# Research articles for the 2019-05-20

SSRN

In this paper we will propose a simple approach to simulating Heston model efficiently and accurately. All existing simulation schemes so far directly work with the mean-reverting square root process of the variance in Heston model, instead we transform the variance to an equivalent volatility which follows a mean-reverting Ornstein-Uhlenbeck process. We will show it is more convenient to simulate the transformed volatility process than the original variance process since the new Ornstein-Uhlenbeck process does not have any term of square root, and is not restricted to any parameter restriction. Based on the transformed volatility process, we suggest a simple and exact scheme for the simulation of Heston model. Numerical examples show that the new scheme and Andersen's QE scheme perform very closely, and outperform other schemes such as log-normal scheme. While QE scheme suffers from the problem of "leaking correlation", transformed volatility scheme does not, and therefore, provides a high-quality alternative to the existing simulation schemes for Heston model.

SSRN

The change in economic and sociodemographic reality, characterized by a continuous increase in longevity, the consequences of the economic crisis, and the lack of adequate adjustments of social security retirement pension systems everywhere, entails risks for workers and the social security systems themselves. Many reforms of public pension systems have been carried out in recent years, based on modifying system parameters and structural changes. Some reforms aim at increasing capitalization in the determination of the final pension through a life annuity to complement the public retirement pension as a second retirement income. Against the background of the change of agentsâ€™ behaviors throughout the life cycle and the presence of an adverse selection problem in the annuities market, we describe in this paper a two-step mixed pension system that tries to solve the pressure that increasing longevity is putting on pension schemes to provide adequate and sustainable pensions for all. In our two-step mixed system, when workers reach their ordinary retirement age they receive a term annuity generated by their previous capitalized savings to be replaced by a social security defined contribution pure life annuity when the so-called grand age is reached. The analysis is carried out from an individual perspective, through the internal rate of return that workers will receive after ordinary retirement in both schemes compared with the one they would get with the same contributions in the current situation. We also analyze some possible transition strategies to the new system.

SSRN

I present empirical results on the first active exchange traded funds (ETFs) based on risk, return and incentives. Using models for both the returns and the volatility of the underlying assets, I compare the performance of the suggested models with the alternative investment solutions such as passive ETFs, mutual funds and hedge funds. The results indicate that active ETFs are found to be more volatile than passive ETFs and overall the active and passive structure is very close in means of final performance. I also find that, in many cases, the active structure is surpassing mutual funds in mean of returns. Finally, there is a unidirectional relation between active funds and hedge funds, since the former is influenced by the latter.

SSRN

Securities lending has been a lucrative business for mutual funds and ETFs over the past decade. We examine the impact of securities lending activities on the return performance of U.S. equity ETFs. We find that income from securities lending has surged in recent years and was at extreme levels during the financial crisis years of 2008 and 2009. We document that income from securities lending activities has been used by these ETFs as a means of considerably reducing tracking errors over time. Our findings have important implications for investors who use tracking error to evaluate the performance of ETFs.

SSRN

The LIBOR Market Model (LMM or BGM) has become one of the most popular models for pricing interest rate products. It is commonly believed that Monte-Carlo simulation is the only viable method available for the LIBOR Market Model. In this article, however, we propose a lattice (or tree) approach to price interest rate products within the LIBOR Market Model by introducing a shifted forward measure and several novel fast drift approximation methods. This model should achieve the best performance without losing much accuracy. Moreover, the calibration is almost automatic and it is simple and easy to implement. Adding this model to the valuation toolkit is actually quite useful; especially for risk management or in the case there is a need for a quick turnaround.

SSRN

Angel investors go by many definitions. By all definitions, though, angels investors act as informal venture capitalists and collectively invest at least billions of dollars in thousands of entrepreneurial projects annually. Despite their importance to small businesses and entrepreneurs, angel investments have received comparatively little attention from investment managers and writers. This paper describes the advantages and disadvantages of angel investing and suggests ways for investors to extract the maximum benefits -- both pecuniary and nonpecuniary -- from angel investing.

SSRN

Using a proprietary and unusually comprehensive database of hedge fund returns, we seek to identify abnormal performance consistent with opportunistic trading (e.g., bear raids) or synchronized actions (e.g., widespread forced liquidations) that could generate systemic risk. We find no evidence that hedge funds systematically benefit from opportunistic trading. In contrast, some funds operating with strategies that commonly utilize leverage (e.g., fixed income arbitrage and event-driven strategies) perform significantly worse than would be expected given ex ante risk-factor loadings. This suggests that forced liquidations probably caused some funds to sell into a falling market at fire sale prices. However, underperformance is not concentrated in specific funds that use leverage or during the height of the systemic risks in September 2008 indicating that selling pressure likely derives from meeting redemptions versus forced selling during the crisis. These results suggest new policies regulating hedge funds should focus on certain fund-level risks instead of strategy or industry risks.

SSRN

While numerous studies have analyzed the asset allocation issue of US stock market from various angles, much less attention has been paid to the asset allocation issue of Chinese stock market. This article investigates the asset allocation in Chinese stock market from a perspective of incorporating return predictability. We find significant out-of-sample return predictability in Chinese stock market based on a host of return predictors. We then examine the performance of active portfolio strategies such as aggregate market timing strategy, and industry, size, and value rotation strategies to profitably exploit return predictability. We provide strong evidence that these portfolio strategies incorporating return predictability can deliver superior outperformance up to 600 basis points per annum and almost double the Sharpe ratios compared to the passive buy-and-hold benchmarks ignoring return predictability.

