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Title: ENVIRONMENTAL PERFORMANCE VS. FINANCIAL PERFORMANCE, MARKET INEFFICIENCY AND INVESTMENTS
Creator: He, Chaohua
Date: 2014, 2014-07
Description: It is challenging to de ne corporate environmental performance or corporate nancial performance. In this study, a company is considered to...
Show moreIt is challenging to de ne corporate environmental performance or corporate nancial performance. In this study, a company is considered to have good environmental performance (namely, be green, environment-friendly or environmentally responsible) if it is among the Top 100 of the 500 US greenest companies ranked by Newsweek, or has environmental strength(s) and no environmental concern in terms of the KLD ratings. A company is regarded to have good nancial performance if it has a high raw return, Sharpe ratio, and excess (or abnormal) return over various benchmarks. Preference will be given to excess return estimated using the Carhart four-factor model [14]. A previous published longitudinal study, co-authored with my advisor [13], unveils that: 1) environmentally responsible companies tend to experience signi cantly positive abnormal performance in the long horizon (e.g. from the fourth to seventh year after being selected); 2) the value-adding e ect and the market's upward price adjustments on undervalued intangible environmental strength(s) might have resulted in the long-term outperformance. Would environmentally responsible companies still outperform during shorter horizons, such as the event period of an environmental disclosure? Using event study methodologies, this paper investigates market responses to independent Newsweek environmental disclosures by analyzing cross-sectional and time-series abnormal security returns. Results suggest that the Top 100 greenest companies tend to display signi cant abnormal returns within 4 days after a disclosure, and the signi cant abnormal returns generally persist for no more than 3 trade days. e.g., the Carhart four-factor abnormal return, with statistical signi cance, is averaged at 0.50% per day over the four disclosure events. The ndings are robust to di erentmodels of normal return, removal of outliers, elimination of confounding e ects, controlling for characteristic factors, and adjusting for cross-sectional correlation and volatility shift on test statistics using BMP-adjusted technology[56]. Signi cant abnormal returns over the event period may indicate ine ciency of the nancial market. Fama-Macbeth regressions further reveal that short-horizon abnormal returns could be explained by a spectrum of characteristic variables, green investing, arbitrage trading, and/or various psychological biases. Complementing the cited longitudinal study, a portfolio-level comparison reveals that an actively managed green portfolio outperforms an actively managed nongreen portfolio in terms of raw return and risk-adjusted measures such as Sharpe ratio, Jensen's alpha and Fama-French alpha in the long horizon. The results are robust to di erent portfolio weighting technologies and the consideration of turnover costs. In addition, the green portfolio's outperformance is driven by a bunch of small, aggressive and relatively inactive stocks that have better performance than the market predicts. No evidence shows that the ever-increasing demand on green securities leads to the green portfolio's outperformance, because green stocks are actually less actively traded. Panel regressions further indicate that long-horizon corporate economic performance positively correlates to historical corporate environmental performance.
Ph.D. in Management Science, July 2014
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Title: INDUSTRIAL UPGRADING IN KOREA
Creator: Woosiklee
Date: 2014, 2014-05
Description: One of the most difficult obstacles facing non-western nations is the issue of technology transfer. The main objective of this dissertation is...
Show moreOne of the most difficult obstacles facing non-western nations is the issue of technology transfer. The main objective of this dissertation is to analyze the how South Korea has succeeded through industrial upgrading through technology transfer in achieving the Han River Miracle- making it in 2011, the fourth largest economy in Asia and the 9th largest in the world. From 1910 to 1945, Korean modernization was continuously developed under the Japanese war economy and its military policy. Japanese capital, technology and entrepreneurs were transferred to Korea due to supplement the shortages of Japanese industries or to take advantage of the low labor costs in Korea in order to prepare for the Sino-Japanese War in 1936 and the Pacific War in 1941. There is no doubt that President Chung-Hee Park (1961-1979) was the architect of the Korean economic miracle. During his authoritarian regime, the government had played an important role in the creation and financing of the modern Korean industrial groupings, called the Chaebols. The government also intervened directly in the formation of their policies. In the 1980s, when the country embarked on financial liberalization, the degree of intervention started to decrease. And finally, the 1997 crisis will be examined, with special attention on the introduction of reforms required by the International Monetary Fund (IMF). In the industrial arena, the focus will be on the rationalization policies undertaken to increase the total factor productivity (TFP). It will cover the currently important industries of steel, automobiles and semiconductors, as well as those promising industries which have led the development of South Korea's knowledge-intensive economy. An integral part of the xi ii analysis will study the repercussions of the 1997 financial reforms on both the large and small and medium-size industries. Conventional wisdom assumes that it was under President Park's rule that South Korea had its first experience with industrialization. This assumption, however, ignores the significant industrialization that took place during the colonial period. It also does not take into account the admittedly limited industrial development that took place during the time before the 1961 coup d'état, when civilian governments were in charge. The dissertation would shed light on these overlooked periods.
