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In this paper we address the relationship between the smile that stochastic volatility models produce and the dynamics they generate for implied volatilities. We introduce a new quantity, which we call the Skew Stickiness Ratio and show how, at order one in the volatility of volatility, it is linked to the rate at which the at-the-money-forward skew decays with maturity. We then focus on short maturity skews and (a) show that the difference between realized and implied SSR can be materialized as the P&L of an option strategy, (b) introduce the notion of realized skew.

This paper investigates the impact of banks’ characteristics, financial structure and macroeconomic indicators on banks’ net interest margins and profitability in the Tunisian banking industry for the 1980-2000 period. Individual bank characteristics explain a substantial part of the within-country variation in bank interest margins and net profitability. High net interest margin and profitability tend to be associated with banks that hold a relatively high amount of capital, and with large overheads. Size is found to impact negatively on profitability which implies that Tunisian banks are operating above their optimum level. On the other hand, we found that macroeconomic variables have no impact on Tunisian bank’s profitability. Turning to financial structure and its impact on banks’ interest margin and profitability, we find that stock market development has a positive effect on bank profitability. This reflects the complementarities between bank and stock market growth. We have found that the disintermediation of the Tunisian financial system is favourable to the banking sector profitability. On the ownership side, we reach the conclusion that private banks tend to perform better than state owned ones. Finally, interest rate liberalization has contrasting effect on net interest margins. In fact, partial liberalization has a negative impact on the interest margin whereas complete liberalization strengthens the ability of Tunisian banks to generate profit margins.

We survey 79 private equity (PE) investors with combined assets under management of more than $750 billion about their practices in firm valuation, capital structure, governance, and value creation. Investors rely primarily on internal rates of return and multiples to evaluate investments. Their limited partners focus more on absolute performance as opposed to risk-adjusted returns. Capital structure choice is based equally on optimal trade-off and market timing considerations. PE investors anticipate adding value to portfolio companies, with a greater focus on increasing growth than on reducing costs. We also explore how the actions that PE managers say they take group into specific firm strategies and how those strategies are related to firm founder characteristics.

We study a dynamic asset allocation problem in which stock returns exhibit short-run momentum and long-run mean reversion. We develop a tractable continuous-time model that captures these two predictability features and derive the optimal investment strategy in closed-form. The model predicts negative hedging demands for medium-term investors, and an allocation to stocks that is non-monotonic in the investor's horizon. Momentum substantially increases the economic value of hedging time-variation in investment opportunities. These utility gains are preserved when we impose realistic borrowing and short-sales constraints and allow the investor to trade on a monthly frequency.

We test for firm-level asset investment effects in returns by examining the cross-sectional relation between firm asset growth and subsequent stock returns. As a test variable, we use the year-on-year percentage change in total assets. Asset growth rates are strong predictors of future abnormal returns. Asset growth retains its forecasting ability even on large capitalization stocks, a subgroup of firms for which other documented predictors of the cross-section lose much of their predictive ability. When we compare asset growth rates with the previously documented determinants of the cross-section of returns (i.e., book-to-market ratios, firm capitalization, lagged returns, accruals, and other growth measures), we find that a firm's annual asset growth rate emerges as an economically and statistically significant predictor of the cross-section of U.S. stock returns.

In this paper, we demonstrate that many stochastic volatility models have the undesirable property that moments of order higher than one can become infinite in finite time. As arbitrage-free price computation for a number of important fixed income products involves forming expectations of functions with super-linear growth, such lack of moment stability is of significant practical importance. For instance, we demonstrate that reasonably parameterized models can produce infinite prices for Eurodollar futures and for swaps with floating legs paying either Libor-in-arrears or a constant maturity swap (CMS) rate. We systematically examine the moment explosion property across a spectrum of stochastic volatility models. Related properties such as the failure of the martingale property, and asymptotics of the volatility smile are also considered.

We extend the Black-Litterman methodology to generic non-normal market distributions and non-normal views. We draw on the copula and opinion pooling literature to express views directly on the market realizations, instead of the market parameters as in the Black-Litterman case. We compare the two approaches and we show an application to a thick-tailed, skewed and highly dependent market, where the views are expressed as uncertainty ranges.

