Resultados de las pruebas - IMPLEMENTACIÓN Y VALIDACIÓN DE LA HERRAMIENTA PARA LA GENERACIÓN DE

CAPÍTULO 3. IMPLEMENTACIÓN Y VALIDACIÓN DE LA HERRAMIENTA PARA LA GENERACIÓN DE

3.5 Pruebas

3.5.2 Resultados de las pruebas

Next, we take up the period from April to September 1995, when the Nikkei 225 fell below ¥15,000. During this period, the yen slowed its pace of appreciation and turned to depreciation from July onward, and the Nikkei 225 fell below ¥15,000 twice (in mid-June and from end-June to the beginning of July).

The changes in market expectations during this phase of falling stock prices (Figure 20) were that the skewness increased along with the price fall in mid-June and maintained this increased level, while the standard deviation rose. The excess kurtosis exhibited unstable movements, although its swing remained small. These movements in the summary statistics suggest that there was a delayed adjustment to the fall in stock prices, and due to the differing prospects about the effects of the economic stimulus package, market expectations seem to have diversified.

In addition, the summary statistics exhibited irregular movements from mid-July to September. Unique to this period were the large positive value of the excess kurtosis and the large jump in the standard deviation when the most actively traded contract months changed. Such changes imply that, even in the course of stock price recovery after July, market participants remained well aware of a downside risk in stock prices.

While a consensus prevailed concerning the economic slowdown that occurred from May to July, the JGB futures prices rose and, from mid-July onward, they turned down, then rose again from mid-August onward. The probability distribution of the JGB futures prices (Figure 21) tells us that, around the turning point of the market in early July, the standard deviation increased and the excess kurtosis also increased with some volatility, which implies that there was a perceived increase in the risk of large price fluctuations. In addition, from mid-August to early September, when the official discount rate was raised, the standard deviation rose, which implies that market participants were gradually absorbing the forthcoming rate raise.

However, there was a large jump in the standard deviation in mid-August, when the most actively traded contract months changed, which suggests that there might have been a large shift in market views around this time.

Figure 19 Market Expectations of the JGB Futures (from December 1994 to May 1995) [1] JGB Futures

2.0 1.5 1.0 0.5 0 –0.5 –1.0 –1.5

Percent Yen

118 116 114 112 110 108 106 Daily changes (left scale)

Futures prices (right scale)

Dec. 1994 Jan. 1995 Feb. Mar. Apr. May

[2] Standard Deviation

8 6 4 2 0

[3] Skewness

1.0 0.5 0 –0.5 –1.0 –1.5

[4] Excess Kurtosis

1.5 1.0 0.5 0 –0.5 –1.0 –1.5

Note: Each vertical line with a circle at the top shows the date when the official discount rate was changed (April 14, 1995: 1.75 percent →1.0 percent), and each vertical dashed line with a diamond at the top shows the date when the most actively traded contract months were changed.

Figure 20 Market Expectations of the Nikkei 225 (from April to September 1995) [1] Nikkei 225 Stock Average

Percent 6 4 2 0 –2 –4

Yen 19,000 18,000 17,000 16,000 15,000 14,000

Apr. 1995 May June July Aug. Sep.

0.35 0.30 0.25 0.20 0.15 0.10 0.05 0

[2] Standard Deviation

[3] Skewness

1.5 1.0 0.5 0 –0.5 –1.0 –1.5 –2.0 –2.5

[4] Excess Kurtosis

6 5 4 3 2 1 0 –1 –2

Note: Each vertical line with a circle at the top shows the date when the official discount rate was changed (September 8, 1995: 1.0 percent →0.5 percent), and each vertical dashed line with a diamond at the top shows the date when the most actively traded contract months were changed.

Daily changes (left scale) Stock price level (right scale)

Figure 21 Market Expectations of the JGB Futures (from April to September 1995) [1] JGB Futures

Percent 1.0 0.5 0 –0.5 –1.0 –1.5

124 122 120 118 116 114 Yen

Apr. 1995 May June July Aug. Sep.

Daily changes (left scale) Futures prices (right scale)

[2] Standard Deviation

8 6 4 2 0

[3] Skewness

1.0 0.5 0 –0.5 –1.0 –1.5

[4] Excess Kurtosis

1.0 0.5 0 –0.5 –1.0 –1.5

IV. Conclusion

In this paper, we have estimated the time series of implied probability distributions for the periods of the collapsing “bubble” (1989–90), serious stock market slump (1992–94), and increasing anxiety about a deflationary spiral (1995). Based on these estimates, we considered (1) how market expectations of future stock prices and long-term interest rates changed; (2) how and when the relationships between such market expectations and economic indicators changed; and (3) how monetary policy implementation affected such market expectations.

In summary, market participants’ expectations are too diverse and informative to be captured merely by using a single summary statistic, i.e., the mean, because the same mean value implies different market expectations and policy implications, depending on the shape of probability distribution of expected outcome. In particular, since market participants’ confidence in stock prices differs substantially depending on timing, we can expect to capture more market information, both qualitatively and quantitatively, by carefully examining the changes in market participants’ expecta-tions that lie behind stock price fluctuaexpecta-tions. The results presented in this paper suggest that the implied probability distribution extracted from option prices will provide useful information for the conduct of monetary policy operations.

This paper found typical patterns linking large fluctuations of asset prices and the changes in the shape of implied probability distribution extracted from option prices by tracking the time-series movements of summary statistics. It also considered how to interpret such time-series movements in probability distribution as changes in market expectations, and discussed possible policy implications. However, studies on how to make use of the information extracted from option prices in policy judgments have only just begun.²⁶ For example, we have dealt with the effects of asset price fluctuations on market expectations, while issues such as the effects of specific patterns of changes in probability distribution on market fluctuations will be worth examining for analyses of market liquidity and stress situations.

In addition, as Woodford (1994) and Bernanke and Woodford (1997) pointed out in considering the role of asset prices in monetary policy operations, if a central bank tries to conduct monetary policy based on a certain feedback rule concerning asset prices, bilateral causality will emerge between asset prices and market participants’ expectations concerning future monetary policy, and thus may lead to a destabilization of the economy.

26. Methods of extracting expectations concerning future asset prices from option price information have already been put in practice by many central banks around the world. Implied forward rates are used in most G-7 countries. However, as regards the utilization of option price information, many countries, at most, evaluate the dispersion of expectations concerning future asset prices by using implied volatility estimated by the Black-Scholes formula. Countries that actively utilize risk-neutral implied probability distributions in monetary policy judgment are still quite limited in number.

APPENDIX 1: METHODOLOGY FOR ESTIMATING IMPLIED

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