This thesis consists of three essays in international finance, with a focus on the foreign exchange market. The first chapter provides an empirical investigation of the predictive ability of average variance and average correlation on the return to carry trades. Using quantile regressions, we find that higher average variance is significantly related to large future carry trade losses, whereas lower average correlation is significantly related to large gains. This is consistent with the carry trade unwinding in times of high volatility and the good performance of the carry trade when asset correlations are low. Finally, a new version of the carry trade that conditions on average variance and average correlation generates considerable performance gains net of transaction costs. In the second chapter I study the evolution over time of the response of exchange rates to fundamental shocks. Using Bayesian time-varying-parameters VARs with stochastic volatility, I provide empirical evidence that the transmission of these shocks has changed over time. Specifically, currency excess returns tend to initially underreact to interest rate differential shocks for the whole sample considered, undershooting the level implied by uncovered interest rate parity and long-run purchasing power parity. In contrast, at longer horizons the previously documented evidence of overshooting tends to disappear in recent years in the case of the euro, the British pound and the Canadian dollar. Instead, overreaction at long horizons is a persistent feature of the excess returns on the Japanese yen and the Swiss franc throughout the whole sample. In the third chapter we provide a comprehensive review of models that are used by policymakers and international investors to assess exchange rate misalignments from their fair value. We survey the literature and illustrate a number of models by means of examples and by evaluating their strengths and weaknesses. We analyse the sensitivity of underlying balance (UB) models with respect to estimated trade elasticities. We also illustrate a fair value concept extensively used by financial markets practitioners but not previously formalised in the academic literature, and dub it the indirect fair value (IFV). As case studies, we analyse the models used by Goldman Sachs and by the International Monetary Fund’s Consultative Group on Exchange Rate Issues (CGER).

The aim of this thesis is to further investigate new empirical methods, results and implications on major topics relating to foreign exchange and interest rate markets. To this end, this thesis is organised in three chapters. The first chapter focuses on nominal exchange rates. It extends the literature of foreign exchange unbiasedness by including information from different derivatives markets. For the purpose of this thesis, it also implicitly provides a lead on the behaviour of interest rate differentials. The second chapter uses innovative econometric methodologies to add new insights in the behaviour of real exchange rates. Finally, Chapter Three explicitly models the international linkages between the interest rate differentials across countries with clear monetary policy implications. More specifically, a large empirical literature has tested the unbiasedness hypothesis in the foreign exchange market using forward exchange rates. In the first chapter we amend the conventional testing framework to exploit the information in currency options, using a newly constructed data set for three major dollar exchange rates. The main results are that: (i) tests based on stationary regressions suggest that options provide biased predictions of the future spot exchange rate; (ii) cointegration-based tests that are robust to several statistical problems afflicting stationary regressions and allow for endogeneity issues arising from a potential omitted risk premium term are supportive of unbiasedness. In the second chapter we test for mean reversion in real exchange rates using a recently developed unit root test for non-normal processes based on quantile autoregression inference in semi-parametric and non-parametric settings. The quantile regression approach allows us to directly capture the impact of different magnitudes of shocks that hit the real exchange rate, conditional on its past history, and can detect asymmetric, dynamic adjustment of the real exchange rate towards its long run equilibrium. Our results suggest that large shocks tend to induce strong mean reverting tendencies in the exchange rate, with half lives less than one year in the extreme quantiles. Mean reversion is faster when large shocks originate at points of large real exchange rate deviations from the long run equilibrium. However, in the absence of shocks no mean reversion is observed. Finally, we report asymmetries in the dynamic adjustment of the RER. Finally, in the third chapter we employ dynamic factor modelling and maximum likelihood estimation to investigate the existence, the patterns and the implications of common fluctuations in the money market rate differentials of a group of countries visa-vis the US or Germany. To the extent that money market rates reflect monetary policy decisions we argue that the resulting global factor represents the common part of monetary policy deviations across countries. We find that a significant part of such policy deviations is shared across countries and in fact is mainly driven by the policy interactions of the EU and the US. In particular, the US interest rate seems to emerge as a potential global interest rate. The implication is that policy makers should pay closer attention to foreign policies when setting domestic ones.