PH.D in Management Science, May 2014
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Title: COLLABORATIVE CONSUMPTION: PROFITS, CONSUMER BENEFITS, AND ENVIRONMENTAL IMPACTS
Creator: Supangkat, Hendrarto Kurniawan
Date: 2014, 2014-05
Description: With increasingly connected consumers and technological advancement, peer- to-peer sharing is emerging as a consumer-led initiative, which is...
Show moreWith increasingly connected consumers and technological advancement, peer- to-peer sharing is emerging as a consumer-led initiative, which is aimed to exploit slack capacities and lower the cost of consuming private goods. Sharing is praised for its potential bene ts of improving consumer access, consumer surplus, and environmental impact. On the other hand, sharing may possess credible threats to producers because of cannibalization and reduced sales quantity. This thesis is composed of three papers on the subject of peer-to-peer sharing of durable goods, e.g., cars, bikes, gadgets, and household appliances. The rst paper studies pricing and product design decisions of a single-product monopolist in a market. We identify the conditions under which a rm would accom- modate or hinder peer-to-peer sharing by pricing the product appropriately. We nd that the rm's pro t can be enhanced only when the consumer valuation heterogene- ity is neither too high nor too low, and the product's intrinsic value is su ciently high. In addition, contrary to the conventional wisdom, we show that sharing does not always improve consumer access to products. Furthermore, some consumers may end up being worse o . Finally, we nd that social sharing may enhance or impede product innovation, depending on consumer heterogeneity and the size of sharing groups. In the second paper, we study whether social sharing will encourage or discour- age product di erentiation. We nd that the two ways of expanding the market, one consumer-initiated and one rm-initiated, can be strategic complements or substi- tutes, depending on consumer heterogeneity, group size, product intrinsic value, and cost structure. We characterize such conditions. For example, we show that accom- modating sharing provides the rm a higher incentive to introduce a di erentiated product when the product intrinsic value and consumer heterogeneity are both low, x or are both high. We also extend the study by allowing consumers to endogenously choose their sharing group size, and show that it may enhance or worsen the rm's pro t. The third paper focuses on the environmental impact stemming from produc- tion and consumption, in the presence of peer-to-peer sharing. The product usage of sharing consumers is modeled as a function of capacity congestion and group size. We show that a "danger" zone exists where sharing is pro table for the rm but is not friendly to the environment. When the rm has an in uence on the sharing group size (e.g., by promoting sharing programs in metropolitan areas or college towns), the economic incentive and environmental impact can be aligned. Speci cally, we nd that stronger congestion e ects may induce the producer to promote sharing in larger groups, which in turn results in a more positive environmental impact. Such situations are more likely to occur when the product unit cost is large. Moreover, we characterize conditions under which the rm may prefer heterogeneous networks composed of groups with di erent sizes or social networks with lower homophily, and meanwhile the environmental impact can be improved.
PH.D in Management Science, May 2014
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Title: PRICING AND APPLICATION OF ELECTRIC STORAGE
Creator: Zhao, Jialin
Date: 2017, 2017-05
Description: Electric storage provides a vehicle to store power for future use. It contributes to the grids in multiple aspects. For instance, electric...
