A Network Model of Financial Markets

This thesis introduces a network representation of equity markets.The model is based on the premise that assets share dependencies on abstract ‘factors’ resulting in exploitable patterns among asset price levels.The network model is a collection of long-run market trends estimated by a 3 layer machine learning framework.The network model’s comprehensive validity is established with 2 simulations in the fields of algorithmic trading, and systemic risk.The algorithmic trading validation applies expectations derived from the network model to estimating expected future returns. It further utilizes the network’s expectations to actively manage a theoretically market neutral portfolio.The validation demonstrates that the network model’s portfolio generates excess returns relative to 2 benchmarks. Over the time period of April, 2007 to January, 2014 the network model’s portfolio for assets drawn from the S&P/ASX 100 produced a Sharpe ratio of 0.674.This approximately doubles the nearest benchmark. The systemic risk validation utilized the network model to simulate shocks to select market sectors and evaluate the resulting financial contagion.The validation successfully differentiated sectors by systemic connectivity levels and suggested some interesting market features. Most notable was the identification of the ‘Financials’ sector as most systemically influential and ‘Basic Materials’ as the most systemically dependent. Additionally, there was evidence that ‘Financials’ may function as a hub of systemic risk which exacerbates losses from multiple market sectors

The bond premium in a DSGE model with long-run real and nominal risks

The term premium on nominal long-term bonds in the standard dynamic stochastic general equilibrium (DSGE) model used in macroeconomics is far too small and stable relative to empirical measures obtained from the data - an example of the "bond premium puzzle." However, in models of endowment economies, researchers have been able to generate reasonable term premiums by assuming that investors face long-run economic risks and have recursive Epstein-Zin preferences. We show that introducing these two elements into a canonical DSGE model can also produce a large and variable term premium without compromising the model's ability to fit key macroeconomic variables.

Globalization and monetary policy: an introduction

Greater openness has become an almost universal feature of modern, developed economies. This paper develops a workhorse international model, and explores the role of standard monetary policy rules applied to an open economy. For this purpose, I build a two-country DSGE model with monopolistic competition, sticky prices, and pricing-to-market. I also derive the steady state and a log-linear approximation of the equilibrium conditions. The paper provides a lengthy explanation of the steps required to derive this benchmark model, and a discussion of: (a) how to account for certain well-known anomalies in the international literature, and (b) how to start "thinking" about monetary policy in this environment.Monetary policy ; Equilibrium (Economics) ; Globalization ; Macroeconomics ; International finance ; Mathematical models

Extracting information from option prices in the markets

By their nature, options markets are forward-looking. The riskneutral densities (RND) provide information on market’s view regarding the future movements of the underlying index and the perception of the risk. In Chapter 2, we use S&P 500 index option prices and the recently introduced China’s 50 Exchange-Traded Fund options to extract densities and find that all methods adopted fit both option data well. However, the non-parametric method outperforms the parametric approaches on the basis of RMSE, MAE, and also the MAPE. We also investigate the dynamic behavior of the densities from smoothing the implied volatility smile in both markets, especially the impacts of higher moments on the price levels and returns of underlying assets. Chapter 3 examines the impact of macroeconomic announcements on S&P 500 option prices and 50 ETF option prices. We aim to distil information with the RND from both options data by employing the stochastic volatility inspired (SVI) method. We investigate the densities and test market efficiency based on the impact of implied moments on current returns. Furthermore, we also distinguish between types of the macroeconomic indicators and examine the reactions of RNDs. In Chapter 4, we apply the Recovery Theorem of Ross (2015) to deduce both the physical distribution and pricing kernel from option prices. The time-homogeneity and irreducibility of the Markov Chain and the path-independence in pricing kernel are two main restrictions. This study aims to test the efficiency of the Recovery Theorem with the application to the options written on Adidas AG. The interpretation of risk aversion and real-world probability distribution is provided. Chapter 5 concludes

Market implied funding liquidity and asset prices

PhD ThesisThis study examines a market-wide liquidity measure based on systematic deviations from Put-Call parity in US equity option markets. We show that this implied funding liquidity measure significantly predicts future excess market returns and explains cross-sectional variations of stock returns. We provide evidence that investing in stocks with the largest exposure to the innovations in implied funding liquidity and shorting stocks with the smallest generate significant returns of about 7.3% per annum. We also observe that implied funding liquidity significantly predicts future changes in a number of macroeconomic variables over a horizon of six months. This result indicates that the funding liquidity measure obtained from the option markets provides forward-looking information about developments in the economy. Furthermore, we also examine the relationship between implied funding liquidity and the cross section of excess returns arising from the carry trades, which are strategies for investing in high interest rate currencies while borrowing in low interest rate currencies. We show that this implied funding liquidity is significantly associated with high interest rate currencies. We also consider the assetpricing implications of the funding liquidity for other asset classes such as hedge funds

Unbiased forward rate and time horizon in emerging economies and implications to hedging practices

PURPOSE OF THE STUDY: The purpose of this study is to test the unbiased forward rate hypothesis in emerging economies and the impact of time horizon. The unbiased forward rate hypothesis tests whether a forward rate is an unbiased predictor of future exchange rate. The implications of findings on hedging foreign exchange risk are intended to be analyzed. DATA AND METHODOLOGY: The data consists of monthly observations of exchange rates and forward premiums for the maturities of 1-, 3-, 6- and 12-months for ten emerging economies: Brazil, Chile, Czech Republic, India, Indonesia, Mexico, Russia, South Africa, South Korea and Turkey. The exchange rate data is retrieved from Bloomberg terminal and all the quotes are against US dollar. For the aforementioned maturities, the unbiased forward rate hypothesis is tested with the Fama regression model using Newey-West standard errors. The time horizon effect for maturities of one and five years is examined by a graphical depiction of the forward prediction error in exchange rate terms. The five year forward premium is approximated by a sum of five consequent one year forward premiums. FINDINGS: On one month interval, the unbiased forward hypothesis is rejected in the emerging economies. Extending the time horizon to one year, the regression model produces increasingly biased estimates of future exchange rate. The graphical depiction of forward forecast error confirms the findings from the regression model. When comparing the one year bias to five year bias, measured in exchange rate terms, the bias is found to increase along with the extended time horizon. In the majority of the sample countries, on the five year maturity the forward prediction error becomes consistently positive implying that the five year forward rate is a systematically upwards biased predictor of future exchange rate. The impact on hedging performance depends on which currency the entity in question is selling and which currency it is buying with the forward contract. Hedging an emerging market currency denominated foreign exchange risk on a five year horizon has either been systematically profitable or unprofitable throughout the sample

Money and capital

We revisit classic questions concerning the effects of money on investment in a new framework: a two-sector model where some trade occurs in centralized and some in decentralized markets, as in recent monetary theory, but extended to include capital. This allows us to incorporate novel elements from the microfoundations literature on trading with frictions, including stochastic exchange opportunities, alternative pricing mechanisms, etc. We calibrate models with bargaining and with price taking in the decentralized market.Money ; Capital ; Monetary policy