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Essays in History & Finance
To which extent may history help us understand current financial outcomes? Financial History typically tests for financial theories using historical data, or studies past financial outcomes to understand the present through analogy. This dissertation focuses on an alternative approach to the use of history in finance, which I label "History & Finance." This approach exploits facts and institutions of the past, and the persistence of the economic and social phenomena they determine, to directly explain current financial outcomes. In the first chapter of the dissertation, I define the scope of History & Finance based on its differences with Economic and Financial History. History & Finance has...
Machine Learning and Data Sciences for Financial Markets
Leveraging the research efforts of more than sixty experts in the area, this book reviews cutting-edge practices in machine learning for financial markets. Instead of seeing machine learning as a new field, the authors explore the connection between knowledge developed by quantitative finance over the past forty years and techniques generated by the current revolution driven by data sciences and artificial intelligence. The text is structured around three main areas: 'Interactions with investors and asset owners,' which covers robo-advisors and price formation; 'Risk intermediation,' which discusses derivative hedging, portfolio construction, and machine learning for dynamic optimization; and 'Connections with the real economy,' which explores nowcasting, alternative data, and ethics of algorithms. Accessible to a wide audience, this invaluable resource will allow practitioners to include machine learning driven techniques in their day-to-day quantitative practices, while students will build intuition and come to appreciate the technical tools and motivation for the theory.
From Financial History to History & Finance
Financial history studies facts and institutions of the past. Such facts and institutions are interesting subjects in themselves, or they can help us interpret the present through analogy. History & Finance reverses the role of history in finance research: it exploits natural experiments of the past as a means to directly explaining current financial outcomes through the long-run persistence of economic and social phenomena. I first define the History & Finance approach and its relationship to Economic and Financial history. Then, I survey the work based on History & Finance across the subfields of finance. I discuss the challenges raised by History & Finance, and how researchers have thus far tackled them. Finally, I comment on the avenues for future research that History & Finance opens to finance scholars and economic historians alike.
Robo-advising
In this chapter, we first discuss the limitations of traditional financial advice, which led to the emergence of robo-advising. We then describe the main features of robo-advising and propose a taxonomy of robo-advisors based on four defining dimensions - personalization, discretion, involvement, and human interaction. Building on these premises, we delve into the theoretical and empirical evidence on the design and effects of robo-advisors on two major sets of financial decisions, that is, investment choices (for both short- or long-term horizons) and the allocation of financial resources between spending and saving. We conclude by elaborating on five broadly open issues in robo-advising, which beget theoretical and empirical research by scholars in economics, finance, psychology, law, philosophy, as well as regulators and industry practitioners.
Handbook of Financial Decision Making
This accessible Handbook provides an essential entry point for those with an interest in the increasingly complex subject of financial decision making. It sheds light on new paradigms in society and the ways that new tools from private actors have affected financial decision making. Covering a broad range of key topics in the area, leading researchers summarize the state-of-the-art in their respective areas of expertise, delineating their projections for the future.
Human Frictions in the Transmission of Economic Policy
Intertemporal substitution is at the heart of modern macroeconomics and finance as well as economic policymaking, but a large fraction of a representative population of men - those below the top of the distribution by cognitive abilities (IQ) - do not change their consumption propensities with their inflation expectations. Low-IQ men are also less than half as sensitive to interest-rate changes when making borrowing decisions. Our microdata include unique administrative information on cognitive abilities, as well as economic expectations, consumption and borrowing plans, and total household debt from Finland. Heterogeneity in observables such as education, income, other expectations, and financial constraints do not drive these patterns. Costly information acquisition and the ability to form accurate forecasts are channels that cannot fully explain these results. Limited cognitive abilities could be human frictions in the transmission and effectiveness of fiscal and monetary policies that operate through household consumption and borrowing decisions.
Historical Antisemitism, Ethnic Specialization, and Financial Development
For centuries, Jews in Europe have specialized in financial services. At the same time, they have been the victims of historical antisemitism on the part of the Christian majority. We find that present-day financial development is lower in German counties where historical antisemitism was higher, compared to otherwise similar counties. Households in counties with high historical antisemitism have similar savings rates but invest less in stocks, hold lower bank deposits, and are less likely to get a mortgage-but not to own a house-after controlling for wealth and a rich set of current and historical covariates. Present-day antisemitism and supply-side forces do not appear to fully explain the results. Present-day households in counties where historical antisemitism was higher express lower trust in finance, but have levels of generalized trust similar to other households.
The Palgrave Handbook of Technological Finance
This handbook provides the first comprehensive overview of the fast-evolving alternative finance space and makes a timely and in-depth contribution to the literature in this area. Bringing together expert contributions in the field from both practitioners and academics, in one of the most dynamic parts of the financial sector, it provides a solid reference for this exciting discipline. Divided into six parts, Section 1 presents a high-level overview of the technologically-enabled finance space. It also offers a historical perspective on technological finance models and outlines different business models. Section 2 analyses digital currencies including guides to bitcoins, other cryptocurrenci...
What Do the Data Tell Us About Inflation Expectations?
Inflation expectations are central to economics because they affect the effectiveness of fiscal and monetary policy as well as realized inflation. We survey the recent literature with a focus on the inflation expectations of households. We first review standard data sources and discuss their advantages and disadvantages. We then document that household inflation expectations are biased upwards, dispersed across individuals, and volatile in the time series. We also provide evidence of systematic differences by gender, income, education, and race. Turning to the underlying expectations formation process, we highlight the role of individuals' exposure to price signals in their daily lives, such as price changes in groceries, the role of lifetime experiences, and the role of cognition. We then discuss the literature that links inflation expectations to economic decisions at the individual level, including consumption-savings and financial decisions. We conclude with an outlook for future research.
Crowdsourcing Financial Information to Change Spending Behavior
We document five effects of providing individuals with crowdsourced spending information about their peers (individuals with similar characteristics) through a FinTech app. First, users who spend more than their peers reduce their spending significantly, whereas users who spend less keep constant or increase their spending. Second, users' distance from their peers' spending affects the reaction monotonically in both directions. Third, users' reaction is asymmetric - spending cuts are three times as large as increases. Fourth, lower-income users react more than others. Fifth, discretionary spending drives the reaction in both directions and especially cash withdrawals, which are commonly used for incidental expenses and anonymous transactions. We argue Bayesian updating, peer pressure, or the fact that bad news looms more than (equallysized) good news cannot alone explain all these facts.
