Modeling and Forecasting Implied Volatility: Implications for Trading, Pricing, and Risk Management

Modeling and forecasting of implied volatility (IV) is important to both practitioners and academics, especially in trading, pricing, hedging, and risk management activities, all of which require an accurate volatility. However, it has become challenging since the 1987 stock market crash, as implied volatilities (IVs) recovered from stock index options present two patterns: volatility smirk(skew) and volatility term-structure, if the two are examined at the same time, presents a rich implied volatility surface (IVS). This implies that the assumptions behind the Black-Scholes (1973) model do not hold empirically, as asset prices are mostly influenced by many underlying risk factors. This thesis, consists of four essays, is modeling and forecasting implied volatility in the presence of options markets’ empirical regularities. The first essay is modeling the dynamics IVS, it extends the Dumas, Fleming and Whaley (DFW) (1998) framework; for instance, using moneyness in the implied forward price and OTM put-call options on the FTSE100 index, a nonlinear optimization is used to estimate different models and thereby produce rich, smooth IVSs. Here, the constant-volatility model fails to explain the variations in the rich IVS. Next, it is found that three factors can explain about 69-88% of the variance in the IVS. Of this, on average, 56% is explained by the level factor, 15% by the term-structure factor, and the additional 7% by the jump-fear factor. The second essay proposes a quantile regression model for modeling contemporaneous asymmetric return-volatility relationship, which is the generalization of Hibbert et al. (2008) model. The results show strong negative asymmetric return-volatility relationship at various quantiles of IV distributions, it is monotonically increasing when moving from the median quantile to the uppermost quantile (i.e., 95%); therefore, OLS underestimates this relationship at upper quantiles. Additionally, the asymmetric relationship is more pronounced with the smirk (skew) adjusted volatility index measure in comparison to the old volatility index measure. Nonetheless, the volatility indices are ranked in terms of asymmetric volatility as follows: VIX, VSTOXX, VDAX, and VXN. The third essay examines the information content of the new-VDAX volatility index to forecast daily Value-at-Risk (VaR) estimates and compares its VaR forecasts with the forecasts of the Filtered Historical Simulation and RiskMetrics. All daily VaR models are then backtested from 1992-2009 using unconditional, independence, conditional coverage, and quadratic-score tests. It is found that the VDAX subsumes almost all information required for the volatility of daily VaR forecasts for a portfolio of the DAX30 index; implied-VaR models outperform all other VaR models. The fourth essay models the risk factors driving the swaption IVs. It is found that three factors can explain 94-97% of the variation in each of the EUR, USD, and GBP swaption IVs. There are significant linkages across factors, and bi-directional causality is at work between the factors implied by EUR and USD swaption IVs. Furthermore, the factors implied by EUR and USD IVs respond to each others’ shocks; however, surprisingly, GBP does not affect them. Second, the string market model calibration results show it can efficiently reproduce (or forecast) the volatility surface for each of the swaptions markets.

Conditional Moments in Asset Pricing

A better understanding of stock price changes is important in guiding many economic activities. Since prices often do not change without good reasons, searching for related explanatory variables has involved many enthusiasts. This book seeks answers from prices per se by relating price changes to their conditional moments. This is based on the belief that prices are the products of a complex psychological and economic process and their conditional moments derive ultimately from these psychological and economic shocks. Utilizing information about conditional moments hence makes it an attractive alternative to using other selective financial variables in explaining price changes. The first paper examines the relation between the conditional mean and the conditional variance using information about moments in three types of conditional distributions; it finds that the significance of the estimated mean and variance ratio can be affected by the assumed distributions and the time variations in skewness. The second paper decomposes the conditional industry volatility into a concurrent market component and an industry specific component; it finds that market volatility is on average responsible for a rather small share of total industry volatility — 6 to 9 percent in UK and 2 to 3 percent in Germany. The third paper looks at the heteroskedasticity in stock returns through an ARCH process supplemented with a set of conditioning information variables; it finds that the heteroskedasticity in stock returns allows for several forms of heteroskedasticity that include deterministic changes in variances due to seasonal factors, random adjustments in variances due to market and macro factors, and ARCH processes with past information. The fourth paper examines the role of higher moments — especially skewness and kurtosis — in determining the expected returns; it finds that total skewness and total kurtosis are more relevant non-beta risk measures and that they are costly to be diversified due either to the possible eliminations of their desirable parts or to the unsustainability of diversification strategies based on them.