Show moreElectric storage provides a vehicle to store power for future use. It contributes to the grids in multiple aspects. For instance, electric storage is a more effective approach to provide electricity ancillary services than conventional methods. Additionally, electric storage, especially fast-responding units, allows owners to implement high-frequency power transactions in settings such as the 5-min real-time trading market. Such high-frequency power trades were limited in the past. However, as technology advances, the power markets have evolved. For instance, the California Independent System Operator now supports the 5-min real-time trading and the hourly day-ahead ancillary services bidding. Existing valuation models of electric storage were not designed to accommodate these recent market developments. To fill this gap, I focus on the fast-responding grid-level electric storage that provides both the real-time trading and the day-ahead ancillary services bidding. To evaluate such an asset, I propose a Monte Carlo Simulation-based valuation model. The foundation of my model is simulations of power prices. This study develops a new simulation model of electric prices. It is worth noting that, unlike existing models, my proposed simulation model captures the dependency of the real-time markets on the day-ahead markets. Upon such simulations, this study investigates the pricing and the application of electric storage at a 5-min granularity. Essentially, my model is a Dynamic Programming system with both endogenous variables (i.e., the State-of-Charge of electric storage) and exogenous variables (i.e., power prices). My first numerical example is the valuation of a fictitious 4MWh battery. Similarly, my second example evaluates the application of two units of 2MWh batteries. By comparing these two experiments, I investigate the issues related to battery configurations, such as the impacts of splitting storage capability on the valuation of electric storage.
Ph.D. in Management Science, May 2017
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Title: SIZE AND VALUE RISK IN FINANCIAL FIRMS
Creator: Baek, Seungho
Date: 2013, 2013-12
Description: Although the Fama and French’s three factor model is now the most popular replacement for CAPM in corporate finance and investment management,...
Show moreAlthough the Fama and French’s three factor model is now the most popular replacement for CAPM in corporate finance and investment management, the exclusion of financial firms can be questioned on both theoretical and empirical grounds. Financial firms are around 19 percent of the value of the U.S. stock market. The financial service industry is the major industry in many large U.S. cities including New York, Chicago, Los Angeles and Miami in that their GDPs of financial services for each city are more than 23 percent. Also, there is no theoretical reason for excluding financial firms. Modigliani and Miller [31] [32] suggest that leverage affects beta, but it does not invalidate the capital asset pricing model. It would therefore be more satisfying if the pricing model applied generally, rather than being restricted to nonfinancial corporations. From this consideration, this paper assesses the validity of size and value risk as common risk factors to measure of expected equity returns in financial companies based on the fact that Fama and French [11] [12] excluded financial firms in their study of the cross-section of expected stock returns. The findings from empirical asset pricing tests suggest that size and value risk premia commonly exist in both nonfinancial and financial firms even if two factors are less explicable in financial firms, that an interest rate risk premium (ΔL/L) which defined as a financial firm specific risk factor only appears in financial companies.
PH.D in Management Science, December 2012
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Title: SYSTEMATIC FINANCE: ESSAYS ON ETHICS, METHODOLOGY AND QUALITY CONTROL IN HIGH FREQUENCY TRADING
Creator: Van Vliet, Benjamin Edward
Date: 2012-04-18, 2012-05
Description: A firm is in a state of strategic competitiveness if it has a plan that it rationally and responsibly believes is capable of success. In the...
Show moreA firm is in a state of strategic competitiveness if it has a plan that it rationally and responsibly believes is capable of success. In the age of automation, what justifies a trading firm’s belief in its strategic competitiveness has changed. Rational and responsible belief in the capability of the firm’s trading strategies can be justified by a prudent process that defines conditions for both initial and sustained belief. The process of developing trading systems is itself systematic and a source of competitive advantage. In this thesis, I present three chapters that address strategic competitiveness in automated trading—ethics, methodology and quality control. These chapters examine responsibility, and develop processes for both initial and sustained belief in the competitiveness of trading systems and the trading firm.
Ph.D. in Management Science, May 2012
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Title: CREDIT DEFAULT SWAP SPREAD FORECASTING USING THE LINEAR BAYESIAN RANDOM COEFFICIENTS MODEL WITH BALANCED PANELS
Creator: Arifi, Imir
Date: 2014, 2014-05
Description: This study (thesis) predicts out of sample one to five year quarterly credit default swap spread curves for subsets of a population comprised...