SSRN

Option prices contain forward looking information about stock price volatility and, potentially, the probability of bankruptcy. We develop a risk-neutral density (RND) model consisting of a mixture of two lognormal densities with a probability of bankruptcy. We calibrate this model to daily stock and option prices of six financial institutions during the onset of the financial crisis to see what information about bankruptcy probabilities can be inferred from option prices. The bankruptcy probability and the shape of the RND for the institutions are examined, particularly on major event dates. The empirical results show that acquiring banks have a lower bankruptcy probability than the acquired banks; RNDs of financial institutions reflect market shocks, especially in fat tails and bankruptcy probability. The results from multivariate regressions for each institution suggest that the small volatile firms, with low returns, have a higher chance of bankruptcy than large stable firms with high returns.

SSRN

One of the most important decisions retirees need to make is the asset allocation of their portfolios. They can have a static or a dynamic allocation, and simplicity usually favors the former. Warren Buffett recently added another vote for static allocations by revealing that he had advised a trustee to split the bequest his wife will receive 90% in stocks and 10% in short-term bonds. The evidence discussed here shows that, relative to other static allocations, a 90/10 split has a very low failure rate and provides investors with very good upside potential and downside protection. The evidence also shows that two minor twists to the 90/10 split result in two very simple dynamic strategies with even better upside potential and downside protection.

SSRN

This paper presents a simple, intuitive investment strategy that improves upon the popular dollar-cost-averaging (DCA) approach. The investment strategy, which we call enhanced dollar-cost-averaging (EDCA), is a simple, rule-based strategy that retains most of the attributes of traditional DCA that are appealing to most investors but yet adjusts to new information, which traditional DCA does not. Simulation results show that the EDCA strategy reliably outperforms the DCA strategy in terms of higher dollar-weighted returns about 90% of the time and nearly always delivers greater terminal wealth for reasonable values of the risk premium. EDCA is most effective when applied to high volatility assets, when cash flows are highly sensitive to past returns, and during secular bear markets. Historical back-testing on equity indexes and mutual funds indicates that investor dollar-weighted returns can be enhanced by between 30 and 70 basis points per year simply by switching from DCA to EDCA.

arXiv

We discuss a concept denoted as Conformal Prediction (CP) in this paper. While initially stemming from the world of machine learning, it was never applied or analyzed in the context of short-term electricity price forecasting. Therefore, we elaborate the aspects that render Conformal Prediction worthwhile to know and explain why its simple yet very efficient idea has worked in other fields of application and why its characteristics are promising for short-term power applications as well. We compare its performance with different state-of-the-art electricity price forecasting models such as quantile regression averaging (QRA) in an empirical out-of-sample study for three short-term electricity time series. We combine Conformal Prediction with various underlying point forecast models to demonstrate its versatility and behavior under changing conditions. Our findings suggest that Conformal Prediction yields sharp and reliable prediction intervals in short-term power markets. We further inspect the effect each of Conformal Prediction's model components has and provide a path-based guideline on how to find the best CP model for each market.

arXiv

Stock prediction is a topic undergoing intense study for many years. Finance experts and mathematicians have been working on a way to predict the future stock price so as to decide to buy the stock or sell it to make profit. Stock experts or economists, usually analyze on the previous stock values using technical indicators, sentiment analysis etc to predict the future stock price. In recent years, many researches have extensively used machine learning for predicting the stock behaviour. In this paper we propose data driven deep learning approach to predict the future stock value with the previous price with the feature extraction property of convolutional neural network and to use Neural Arithmetic Logic Units with it.

SSRN

This paper analyzes the effect of counterparty credit risk on optimal early exercise policy and value of American options. In contrast with the existing literature we find that the price of the underlying asset at which it is optimal to exercise an American option can be significantly different when there is counterparty credit risk. We show that it is not always optimal to exercise when a credit event is likely yet it is sometimes optimal to exercise for credit reasons even when the risk of a credit event is fairly remote. Further, we find that discounting the expected payoff on American options at a higher credit-risk-adjusted rate may lead to inaccurate valuation results. Numerical examples illustrate that early exercise can mitigate only approximately one third of the expected credit loss for American options. This result conflicts with the existing literature that claims early exercise can largely eliminate such expected credit loss. The remaining expected credit loss can be attributed to two sources: the write-down of the payoff if financial distress occurs; and the loss of time value if early exercise was motivated by credit concerns.

arXiv

This paper presents several numerical applications of deep learning-based algorithms that have been introduced in [HPBL18]. Numerical and comparative tests using TensorFlow illustrate the performance of our different algorithms, namely control learning by performance iteration (algorithms NNcontPI and ClassifPI), control learning by hybrid iteration (algorithms Hybrid-Now and Hybrid-LaterQ), on the 100-dimensional nonlinear PDEs examples from [EHJ17] and on quadratic backward stochastic differential equations as in [CR16]. We also performed tests on low-dimension control problems such as an option hedging problem in finance, as well as energy storage problems arising in the valuation of gas storage and in microgrid management. Numerical results and comparisons to quantization-type algorithms Qknn, as an efficient algorithm to numerically solve low-dimensional control problems, are also provided; and some corresponding codes are available on https://github.com/comeh/.