Factors affecting farmland prices in Finland

The purpose of the study was to analyse factors affecting the differences in land prices between regions. The key issue was to find out the policy effects on farmland prices. In addition to comprehensive literature review, a theoretical analysis as well as modern panel and spatial econometric techniques were utilized. The study clearly pointed out the importance of taking into account the possible spatial dependence. The data were exceptionally large, comprising more than 6 000 observations. Thus, it allowed a thorough econometric estimation including the possibility to take into account the spatial nature of the data. This study supports the view that there are many other factors that affect farmland prices besides pure agricultural returns. It was also found that the support clearly affects land prices. However, rather than assuming the discount rates for support and market returns to be similar, the rough analysis refers to the discount rate for support being a little lower. If this were true it would indicate that farmers rely more on support income than market returns. The results support the view presented in literature that land values are more responsive to government payments when these payments are perceived to be permanent. An important result of this study is that the structural differences between regions and the structural change in agriculture seemed to have a considerable role in affecting land prices. Firstly, the present structure affects the competition in the land market: the more dense farms are in the region the more there are potential buyers, and the land price increases. Secondly, the change in farm structure (especially in animal husbandry) connected to the policy changes that increase area-based support affects land prices. The effect comes from two sources. Growing farms need more land for the manure, and the proportion of retiring farmers may be lower. The introduction of the manure density variable proved to be an efficient way to aggregate the otherwise very difficult task of taking into account the environmental pressure caused by structural change in animal husbandry. Finally, infrastructure also has a very important role in determining the price level of agricultural land. If other industries are prospering in the surrounding area, agricultural viability also seems to improve. The non-farm opportunities offered to farm families make continuing and developing farming more tempting.

Essays on Market Microstructure: Price Discovery and Informed Trading

Market microstructure is “the study of the trading mechanisms used for financial securities” (Hasbrouck (2007)). It seeks to understand the sources of value and reasons for trade, in a setting with different types of traders, and different private and public information sets. The actual mechanisms of trade are a continually changing object of study. These include continuous markets, auctions, limit order books, dealer markets, or combinations of these operating as a hybrid market. Microstructure also has to allow for the possibility of multiple prices. At any given time an investor may be faced with a multitude of different prices, depending on whether he or she is buying or selling, the quantity he or she wishes to trade, and the required speed for the trade. The price may also depend on the relationship that the trader has with potential counterparties. In this research, I touch upon all of the above issues. I do this by studying three specific areas, all of which have both practical and policy implications. First, I study the role of information in trading and pricing securities in markets with a heterogeneous population of traders, some of whom are informed and some not, and who trade for different private or public reasons. Second, I study the price discovery of stocks in a setting where they are simultaneously traded in more than one market. Third, I make a contribution to the ongoing discussion about market design, i.e. the question of which trading systems and ways of organizing trading are most efficient. A common characteristic throughout my thesis is the use of high frequency datasets, i.e. tick data. These datasets include all trades and quotes in a given security, rather than just the daily closing prices, as in traditional asset pricing literature. This thesis consists of four separate essays. In the first essay I study price discovery for European companies cross-listed in the United States. I also study explanatory variables for differences in price discovery. In my second essay I contribute to earlier research on two issues of broad interest in market microstructure: market transparency and informed trading. I examine the effects of a change to an anonymous market at the OMX Helsinki Stock Exchange. I broaden my focus slightly in the third essay, to include releases of macroeconomic data in the United States. I analyze the effect of these releases on European cross-listed stocks. The fourth and last essay examines the uses of standard methodologies of price discovery analysis in a novel way. Specifically, I study price discovery within one market, between local and foreign traders.

Essays on the Linkages Between Financial Markets, and Risk Asymmetries (summary section only)

During the last few decades there have been far going financial market deregulation, technical development, advances in information technology, and standardization of legislation between countries. As a result, one can expect that financial markets have grown more interlinked. The proper understanding of the cross-market linkages has implications for investment and risk management, diversification, asset pricing, and regulation. The purpose of this research is to assess the degree of price, return, and volatility linkages between both geographic markets and asset categories within one country, Finland. Another purpose is to analyze risk asymmetries, i.e., the tendency of equity risk to be higher after negative events than after positive events of equal magnitude. The analysis is conducted both with respect to total risk (volatility), and systematic risk (beta). The thesis consists of an introductory part and four essays. The first essay studies to which extent international stock prices comove. The degree of comovements is low, indicating benefits from international diversification. The second essay examines the degree to which the Finnish market is linked to the “world market”. The total risk is divided into two parts, one relating to world factors, and one relating to domestic factors. The impact of world factors has increased over time. After 1993, when foreign investors were allowed to freely invest in Finnish assets, the risk level has been higher than previously. This was also the case during the economic recession in the beginning of the 1990’s. The third essay focuses on the stock, bond, and money markets in Finland. According to a trading model, the degree of volatility linkages should be strong. However, the results contradict this. The linkages are surprisingly weak, even negative. The stock market is the most independent, while the money market is affected by events on the two other markets. The fourth essay concentrates on volatility and beta asymmetries. Contrary to many international studies there are only few cases of risk asymmetries. When they occur, they tend to be driven by the market-wide component rather than the portfolio specific element.