Show moreThis study (thesis) predicts out of sample one to five year quarterly credit default swap spread curves for subsets of a population comprised of 308 companies via the linear Bayesian Random Coefficient Model (RMC) with balanced panel construction, capturing over 80% of reference entities with liquid CDS term structures. The use of scoring, structural and reduced form model variations generates credit spread tenure points and curves at the company level. The Altman Z-score and classic Merton structural framework explain too little of the credit default swap spreads out of sample. However, The Merton structural framework works well in predicting out of sample credit default swap spreads when modified by deriving the implied leverage ratio via market spreads. The widely used, Bloomberg implemented, JPMorgan 2001(CDSW) model works well for the period the study covers. The Bayesian Random Coefficients model explains 87% of observed credit default swap spreads one quarter out of sample, substantially exceeding any published research on the credit spread forecasting subject.
PH.D in Management Science, May 2014
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Title: MARKOV SWITCHING MODELS OF POPULAR FOREIGN EXCHANGE CARRY TRADE STRATEGIES
Creator: Miller, Larissa J.
Date: 2016, 2016-07
Description: The nature of the carry trade produces periods of steady profitability and periods of extreme terror. The 1980s proved to be a particularly...
Show moreThe nature of the carry trade produces periods of steady profitability and periods of extreme terror. The 1980s proved to be a particularly profitable time period. However, during market crashes in the either equity or bond market, the carry trade is marked with short periods of substantial losses (Menkhoff, Saro, Schmeling, Scrimpf 2012). The global financial crisis of 2007 – 2008 was associated with large losses to carry trades. History repeatedly suggests these two bull and bear states in the economic environment (Fabozzi, Francis 1977). An additional state of market neutrality or stability could also be considered. The purpose of this dissertation is to develop a model of the carry trade with multiple states using the Markov switching methodology. To accomplish this, we use two different popular carry trade strategies: (a) logistic regression and (b) mean-variance optimization. As a benchmark, we include an equally weighted portfolio of long positions in foreign currencies against the dollar. We develop a single state model as well as a normal mixture model for each of the two carry trade strategies. The mixture models assume a static probability of the economy being in either state. However, the financial markets are not static. Applying a Markov chain allows us to build a dynamic model, which allows for new information to determine the probability of the next state. We applied a Markov chain to determine the probability of the current state and the next state to improve trading results. We found the application of a Markov chain did not improve trading performance. The portfolio consists of 12 different currencies including both mature and emerging markets. The training period for determining the weights is 1998 through 2002. Using daily data from 2002 through 2015, we evaluate the performance of each strategy using cumulative returns. These results demonstrate the periods of profitability followed by short periods of terror. Next we evaluate the performance of each strategy with an applied mixture-model. The mixture-model improves the results of each strategy. Applying a Markov chain allows for better determination of both the bear and bull states. We use only the two state environment as the three state environment was unstable.
Ph.D. in Management Science, July 2016
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Title: ELECTRIC VEHICLE (EV) STORAGE SUPPLY CHAIN RISK AND THE ENERGY MARKET: A MICRO AND MACROECONOMIC RISK MANAGEMENT APPROACH
Creator: Aguilar, Susanna D.
Date: 2015, 2015-12
Description: NO ABSTRACT
Ph.D. in Management Science, December 2015

Title: ESSAYS IN ENVIRONMENTAL FINANCE
Creator: Li, Jing
Date: 2013, 2013-07
Description: The Clean Development Mechanism (CDM) is a mechanism de ned in the Ky- oto protocol that incentivizes parties to the protocol to fund...
