There exist a plethora of studies on theexchange rate modelling. The forecastability of theexchange rate based on fundamentals has been debated in the economic literature and there does not appear to be a consensus that the out-of-sample forecasts of a random work model can be improved upon. While both theoretical and empirical research still explore possibilities to improve standard macro fundamentals-based exchange rate models, to explain or predict theexchange rate movement reliably (the mean equation), we concentrate on the second moment (i.e. volatility) and aims to analyze thevolatilityspillover from across different financial markets to theexchange rate market. Moreover, we use high frequency (daily) data and consider those financial variables that are frequently referred while quoting the day-to-day rates by the traders and market participants in the Emerging Markets (EMEs). In particular, our study concentrates on a set of variables (equity prices, short and long run rates, term spread, Ted-spread, crude prices and Dollar-index) that the traders in the forex desk closely monitor and immediately react along with other long run macroeconomic variables.
they were not as significant as in the stage of continued RMB appreciation. Some scholars believe that thespillover effects between these two markets would become progressively significant with increasing capital market reform and the continuous de- velopment of financial liberalization. However, it is the actual operations performance of theforeignexchange and stock markets that can test whether those theories and such reasoning are correct. The global stock market suffered a slump due to global fi- nancial crisis. At the same time, China effectively halted the trend of RMB appreciation in order to protect exports from greater decline. Consequently, the RMB/USD ex- change rate began to shift from continuous appreciation to constant shocks to maintain the stability of the stock market. We have to take flexible measures to deal with emergencies while recognizing market-oriented trends in the financial markets. The government ’s strong regulation plays an important role in maintaining the stability of the stock market. However, the financial crisis dampened investor enthusiasm and con- fidence, and the expectation of RMB appreciation at this stage can no longer boost the stock market boom as fast as the earlier stage of continuous RMB appreciation. These days, as foreign demands for RMB appreciation intensifies, the airline industry is bene- fiting from theexchange rate advantage and is demonstrated an ascending trend. This further confirms the impact of theforeignexchangemarket on the stock market.
some evidence of bidirectional spillover of volatility. Choo et al., (2011) found volatilityspillover between different indices in the same country of Malaysia. They also concluded that the large caps volatility was more than small caps. Al-Rjoub & Azzam (2012) examined the effect of financial crises on Jordan equity market. They found significant results and concluded that all the financial sectors are effect by financial crises but banking sector absorbs more shocks than other sectors. Sakthivel et al., (2012) examined integration among US, Japan, UK, India and Australia equity markets. From GARCH model, they found volatilityspillover between US and Indian equity market. They also found shock spillover from Japan and UK to Indian equity markets. Mukherjee & Mishra (2010) examined Indian equity market with 12 Asian stock markets. Their analyses reveal significant volatilityspillover from most of the stock markets to Indian equity market. They also concluded that Indian equity market strongly influence the stock market of Srilanka and Pakistan. Joshi (2011) investigated six Asian stock markets (i.e. China, Korea, Jakarta, Hong Kong, India, and Japan). By applying GARCH BEKK model, they found some evidence of volatilityspillover between equity markets of Asia. Recently, Li & Giles (2015) examined volatilityspillover across US and Japan to emerging equity markets of Asia. They found volatilityspillover from Japan and US equity market to emerging market of Asia. They concluded that thevolatilityspillover was stronger during Asian financial crises. Majdoub & Mansour (2014) empirically found new evidence of volatilityspillover from US stock markets to 5 emerging Islamic equity markets indices (namely, Qatar, Pakistan, Turkey, Malaysia and Malaysia). Their analyses show weak integration in selected markets in terms of volatilityspillover.