SSRN

A number of exchanges around the world have attempted to introduce single-stock futures, but only a few have succeeded. We argue that this situation can be attributed to the use of inadequate selection criteria for the underlyings. Therefore, our paper investigates the determinants of trading activity on the Eurex derivative exchange and looks beyond systematic reasons extensively examined in prior research. It is found that trading activity is higher for single-stock futures on stock characterized by low institutional ownership and high volume and volatility on the spot market. The mispricing between the spot and futures markets also attracts investors to the single-stock futures market. Moreover, factors such as the size of contract, tick size, and age of contract on a particular stock significantly contribute to the increase of open interest and traded volume. Furthermore, evidence is found that single-stock futures become more efficiently priced around an ex-dividend date for the underlying stock. This is due to dividend stripping trading which allows a reduction in the tax burden. Our findings have important implications for investors who have an interest in that segment of the derivatives market. These implications should also be taken into consideration by market regulators and tax authorities.

arXiv

Uber and Lyft ride-hailing marketplaces use dynamic pricing, often called surge, to balance the supply of available drivers with the demand for rides. We study pricing mechanisms for such marketplaces from the perspective of drivers, presenting the theoretical foundation that has informed the design of Uber's new additive driver surge mechanism. We present a dynamic stochastic model to capture the impact of surge pricing on driver earnings and their strategies to maximize such earnings. In this setting, some time periods (surge) are more valuable than others (non-surge), and so trips of different time lengths vary in the opportunity cost they impose on drivers. First, we show that multiplicative surge, historically the standard on ride-hailing platforms, is not incentive compatible in a dynamic setting. We then propose a structured, incentive-compatible pricing mechanism. This closed-form mechanism has a simple form, and is well-approximated by Uber's new additive surge mechanism.

SSRN

In this paper, we propose a novel parametric approach to extract the implied risk-neutral density function from a cross-section of call option prices. The method is based on the framework proposed by Orosi (2011), who presents a multi-parameter extension of the models of Figlewski (2002) and Henderson, Hobson, and Kluge (2007). By choosing a proper functional form, we show that well-behaved risk neutral densities can be generated by imposing restrictions on the parameters of the model. The results of our numerical experiments demonstrate that the method is capable of extracting risk neutral densities with complex characteristics. Moreover, we demonstrate the pricing performance of our method by generating arbitrage-free call option prices that can be used to produce well-behaved densities from S&P 500 Index options. Additionally, the model is extremely easy to implement and calibrate, and further extensions are straightforward. NOTE: This is a preprint. The published version contains, in addition to extensive empirical tests, a generalization of the main model applicable to defaultable stocks, and an intuitive explanation of the choice of the model parameters.

SSRN

The valuation of options using a binomial non-recombining tree with discrete dividends can be intricate. This paper proposes three different enhancements that can be used alone or combined to value American options with discrete dividends using a non-recombining binomial tree. These methods are compared in terms of both speed and accuracy with a large sample of options with one to four discrete dividends. This comparison shows that the best results can be achieved by the simultaneous use of the three enhancements. These enhancements when used together result in significant speed/accuracy gains in the order of up to 200 times for call options and 50 times for put options. These techniques allow the use of a non-recombining binomial tree with very good accuracy for valuing options with up to four discrete dividends in a timely manner.

SSRN

We survey the theory and empirical evidence on GARCH option valuation models. We provide an overview of different functional forms for the volatility dynamic, multifactor models, nonnormal innovation distributions and valuation techniques. We also discuss alternative pricing kernels used for risk neutralization, various strategies for empirical implementation, and the links between GARCH and stochastic volatility models. In the appendix we provide Matlab computer code for option pricing via Monte Carlo simulation for nonaffine models as well as via Fourier inversion for affine models.

arXiv

The effects of weather on agriculture in recent years have become a major concern across the globe. Hence, the need for an effective weather risk management tool (weather derivatives) for agricultural stakeholders. However, most of these stakeholders are unwilling to pay for the price of weather derivatives (WD) because of product-design and geographical basis risks in the pricing models of WD. Using machine learning ensemble technique for crop yield forecasting and feature importance, the major major weather variable (average temperature) that affects crop yields are empirically determined. This variable (average temperature) is used as the underlying index for WD to eliminate product-design basis risks. A model with time-varying speed of mean reversion, seasonal mean, local volatility that depends on the average temperature and time for the contract period is proposed. Based on this model, pricing models for futures, options on futures, and basket futures for cumulative average temperature and growing degree-days are presented. Pricing futures on baskets reduces geographical basis risk as buyer's have the opportunity to select the most appropriate weather stations with their desired weight preference. With these pricing models, agricultural stakeholders can hedge their crops against the perils of weather.

SSRN

There is a growing retirement crisis, and most of the focus has been on the fact that individuals are not saving enough for retirement, may not have access to pension schemes, and find it difficult to choose from a wide range of retirement investment products. However, the bigger issue might be that the assets and financial products available to investors, including those that offer legal protection to plan sponsors, may not be appropriate for the typical individual saving for retirement. As Merton (2014) notes, the model adopted to plan for retirement for the majority of the population focuses on wealth at retirement as opposed to the level of retirement income that an individual can earn. As a result, current assets and many products are risky from a retirement-income perspective. All else equal, with respect to retirement income, individuals retiring a few years apart can have vastly different outcomes (making retirement outcomes a function of oneâ€™s conception or retirement date), and this impacts policymakers (and potentially individuals worried about retirement security). A new bond has been proposed to improve retirement security; it includes a forward-start (tied to date of retirement), income-only (because individuals need steady income), real cash-flow stream (linked to appropriate indexes), for a fixed period (tied to average life expectancy). This paper examines standard portfolio choices (e.g., 60/40, target-date funds), along with holding this new bond in isolation, from a retirement-income perspective to demonstrate how this new bond, either individually or when used in standard portfolio choices, could improve retirement outcomes. The paper concludes with a Monte Carlo simulation that further validates the value of this new bond given the potential risks to all investment choices for reasonable future equity, interest rate, and inflation scenarios.