Show moreThe Clean Development Mechanism (CDM) is a mechanism de ned in the Ky- oto protocol that incentivizes parties to the protocol to fund sustainable development projects in countries that are not party to the protocol. In the rst chapter of this paper, I introduce the CDM and how the nancing mechanism works. In the second chapter, I analyze a target contract nancing structure for di erent CDM projects in order to see under what conditions the nancing structure is e cient and to explore the contract's allocation of pro t among the rms. In the two broad categories of CDM projects I consider, I nd the optimal investment decision for the investor and for the overall system. I also analyze how the residual value of technology would a ect the nancing, target contract's e ciency, and allocation of pro t. In the third chapter, I conduct empirical analysis on the actual CDM outputs, Certi ed Emission Reduction units (CERs), for a sample of wind CDM projects in China. I nd that CDM projects greatly under perform relative to the promises they make. Based on this under-performing records, in the fourth chapter, I analyze the economic bene ts investors could gain if they were able to directly fund a portfolio of CDM projects and obtain returns from the anticipated CER issuances and underlying energy generated from the portfolio of CDM projects. I consider a variety of funding constraints that the CDM fund/portfolio manager (CDM-PM) may face and determine their economic performance against actual CDM project data for wind CDM projects in China.
PH.D in Management Science, July 2013
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Title: ALTERNATIVE APPROACH TO VOLATILITY FORECASTING AND EVALUATING FORECASTING PERFORMANCE
Creator: Lim, Hyungjin
Date: 2012-10-08, 2012-12
Description: Studies in the volatility process of financial markets have focused more on volatility modeling aspects, using parametric assumptions....
Show moreStudies in the volatility process of financial markets have focused more on volatility modeling aspects, using parametric assumptions. Compared with the vast amount of research in parametric modeling, there is a lack of studies in nonparametric approaches in volatility forecasting and forecasting performance evaluation. This research intends to explore alternative approaches to forecasting volatility of financial returns, and evaluation of forecasting models. This research will employ grammatical evolution to propose a hybrid forecasting model that utilizes the benefits of parametric and genetic programming models. Furthermore, an alternative methodology to handle structural breaks in volatility is examined by utilizing an adaptive approach in dynamic environments. In an extensive empirical study, the proposed models will be compared with the other models widely used in the literature using statistical and economic tests. Specifically, as an alternative to the statistical performance evaluation measure, a nontraditional method derived from the idea of speculating on asset volatility will be employed to compare the performance as well as to assess economic usefulness of competing volatility models. The hybrid model provided superior forecasting performance than traditional techniques both on economic and statistical measures.
PH.D in Management Science, December 2012
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Title: DEVELOPING ALGORITHMIC TRADING STRATEGIES AND EMPIRICAL ANALYSIS WITH HIGH FREQUENCY TRADING DATA
Creator: Lee, Jeonghoe
Date: 2015, 2015-07
Description: The PhD dissertation research topics aim at developing algorithmic trading strategies and demonstrating data analysis skills. To be a...
Show moreThe PhD dissertation research topics aim at developing algorithmic trading strategies and demonstrating data analysis skills. To be a quantitative analyst as well as an academic scholar in financial trading area, these two professional backgrounds are indispensable. In detail, chapter 1 shows multi-objective optimization and spontaneous optimization of design variables. For instance, while conventional trading systems explore a single objective function, multi-objective optimization allows us to manage the essential trade-off among profit, standard deviation and maximum-drop. In addition, design parameters such as trading volume, the amount of historical data, and trading gateways of technical indicators are continuously optimized in real time. In chapter 2, this chapter shows an algorithmic trading system with the concept of machine learning, and demonstrating its various applications. The main purpose of this research is to propose objective numerical development framework in algorithmic trading. Chapter 3 pursues understanding liquidity measures which are critical for algorithmic traders and investors. Various liquidity measures have been suggested and they have different sensitivities to the market. This research analyzes liquidity measures and clarifies the relation between market price return & realized volatility and liquidity measures. In sum, with these three chapters, this dissertation will demonstrate necessary research topics in algorithmic trading.
Ph.D. in Management Science, July 2015
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Title: MODELING STRATEGIC COMPETITION, TACTICAL DESIGN, AND OPERATIONAL PLANNING TO IMPROVE SUPPLY CHAIN PERFORMANCE
Creator: Li, Chia-hang
Date: 2017, 2017-05
Description: A supply chain is a network of facilities responsible for the production and delivery of goods and services from the initial raw materials to...