Polynomial splines are popular in the estimation of discount bond term structures, but suffer from well-documented problems with spurious inflection points, excessive convexity, and lack of locality in the effects of input price perturbations. In this paper, we address these issues through the use of shape-preserving splines from the class of generalized tension splines. Our primary focus is on the classical hyperbolic tension spline which we derive non-parametrically from a penalized least squares criterion, but extensions to generalized tension splines - such as rational splines and exponential splines - are also covered. Our methodology allows both for best-fitting of noisy bonds and for the construction of an exact interpolatory term structure to a set of liquid instruments. Throughout, we work with a local tension B-spline basis, and support both fully non-parametric and user-imposed knot location strategies.

The East Asian countries of Hong Kong, Malaysia, Singapore and Thailand provide a rare opportunity to study the interaction between the accounting standards under which financial statements are prepared and the incentives of managers and auditors who prepare them. Their accounting standards are largely derived from common law sources [UK, US and International Accounting Standards (IAS)], which are widely viewed as higher quality than code law standards. However, economic and political influences on preparers' incentives predict low quality financial reporting. We show that reported earnings in these countries generally are no higher in quality than in code law countries. We define quality as timeliness in incorporating economic income (particularly economic losses). Countries frequently are classified in terms of accounting standards, or standard-setting institutions. Examples include international accounting literature and texts; compilation of transparency indexes; advocacy of financial reporting reform; and advocacy of International Accounting Standards (IAS). Our results imply this is incomplete and misleading without adequate consideration of preparer incentives.

We use two extremely liquid S&P 500 ETFs to analyze the prevailing trading conditions when mispricing allowing arbitrage opportunities is created. While these ETFs are not perfect substitutes, we show that their minor differences are not responsible for the mispricing. Spreads increase just before arbitrage opportunities, consistent with a decrease in liquidity. Order imbalance increases as markets become more one-sided and spread changes become more volatile which suggests an increase in liquidity risk. The price deviations are economically significant (mean profit of 6.6% p.a. net of spreads) and are followed by a tendency to quickly correct back towards parity.

In a sample of 102 non-European Union countries, we study variations in the decision to adopt International Financial Reporting Standards (IFRS). There is evidence that more powerful countries are less likely to adopt IFRS, consistent with more powerful countries being less willing to surrender standard-setting authority to an international body. There is also evidence that the likelihood of IFRS adoption at first increases and then decreases in the quality of countries’ domestic governance institutions, consistent with IFRS being adopted when governments are capable of timely decision making and when the opportunity and switching cost of domestic standards are relatively low. We do not find evidence that levels of and expected changes in foreign trade and investment flows in a country affect its adoption decision: thus, we cannot confirm that IFRS lowers information costs in more globalized economies. Consistent with the presence of network effects in IFRS adoption, we find that a country is more likely to adopt IFRS if its trade partners or countries within in its geographical region are IFRS adopters.

Twenty years after the papers by Modigliani and Miller, the introduction in 1982 of SEC rule 10b-18 fundamentally changed the rules of corporate finance, by allowing public companies open-market repurchases of their own stock and making it easier to manipulate capital structure. We present a new ‘capital structure substitution’ theory that is based on one simple hypothesis: company managements manipulate capital structure such that earnings-per-share are maximized. The substitution theory is used to reassess the ‘Fed model’, which describes the equilibrium observed between the average S&P 500 earnings yield (E/P) and the US government bond yield. We conclude that the Fed model is miss-specified: the S&P 500 earnings yield is not in equilibrium with the government bond yield but with the average after-tax interest rate on corporate bonds. The proposed theory also sheds new light on a variety of other phenomena observed in corporate finance. It is used to formulate a new theory on dividend policy, explaining why some companies prefer dividends over share repurchases and why dividend policy has changed in the early 1980s. It also provides a new explanation for the stock market’s reaction to monetary and fiscal policy. And it is used to explain why the positive relationship between leverage and beta, as predicted by Hamada, is not observed in market data.

The first time this author became aware of behavioral finance was in June 1998. At that point in time, there was no apparent or precise source of information for a new scholar interested in the field to select as a research starting point. For new scholars in the field, it was my intention by writing this paper to provide a research starting point and inspire them to conduct research in this field. The author of this paper provides the reader with a discussion concerning the discipline of behavioral finance with the new scholar in mind. Behavioral finance investigates the cognitive factors and emotional issues that individuals, financial experts, and traders exhibit within the securities markets. Upon examination, the literature reveals behavioral finance is based on the notion of interdisciplinary research from a wide range of fields. Therefore, there is a presentation of the substantive nature of the interdisciplinary philosophy as well as the value and strong contributions this type of discipline borrowing could have within academic finance. Lastly, the author provides an extensive catalog of the concepts, and books by behavioral finance scholars as well as a sample of influential papers and dissertations.