arXiv

Empirical research often cites observed choice responses to variation that shifts expected discounted future utilities, but not current utilities, as an intuitive source of information on time preferences. We study the identification of dynamic discrete choice models under such economically motivated exclusion restrictions on primitive utilities. We show that each exclusion restriction leads to an easily interpretable moment condition with the discount factor as the only unknown parameter. The identified set of discount factors that solves this condition is finite, but not necessarily a singleton. Consequently, in contrast to common intuition, an exclusion restriction does not in general give point identification. Finally, we show that exclusion restrictions have nontrivial empirical content: The implied moment conditions impose restrictions on choices that are absent from the unconstrained model.

SSRN

Implied binomial trees are typically constructed by fitting a risk-neutral density (in the form of ending nodal probabilities) to observed option prices (e.g., Rubinstein [1994]). This commonly used approach requires the solution of a high dimensional quadratic program with the number of unknowns proportional to the number of binomial periods. In this paper, we propose a more efficient implementation of implied binomial trees by incorporating cubic spline smoothing in the quadratic program. Only a selected subset of ending nodal probabilities is treated as unknowns while the remainder is interpolated using cubic splines. The reduction in dimensionality of the quadratic program can substantially improve the efficiency of implied binomial trees without any loss in numerical accuracy. More importantly, our smoothing method can overcome the overfitting problem in the implied binomial tree scheme and minimize distortions to the extracted risk-neutral density even when option prices are observed with error.

SSRN

A holistic wealth overview coupled with goal-based investing is the basis for excellent wealth management and increased investor happiness. Potentially innovative technologies and a shift in focus of financial advisors will offer the tools clients need to understand and manage their holistic wealth situation, empowering them to gain full control over their wealth and to avoid behavioral biases.

SSRN

The credit valuation adjustment (CVA) of OTC derivatives is an important part of the Basel III credit risk capital requirements and current accounting rules. Its calculation is not an easy task - not only it is necessary to model the future value of the derivative, but also the probability of default of a counterparty. Another complication arises in the calculation when the exposure to a counterparty is adversely correlated with the credit quality of that counterparty, i.e. when it is needed to incorporate the wrong-way risk. A semi-analytical CVA formula simplifying the interest rate swap (IRS) valuation with the counterparty credit risk including the wrong-way risk is derived and analyzed in the paper. The formula is based on the fact that the CVA of an IRS can be expressed using swaption prices. The link between the interest rates and the default time is represented by a Gaussian copula with constant correlation coefficient.Finally, the results of the semi-analytical approach are compared with the results of a complex simulation study.

SSRN

In this paper we argue that investors and investment managers make a mistake if they try to focus on achieving high returns or high risk-adjusted returns and are likely disappointing investors in the long run. Instead, we argue that investment management should focus almost exclusively on managing the risks of an investment portfolio; above average returns will be a natural outcome of a proper risk management process. We describe the key risk management steps and why we believe this process leads to superior investment performance.

SSRN

In order to ensure long-term viability and impact, many private foundations have three basic investment policy objectives: 1) Distribute 5% of the net fair value of their assets per year; 2) Maintain at least a constant level of real (inflation-adjusted) charitable giving per year; and 3) Do so in perpetuity.The investment hurdle rate for a private foundation, defined as the return in excess of short term nominal interest rates necessary meet the above objectives, is therefore a function of the 5% distribution requirement, nominal interest rates, and the level of inflation. The current market environment of low nominal interest rates and negative real interest rates presents perhaps the most challenging period in the last thirty years for achieving these goals. We use a simulation analysis based on market-derived capital market assumptions to estimate probabilities of success for three portfolios of various estimated risk levels over the next two decades. Notably, our analysis implies that most foundations are unlikely to maintain the inflation-adjusted value of their corpus in addition to meeting the 5% distribution requirement over the next 10-20 years.

SSRN

This article provides in-depth discussion of important issues related to mutual fund distribution. The first two topics are fund distribution channel characteristics and Rule 12b-1 fees and distribution. Distribution channel characteristics discuss direct channel, advice channel, retirement channel, institutional channel, supermarket channel, and multiple-share classes. The discussion of Rule 12b-1 fees and distribution covers adoption of Rule 12b-1, Rule 12b-1 after adoption, current 12b-1 fees, issues with 12b-1 fees, and summary of 12b-1 fees attributes. The remaining topics include direct-sold and broker-sold services, Rule 12b-1 fees and revenue sharing, revenue sharing issues, soft-dollar trading, distribution and flows, opacity and agency conflicts, expense shifting agency conflicts, and intermediated distribution and portfolio managers.