developed and emerging markets of Asia. The Asian countries included in this study are; China, India, Hong Kong, Japan, Pakistan and Sri Lanka. The sample constitutes developed country of Japan and markets of China, India, Hong Kong Pakistan and Sri Lanka. The sample also represents three countries from South Asia i.e. Sri Lanka, India and Pakistan; and three countries from East Asia i.e. Japan, Hong Kong and China. The contribution of the study will be in the following aspects. First, instead of analyzing a single country, this study investigates volatilityspillover between stock market and for- eign exchangemarket in sample of different Asian countries. Second, this study will add some valuable knowledge to existing literature in terms of selected Asian countries sample. In reference to Pakistan; we only found a single study of Qayyum and Kamal (2006) that employed weekly data covering the period from 1998 to 2006. The contri- bution of this study in reference to Pakistan is as follow. First, we have used daily data instead of weekly because stock and foreignexchangemarket trading occurs on daily basis and the shock that arises on daily basis is absorbed in weekly data. Second, we have used data set covering the period from 1999 to 2014. In reference to Sri Lanka, up to best of our knowledge, this study is the first to address volatilityspillover between stock market and foreignexchangemarket. In this aspect, this study will be a novel contribution in reference to Sri Lanka. In context of China, Hong Kong, India and Japan, we have found many studies but with mixture of results like (Chkili 2012) and (Beer and Hebein 2011) reported contrasting results in case of Hong Kong. Similarly, (Mishra et al. 2007) and (Beer and Hebein, 2011) found different results for India. (Kanas 2000; Yang and Doong 2004) and (Beer and Hebein 2011; Francis et al. 2006) found contrasting results for Japan. Therefore there is still a gap to explore knowledge about thevolatilityspillover dynamics in the selected countries. The other contribution of this study is considering daily data covering period of 15 years in order to examine volatilityspillover in long run. The reason behind selection of daily data is to capture more information that we can do in weekly and monthly data. Furthermore, the results of this study will be important for economic policy makers, investors and multinational firms. The policy makers will benefit from this study by knowing the behavior of two markets in order to implement policies for financial stability perspective. Investors will use the information to manage their international portfolio risk and currency risk strat- egies. This study is also important for multinational firms which intend to manage their international currency exposures.
announced. On this basis, the possibility of private information in FX markets has often been questioned.
Early evidence consistent with the presence of private information in FX markets came from a number of studies that provided evidence of price leadership of dealers in FX markets. Peiers (1997) finds that Deutsche Bank was a price-leader in the Deutschemark and could anticipate Bundesbank interventions by up to 60 minutes. Similarly Covrig and Melvin (2002) find that Tokyo-based banks exhibit price leadership in the JPY and their quotes lead the rest of themarket when informed players are active. Ito et al. (1998) study how volatility rose over lunch time in response to informed trading by Tokyo-based traders after the local prohibition against dealer trading over lunch time was removed. Since volatility often reflects the arrival of private information, this finding suggests that such information was emerging at that time. Killeen et al. (2006) find that the French franc–DEM exchange rate was cointegrated with cumulative order flow before the rigid parity-rates were announced in May 1998 but not after. This finding also points to a role for private information, since information would only be important when rates are flexible.
Similarly, Dicle & Levendis (2010) investigate the efficiency of the Athens Stock Exchange in relation to market tests and individual stock returns. Both at market and stock return level, the research provides evidence of inefficiency. In an earlier study Mollah and Mobarek (2009), noted that there is a long-term persistence shock in emerging markets compared to developed markets. That also indicates efficiency. Moreover, Dicle & Levendis (2010) based on the premise that approximately 94% of the Greek stock returns are Granger-caused by at least one foreignmarket, it is concluded that the Greek market does not provide evidence of international diversification. Considering the importance of liquidity for emerging markets, its impact on Greek stocks is assessed as part of the analysis of market efficiency. Hence, liquidity is found to be a statistically significant cause for the returns of less than 10% of the Greek market, which implies that despite being significant, liquidity it is not accountable for the returns of about 90% of Greek stocks.
Two main types of heuristics for predicting theexchange rate were identified in foreignexchange markets: fundamental and technical analysis (e.g., Frankel and Froot , 1990 ). Traders using technical analysis (henceforth referred to as chartists) infer the future exchange rate based on past price movements and are to a great extent the target group that Tobin intended to impair due to their supposedly destabilizing behavior. Traders using fundamental analysis (henceforth referred to as fundamentalists), by contrast, assume the convergence of themarket price to some fundamental value and are believed to be stabilizing themarket. Questionnaire surveys suggest that most traders in foreignexchange markets are familiar with both types of analysis and consider them to be equally important (e.g., Taylor and Allen , 1992 ; Oberlechner , 2001 ). In our model, we will follow De Grauwe and Grimaldi ( 2006 ) and approximate these two ample families of forecasting heuristics using two simple forecasting rules. Furthermore, we add an autoregressive stochastic term to the original equations to address the persistent variability of forecasting heuristics within families.