Special Purpose Acquisition Companies, or SPACs, have grown into one of the largest segments of the U.S. IPO market, raising more than $20 billion in gross proceeds since 2003. SPACs bear a strong resemblence to private equity funds, yet are largely free of the selection and survivorship biases that are often present in private equity datasets. I find that a portfolio of SPACs resembling "public LBOs" has a market beta near unity despite an average leverage multiple of nearly two, yielding new evidence regarding the systematic risk of leveraged buyouts. I also find that SPACs' highly predictable lifecycle yields highly predictable returns, with a monthly four-factor portfolio alpha of approximately 2% following the announcement of an acquisition and -2% after an acquisition has been completed. Finally, I provide evidence of a persistent discount in SPAC prices prior to the completion of an acquistion, which I attribute to fragmentation within SPACs' unique shareholder base.

We examine how volatility risk, both at the aggregate market and individual stock level, is priced in the cross-section of expected stock returns. Stocks that have past high sensitivities to innovations in aggregate volatility have low average returns. We also find that stocks with past high idiosyncratic volatility have abysmally low returns, but this cannot be explained by exposure to aggregate volatility risk. The low returns earned by stocks with high exposure to systematic volatility risk and the low returns of stocks with high idiosyncratic volatility cannot be explained by the standard size, book-to-market, or momentum effects, and are not subsumed by liquidity or volume effects.

Despite the recent growth of inflation linked derivatives market, the publicly available literature is very small. The various macro econometrics models are helpless when it comes to pricing inflation derivatives. The only freely accessible model, the Jarrow and Yildirim [4], relies on non observable data such as real yields. This makes this model hard to calibrate. In addition, it does not provide simple connection between liquid instruments like year on year, zero coupon swap and the modeling of the corresponding CPI correlation. To fill this gap, we adapt a market model to inflation. This can be seen as a simple translation of the Libor market model to inflation. We see how volatilities of year on year, zero coupon swap and the integrated CPI correlation are related. Hence, out of the three, only two are independent and these two provide the latter. We derive an upper and lower bound for the non independent parameter leading to coherence tests. We conclude by convexity correction formula for year on year rates, emphasizing the impact of correlation between interest and inflation rates.

There are many benefits to investing in hedge funds, particularly when using a diversified multi-strategy approach. Over the recent years, multi-strategy funds of hedge funds have flourished and are now the favorite investment vehicles of institutional investors to discover the world of alternative investments. More recently, funds of hedge funds that specialize within an investment style have also emerged. Both types of funds put forward their ability to diversify risks by spreading them over several managers. However, diversifying a hedge fund portfolio also raises a number of issues, such as the optimal number of hedge funds to really benefit from diversification, and the influence of diversification on the various statistics of the return distribution (e.g. expected return, skewness, kurtosis, correlation with traditional asset classes, value at risk and other tail statistics). In this paper, using a large database of hedge funds over the 1990-2001 period, we study the impact of diversification on naively constructed (randomly chosen and equally weighted) hedge fund portfolios. We also provide some insight into style diversification benefits, as well as the inter-temporal evolution of diversification effects on hedge funds.

We investigate the use of Generative Adversarial Networks (GANs) for probabilistic forecasting of financial time series. To this end, we introduce a novel economics-driven loss function for the generator. This newly designed loss function renders GANs more suitable for a classification task, and places them into a supervised learning setting, whilst producing full conditional probability distributions of price returns given previous historical values. Our approach moves beyond the point estimates traditionally employed in the forecasting literature, and allows for uncertainty estimates. Numerical experiments on equity data showcase the effectiveness of our proposed methodology, which achieves higher Sharpe Ratios compared to classical supervised learning models, such as LSTMs and ARIMA.

We review the main approaches to dynamically reallocate capital between a risky portfolio and a risk-free account: expected utility maximization; option-based portfolio insurance (OBPI); and drawdown control, closely related to constant proportion portfolio insurance (CPPI). We present a refresher of the theory under general assumptions. We discuss the connections among the different approaches, as well as their relationship with convex and concave strategies. We provide explicit, practicable solutions with all the computations as well as numerical examples. Fully documented code for all the strategies is also provided.

