Nonlinear dynamics of daily futures prices: Conditional heteroskedasticity or chaos?

Foreign exchange market efficiency tests: Implications of recent empirical findings

Exchange rates of currencies in the Exchange Rate Mechanism (ERM) of the European Monetary System (EMS) are characterized by long periods of stability interrupted by periods of extreme volatility. The periods of volatility appear at times of realignments of the central parities and at times when the exchange rate is within the ERM bands. We begin by considering a procedure for finding outliers based on measuring distance as a quadratic form. The evidence suggests that the exchange rates of the EMS can be described by a mixture of two distributions. We therefore model the exchange rate as switching between two distributions--one that holds in stable times and the other that holds in volatile times. In particular, we use Hamilton's Markov-switching model. In addition, we extend Hamilton's model by allowing the probability of switching from one state to another to depend on the position of the exchange rate within its EMS band. This model has the interesting implication that near the edge of the band, large movements--either realignments or large jumps to the centre of the band--are more likely if the move to the edge of the band has been precipitous. Copyright @ 1996 by John Wiley & Sons, Ltd. All rights reserved.

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The distribution of exchange rates in the ems

Empirical evidence shows that log-return relatives on commodity futures prices are not normally distributed. This departure from normality seems to be caused by large price changes occurring in the commodity markets with the arrival of important new information. This suggests that a jump-diffusion model may be a plausible choice for modeling the stochastic process underlying commodity option prices. Merton (1976a) develops a jump-diffusion option pricing model assuming that jump risk is unsystematic. However, the jump-diffusion model developed by Bates (1991) is more appropriate for commodity option pricing since it allows jump risk to be systematic. In this article, recent transactions data on futures and futures options are used to test out-of-sample options using American versions of Black's diffusion and Bates's jump-diffusion models. The results show that Bates's model performs considerably better than Black's model. Jump-diffusion Asian option prices are also shown to differ considerably from geometric Brownian motion Asian option prices.

Jump Processes in Commodity Futures Prices and Options Pricing

Cross border capital flows and returns on assets are two key variables in international macroeconomics. Difficult endogeneity issues plague any analysis of their correlations in aggregate data. This paper examines the dynamics of international portfolios with a unique data set on the stock allocations of approximately 6,500 international equity funds domiciled in four different currency areas during a5y ear period. The disaggregated data structure allows us to examine the effect of realized returns on portfolio adjustments. Do managers rebalance their portfolios towards their desired weights or do they increase their exposure to appreciating assets? We find strong support for portfolio rebalancing behavior aimed at stabilizing exchange rate risk and equity risk exposure around desired levels. These findings are important for the new open economy macroeconomics models featuring endogenous portfolio choice. They should also help inform the burgeoning theoretical literature in macroeconomics and in finance that aims at modeling financial intermediaries.

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Global Portfolio Rebalancing Under the Microscope

The probability distribution of futures prices in the foreign exchange market: A comparison of candidate processes

Tests of the hypothesis of the existence of risk premium in the foreign exchange market

Optimal hedged portfolios: the case of jump-diffusion risks

Purpose: On the backdrop of the recent value versus growth debate in both academics and investment community, this paper investigates which is a better strategy, value or growth strategy. Design/methodology/approach: Reworking the Euler equation, this paper derives the relationship among return, profit growth, and risk. We use three different risk metrics proposed by Park and Fang (2021). We regress the value minus growth return on profit growth and risk variables to determine which is the primary driver of the return in the Korean stock market. The data run from 2000 through 2021. Findings: Our data show that the accumulated return on value minus growth stocks steadily increases over 2000- 2012 in Korea, indicating that value stocks outperform growth stocks over the long horizon. Our regression results show that the time-varying risk effect reverts from negativity contemporaneously to positivity with a time lag, and its temporal effect is negligible when aggregated in time. There exists a positive long-run risk effect on the value minus growth return. However, the effect of profit growth on return is not significant, indicating that growth firms’ profit prospect is not a factor in the determination of value minus growth return. Research limitations/implications: In the past, stock market uncertainty (risk) have been most caused by either financial system failures or technological innovations. Whether value stocks outperform growth stocks or vice versa may crucially depends on the causes of stock market uncertainty. We need to refine our model to account for the differences in the causes of stock market uncertainty. Originality/value: Our model is a first attempt to combine profit growth and risk in a unifying framework to explain the value and growth spread in the stock market. The conditional CAPM is a risk-based approach in which profit growth is not accounted for. 

Keehwan Park

Papers

The probability distribution of futures prices in the foreign exchange market: A comparison of candidate processes

Tests of the hypothesis of the existence of risk premium in the foreign exchange market

Optimal hedged portfolios: the case of jump-diffusion risks

Which is Better: Value Strategy or Growth Strategy?

Safe-haven currency behavior in crisis periods: The U.S. dollar, the Japanese yen, and the Swiss franc