The Number of Regimes Across Asset Returns: Identification and Economic Value

Cahier de recherche du CERAG 2011-05 E2A shared belief in the financial industry is that markets are driven by two types of regimes. Bull markets would be characterized by high returns and low volatility whereas bear markets would display low returns coupled with high volatility. Modeling the dynam- ics of different asset classes (stocks, bonds, commodities and currencies) with a Markov- Switching model and using a density-based test, we reject the hypothesis that two regimes are enough to capture asset returns' evolutions for many of the investigated assets. Once the accuracy of our test methodology has been assessed through Monte Carlo experi- ments, our empirical results point out that between two and five regimes are required to capture the features of each asset's distribution. Moreover, we show that only a part of the underlying number of regimes is explained by the distributional characteristics of the returns such as kurtosis. A thorough out-of-sample analysis provides additional evidence that there are more than just bulls and bears in financial markets. Finally, we high- light that taking into account the real number of regimes allows both improved portfolio returns and density forecasts

The Number of Regimes Across Asset Returns: Identification and Economic Value

A shared belief in the financial industry is that markets are driven by two types of regimes. Bull markets would be characterized by high returns and low volatility whereas bear markets would display low returns coupled with high volatility. Modeling the dynam- ics of different asset classes (stocks, bonds, commodities and currencies) with a Markov- Switching model and using a density-based test, we reject the hypothesis that two regimes are enough to capture asset returns' evolutions for many of the investigated assets. Once the accuracy of our test methodology has been assessed through Monte Carlo experi- ments, our empirical results point out that between two and five regimes are required to capture the features of each asset's distribution. Moreover, we show that only a part of the underlying number of regimes is explained by the distributional characteristics of the returns such as kurtosis. A thorough out-of-sample analysis provides additional evidence that there are more than just bulls and bears in financial markets. Finally, we high- light that taking into account the real number of regimes allows both improved portfolio returns and density forecasts.Bull and bear markets; Markov switching models; Number of regimes; Density based tests

Relating Volatility and Jumps between two markets under Directional Change

Directional change (DC) is a new concept in sampling financial market data. Instead of recording the transaction prices at fixed time intervals, as is done in time series, DC lets the data alone decide when to record a transaction. In DC, a data point is recorded when the price has risen or dropped against the current trend by a significant percentage, which is known as the threshold. The magnitude of the threshold is determined by the analyst. Previous studies on DC mainly focus on analysing single price sequences of one market. This thesis focuses on a new path; working on the DC comparative analysis between two markets. We propose a novel data-driven approach to combine the observed DC series of two markets into a single data sequence, which we call the DC combined sequence. This allows us to conduct a comparative analysis between two markets under DC. Based on this approach, we propose a novel indicator that measures the relative volatility between two markets. In addition, we define jumps under DC. Under this measure, we can pinpoint the size, direction, and quantity of DC jumps in a market. Lastly, under the DC comparative analysis, we build a new DC approach to identify co-jumps between two markets

Three Essays On Foreign Exchange Options

Over-the-counter (OTC) foreign exchange (FX) option market is the fourth largest derivatives market in the world. However, the extant literature on their pricing is noticeably thin, especially for less actively traded contacts, including FX options on pegged currency pairs. To price these FX options, firstly I propose a new discrete time exponential-affine model in Chapter 3, with multiple estimation strategies and pricing confidence intervals for the resulting synthetic volatility surface. Then I test the various specifications out-of-sample on five liquid currencies versus the dollar. My specification can be estimated directly from spot FX and deposit rate quotes without recourse to quoted volatility surfaces. Results indicate that both short and long tenor OTC FX options can be accurately priced with minimal calibration. I further extend the model to allow autoregressive conditional Poisson jumps and multiple factors in the interest rates to handle the latent interest factors in Chapter 4. I propose to adjust the discrete time-step size to price FX options with different tenors, because this adjustment helps preserve the volatility surface dynamic of longer maturity options. In the empirical test on G7 currencies, the model is calibrated against market FX option quotes to extract the hidden factors in both the domestic and foreign interest rates. Results show that these hidden factors have strong persistence property and certain correlation with the spot variance. In order to price FX options on pegged FX rates, I propose to capture the trading and realignment uncertainties embedded in the forward FX rate deviation by a jump diffusion model in Chapter 5. Given the fact that transactions of FX option on such currency pairs are currently rare with very limited data available, I design a novel approach to estimate the model parameters. I then apply the proposed approach on four representative pegged currency pairs (EURDKK, USDSAR, USDQAR and USDNGN) and provide option quotes under the market convention. Distinguishing from traditional option pricing model based on historical information, the proposed model is based on forward looking information. These forward price deviation and synthetic volatility surfaces offer an alternative way to manage the FX rate risk for pegged currency pairs

Measurement, Dynamics, and Implications of Heterogeneous Beliefs in Financial Markets

__Abstract__ This dissertation is part of a growing research field in which the heterogeneity of economic actors is incorporated. It bundles four studies that consider the m