The Relationship Between Liquidity, Trading Activity and Return - Studies of the Finnish and Swedish Stock Markets

Liquidity, or how easy an investment is to buy or sell, is becoming increasingly important for financial market participants. The objective of this dissertation is to contribute to the understanding of how liquidity affects financial markets. The first essays analyze the actions taken by underwriters immediately after listing to improve liquidity of IPO stock. To estimate the impact of underwriter activity on the pricing of the IPOs, the order book during the first weeks of trading in the IPO stock is studied. Evidence of stabilization and liquidity enhancing activities by underwriters is found. The second half of the dissertation is concerned with the daily trading of stocks where liquidity may be impacted by policy issues such as changes in taxes or exchange fees and by opening the access to the markets for foreign investors. The desirability of a transaction tax on securities trading is addressed. An increase in transaction tax is found to cause lower prices and higher volatility. In the last essay the objective is to determine if the liquidity of a security has an impact on the return investors require. The results support the notion that returns are negatively correlated to liquidity.

Modeling Nonlinearities and Asymmetries in Asset Pricing

Financial time series tend to behave in a manner that is not directly drawn from a normal distribution. Asymmetries and nonlinearities are usually seen and these characteristics need to be taken into account. To make forecasts and predictions of future return and risk is rather complicated. The existing models for predicting risk are of help to a certain degree, but the complexity in financial time series data makes it difficult. The introduction of nonlinearities and asymmetries for the purpose of better models and forecasts regarding both mean and variance is supported by the essays in this dissertation. Linear and nonlinear models are consequently introduced in this dissertation. The advantages of nonlinear models are that they can take into account asymmetries. Asymmetric patterns usually mean that large negative returns appear more often than positive returns of the same magnitude. This goes hand in hand with the fact that negative returns are associated with higher risk than in the case where positive returns of the same magnitude are observed. The reason why these models are of high importance lies in the ability to make the best possible estimations and predictions of future returns and for predicting risk.

Topics in Spatial Econometrics - With Applications to House Prices

Topics in Spatial Econometrics — With Applications to House Prices Spatial effects in data occur when geographical closeness of observations influences the relation between the observations. When two points on a map are close to each other, the observed values on a variable at those points tend to be similar. The further away the two points are from each other, the less similar the observed values tend to be. Recent technical developments, geographical information systems (GIS) and global positioning systems (GPS) have brought about a renewed interest in spatial matters. For instance, it is possible to observe the exact location of an observation and combine it with other characteristics. Spatial econometrics integrates spatial aspects into econometric models and analysis. The thesis concentrates mainly on methodological issues, but the findings are illustrated by empirical studies on house price data. The thesis consists of an introductory chapter and four essays. The introductory chapter presents an overview of topics and problems in spatial econometrics. It discusses spatial effects, spatial weights matrices, especially k-nearest neighbours weights matrices, and various spatial econometric models, as well as estimation methods and inference. Further, the problem of omitted variables, a few computational and empirical aspects, the bootstrap procedure and the spatial J-test are presented. In addition, a discussion on hedonic house price models is included. In the first essay a comparison is made between spatial econometrics and time series analysis. By restricting the attention to unilateral spatial autoregressive processes, it is shown that a unilateral spatial autoregression, which enjoys similar properties as an autoregression with time series, can be defined. By an empirical study on house price data the second essay shows that it is possible to form coordinate-based, spatially autoregressive variables, which are at least to some extent able to replace the spatial structure in a spatial econometric model. In the third essay a strategy for specifying a k-nearest neighbours weights matrix by applying the spatial J-test is suggested, studied and demonstrated. In the final fourth essay the properties of the asymptotic spatial J-test are further examined. A simulation study shows that the spatial J-test can be used for distinguishing between general spatial models with different k-nearest neighbours weights matrices. A bootstrap spatial J-test is suggested to correct the size of the asymptotic test in small samples.