Show moreA supply chain is a network of facilities responsible for the production and delivery of goods and services from the initial raw materials to the end customers. Supply chain management, therefore, involves management of activities both within and among the organizations throughout the chain at every level of business management. In this dissertation, we address three specific supply chain problems at three distinct level of business management: (1) Operational capacity and production planning; (2) Tactical closed-loop channel structure design; and (3) Strategic platform competition. In each work, we identify strategies that lead the supply chain improvements.
Ph.D. in Management Science, May 2017
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Title: HIGH-FREQUENCY TRADING, LOW-FREQUENCY TRADING AND THE LIMIT ORDER MARKET
Creator: Li, Kun
Date: 2015, 2015-07
Description: The emergence of High-Frequency Trading (HFT) has met with mixed reactions in both investment and academic communities. However, there still...
Show moreThe emergence of High-Frequency Trading (HFT) has met with mixed reactions in both investment and academic communities. However, there still exist gaps on distinguishing and interpreting the impact of HFT on the Low-Frequency Trading (LFT) side. In this thesis, I present three chapters that address the impact of HFT to LFT. I find evidence to distinguish trading generated by HFT in the limit order market, and consequently apply to explore how HFT affects LFT in terms of the liquidity and the order execution quality. In addition, I further explore the fleeting orders generated by HFT and their impact on the liquidity of LFT.
Ph.D. in Management Science, July 2015
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Title: VOLATILITY FORECASTING USING A DECISION-BASED ATTRIBUTION FRAMEWORK
Creator: Li, Tingting
Date: 2016, 2016-05
Description: This research develops a portfolio volatility forecasting method for absolute return equity strategies with consideration of managers’...
Show moreThis research develops a portfolio volatility forecasting method for absolute return equity strategies with consideration of managers’ investment skills. Besides the portfolio holdings and prices that are commonly used by existing volatility forecast methodologies, the method proposed in this research takes account of investment skills and their volatility attribution. Investment skills are indicated by decisions of constructing portfolio overtime. Portfolio volatility is attributed to investment decisions through use of decision-based performance attribution model. It is shown that tracking the information contained in the time series of investment decision attribution leads to better volatility forecasts than commonly used forecasting methods which directly use returns and holdings. The forecasting method proposed has advantage of explaining risk forecast in terms of actual investment decisions, and changes to those decisions in real time.
Ph.D. in Management Science, May 2016
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Title: RISK SHIFTING, MANAGER SENTIMENT AND NEW INVESTMENT EFFICIENCY IN MANAGED FUTURES
Creator: Jiang, Cheng
Date: 2017, 2017-05
Description: This dissertation focuses on a subset of hedge fund, Commodity Trading Advisors (CTAs), which has grown in the past 35 years and highlighted...
Show moreThis dissertation focuses on a subset of hedge fund, Commodity Trading Advisors (CTAs), which has grown in the past 35 years and highlighted by its diversification benefit to traditional asset classes. I will study the risk-taking, market timing and market capacity of this type of hedge fund. I study the volatility of an extensive sample of live and defunct Commodity Trading Advisor funds from 1994 to 2013. Utilizing the gross-of-fee return, I document significant mean-reversion in volatility in the time series of CTA funds. I further examine the impact of performance on volatility shift, and find consistent evidence of risk tournament behavior, especially when the CTA industry is performing well. Moreover, the risk shifting of CTA managers depend upon both relative and absolute fund performance. The practice of this conditional risk shifting has benefitted the fund managers at the cost of fund investors. I estimate the average benefit to manager's return income and the average cost to investor's Sharpe ratio. My findings provide a first comprehensive evidence on the risk strategy of CTA funds, suggesting that managerial career concerns do not eliminate the moral hazard problem in the CTA space. The asymmetric nature of performance-based compensation in hedge funds produces a strong incentive for risk-shifting, but empirical research presents mixed evidence of risk-seeking behavior. The driver of the change in risk can also be related to other reasons other than incentive fees. I introduce a behavioral regime-switching model of fund manager sentiment in which Bayesian learning is used to update beliefs about market environment in an effort to predict future performance and anticipate market moves. I use a subset of hedge funds in the managed futures industry between 1994 and 2014 and find that the risk-taking behavior of fund managers is influenced by human emotions but in two distinctly different ways. The capital flow to hedge funds has well-known price pressure and smart money effect. This paper studies the capital flows impact on CTA future performance. It had been observed both in mutual funds and hedge funds that mangers scale their existing holding up or down by using new capital inflow rather than trade new positions. This strategy will generate positive returns for the funds due to the price pressure effect. It is interesting whether it will exist in managed future space. I use Vector auto-regression (VAR) to evaluate a system of 2 variables: capital inflow and future performance. If the relationship is negative, one possible reason could be the market impact that erodes the profit generated by price pressure. Therefore, I will implement a market impact test that investigate the market capacity in terms of Sharpe ratio and t-statistics of alpha.