Essays in international finance

This Ph.D. thesis contains 3 essays in international finance with a focus on foreign exchange market from the perspectives of empirical asset pricing (Chapter 2 and Chapter 3), forecasting and market microstructure (Chapter 4). In Chapter 2, I derive the position-unwinding likelihood indicator for currency carry trade portfolios in the option pricing model, and show that it represents the systematic crash risk associated with global liquidity imbalances and also is able to price the cross-section of global currency, sovereign bond, and equity portfolios; I also explore the currency option-implied sovereign default risk in Merton’s framework, and link the sovereign CDS-implied credit risk premia to currency excess returns that it prices the cross section of currency carry, momentum, and volatility risk premium portfolios. In Chapter 3, I investigate the factor structure in currency market and identify three important properties of global currencies – overvalued (undervalued) currencies with respect to equilibrium exchange rates tend to be crash sensitive (insensitive) measured by copula lower tail dependence, relatively cheap (expensive) to hedge in terms of volatility risk premium, and exposed to high (low) speculative propensity gauged by skew risk premium. I further reveal that these three characteristics have rich asset pricing and asset allocation implications, e.g. striking crash-neutral and diversification benefits for portfolio optimization and risk management purposes. In Chapter 4, I examine the term structure of exchange rate predictability by return decomposition, incorporate common latent factors across a range of investment horizons into the exchange rate dynamics with a broad set of predictors, and handle both parameter uncertainty and model uncertainty. I demonstrate the time-varying term-structural effect and model disagreement effect of exchange rate determinants and the projections of predictive information over the term structure, and utilize the time-variation in the probability weighting from dynamic model averaging to identify the scapegoat drivers of customer order flows. I further comprehensively evaluate both statistical and economic significance of the model allowing for a full spectrum of currency investment management, and find that the model generates substantial performance fees

Validation of trading strategies in the foreign exchange

The aftermath of the recent financial crisis has caused the narrowing of investment opportunities for foreign exchange (FX) traders and investors. A debate about the profitability of trading strategies in FX has started among practitioners and academic researchers who have wondered whether is still possible to obtain positive excess returns (alpha). In this research I validate a set of trading strategies for FX. Seven experiments are carried out on macroeconomic market factors like trendfollowing, carry and value, separately. The outcome holds that the dissolution of synchronous monetary policies increases the probability of observing trends and carry opportunities in the FX. The failure of the uncovered interest rate parity by the so-called forward rate puzzle and that of the purchase parity power open opportunities for strategies like momentum, carry and value. Carry is not only applicable to spot rates as can also be used to trade FX options. Two experiments are performed to study the consistency of FX option premia and the performance of carry trade for options. For short-dated options, like the weekly ones, carry cannot produce material profits as the error implied by the forward rate is not large enough. Conversely, the premium earned from trading FX call options is a consistent source. A second line of research is dedicated to the analysis of trading strategies for FX highfrequency data. This study consists of implementing machine learning algorithms, like the exponentially-smoothing recurrent neural networks (RNN), to forecast future prices and derive a trading strategy from it. The training of these models appear to be computationally intensive but simpler than that of other neural networks like the long-short-term memory ones (LSTM). The accuracy of the forecast is adequate with no signs of over-fitting. The performance appears to be highly influenced by the presence of intra-day seasonality and jumps. A range of solutions are explored to address such a limitation

Essays in international finance

This Ph.D. thesis contains 3 essays in international finance with a focus on foreign exchange market from the perspectives of empirical asset pricing (Chapter 2 and Chapter 3), forecasting and market microstructure (Chapter 4). In Chapter 2, I derive the position-unwinding likelihood indicator for currency carry trade portfolios in the option pricing model, and show that it represents the systematic crash risk associated with global liquidity imbalances and also is able to price the cross-section of global currency, sovereign bond, and equity portfolios; I also explore the currency option-implied sovereign default risk in Merton’s framework, and link the sovereign CDS-implied credit risk premia to currency excess returns that it prices the cross section of currency carry, momentum, and volatility risk premium portfolios. In Chapter 3, I investigate the factor structure in currency market and identify three important properties of global currencies – overvalued (undervalued) currencies with respect to equilibrium exchange rates tend to be crash sensitive (insensitive) measured by copula lower tail dependence, relatively cheap (expensive) to hedge in terms of volatility risk premium, and exposed to high (low) speculative propensity gauged by skew risk premium. I further reveal that these three characteristics have rich asset pricing and asset allocation implications, e.g. striking crash-neutral and diversification benefits for portfolio optimization and risk management purposes. In Chapter 4, I examine the term structure of exchange rate predictability by return decomposition, incorporate common latent factors across a range of investment horizons into the exchange rate dynamics with a broad set of predictors, and handle both parameter uncertainty and model uncertainty. I demonstrate the time-varying term-structural effect and model disagreement effect of exchange rate determinants and the projections of predictive information over the term structure, and utilize the time-variation in the probability weighting from dynamic model averaging to identify the scapegoat drivers of customer order flows. I further comprehensively evaluate both statistical and economic significance of the model allowing for a full spectrum of currency investment management, and find that the model generates substantial performance fees