Woraphon Yamaka

Analyzing Financial Risk and Co-Movement of Gold Market, and Indonesian, Philippine, and Thailand Stock Markets: Dynamic Copula with Markov-Switching

In this paper, we analyze the dependency between the Thailand, Indonesia, and the Philippine (TIP) stock markets and gold markets using dynamic copula with the Markov-switching model with 2 regimes, namely high dependence and low dependence regimes, and extend the obtained correlation to measure the market risk. We are particularly interested in examining whether or not gold serves as a hedge in the TIP stock markets. Using daily data from January 2008 to November 2014, we find that the Gaussian copula identifies a long period of high dependence of TIPGOLD returns (market downturn) which coincides with the European debt crisis. However, if we do not take gold into account, the dependence between the TIP returns is lower in both regimes, thereby leading to a higher value at risk (VaR) and expected shortfall (ES). Therefore, gold can serve as a hedging, or a safe haven, for TIP stock markets during market downturns and upturns. Additionally, the Kupiec unconditional coverage and the Christoffersen conditional coverage test are conducted for VaR and ES backtesting. The results reveal that the Gaussian Markov-switching dynamic copula is the appropriate model to estimate a dynamic VaR and ES.

Spillovers of Quantitative Easing on Financial Markets of Thailand, Indonesia, and the Philippines

This paper provides the results of the effectiveness of the quantitative easing (QE) policy, including purchasing mortgage-backed securities, treasury securities, and other assets in the United States, on the financial markets of Thailand, Indonesia, and the Philippines (TIP) in the post-QE introduction period. In this study, we focused on three different financial markets, which include the exchange rate market, stock market, and bond market. We employed a Bayesian Markov-switching VAR model to study the transmission mechanisms of QE shocks between periods of expansion in the QE policy and turmoil with extraordinarily negative events in the financial markets and the global economy. We found that QE may have a direct substantial effect on the TIP financial markets. Therefore, if the Federal Reserve withdraws the QE policy, the move might also have an effect on the TIP financial market. In particular, purchasing the mortgage-backed securities (MBS) program is more likely to affect the TIP financial markets than purchasing the other programs.

A Copula-Based Markov Switching Seemingly Unrelated Regression Approach for Analysis the Demand and Supply on Sugar Market

This paper conducted a Markov switching seemingly unrelated regression without assuming a normal distribution of the error term. We proposed the use of both Archimedean and Elliptical copula classes to join the different marginal of the system equations. The results show that normal distribution for both demand and supply equations and joint distribution by Frank copulas present the lowest AIC and BIC. Moreover, the model is, then, applied for estimating the demand and supply in Thai sugar market. Thai export price and Brazil’s export price were found to be the factors affecting the demand and supply of the Thai sugar market. Finally, the results on smoothed probabilities indicate the oversupply condition in Thai sugar market along our sample period.

Co-Movement and Dependency Between New York Stock Exchange, London Stock Exchange, Tokyo Stock Exchange, Oil Price, and Gold Price

This paper aims to analyze the co-movement and dependence of three stock markets, oil market, and gold market. These are gold prices as measured by gold future, crude oil prices as measured by Brent, and stock prices as measured by three developed stock markets comprising the U.S. Dow Jones Industrial Average, the London Stock Exchange, and the Japanese Nikkei 225 index. To capture the correlation and dependence, we employed the application of C-vine copula and D-vine copula. The results demonstrate that the C-vine copula is a structure more appropriate than the D-vine copula. In addition, we found positive dependency between the London Stock Exchange and the other markets; however, we also obtained complicated results when the London Stock Exchange, the Dow Jones Industrial Average, and Brent were given as the conditions. Finally, we found that gold might be a safe haven in this portfolios.