This thesis examines whether accounting quality, measured as the difference between accounting and market price change, had an impact on the five primary UK banks that adopted IASB’s IFRS accounting standards in 2005. The findings reveal that the changes in accounting standards resulted in the banks experiencing decreased levels of accounting quality and increased levels of exposure to financial distress risk in the period 2005 to 2008, compared to the pre-adoption period of 1992 to 2004. These findings are corroborated when examining a secondary sample of banking related firms that also adopted the same standards in 2005. A control group that did not adopt these standards exhibited an opposite trend, recording a comparative increase in accounting quality from 2005 to 2008. For all firms tested, the 1-day market price Value-at-Risk (VaR) levels increased year-on-year from 2005 to 2009, with VaR breaches during March and May 2006. These firms, for the 2005 to 2009 period, also displayed increased levels of financial market volatility. Importantly, examining the banks’ Basel capital requirements, it is implied that their levels increased after 2005. These findings, in general, contribute to extending literature that focuses on the accounting standards change. One of the findings from this examination is that contrary to the European Commission’s 2002 (EC 2002) and IASB’s (IASB 2009) expectation to strengthen the efficient functioning of the European and global financial markets, in the UK the banking sector’s investor uncertainty increased significantly during 2005 to 2009. Another finding relates to the measurements applied in this research. Changes in accounting quality and the Basel minimum capital requirement are examined by applying two measures systemised as the relative delta and the regulatory relative delta respectively. Both function by quantifying differences between accounting totals and market price. It is discovered that these measures, accounting VaR, and the technology framework, as introduced in this study, have potential benefits and regulatory implications. These are aimed at facilitating the mitigation of risks that impact on accounting quality.

This thesis makes three main contributions to the literature on convertible bond financing. First, we provide a new theoretical explanation for convertible bond financing. Unlike the existing theory, our new theory provides a rationale for the issuance of both callable and non-callable convertible bonds. We also undertake empirical tests of the implications of the new theory and find that the new theory is supported by the empirical evidence. Second, we empirically examine the way in which firms choose the design of convertible bonds and investigate the effect of financial constraints on the firms’ convertible design decision. Consistent with our new theory, we find that the design of convertible bonds is influenced by both adverse selection costs and financial distress costs. Moreover, we find that the design of convertible bonds for relatively constrained firms is determined in a different manner from the design of convertible bonds for relatively unconstrained firms. Our findings suggest that taking into account the effect of financial constraints is important in the understanding of convertible design decisions. To the best of our knowledge, our study is the first to document the effect of financial constraints on choice of convertible design. Third, we empirically examine two alternative explanations for the late call of a convertible bond: the “optimal” call theory of Butler (2002) and the financial distress costs theory of Jaffee and Shleifer (1990). In contrast to the existing evidence reported in Altintig and Butler (2005), we find that the observed late calls cannot be explained by the effect of the notice period as incorporated in the optimal call theory of Butler (2002). The observed conversion premium is much higher than Butler’s optimal conversion premium. On the other hand, we find strong empirical support for the financial distress costs theory. Firms do not make a conversion-forcing call until the conversion premium is large enough to avoid a failed conversion, which could give rise to financial distress. We find that by the time a call is made, the probability of failed conversion is very small and the cross-sectional variation in the conversion premium is mainly explained by potential distress costs.

In the light of the events of the recent financial crisis and of the increased importance of liquidity for the functionality of firms and financial markets, this thesis studies how a lack of liquidity (illiquidity) can affect the prices of credit derivatives and how illiquidity can propagate across credit and equity markets. The thesis incorporates three self-contained research papers. The first paper (Chapter 2) examines the effect of liquidity on the pricing of senior structured and unstructured credit indices (Senior Tranche of CDX.NA.IG Index and AAA Corporate Bond Index) over the period 2006-2009. The paper reveals that for both instruments the credit spreads align over time with the returns and the volatility of the equity market and with interest rates, as suggested by the structural model theory (Merton, 1974). However, it also shows that during the subprime crisis the highly-rated tranche of the CDX.NA.IG Index suffered from a substantial discount due to the lack of depth in the relevant markets, the scarcity of risk-capital, and the high liquidity preference exhibited by investors. By contrast, market liquidity and funding liquidity are found to be less significant in explaining the increase in the spread of the AAA Bond Index. The second paper (Chapter 3) investigates the existence of illiquidity commonality across equity and credit markets and the potential channels that can explain this phenomenon. Illiquidity appears to co-move across equities and credit default swaps in particular over crisis periods. For most firms, illiquidity is transmitted from one market (CDS) to the other (equity). Higher funding costs, market volatility and firms' systematic risk cause the equity-CDS illiquidity commonality to increase. However, the illiquidity commonality is also strongly related to the debt-to-equity hedge ratio which captures the arbitrage linkage between equity and CDSs. The paper shows that the illiquidity contagion across two fundamentally-linked assets can be generated by higher demand of liquidity for hedging and speculative trading. The third paper (Chapter 4) studies possible explanations for the credit spread puzzle. First, the paper shows that the credit spread puzzle can be partially explained by investors' aversion to a firm's extreme losses. The paper implements a novel calibration of the Merton (1974) model to a measure of sensitivity of CDS premia to equity volatility (which captures changes in the fat left tail of the firm's risk-neutral distribution). The predicted CDS premia are higher than those obtained using more traditional calibration methodologies, but still lower than those observed in the market. Therefore, the paper turns to studying the effects of investors' ambiguity aversion and CDS market illiquidity on CDS premia. The results show that when a market is illiquid and uncertainty is greater, sellers of credit default swaps charge more and CDS premia increase.