The growth in foreign equity portfolio investments in emerging markets like India has significant implications. Historically, one of the main motivations for investing in emerging markets like India was significant diversification benefits it offered to international investors because it was viewed as a segmented market (Chatrath et al., 1996). However, if the present magnitude and pace of foreign investments are sustained over time then emerging markets like India may not remain segmented. This will not only reduce international portfolio diversification benefits but will also make theIndianmarket more vulnerable to the global shocks. There is evidence which suggests that foreign investors have short-term investment interest and at the sign of slightest trouble, theforeign capital tends to leave at a much greater pace than the pace at which it arrives in emerging markets (Bekaert, Harvey and Lumsdaine, 2002). Further, the massive losses experienced by investors following the sub-prime crisis since August 2007 makes it all the more critical that the globalisation paradigm is re-examined using a case study of India since it is one of the few emerging markets at the forefront of the global economic growth. Thus it is both topical as well as critical for academics and policy makers to have a greater understanding of the role and influence of foreign investors’ activities. This paper addresses this key issue by providing empirical evidence on the impact of foreign portfolio flows on the short- run and long-run behaviour of theIndian stock market.
“Dealers” or “market makers” emerged naturally to fulfil the search function among trading counter- parties. Dealers stand ready to trade with anyone needing FX at a moment’s notice. To initiate a FX trade, an agent calls a dealer indicating the currency and quantity s/he wishes to trade and asking for the price. The dealer states a price at which s/he is willing to buy (the “bid”) and a price at which s/he is willing to sell (the “ask”). Finally, the customer decides whether to buy, sell, or pass. The dealer is compensated for the burdens of liquidity provision – such as bearing inventory risk and screening agents for credit quality – by a favourable gap between the quoted buy and sell prices, the “bid-ask spread.” Markets of this structure, known as “over-the-counter” (or OTC) markets, have arisen naturally in contexts including municipal and corporate bonds, derivatives, and equities. Though over-the-counter dealers are under no formal obligation to provide liquidity, they tend to be reliable because otherwise their reputation – and potentially their market share – will suffer.
In summary, the Sugar return series seems that it is best described by an unconditional leptokurtic distribution and possesses significant conditional heteroskedasticity. This renders the ARCH models a very good choice for modeling the Sugar return series. The autoregressive conditional heteroskedasticity (ARCH) model introduced by Engle (1982), and its extension to the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model (Bollerslev, 1986), allow the fat tails which are often observed in financial distributions and impose an au- toregressive structure on the conditional variance and therefore is capable of capturing not only thevolatility persistence of return series over time but also thevolatility clustering as well. Volatility clustering is an important feature of financial distributions and appears when there is a tendency that large changes in returns prices will follow large changes, and small changes will follow small changes (Kyle, 1985). Moreover, this model is a weighted average of past squared residuals, but it has declining weights that never go completely to zero.
According to descriptive statistics, volatility, as measured by standard deviation is high (0.0745042). It is not surprising that this series exhibit asymmetric and leptokurtic (fat tails) properties. The VIX return series have positive skewness, and the excess kurtosis exceeds zero indicating fat tails and leptokurtic distribution. Thus, the VIX returns are not normally distributed. Additionally, by Jarque-Bera statistic and corresponding p-value, we reject the null hypothesis that returns are well approximated by the normal distribution. For this reason, in this study we used the Student-t distribution and GED distribution, which takes into account fat tail problem. ARCH-LM statistics highlight the existence of conditional heteroskedastic ARCH effect. The VIX return series are subjected to two unit root tests to determine whether stationary I(0). The Augmented-Dickey–Fuller (ADF) and Phillips–Peron (PP) test statistics reject the hypothesis of a unit root at the 1% level of confidence. MacKinnon critical value at the 1% confidence level is -2.57.