A Generalized Information Theoretical Approach to Non-linear Time Series Model

The limited data will bring about an underdetermined, or ill-posed problem for the observed data, or for regressions using small data set with limited data and the traditional estimation techniques are difficult to obtain the optimal solution. Thus the approach of Generalized Maximum Entropy (GME) is proposed in this study and applied it to estimate the kink regression model under the limited information situation. To the best of our knowledge, the estimation of kink regression model using GME has been not done yet. Hence, we extend the entropy linear regression to non-linear kink regression by modifying the objective and constraint functions under the context of GME. We use both Monte Carlo simulation and real data study to evaluate the performance of our estimation from Kink regression and found that GME estimator performs slightly better compared to the traditional Least squares and Maximum likelihood estimators.

Estimating Efficiency of Stock Return with Interval Data

Existing studies on capital asset pricing model (CAPM) have basically focused on point data which may not concern about the variability and uncertainty in the data. Hence, this paper suggests the approach that gains more efficiency, that is, the interval data in CAPM analysis. The interval data is applied to the copula-based stochastic frontier model to obtain the return efficiency. This approach has proved its efficiency through application in three stock prices: Apple, Facebook and Google.

Forecasting Asian Credit Default Swap Spreads: A Comparison of Multi-regime Models

This paper aims to explore the best forecasting model for predicting the Credit Default Swap (CDS) index spreads in emerging markets Asia by comparing the forecasting performance between the multi-regime models. We apply threshold, Markov switching, Markov switching GARCH and simple least squares for structural and autoregressive modeling. Both in- and out-of-sample forecasts are conducted to compare the forecasting performance between models. The results suggest that Markov switching GARCH(1,1) structural model presents the best performance in predicting Asian Credit Default Swap (CDS) index spreads. We also check the preciseness of our selected model by employing the robustness test.

Pair Trading Rule with Switching Regression GARCH Model

Pairs trading strategy is a famous strategy and commonly taken by many investors. There are various approaches to define the pairs trading signal which is the important part of the strategy. This study aims to propose an alternative approach, Markov Switching Regression GARCH model, to specify the trading signal for stock pair taking into account the structural change in the pair return. We applied our proposed model to the Stock Exchange of Thailand and the result shows our pairs trading strategy is relatively more effective for financial investment management compared with the single mean return from individual stock method.

Dependence Structure of and Co-Movement Between Thai Currency and International Currencies After Introduction of Quantitative Easing

We analyze the dependence relationship between the Thai currency and international currencies after the introduction of quantitative easing (QE). The daily currency exchange rates of Thailand, European countries, Great Britain, Japan, Indonesia, the Philippines, Singapore, and Malaysia during 2009–2014 are applied in this study. We proposed a Markov-switching dynamic copula approach to test the co-movement between the exchange rates and the Thai Baht. The results show that there is a dependence relationship between the Thai Baht and the other currencies except in the case of the Great British Pound. Additionally, we also found that a high dependence regime has higher volatility than a low dependence regime.

Effect of Quantitative Easing on ASEAN-5 Financial Markets

After the economic crisis in 2007, the United States enter to the economic recession. Thus the central banks (Fed) purposed an unconventional policy and launch various programs in order to restore the weak economic. However, it also generated a spillover effects toward Emerging countries through capital flow. Therefore, the paper aims to provide a new empirical finding by examining the effect of quantitative easing (QE) policy of the United States on Thailand, Indonesian, and the Philippine, Singapore, and Malaysian financial markets (ASEAN-5). In this study, the ASEAN-5 financial markets, comprising the exchange rate market, the stock market, and the bond market are considered. To measure the effect of QE on those markets, we employed the Markov-switching VAR model to study the transmission mechanisms of QE shocks between periods of expansion in the QE program and QE tapering. Moreover, we restrict the structure of the model in order to identify the determinant of the structural change. This paper finds that ASEAN-5 financial markets receive the effect form QE. The treasury securities purchase program seems to generate a larger effect to the ASEAN-5 financial market than other programs. Moreover, the test of best MS-VAR specification, provide the result that MSH(2)-VAR(1) is the best specification model for the exchange rate market and the stock market, while MSIH(2)-VAR(1) is the best specification model for bond markets. This indicates that QE was not the factor leading the ASEAN-5 financial markets switch from one regime to another regime.