SSRN

First, this study reviews Morningstar analytical grading measures used by investors to choose mutual funds. These measures include Morningstar star ratings, analyst ratings, total pillar ratings, upside and downside capture ratios, and stewardship ratings. Second, the study provides results of research that assesses the effectiveness of Morningstar fund grading measures. Third, a model is proposed that systematically applies selected Morningstar measures to ease investor choice of equity funds. In this case, the model is applied to Vanguard domestic actively managed equity funds, less sector funds. The effectiveness of this model is best tested using future performance of the selected Vanguard domestic actively managed equity funds over three-, five-, and 10-year periods.

arXiv

Consider a multiperiod optimal transport problem where distributions $\mu_{0},\dots,\mu_{n}$ are prescribed and a transport corresponds to a scalar martingale $X$ with marginals $X_{t}\sim\mu_{t}$. We introduce particular couplings called left-monotone transports; they are characterized equivalently by a no-crossing property of their support, as simultaneous optimizers for a class of bivariate transport cost functions with a Spence--Mirrlees property, and by an order-theoretic minimality property. Left-monotone transports are unique if $\mu_{0}$ is atomless, but not in general. In the one-period case $n=1$, these transports reduce to the Left-Curtain coupling of Beiglb\"ock and Juillet. In the multiperiod case, the bivariate marginals for dates $(0,t)$ are of Left-Curtain type, if and only if $\mu_{0},\dots,\mu_{n}$ have a specific order property. The general analysis of the transport problem also gives rise to a strong duality result and a description of its polar sets. Finally, we study a variant where the intermediate marginals $\mu_{1},\dots,\mu_{n-1}$ are not prescribed.

SSRN

The purpose of this study is to discuss research that identifies heterogeneous mutual fund and investor attributes and relations that explain dispersion in fund fees. One might think there is a short list of attributes and relations, such as high versus low expense ratios, that tells the full story of fund fee dispersion, but the story is much more complicated and nuanced. The research topics discussed are not inclusive of heterogeneous fund and investor attributes and relations that generate dispersions in fund fees, but they do provide this depth within their particular research domains.The topics discussed related to this research are as follows: 1) disproportionate fee spreads and fund agency conflicts and services; 2) fee dispersion and heterogeneity in decisions concerning fund and investor attributes; 3) fee dispersion and strategic pricing in actively managed funds; 4) fee markups within fee-setting scenarios; 5) fee dispersion and market segmentation; and 6) fee dispersion and heterogeneity in board and sponsor decisions. The final, more traditional discussion discussion reviews factors affecting fund expense ratios over time.

arXiv

In this paper we discuss a natural extension of infinite discrete partition-of-unity copulas which were recently introduced in the literature to continuous partition of copulas with possible applications in risk management and other fields. We present a general simple algorithm to generate such copulas on the basis of the empirical copula from high-dimensional data sets. In particular, our constructions also allow for an implementation of positive tail dependence which sometimes is a desirable property of copula modelling, in particular for internal models under Solvency II.

arXiv

We derive analytic series representations for European option prices in polynomial stochastic volatility models. This includes the Jacobi, Heston, Stein-Stein, and Hull-White models, for which we provide numerical case studies. We find that our polynomial option price series expansion performs as efficiently and accurately as the Fourier transform based method in the nested affine cases. We also derive and numerically validate series representations for option Greeks. We depict an extension of our approach to exotic options whose payoffs depend on a finite number of prices.

SSRN

Using firm-level option and stock data, we examine the predictive ability of option-implied volatility measures proposed by previous studies and recommend the best measure using up-to-date data. Portfolio level analysis implies significant non-zero risk-adjusted returns on arbitrage portfolios formed on the call-put implied volatility spread, implied volatility skew, and realized-implied volatility spread. Firm-level cross-sectional regressions show that, the implied volatility skew has the most significant predictive power over various investment horizons. The predictive power persists before and after the 2008 Global Financial Crisis.

SSRN

We showed that traditional performance measures are not adequate for the performance evaluation of hedge funds portfolios because they take into account neither the asymmetry of returns nor the risk perception of investors. In order to overcome this problem, we made recourse to performance measures in the downside risk framework. By using the Credit Suisse/Tremont Hedge Fund database, we showed that Sortino ratio; upside potential ratio and Omega measure make it possible to overcome the drawbacks of Sharpe ratio. The results obtained also showed that the index of Mamoghli and Daboussi is the adequate measure which makes it possible to surmount the drawbacks of Treynor index and Mishra and Rahman index. Likewise, the results proved that alpha of Mamoghli and Daboussi measures more correctly than Jensen alpha and Mishra and Rahman alpha the performance of hedge funds.

SSRN

We analyze a unique, comprehensive, multi-decade dataset of all communications with clients by a boutique investment advisory and investment management firm to explore the behavior of individuals involved in financial decision making. We propose and test a theory of self-regulation to explain both the appeal and the value of investment managers to individual investors, and we find that all of the predictions of the theory are borne out by the data. In short, our unique dataset allows us to provide evidence that an important service provided by investment advisors, and apparently desired by individual investors, is the barrier the advisor provides to prevent the individual from aggressively trading and thereby losing money.

SSRN

This article provides an in-depth analysis of pricing and structuring of contingent convertibles (CoCos). These debt instruments convert into the equity of the issuing bank or suffer a write-down of the face value upon the appearance of a trigger event. This trigger mechanism provides an automatic strengthening of the capital structure of the bank. Equity is in this case injected on the very moment the bank is failing to meet the minimum regulatory capital requirements or when it is heading towards a state of non-viability. In this paper the pricing of CoCos is handled using two different approaches. The first approach starts from a credit derivatives background. A second approach tackles the pricing and structuring of a CoCo as an equity derivatives problem. Both models are applied on the CoCos issued by Lloyds and Credit Suisse and allow to quantify the risks embedded within each of these structures.