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This thesis studies the modeling of irregularly spaced tick data using intensity mod- els, and the optimal trading strategy for executing orders based on these models. It is divided into five chapters: Time-deformation modeling of FX returns, Modeling the inten- sity of trades using order book information, Optimal execution with Hawkes market impact functions, A dynamic adaptive strategy, and Applications of dynamic adaptive strategy. Time-deformation modeling of FX returns. We model trade arrival rates using a Hawkes process in an FX market. We show that the Hawkes process produces a good fit and is able to capture the empirical characteristics of the trade arrival data. Using a wavelet jump detection method we separate the data into two components and employ Hawkes processes to model each individually. An intensity-based volatility estimator is proposed and tested with market data, and compared with realized volatility measures in a forecasting exercise. The intensity-based volatility is derived from a structural volatility model and we show that it is able to forecast volatility with great precision. Modeling the intensity of trades using order book information. Using information from the limit order book, the proposed framework takes into account measures of aggregated market activity and order imbalance in the bid and ask queue to model intensity. Empirical analysis shows that the inclusion of covariates in the Hawkes model improves the fit of the intensity model and provides a better volatility forecast. In addition we show how order book resiliency can be measured using estimates of the Hawkes process. Optimal execution with Hawkes market impact functions. We derive the optimal execu- tion strategy without imposing the assumption of a pure buy strategy. The optimal solution is obtained by finding a trade-o¤ between the market impact costs of trading and the price risk of slow execution. We derive the optimal solution in closed form in a variety of settings and study their properties. A dynamic adaptive strategy. We modify the strategy derived in chapter 4 to a dynamic adaptive strategy by admitting only a pure buy strategy. We study the dynamic adaptive strategy in various situations such as including a positive or negative drift in the price process and a risk aversion coefficient. The strategy allows for adaption to changes of market conditions. We test it using simulated data and compare it with commonly use practical execution strategies such as VWAP and POV. Applications of the dynamic adaptive strategy. We examine the optimal execution strat- egy where the market resiliency function is specified by a Hawkes process with a power law decay function and then implement the optimal trading strategy using real market data.

The aim of this thesis is to investigate the dynamics of exchange rates for emerging markets (EM) taking into account their riskier nature from the viewpoint of foreign exchange investors. We use two different, albeit related, approaches to model the exchange rate. First, we revisit the forward bias puzzle under a setting where the global risk aversion plays a key role in the effect the forward premium has on the dynamics of the exchange rate. We argue that during low levels of risk aversion the high carry offered by EM attracts speculative capital which causes the currency to appreciated when, according to the UIP, one would have expected investors to demand a higher interest rate on currencies expected to fall. During high levels of risk aversion, investors pull their positions from the riskier economies, thus unwinding carry trades, which leads to the depreciation of the high-yielding currencies and we see deviations from UIP revert back to equilibrium. In the second approach, we investigate how well interest rate deviations from a Taylor-type rule explain returns to the carry trade, a currency trading strategy that takes advantage of the interest rate differential between countries, exposing itself only to the depreciation risk associated with the high-yielding currency. We argue that Central Banks take into account the exchange rate when setting the interest rate and thus may deviate from the policy rule in an attempt to influence the path of the exchange rate. These deviations, perceived as excess compensation for risk, make EM target currencies for carry trades increasing their demand and thus leading to their appreciation. This, in turn, implies large returns to carry trades since investors collect on top of the carry the exchange rate return as they transfer back the funds invested in the high-yielding currency. All in all, our findings based on both frameworks suggest that investors’ appetite for risk plays a key role, especially in the dynamics of the EM exchange rates.

