's reaction to announcements on the Federal Reserve System's monetary policy was assessed with and without highlighting the financial cycle phases.
It was established that the Ukrainian stock market return reaction to the Federal Reserve System's monetary signals is quite significant. The effect of monetary decisions on the Federal Reserve System's discount rate (which fits into the logic of risk management) is more expressive at the decline phase than at the ascent phase of the financial cycle.
It is proved that the surprise component of the Federal Reserve System's monetary signal regarding the discount rate at the decline phase (to support the markets) increases the return of the PFTS stock index but destabilizes (increases volatility) of the Ukrainian stock market. Nevertheless, the Federal Reserve System's monetary decisions on the discount rate at the ascent phase in the Ukrainian stock market's cyclical fluctuations stabilize it.
A promising area of further research is to assess the return and volatility effects of the Ukrainian stock market of monetary decisions regarding the discount rate of the National Bank of Ukraine in the expected and the surprise components since there is no unified approach to determining such components of the national banking regulator's financial information signals.