SSRN

This paper examines if firms in the United States with quality training programs can enjoy above-the-market-average benefits and performance by analyzing risk premiums and risk-adjusted excess returns of a portfolio of public firms in the United States, which are ranked consecutively from 2006 to 2011 in the top 50 of the Training Top 125, to determine if the portfolio risk premiums are higher than the market risk premiums and to investigate if the portfolio can generate positive risk-adjusted excess returns. The portfolio average risk premiums are all positive and economically greater than the market risk premiums for the 5-year holding period intervals. All of the portfolio average risk-adjusted excess returns from the single-index and four-factor models are positive (some are statistically significant) for the 3-year and 5-year holding period intervals. This study shows that firms in the United States with quality training programs should be able to enjoy above-the-market-average benefits and performance in the long run, on average.

SSRN

Small-cap stocks are typically viewed as riskier than large-cap stocks, and value stocks as riskier than growth stocks. But are they? It depends, both on an investorâ€™s holding period and the way he assesses risk. If an investor is concerned with volatility, either during or at the end of the holding period, then the conventional wisdom is correct. However, if an investor focuses on his long-term terminal wealth, then the conventional wisdom is turned on its head: The evidence discussed in this article strongly suggests that small stocks should be viewed as less risky than large stocks, and value stocks as less risky than growth stocks. This is the case because small and value stocks offer both more upside potential and, when tail risks strike, better downside protection than do large and growth stocks.

SSRN

We propose a novel and intuitive risk-neutral valuation model for real estate derivatives. We first model the underlying efficient market price of real estate and then construct the observed index value with an adaptation of the price update rule by Blundell and Ward (1987). The resulting index behavior can easily be analyzed and closed-form pricing solutions are derived for forwards, swaps and European put and call options. We demonstrate the application of the model by valuing a put option on a house price index. Autocorrelation in the index returns appears to have a large impact on the option value. We also study the effect of an over- or undervalued real estate market. The observed effects are significant and as expected.

arXiv

This paper studies the finite time risk-sensitive portfolio optimization in a regime-switching credit market with physical and information-induced default contagion. The Markovian regime-switching process is assumed to be unobservable, which has countable states that affect default intensities of surviving assets. The stochastic control problem is formulated under partial observations of asset prices and default events. By proving an innovative martingale representation theorem based on incomplete and phasing out filtration, we characterize the value function in an equivalent but simplified form. This allows us to connect the previous control problem to a quadratic BSDE with jumps that is new to the literature, in which the driver term has non-standard structures and carries the conditional filter as an infinite-dimensional parameter. By proposing some novel truncation techniques, we obtain the existence of solution to this new BSDE using the delicate convergence of solutions associated to some truncated BSDEs. The verification theorem and the characterization of the optimal trading strategy can be concluded with the aid of our newly established BSDE results.

SSRN

Many advisors struggle to get clients to focus on long-term investing and ignore the constant short-term noise spewed by the media. This paper provides a series of easily understood tables and figures that should help clients realize why financial advisors must use appropriate time horizons when formulating lifetime financial plans. It also explores the intuitive nature of dedicated portfolios for retirement, and the critical path that splits the future into â€œsafe zonesâ€ and â€œdanger zones.â€The images use the same style box and color scheme that Morningstar uses for its Market Barometer. They are backed up technically with regression analyses to demonstrate that time horizons as well as size and value-growth dimensions are statistically significant in explaining return rates. The same is true for the probabilities of earning selected returns, such as chances of earning 10 percent or more over various time horizons. This paper also challenges what we believe are incorrect interpretations of volatility as risk in modern portfolio theory (MPT).

SSRN

Financial literacy has become a major area of research in recent years, both in the investment and retirement literature with respect to the increasing complexity of financial products and need to save for retirement. Studies generally find individuals are financially uninformed and lacking in basic financial principles. This study discusses in depth research with detailed analyses of financial literacy, financial education, individual investment outcomes, genetic investment biases, and related issues.A vast literature concerning investor financial literacy and education exists. The SECâ€™s [2012] study mandated under the Dodd-Frank Act provides a recent overall review and highlights existing levels of retail investor financial literacy and preferences for formats and timing of intermediary disclosures prior to making investment decisions, and more.Lusardi and Mitchell [2013] assess research on financial literacy. Topics include theoretical research that casts financial literacy as an investment in human capital, how much financial knowledge individuals and groups have, the impact of financial literacy on financial decision-making, and what yet remains to be learned. Fernandes, Lynch, and Netemeyer [2014] review research on financial literacy, financial education, and consumer financial outcomes. Meta-analysis is performed on financial literacy and financial education relationships in 201 non-redundant studies. Interventions to improve financial literacy explain only 0.10% of variance in financial behaviors.Glaser and Walther [2014] combine psychology research with empirical findings on the usefulness of financial literacy for investment decisions. The personal behavior of individuals with high levels of financial literacy may depend on the prevalence of two styles of thinking in dual-process theories: intuition and cognition. Collins [2012] finds the lack of financial literacy can reduce ability of individuals to make informed financial decisions. But, financial advice has the potential to substitute for lack of ability in financial decision-making. However, advice more often complements financial capability for individuals with higher levels of income, education, and financial literacy.