The UK has been a net debtor over the past two decades and the sterling exchange rates are sensitive to any chaos that might occur in the financial market. This paper examines the importance of the inter- national financial imperfections in the sterling exchange rate dynamics. We build a small open economy DSGE model with the constrained international financial institutions that intermediate capital flows, and derive tractable analytical solutions. The constraint works to introduce a wedge between lending and borrowing rates, which compensates financiers for their currency risk-taking. The model has been estimated by using a simulation-based Indirect Inference approach, which provides a natural framework for testing the hypothesis implied by the model. We find that the model cannot be rejected by the UK data. Shocks to financial forces are the main driving forces behind the large and sudden depreciation of the Sterling exchange rates in the aftermath of the collapse of Lehman Brothers and the Brexit vote. Furthermore, the optimal policy rules have been proposed.
Research in both economics and psychology suggests that, when agents predict the next value of a random series, they frequently exhibit one of two types of bias, called respectively the gambler’s fallacy (GF) and the hot hand fallacy (HHF) (for a survey, see Ayton and Fischer, 2004). The gambler’s fallacy is to expect a negative correlation in a process which is in fact random (for example, to believe that the next toss of a fair coin is more likely to be tails after a run of heads). The hot hand fallacy, which works in the opposite direction, is to expect that another toss of heads is more likely after a run of heads. These fallacies may seem mutually contradictory, but the empirical evidence suggests that they apply in slightly different contexts, with the HHF more likely to occur where human performance is thought to be involved. For example, Croson and Sundali (2005) find that, amongst gamblers at a roulette wheel in a casino, a streak of one colour is more likely to induce bets on the opposite colour (GF), but that bets are made on more numbers after winning than losing, as if the gambler’s own performance is positively serially correlated (HHF). Though there is plenty of evidence both from laboratory experiments and from the field (lotteries and casinos) on the GF and the HFF, most of it is limited to purely random environments with no variation in signal strength (e.g. the toss of a coin), and with winning probabilities that are not affected by psychological biases, so we know remarkably little about whether these biases can be overcome when they are punished.
TABLE 12. Effects of Foreign Monetary Policy Easing on Loan Terms. Characteristics of Domestic Corporations
The table reports regression results from specification (3). The dependent variable (ln(loan amount) or Interest Rate) is regressed on borrower characteristics and their interaction with theforeign monetary policy measured. The monetary policy measured used is Cumulative Cuts, which corresponds to the sum of cumulative drops on the interest rate and it is calculated as shown in equation (2). Lender-Time fixed effects are included in all the specifications to control for any observed and unobserved heterogeneity at a lender, time and lender-time level. Thus, the coefficients are estimated using only the within time-lender variation. Columns (VII-XII) include in addition Borrower fixed effects. Definitions of the variables can be found in the Table 1. Coefficients are listed in the first row, robust standard errors that are corrected for clustering at the lender level are reported in the row below in parentheses, and the corresponding significance levels are in the adjacent column. Note: *** Significant at 1%, ** significant at 5%, * significant at 10%.
Reflecting the deeper integration of the Republic of Korea’s equity market into the global financial system, stock price indices such as the Korea Composite Stock Price Index (KOSPI), a capitalization-weighted index of all common shares traded on the Republic of Korea Stock Exchange, have moved closely with similar indices such as the Standard and Poor’s (S&P) 500 of the US, and the co-movement has become more pronounced since the 1997 financial crisis. In view of the asymmetry in cross-border equity investments between Republic of Korea and foreign investors, however, it is not surprising that the price co-movement has also been unidirectional; changes in the US stock price index move the Republic of Korea’s index, but not the other way around. When two stock markets are integrated, as in the case of the Republic of Korea and the US, floating exchange rates are expected to moderate cross-border equity flows and hence changes in stock prices to help preserve monetary independence. However, in reality, this has not been the case. The effect of changes in the won–dollar exchange rate on equity flows has been small and sometimes ambiguous.
parents and pay more attention to the most recent stock price developments. The latter biases the young’s beliefs about the future course of dividends and stock prices toward simple extrapolation of the recent past, and their trading activities push the asset price away from the fundamental. On the other hand, there is a force of reversal to the rational expectations trend. When the stock price rises too far above the fundamental value, constraints on how much an individual can borrow in order to invest in the risky asset begin to bind. Because any given investor (including the optimistic types) can buy fewer shares, the asset price must decline to the valuation of less optimistic investors for themarket to clear. The same re‡ecting force works also "from below" when the stock price falls far below the fundamental value. The combination of these two factors –momentum and trend reversion –results in boom-and-bust cycles that are only loosely related to dividends and are mainly due to speculation about the future course of the stock price, in the spirit of Harrison and Kreps (1978).