This thesis consists of three essays and aims to deepen our understanding of agent's actions in financial markets at different aggregation levels and using various data. In the first essay, we analyse the trades of brokers in a non-anonymous market. Specifically, we explore the information context of broker identities and how their disclosure can be exploited by other investors. Using data from the Helsinki Stock Exchange we form dynamic mean-variance strategies with daily rebalancing which condition on the net flow of brokers. We find that investors can benefit from knowing who trades compared to a portfolio that disregards this information. We demonstrate a link between the information content of broker order flow and the sophistication of their clients. In the second essay, we investigate the forecasts of sell-side analysts. We use banking sector news to proxy for the severity of career concerns and examine their impact on analysts' tendency to make bold forecasts. We show that analysts follow the consensus forecast more closely when the prospects of the banking sector are negative. The more established analysts, in terms of reputation and experience, are generally unaffected by banking news. In contrast, their less established peers cluster their forecasts near the consensus after negative news for banks. In the last essay, we are interested in the estimation of the covariation matrix of equity prices in the presence of market microstructure noise and non-synchronous trading. We base our analysis on a simple framework that derives separate pooled OLS regressions from other well-known estimators, whose byproducts are the integrated variance and covariance, and noise components. A comprehensive simulation study shows that our estimator is very precise and out-performs other widely applied estimation techniques. A similar picture emerges when we use historical data. Finally, we document the association of the noise component with liquidity frictions.

This thesis studies three important issues in portfolio management: the impact of estimation risk on portfolio optimization, the role of fundamental analysis in portfolio selection and the power of the bootstrap approach for separating skill from luck across a sample of portfolio managers. The first study examines the practical value of the mean-variance portfolio optimization. This issue arises from the concern that the performance of the meanvariance portfolio suffers seriously from estimation errors in input parameters. Based on simulated asset returns, we compare the performance of selected popular portfolios against the naïve equally weighted portfolio (1/N) in terms of the Sharpe Ratio. We conclude that given relatively small and persistent anomalies, some sophisticated portfolio rules can outperform the naïve one at estimation windows of reasonable lengths. We find that (1) an estimation window of 120 months is needed for the optimization-based portfolio rules to outperform the 1/N rule when annual abnormal returns lie between a certain range; (2) given the same abnormal returns, even longer estimation windows are needed when asset returns exhibit fat tails; (3) our preferred portfolio rule, which combines optimally the sample tangency portfolio with MacKinlay and Pástor’s (2000) portfolio, performs well relative to other rules. Our second study examines the role of fundamental analysis in portfolio selection. Fundamental analysis assumes implicitly that asset prices mean-revert to their fundamental values. We solve the instantaneous mean-variance portfolio choice problem when asset prices mean-revert to their fundamentals and analyze how this meanreversion feature affects the performance of the optimal portfolio. Our analytical results show that the expected appraisal ratio of the optimal portfolio is increasing in the meanreversion speed for a given stationary distribution of the mispricing and it is increasing in the standard deviation of the stationary distribution for a given level of the meanreversion speed. The contribution from dividends is positive, increasing in the dividend yield and is tantamount to increasing the mean-reversion speed. Our numerical examples indicate that fundamental analysis can be more helpful than practitioners’ performance shows. One implication of this is that it must be very challenging to obtain reasonable forecasts of the mispricing. Our third study provides a simulation analysis of the power of the bootstrap approach for identifying skill among a large population of mutual funds. Unlike the standard t-test, this approach does not require ex ante parametric assumption on fund alphas and allows us to infer on the existence of genuine skill across a large sample of fund managers. Its recent applications in mutual fund performance analysis have produced strikingly different findings from those documented in the classical literature. However, as far as we know, its power has not been subject to any rigorous statistical analysis. We provide a Monte Carlo simulation analysis of the validity and power of this method by applying it to evaluating the performance of hypothetical funds under varieties of parameter assumptions. We find that this method can be misleading, which is true regardless of using alpha estimates or their t-statistics. This makes the recent findings dubious. The major problem with this method lies in the inappropriate use or misinterpretation of what Fama and French (2010) call "likelihoods" in testing for difference between realized and bootstrapped alphas at selected percentiles. We also show that the variance decomposition and the Kolmogrov-Smirnov test can lead to correct inferences on fund managers’ skill when likelihoods fail to do so.