SSRN

Baker and Wurgler [2007] take a â€œtop downâ€ approach to behavioral finance and the stock market. Investor sentiment is taken to be exogenous and the focus is on its empirical effects. Sentiment is measurable and its waves have clearly discernible, important, and regular effects on firms and the overall stock market. Stocks that are hardest to arbitrage or value are most affected by sentiment.Other studies discussed relate to aspects of investor sentiment and sentiment indexes in Baker and Wurgler [2007] and/or Baker and Wurgler [2006]. Massa and Yadav [2012] analyze whether mutual funds opportunistically exploit market inability to identify sentiment risk. Gasbarro et al. [2012] determine that when fund investor sentiment is high (low), returns are higher for funds with low (high) sentiment-beta portfolios. Irek and Lehnert [2013] use the sentiment index and find that market risk is not a priced factor of expected fund returns when investor sentiment is positive. Sibley et al. [2013] determine that although sentiment is orthogonal to macroeconomic conditions, sentiment indexes have substantial information related to business cycles. Joseph et al. [2011] find that intensity of searches for ticker symbols serves as a valid proxy for investor sentiment, which is useful for forecasting stock returns and trade volume. Huang et al. [2014] determine that the sentiment index likely understates the predictive power of investor sentiment.

arXiv

Risk assessment under different possible scenarios is a source of uncertainty that may lead to concerning financial losses. We address this issue, first, by adapting a robust framework to the class of spectral risk measures. Second, we propose a Deviation-based approach to quantify uncertainty. Furthermore, the theory is illustrated with a practical case study from NASDAQ index.

SSRN

Wrong way risk can be incorporated in Credit Value Adjustment (CVA) calculations in a reduced form model. Hull and White (2012) introduced a CVA model that captures wrong way risk by expressing the stochastic intensity of a counterparty's default time in terms of the financial institution's credit exposure to the counterparty. We consider a class of reduced form CVA models that includes the formulation of Hull and White and show that wrong way CVA need not exceed independent CVA. This result is based on some general properties of the model calibration scheme and a formula that we derive for intensity models of dependent CVA (wrong or right way). We support our result with a stylized analytical example as well as more realistic numerical examples based on the Hull and White model. We conclude with a discussion of the implications of our findings for Basel III CVA capital charges, which are predicated on the assumption that wrong way risk increases CVA.

SSRN

The time diversification controversy, one of the most contentious issues in asset allocation, refers to the relationship between risk and the holding period. One of the aspects of this controversy is related to whether stocks become more or less risky than bonds as the holding period lengthens. To be sure, this question does not have an unequivocal answer. But the bulk of the comprehensive evidence analyzed in this article, spanning over 19 countries and 110 years, suggests that time does diversify risk. In other words, although not all results point in exactly the same direction, the overall picture that emerges is that as the holding period lengthens stocks do become less risky than bonds. This conclusion follows from an analysis based on two ways of assessing returns and several ways of assessing risk.

SSRN

This study explores which asset classes add value to a traditional portfolio of stocks, bonds and cash. Next, we determine the optimal weights of all asset classes in the optimal portfolio. This study adds to the literature by distinguishing ten different investment categories simultaneously in a mean-variance analysis as well as a market portfolio approach. We also demonstrate how to combine these two methods. Our results suggest that real estate, commodities and high yield add most value to the traditional asset mix. A study with such a broad coverage of asset classes has not been conducted before, not in the context of determining capital market expectations and performing a mean-variance analysis, neither in assessing the global market portfolio.

arXiv

Sharpe ratio (sometimes also referred to as information ratio) is widely used in asset management to compare and benchmark funds and asset managers. It computes the ratio of the (excess) net return over the strategy standard deviation. However, the elements to compute the Sharpe ratio, namely, the expected returns and the volatilities are unknown numbers and need to be estimated statistically. This means that the Sharpe ratio used by funds is likely to be error prone because of statistical estimation errors. In this paper, we provide various tests to measure the quality of the Sharpe ratios. By quality, we are aiming at measuring whether a manager was indeed lucky of skillful. The test assesses this through the statistical significance of the Sharpe ratio. We not only look at the traditional Sharpe ratio but also compute a modified Sharpe insensitive to used Capital. We provide various statistical tests that can be used to precisely quantify the fact that the Sharpe is statistically significant. We illustrate in particular the number of trades for a given Sharpe level that provides statistical significance as well as the impact of auto-correlation by providing reference tables that provides the minimum required Sharpe ratio for a given time period and correlation. We also provide for a Sharpe ratio of 0.5, 1.0, 1.5 and 2.0 the skill percentage given the auto-correlation level.

arXiv

The 2008 financial crisis has been attributed to "excessive complexity" of the financial system due to financial innovation. We employ computational complexity theory to make this notion precise. Specifically, we consider the problem of clearing a financial network after a shock. Prior work has shown that when banks can only enter into simple debt contracts with each other, then this problem can be solved in polynomial time. In contrast, if they can also enter into credit default swaps (CDSs), i.e., financial derivative contracts that depend on the default of another bank, a solution may not even exist.

In this work, we show that deciding if a solution exists is NP-complete if CDSs are allowed. This remains true if we relax the problem to $\varepsilon$-approximate solutions, for a constant $\varepsilon$. We further show that, under sufficient conditions where a solution is guaranteed to exist, the approximate search problem is PPAD-complete for constant $\varepsilon$. We then try to isolate the "origin" of the complexity. It turns out that already determining which banks default is hard. Further, we show that the complexity is not driven by the dependence of counterparties on each other, but rather hinges on the presence of so-called naked CDSs. If naked CDSs are not present, we receive a simple polynomial-time algorithm. Our results are of practical importance for regulators' stress tests and regulatory policy.