jointly by applying a Wald test. To deal with the overlapping nature of the PITs, Newey-West stand- ard errors are used. Therefore, no density has to be discarded making it possible to test the forecast-
ing ability of the RNDs for all maturities. 26
Whether or not the CNH is a good proxy for the CNY is a difficult question. On one hand, market participants maintain that the offshore CNH market provides genuine price discovery, free from the influence of onshore interventions at least partially driven by political considerations. There are plenty of precedents where offshore FX market prices more closely resemble reality than official policy views at the time. On the other hand, it may be that high-frequency CNH traders exacerbate volatility in less certain times. For this reason, the impact the offshore CNH market has on onshore CNY prices appears to be an unanswered question. To analyze the information content of the CNH FX option market for the CNY, we use CNH RNDs to test their forecasting ability for the CNY by applying the inverse normal PIT transformation of (11) for the CNY/USD realizations. The Berkowitz forecast results for the CNH and the CNY exchange rates and one-month
What if the EU were to push ahead with tax harmonisation regardless of these considerations? Some estimates were presented earlier of how much FDI Ireland might stand to lose. Adjustment would be very difficult if the country were forced to rely on its own domestic-industry resources. Only 10 percent of indigenous manufacturing employment is in high-tech sectors, compared to 56 percent of jobs in theforeign sector. Indigenous manufacturing firms export less than one-third of their output, which is quite low by EU standards, and are heavily concentrated on the UK market, making them vulnerable to currency fluctuations. They spend little on R&D and the sector has a poor record in developing patentable processes or inventions. Furthermore, Irish-owned TNCs are disproportionately located in non-traded sectors, such as construction and paper and packaging, and do not exhibit the type of “created asset” intensity – derived from R&D and strong product differentiation – that has been found for Korean or Taiwanese TNCs by Dunning et al. (2001). If Ireland’s foreign industry were to disappear precipitously, much of the economic progress made over the boom period could well disappear along with it.
where α is the constant term, β measures the total foreignexchange rate exposure, r is the yield of the equity index, sdr corresponds to the yield of the national currency per special drawing right (SDR), R ◦ W is the orthogonalized yield of an equity world index, γ is the corresponding coefficient and is the error term. We assume that foreignexchange rate exposure depends on the importance of international trade for each national economy. Importance of international trade is measured by the export and import quota defined by exports and imports relative to the GDP for each country. The relationship of both variables indicates whether a more export-oriented or more import-oriented country is observed. If the national currency unit (NCU) is depreciated, firms in export-oriented countries earn higher profits since goods sold abroad at a constant price in the national currency are less expensive. This implies a higher demand for exported products such that profits and stock prices rise. Therefore, we expect to measure a foreignexchange rate exposure β greater than zero which positively depends on the size of export quota. For import-oriented countries, the line of reasoning is the same except that the sign is reversed. A
carrying capacity that operated with narrower bandwidths and utilized transistors rather than vacuum tubes as repeaters. 15
Coaxial cables were superseded in the 1980s by fiber-optic cables. 16 Fiber- optic cables transfer data at a speed of 180,000-200,000 kilometers per second (i.e. the speed of light in glass), resulting in latency per kilometer of 5 to 5.5 microseconds (a 10 to 11 millisecond delay for a roundtrip of 1,000 kilometers); latency time will be important to our subsequent story. Fiber optic cable connections also increase bandwidth (i.e. the amount of data that can be put through per unit of time) significantly relative to coaxial cables. They reduce losses in signal transmission over long distances. The first submarine fiber-optic cable, TAT-8, entered service in December 1988. Financed by a consortium led by AT&T, France Télécom (now Orange) and British Telecom, TAT-8 had a branching unit underwater, off the coast of Great Britain, enabling it to connect to both the US and France. It had a capacity of 40,000 circuits, allowing it to carry as many as 40,000 simultaneous telephone calls or similar communications, a tenfold increase relative to coaxial cables.