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This edition of the OECD Sovereign Borrowing Outlook reviews developments in response to the COVID-19 pandemic for government borrowing needs, funding conditions and funding strategies in the OECD area.
This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.
My dissertation consists of three chapters that examine how information production by financial intermediaries impacts on the capital market.My first chapter investigates whether extreme but rare events, i.e., major climatic disasters, influence the productivity of professional financial analysts, whose output is highly crucial in the capital market. We use 21 major natural disasters in the U.S. and find that disaster-zone analysts reduce their forecast accuracy by reiterating their previous forecast within 3 months after disasters. This effect is driven by distracted attention, rather than resource constraints. Though the effect is short term, we reveal a spillover negative impact from climatic disasters to information environment of firms which do not experience disasters, via the channel of disaster-zone analysts, highlighting the importance of the financial intermediary and also the economic consequences of severe climate events. My second chapter is motivated by the increasing global expansion by U.S. firms in recent decades and examines how geographic distribution of U.S. firms' offshore network affects the coverage incentive of non-U.S. analysts. We combine analyst country location database and the novel dataset of offshore activities by Hoberg and Moon (2017) who quantify a U.S. firm's local exposure in a foreign country and we discover that foreign analysts, are more likely to initiate coverage of U.S. firms with offshore activities in their domiciled countries and provide more accurate forecasts compared to non-domiciled foreign analysts. This study uncovers an important channel, i.e., offshore network, through which non-U.S. analysts can contributes to U.S. market with information advantage. In my third chapter, I study an emerging group of equity analysts, i.e., social media analysts, who post equity research on social media platforms and share investment opinions. I employ initial public offering (IPO) as a laboratory setting because during pre-IPO period, a period with high information asymmetry, professional sell-side analysts are restricted to issue reports under the restriction enforced by SEC, which provides a great setting to study the informational role of this group. I exploit research articles on Seeking Alpha website and find that pre-IPO social media analyst coverage has a positive impact on first day initial return, with the effect driven by heightened retail investor attention. This study highlights the role of social media analysts, as a new information intermediary in the capital market during the internet era.
My dissertation consists of three chapters which address questions in international finance and currency economics. Chapter 1 studies the persistence of covered interest rate parity (CIP) deviations. Since global financial crisis (GFC), the CIP deviations have implied a persistent dollar financing premium for banks versus other major currencies. In this paper, I decompose the CIP deviation into three parts: credit spread differential between U.S. and non- U.S. economies, bank’s default premium, and the liquidity needs of global banks. Then I empirically examine whether the data accords with the model predictions, and find that the relative significance of each component in CIP deviation has changed over time, as default premium was the dominant driver around GFC, credit spread differential has been catching up significantly in recent years. In chapter 2, we use a joint model of macroeconomic and term structure dynamics to estimate the term premia and inflation risk premia embedded in the euro area and U.S. sovereign bonds yields. We find that the fall in real risk premia has been the primary driver of declining yields, given ECB assets purchases and forward guidance which lowered the uncertainty over the projected path of short-term rates. In addition, contrary to the Federal Reserve, the ECB’s new strategy review has yet to lift inflation expectations in our sample period with financial markets expecting inflation to remain below 2 percent. We subsequently build a model of the term premia to forecast the euro area 10-year yield curve and find that yields will likely remain depressed over the medium-term under various scenarios. In chapter 3, we examine the economic determinants of the foreign exchange uncertainty with a focus on options prices. FX option prices theoretically contain information over and above that is included in the spot exchange rate markets, as they reflect the market’s perception of the uncertainty surrounding future exchange rate developments. However, little research efforts have been devoted to examine the economic determinants of the FX uncertainty with a focus on options prices. This paper addresses this issue using the option data by characterizing the economic determinants of FX market un- certainty. In a data-rich environment containing a large number of macroeconomic variables, we find that shocks of output and income variables, as well as monetary and credit variables generate significant and consistent impacts on the general risk sentiment and tail risk in the FX market. Shrinkage method of group LASSO also selects macroeconomic fundamentals and financial variables to have consistent impacts on FX market uncertainties. Besides the standard linear analyses, we adopt the neural network method to examine the non-linear association between economic determinants and FX option volatility. The results connect the time-varying FX market risks at both short and long term with macroeconomic fundamentals, and may in addition suggest that financial uncertainty co-movements also exist in currency markets.
This thesis studies how information affects trading and firm investment. In the first chapter I examine the conditions for the no-trade theorem to hold in multiperiod consumption settings and show it no longer holds in many reasonable scenarios. In situations where agents have different concerns for intertemporal substitution, information-based trade can be mutually acceptable because it enables agents to readjust their consumption profiles based on future consumption shocks. I show that the existing literature that finds no-trade results in various multiperiod consumption settings crucially depends on specific preference assumptions that lead to risk aversion dominating concerns for intertemporal substitution. The no-trade theorem fails to hold when a wider range of utility functions with a more important role for intertemporal substitution are considered.Chapter 2 presents quantitative analysis on the intertemporal substitution as a rational channel to generate trading. Intertemporal substitution bridges information-based trading and consumption-based asset pricing. Consumption-based asset pricing models are natural candidates to analyze information-based trading, and information-based trading affects the volatility of individual consumption processes. Quantitative analysis demonstrates that besides asset pricing implications, information-based trading related to intertemporal consumption smoothing can also explain a significant part of the trading volume observed in financial markets.Finally, Chapter 3 studies how a firm's growth is affected by the evolution of its external debt financing environment. Asymmetric information about the qualities of projects the firm can undertake makes external financing costly. Collateral can mitigate this problem, but its availability is limited by the size of the firm. As a firm grows, more collateral becomes available, broadening the firm's access to external debt financing channels and lowering its cost of capital. The firm's growth decision is affected by how effective additional collateral can be in lowering its cost of capital and the amount of assets it needs to accumulate to broaden its access to potential lending channels. A small firm may optimally choose to stay small when it is financially constrained and far from the size necessary to have access to formal lending. When the size of a small firm approaches the level needed to have access to formal lending there arises a strong incentive to expand, making the firm locally risk loving. The framework I study also raises some questions about the frequent use of a firm's growth rate as an empirical proxy for firm value. I show that a high growth rate is not necessarily associated with high firm value.