Jitka Hilliard

Estimating Early Exercise Premiums on Gold and Copper Options Using a Multifactor Model and Density Matched Lattices

We use the standard geometric Brownian motion augmented by jumps to describe the spot underlying and mean regressive models of interest rates and convenience yields as state variables for gold and copper prices. Estimates of parameters of the diffusion processes are obtained by the Kalman filter. Using these estimates, jump parameters are estimated in the second stage by least squares. Early exercise premia on puts and calls are computed using a lattice with probabilities assigned by the density matching technique. We find that while deep in the money options have greater absolute early exercise premiums, the early exercise premium is roughly constant as a percent of option price. Our findings also confirm that gold behaves like an investment asset and copper behaves like a commodity.

A Comparison of Rebalanced and Buy and Hold Portfolios: Does Monetary Policy Matter?

We examine buy and hold and a number of rebalancing strategies on a portfolio of indices that are tracked by ETFs. The indices include Barkleys treasuries and MSCI indices on emerging markets, Pacific and European markets, value funds, and growth funds. Portfolios are rebalanced using threshold schemes and compared with portfolios rebalanced using weights from different points on the Markowitz efficient frontier. We also examine portfolios that are rebalanced across monetary policy regimes. We find that portfolios rebalanced using Markowitz weights that allow for shifts in monetary policy regimes easily outperform both threshold rebalancing and buy and hold strategies.

Pricing American options when there is short–lived arbitrage

Models in financial economics derived from no-arbitrage assumptions are standard fare among theoreticians and practitioners. However, several authors have investigated the impact of short lived arbitrage on European options using models borrowed from disequilibria in physics. In this paper, we extend that research by assessing the impact of arbitrage on American options. We use an Ornstein-Uhlenbeck Bridge as a model for the arbitrage process and calculate American option prices using a bivariate lattice with density matched probabilities. We find that arbitrage correlated with the underlying has an economically meaningful sizeable impact on option prices. Short lived arbitrage has essentially virtually no economic impact on option prices when the arbitrage is uncorrelated with underlying asset returns.

Timing versus Buy and Hold: A Model for Determining Predictive Accuracy Required for Superior Performance

In this application, we develop a model to simulate the decisions of a trader whose subjective distribution of returns may be correlated with realized stock returns. Using empirically estimated parameters from stocks in the CRSP database, we obtain performance data on a number of measures, including mean returns, volatility, the Sharpe measure, and the probability of a correct trading decision. The model suggests that daily trading of a portfolio of 20 volatile stocks gives a Sharpe measure better than that of buying and holding the S&P 500 when timing accuracy is 53% or better.

Rebalancing versus Buy and Hold: Theory, Simulation and Empirical Analysis

We consider returns from rebalanced and buy and hold portfolios consisting of the same stocks. Theoretical properties are derived using Jensen’s inequality and the Holder’s Defect Formula. Simulations are used to confirm theory and to investigate ambiguous cases where theory is silent. Rebalancing decreases total return volatility, while buy and hold produces greater expected return. Results are more opaque with respect to Sharpe Ratios and expected geometric means. Our empirical tests are based on portfolios composed of the risk-free asset, CRSP market value returns and returns from five Fama–French industries. While rebalancing reduces volatility and momentum effect, our tests largely favor the buy and hold strategy due to the high relative returns enjoyed by stocks vis-a-vis the risk-free asset. Transactions cost for rebalancing the portfolio are economically negligible.

Option pricing under short-lived arbitrage: theory and tests

Models in financial economics derived from no-arbitrage assumptions have found great favor among theoreticians and practitioners. We develop a model of option prices where arbitrage is short lived. The arbitrage process is Ornstein-Uhlenbeck with zero mean and rapid adjustment of deviations. We find that arbitrage correlated with the underlying can have sizeable impact on option prices. We use data from five large capitalization firms to test implications of the model. Consistent with the existence of arbitrage, we find that liquidity factors significantly effect arbitrage model parameters.

Market Sentiment as a Factor in Asset Pricing

This paper explores whether market sentiment should be used as an additional factor in the asset-pricing model. We use a unique dataset from Investor Intelligence as a direct measure of market sentiment. We form ten portfolios based on their correlations with the new market sentiment measure. Following Fama and French (1993) we build a market sentiment factor (SENT) and add this factor to the Carhart four-factor model. We find that SENT is significant for all portfolios in the sentiment augmented four-factor model and increases explanatory power of the model measured by adjusted R2s. We also find that the addition of SENT factor reduces the explanatory power of all other risk factors in the four-factor model.This paper explores whether market sentiment should be used as an additional factor in the asset-pricing model. We use a unique dataset from Investor Intelligence as a direct measure of market sentiment. We form ten portfolios based on their correlations with the new market sentiment measure. Following Fama and French (1993) we build a market sentiment factor (SENT) and add this factor to the Carhart four-factor model. We find that SENT is significant for all portfolios in the sentiment augmented four-factor model and increases explanatory power of the model measured by adjusted R2s. We also find that the addition of SENT factor reduces the explanatory power of all other risk factors in the four-factor model.

How Does a Borrower's Education Influence Demand for Peer-to-Peer Funding? New Evidence from China

This paper examines the role of education level in China’s fast-growing peer-to-peer (P2P) lending market. The level of education, as part of a borrower’s profile, is an important yet relatively neglected factor that can affect both the demand and supply of credit in an increasingly more technologically-oriented marketplace. With this in mind, we test the relationships between borrowers’ education levels and interest rates, loan amounts, and loan maturities in China’s P2P marketplace. Based on more than 10,000 transactions from Renrendai.com and, controlling for a variety of other factors, we find that individuals with higher education levels obtain lower interest rates, larger loan amounts and longer maturities.

The US Financial Crisis and Corporate Dividend Reactions: For Better or for Worse?

We examine how changes in dividend policy in 2008 as the financial crisis was unfolding influenced firm risk-adjusted returns in the following years. Our sample consists of NYSE- and NASDAQ-traded firms that paid dividends in 2007. We divide these firms into four groups based on their dividend policy in 2008. We find that firms that decreased or eliminated dividends in 2008 had higher risk-adjusted returns in 2009. The higher risk-adjusted return is consistent with the better corporate governance in 2007. This finding suggests that the firms that quickly reacted to the deteriorating economic conditions by cutting dividends and preserving cash were able to better weather the coming financial crisis.

Matching non-synchronous observations in derivative markets: choosing windows and efficient estimators

Equilibrium and arbitrage-based option pricing models are based on the assumption that the derivative and its underlying asset are simultaneously observable. However, empirical testing with transactions data must deal with less than perfect synchronicity and windows defining a ‘match’ between the derivative and its underlying must be specified. A narrow window minimizes measurement error at the expense of a smaller sample size. The analysis in this paper assumes Poisson transaction arrivals and smooth diffusion price processes. Optimal windows and efficient estimators are derived and further evaluated by simulation. Benchmarks options are chosen using data from pit-traded S&P 500 futures options and Globex traded Euro options.