Ph.D. in Management Science, May 2017
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Title: THE BUSINESS CYCLE, FORECAST HORIZONS AND STOCK RETURN PREDICTABILITY
Creator: Irons, Robert
Date: 2012-12-04, 2012-12
Description: This paper investigates the impact of the business cycle when forecasting equity returns over different forecast horizons. Weigand and Irons ...
Show moreThis paper investigates the impact of the business cycle when forecasting equity returns over different forecast horizons. Weigand and Irons [2007] show that relative valuation matters when forecasting long-term returns to the market, a conclusion that is verified in this study with reference to the period 1934-1949. This study reveals that the business cycle matters when forecasting short-term (one year or less) market returns, over the entire period of study (1934-1999). An econometric issue first noted in Weigand and Irons [2008] is verified and pinpointed more precisely in time, to the year 1950. The market earnings yield (the inverse of the market P/E ratio), one of the foremost predictors of future market returns, is shown to be ineffective in forecasting returns over any forecast horizon in the second half of the 20th century. This result is further evidence of the impact of investors' belief in the Fed Model, which equates the yields on bonds to the returns on stocks. The term spread of interest rates, one of the business cycle proxies used in this paper, is shown to have a significant impact when forecasting market returns over any horizon during the period 1950-1999, which is consistent with the Fed Model.
PH.D in Management Science, December 2012
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Title: BAYESIAN MOMENTUM STRATEGY OF EXCHANGE RATES
Creator: Lee, Namhoon
Date: 2011-11, 2011-12
Description: A disagreement has existed between the foreign currency trading community and academic researchers relating to the time series properties of...
Show moreA disagreement has existed between the foreign currency trading community and academic researchers relating to the time series properties of exchange rates. Traders typically view exchange rates as strongly trending prices and suggest that simple rules, based solely on past prices, have generated predictable profits with acceptable risk over most of the floating-rate period. However, many surveys presenting controversial results. This research identifies the non-linear trend momentum in monthly exchange rate and examines the profitability of momentum trading model within exchange rate returns in the context of Bayesian econometrics. A development of Bayesian momentum trading strategy based on trend component of the spot exchange rate is established. First, parameters of momentum model for each main currency are estimated. The momentum is defined as a simple nonlinear function of return series and the model is designed to estimate the expected conditional mean and associated conditional volatilities simultaneously. The empirical results reported several notable confirmation and findings; first, predictability of momentum model with Bayesian approach show better accuracy than model with maximum likelihood estimation or moving average rule in terms of directionality and model fitting. Second, parameters are restricted to be same across the currencies with the assumption that currencies share some degree of commonality within the system. The result confirms that the restricted model work as well as the unrestricted model within the currency model in terms of model fitting and directional accuracy. Third, principal component analysis is used to analyze the exchange rate movements. PCA found that the first principal component shows parallel shift of all currencies and second principal component tilt shift where high yield currencies move down and low yield currencies move up. Fourth, the parameter estimates from the models are used for portfolio allocation ix applying Bayesian Principal Component(PC) GARCH(1,1) model and the portfolio performance is compared with the performance with classical maximum likelihood approach and other benchmarks. The results show that the Bayesian PC-GARCH(1,1) performs better than classical PC-GARCH(1,1) in terms of Sharpe ratio, Value at Risk, Expected shortfall, maximum drawdown and other statistical criteria. Sixth, the GARCH parameter space is found to be non-symmetric confirming that maximum likelihood estimation would have over or under estimated the parameter causing misspecifying the model parameters. The result from this research confirms simple nonlinear momentum model combined with Bayesian approach can be a good forecasting tool, and restricted model can simplify the complexity of parameter space of exchange rate movement. In addition, by correctly detecting the parameter space, Bayesian approach outperforms the classical maximum likelihood approach. Keywords : Bayesian framework, Momentum, Moving Average rules, Carry trade strategy, Mean-variance Optimization, Trading strategy, Metropolis-Hastings Algorithm, Gibbs Sampler
Ph.D. in Management Science, December 2011
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Title: CREDIT DERIVATIVES AND COUNTERPARTY CREDIT RISK UNDER VOLATILE MARKETS
Creator: Li, Dan
Date: 2012-11-20, 2012-12
Description: Both counterparty credit risk and credit derivatives have come under greater scrutiny under volatile markets especially after the 2007’s...