An influential emerging literature documents strong correlations between carbon emissions and stock returns. We reexamine that data and conclude that these associations are driven by two factors. First, stock returns are correlated only with unscaled emissions estimated by the data vendor, but not with unscaled emissions actually disclosed by firms. Vendor-estimated emissions systematically differ from firm-disclosed emissions and are highly correlated with financial fundamentals, suggesting that prior findings primarily capture the association between such fundamentals and returns. Second, unscaled emissions, the variable typically used in academic literature, is correlated with stock returns but emissions intensity (emissions scaled by firm size), an equally important measure used in practice, is not. While unscaled emissions represent an important metric for society, we argue that, for individual firms, emissions intensity is an appropriate measurement choice to assess carbon performance. The associations between emissions and returns disappear after accounting for either of the issues above.

We study how the excess market return depends on the time of the day using E-mini S&P 500 futures actively traded for almost 24 hours. Strikingly, four hours around European open account for the entire average market return. This period’s returns are positive every year and have a 1.6 Sharpe ratio that remains high after costs. Average returns are a noisy zero during the remaining 20 hours. High returns around European open are consistent with European investors processing information accumulated overnight and thus resolving uncertainty. Indeed, uncertainty reflected by VIX futures prices rises overnight and falls around European open. The results are stronger during the 2020 COVID crisis.

We study the effect of algorithmic trading (AT) on market quality between 2001 and 2011 in 42 equity markets around the world. We use exchange co-location service that increases AT as an exogenous instrument to draw causal inferences of AT on market quality. On average, AT improves liquidity and informational efficiency but increases short-term volatility. Importantly, AT also lowers execution shortfalls for buy-side institutional investors. Our results are surprisingly consistent across markets and thus across a wide range of AT environments. We further document that the beneficial effect of AT is stronger in large stocks than in small stocks.

We model an IPO company's optimal response to the presence of sentiment investors and short sale constraints. Given regulatory constraints on price discrimination, the optimal mechanism involves the issuer allocating stock to 'regular' institutional investors for subsequent resale to sentiment investors, at prices the regulars maintain by restricting supply. Because the hot market can end prematurely, carrying IPO stock in inventory is risky, so to break even in expectation regulars require the stock to be underpriced - even in the absence of asymmetric information. However, the offer price still exceeds fundamental value, as it capitalizes the regulars' expected gain from trading with the sentiment investors. This resolves the apparent paradox that issuers, while shrewdly timing their IPOs to take advantage of optimistic valuations, appear not to price their stock very aggressively. The model generates a number of new and refutable empirical predictions regarding the extent of long-run underperformance, offer size, flipping, and lock-ups.

Under the recent negative interest rate situation, the Bachelier model has been attracting attention and adopted for evaluating the price of interest rate options. In this paper, we will derive an option pricing formula based on the Bachelier model and compare it with the prior researches. We will derive it by eight methods and clarify the property of the Bachelier model.Then we will confirm the validity of the Normal model that is actually used in the valuation of interest rate options under negative interest rate, while comparing it with the Bachelier model for stocks. We start from the natural setting of modeling the undiscounted stock price by the Ornstein=Uhlenbeck process, and derive the Bachelier formula in consideration of discount.On the other hand, since the major prior researches start from modeling the discounted stock price by the Brownian motion, their models of the undiscounted stock price has an unnatural setting that the price of the numeraire asset is included. Furthermore, It has been confirmed that their formulas are not consistent among them. During the derivation process, we have obtained various results concerning the Bachelier model. In particular, in the case of the Bachelier model, it has been confirmed that the utility function of a representative agent is the CARA utility function unlike the Black-Scholes model. The assumption of the exponential type utility function is quite natural setting. In addition, we have derived other expressions of the Bachelier's formula (the formula decomposed into the intrinsic value and the time value and the formula using a characteristic function). As for the Normal model used for pricing interest rate options, we have derived an original pricing formula (Modified Normal model) in which the unnatural points of the Normal model of the forward LIBOR and forward swap rate have been partially corrected.

We propose a direct and robust method for quantifying the variance risk premium on financial assets. We theoretically and numerically show that the risk-neutral expected value of the return variance, also known as the variance swap rate, is well approximated by the value of a particular portfolio of options. Ignoring the small approximation error, the difference between the realized variance and this synthetic variance swap rate quantifies the variance risk premium. Using a large options data set, we synthesize variance swap rates and investigate the historical behavior of variance risk premia on five stock indexes and 35 individual stocks.