SSRN

This article examines the fine structure of risk-neutral currency returns. For this purpose, I specify models comprising pure or time-changed diffusion risk, pure or time-changed jumps, or both. The models are calibrated to vanilla options and subsequently applied to the one-touch option market. Since one-touches are unspanned by a complete set of vanilla options, they lend themselves to a rigorous out-of-sample test. The results suggest that vanilla and one-touch option markets do not generally agree on the fine structure of currency returns: Evidence from the vanilla market favors a complex model with stochastic volatility and jumps, whereas one-touch options imply purely diffusive currency dynamics. This latter finding gives rise to two interpretations. Either, the high activity in currency markets is best reflected by the infinite variation of a diffusive risk factor. Alternatively, the result is an artefact of market makers who anchor their quotes to what the pure diffusion Black-Scholes model implies.

SSRN

This paper characterize equilibrium pricing and trading strategies in a competitive market where a subset of liquidity traders have a preference for executing their trades at a benchmark price. In the model, order flow is at a maximum while price impact is at a minimum when the price benchmark is set. These results are consistent with recent empirical evidence from foreign exchange markets. The market structure in the model give incentives for the use of manipulative frontrunning strategies, but I show that the presence of a rational market maker partly negates the use of such strategies.This has important implications for benchmark design and understanding benchmark manipulation.

SSRN

We estimate post-jump volatility-decay risk premia as the predictable â€Ždifference between periods of high and low diffusive volatility. By â€Žconstructing straddle portfolios after positive and negative jumps occur, we â€Žshow that the gains that these hedged options' portfolios yield compensate â€Žinvestors for the uncertain magnitude and duration of volatility decay, as well â€Žas for vega exposure. This paper adds to the literature by distinguishing â€Žbetween the premia after positive versus negative jumps, and by exploring â€Žpremia patterns over time. In particular, we find that GARCH(1,1) is an â€Žinefficient identifier of jumps, and show that Hampel [1971] is a superior â€Žprocedure. â€Ž

SSRN

This paper intends to provide some guidance into what is an appropriate asset allocation strategy and draw down rate. We examine a number of commonly used strategies, these being the mean variance strategy, fixed asset allocation strategy and lastly a time varying asset allocation strategy. The overall findings are that the straight forward rule of a 4% real draw down is consistent with earlier studies. The simple allocation of 80% equities and 20% bonds seems to be a good rule of thumb. However, this approach has been criticised by some researchers as being suboptimal as the strategy is inefficient and there are embedded costs in this strategy that are wasteful. The simplistic nature of the strategy does not take into account mean reversion of stock prices and can suffer from extreme downside risk as illustrated by the poor performance of the stock market during bear markets. Having a high equity exposure during these times can substantially reduce ones capital. It therefore makes sense to adopt a flexible asset allocation strategy depending upon the relative attractiveness of equities, bonds and cash. We examine a number of TAA strategies and find that all out perform the static 80/20 strategy. The attractive feature of these strategies is that they may not generate as high returns when equities are performing well but they perform substantially better in down markets.

SSRN

The GARCH framework has been used for option pricing with quite some success. While the initial work assumed conditional Gaussian innovations, recent contributions relax this assumption and allow for more flexible parametric specifications of the underlying distribution. However, until now the empirical applications have been limited to index options or options on only a few stocks and this using only few potential distributions and variance specifications. In this paper we test the GARCH framework on 30 stocks in the Dow Jones Industrial Average using two classical volatility specifications and 7 different underlying distributions. Our results provide clear support for using an asymmetric volatility specification together with non-Gaussian distribution, particularly of the Normal Inverse Gaussian type, and statistical tests show that this model is most frequently among the set of best performing models.

RePEC

This paper begins by a recap on the ambition and mechanism behind Bitcoin, followed by an overview of the top 10 cryptocurrencies by market capitalization. Our focus is on their price dynamics and volatility relative to those of fiat paper money and gold, assets that have traditionally served the functions of money and international reserves. We then perform a counterfactual analysis using the Bank of England's foreign currency reserves to determine the hypothetical performance in terms of relative volatility of two alternative reserve portfolios consisting of 0.1%, 1%, or 10% holdings of either Bitcoin only, since July 2010, or of a portfolio of 50% Bitcoin and 50% Ethereum, since July 2015. Revisiting in this light the functions of money and international reserves, we expound on why private cryptocurrencies do not meet the inherent requirements for both money and international reserve assets, whereas central bank digital currencies do meet these requirements. We, finally, "scale" the magnitude and dynamics of the recent Bitcoin bubble into a historical perspective, and conclude by a discussion of areas where blockchain-based and FinTech technologies could be beneficial in international trade, payments, banking and finance.

SSRN

Retirees have long been considered financially fragile. The notion that they are ill-equipped to absorb financial shocks is captured in the traditional trope that they live on fixed incomes. Going forward, retirees will get much less income from fixed Social Security and employer pensions, and much more from savings in 401(k) plans and individual retirement accounts (IRAs). These savings give retirees greater flexibility to respond to shocks. But tapping into their nest eggs comes at the cost of having fewer resources to cover ongoing expenses. The increased dependence on financial assets also introduces new sources of riskâ€"that households accumulate too little over their working years or draw down their savings too quickly in retirement, and their finances increasingly are exposed to financial market downturns. To the extent these changes increase the financial fragility of retirees, they create new challenges that must be addressed.