Customer asset management in action: using customers portfolio for allocating resources across business-to-business relationships for improved shareholder value

Suvi Nenonen Customer asset management in action: using customer portfolios for allocating resources across business-to-business relationships for improved shareholder value Customers are crucial assets to all firms as customers are the ultimate source of all cash flows. Regardless this financial importance of customer relationships, for decades there has been a lack of suitable frameworks explaining how customer relationships contribute to the firm financial performance and how this contribution can be actively managed. In order to facilitate a better understanding of the customer asset, contemporary marketing has investigated the use of financial theories and asset management practices in the customer relationship context. Building on this, marketing academics have promoted the customer lifetime value concept as a solution for valuating and managing customer relationships for optimal financial outcomes. However, the empirical investigation of customer asset management lags behind the conceptual development steps taken. Additionally, the practitioners have not embraced the use of customer lifetime value in guiding managerial decisions - especially in the business-to-business context. The thesis points out that there are fundamental differences between customer relationships and investment instruments as investment targets, effectively eliminating the possibility to use financial theories in a customer relationships context or to optimize the customer base as a single investment portfolio. As an alternative, the thesis proposes the use of customer portfolio approach for allocating resources across the customer base for improved shareholder value. In the customer portfolio approach, the customer base of a firm is divided into multiple portfolios based on customer relationships’ potential to contribute to the shareholder value creation. After this, customer management concepts are tailored to each customer portfolio, designed to improve the shareholder value in their own respect. Therefore, effective customer asset management with the customer portfolio approach necessitates that firms are able to manage multiple parallel customer management concepts, or business models, simultaneously. The thesis is one of the first empirical studies on customer asset management, bringing empirical evidence from multiple business-to-business case studies on how customer portfolio models can be formed, how customer portfolios can be managed, and how customer asset management has contributed to the firm financial performance.

Customer asset management in action: using customers portfolio for allocating resources across business-to-business relationships for improved shareholder value

Suvi Nenonen Customer asset management in action: using customer portfolios for allocating resources across business-to-business relationships for improved shareholder value Customers are crucial assets to all firms as customers are the ultimate source of all cash flows. Regardless this financial importance of customer relationships, for decades there has been a lack of suitable frameworks explaining how customer relationships contribute to the firm financial performance and how this contribution can be actively managed. In order to facilitate a better understanding of the customer asset, contemporary marketing has investigated the use of financial theories and asset management practices in the customer relationship context. Building on this, marketing academics have promoted the customer lifetime value concept as a solution for valuating and managing customer relationships for optimal financial outcomes. However, the empirical investigation of customer asset management lags behind the conceptual development steps taken. Additionally, the practitioners have not embraced the use of customer lifetime value in guiding managerial decisions - especially in the business-to-business context. The thesis points out that there are fundamental differences between customer relationships and investment instruments as investment targets, effectively eliminating the possibility to use financial theories in a customer relationships context or to optimize the customer base as a single investment portfolio. As an alternative, the thesis proposes the use of customer portfolio approach for allocating resources across the customer base for improved shareholder value. In the customer portfolio approach, the customer base of a firm is divided into multiple portfolios based on customer relationships’ potential to contribute to the shareholder value creation. After this, customer management concepts are tailored to each customer portfolio, designed to improve the shareholder value in their own respect. Therefore, effective customer asset management with the customer portfolio approach necessitates that firms are able to manage multiple parallel customer management concepts, or business models, simultaneously. The thesis is one of the first empirical studies on customer asset management, bringing empirical evidence from multiple business-to-business case studies on how customer portfolio models can be formed, how customer portfolios can be managed, and how customer asset management has contributed to the firm financial performance.

Cobreaking of Stock Prices and Contagion

Financial crises have shown that dramatic movements in one financial market can have a powerful impact on other markets. The paper proposes to use cobreaking to model comovements between financial markets during crises and to test for conta-gion. It finds evidence of cobreaking between stock returns in developed markets. Finding cobreaking has implications for the diversification of international investments. For emerging mar-ket stock returns the evidence of cobreaking is mainly due to the non-financial event of the 9/11 terrorist attacks in 2001. Fi-nancial crises originating in one emerging market do not spread to other markets, i.e., no contagion.

An Empirical Study of the Mixture of Time and Movements in Prices

This paper investigates the persistent pattern in the Helsinki Exchanges. The persistent pattern is analyzed using a time and a price approach. It is hypothesized that arrival times are related to movements in prices. Thus, the arrival times are defined as durations and formulated as an Autoregressive Conditional Duration (ACD) model as in Engle and Russell (1998). The prices are defined as price changes and formulated as a GARCH process including duration measures. The research question follows from market microstructure predictions about price intensities defined as time between price changes. The microstructure theory states that long transaction durations might be associated with both no news and bad news. Accordingly, short durations would be related to high volatility and long durations to low volatility. As a result, the spread will tend to be larger under intensive moments. The main findings of this study are 1) arrival times are positively autocorrelated and 2) long durations are associated with low volatility in the market.