Show moreBoth counterparty credit risk and credit derivatives have come under greater scrutiny under volatile markets especially after the 2007’s credit crunch and the 2008’s global recession. This dissertation covers three essays topics that reflect different perspectives in credit derivatives and counterparty credit risk under volatile markets. In the first essay topic, we focuses on the modeling challenge after the 2007/2008 crisis in counterparty risks measurement by introducing a 4-factor model for simplicity with extensive comparison with a 2-factor model for both pre-crisis and post-crisis scenarios. Besides the correlation effects and basis risks concluded from the experimental results, those also implied the urgent needs for regulatory standardization (and transparency) for counterparty risk management (e.g. CVA, CSA, collateralization, etc.). Since CDS is one of the main hedging instruments for counterparty risks, therefore, we then tackle CDS in volatile market in our second essay topic. We will review some common practices in handling CDS since the standard bootstrapping failed using conventional JPM (2001). We will also examine the corresponding assumptions and limitations of the latest CDS standardization (ISDA (2009)). And we will compare this with the conventional CDS model. The third essay topic is a modeling survey on CDS with a special underlying – loan (LCDS) that unveils the potential usage and corresponding limitations of each prevailing modeling approach.
PH.D in Management Science, December 2012
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Title: Combined Optimization Model for Sustainable Energization Strategy
Creator: Abtew, Mohammed
Date: 2011-04-01, 2011-05
Description: Access to energy is a foundation to establish a positive impact on multiple aspects of human development. Both developed and developing...
Show moreAccess to energy is a foundation to establish a positive impact on multiple aspects of human development. Both developed and developing countries have a common concern of achieving a sustainable energy supply to fuel economic growth and improve the quality of life with minimal environmental impacts. The Least Developing Countries (LDCs), however, have different economic, social, and energy systems. Prevalence of power outage, lack of access to electricity, structural dissimilarity between rural and urban regions, and traditional fuel dominance for cooking and the resultant health and environmental hazards are some of the distinguishing characteristics of these nations. Every year, 1.5 million people die due to exposure to indoor biomass stoves fumes. Rising demand for the decreasing supply of fuel wood is evident. Desertification is estimated to put 135 million people at a risk of being driven away from their land if no action is taken by 2020. Most energy planning models have been designed for developed countries' socio-economic demographics and have missed the opportunity to address special features of the poor countries. Therefore, it is critical to develop models that address the unique social-economic demographics of LCDs and are instrumental to appropriate energy policies choices. Such models must consider energization beyond electricity supply and help reduce over reliance of LCDs on limited energy sources that are fraught with high volatility and health hazard, thus providing a stable supply of energy that these countries badly need to meet their sustainable development goals. An improved mixed-integer programming energy-source optimization model is developed to address limitations associated with using current energy optimization models for LDCs, tackle development of the sustainable energization strategies, and ensure diversification and risk management provisions in the selected energy mix. The Model predicted a shift from traditional fuels reliant and weather vulnerable energy source mix to a least coast and reliable modern clean energy sources portfolio, a climb on the energy ladder, and scored multifaceted economic, social, and environmental benefits. At the same time, it represented a transition strategy that evolves to increasingly cleaner energy technologies with growth as opposed to an expensive solution that leapfrogs immediately to the cleanest possible, overreaching technologies.
Ph.D. in Management Science, May 2011
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