The fair value of a token: How do markets price cryptocurrencies?

With the rise of cryptocurrency tokens as a new asset class, the question of the fair evaluation of a cryptocurrency token has become a question of increasing importance. We estimate the pricing kernel with which users price factors affecting their token holdings. We investigate how traditional risk factors such as market risk are evaluated, as well as how blockchain specific risk factors are priced in. In order to do so, we introduce an asset pricing model and modify its properties to make it applicable to cryptocurrency markets. We group the risk factors into market related and Bitcoin- and Ethereum blockchain specific risk factors. We find that blockchain specific risk factors are priced in. There is evidence that risk factors have moved from Bitcoin to Ethereum specific risk factors with an increasing importance of market factors, providing evidence for a decoupling of on-chain and off-chain trading activity.     

News‐Specific Price Discovery in Credit Default Swap Markets

We examine the lead and lag relation between equity and credit default swap (CDS) markets. We find that price discovery in equity markets only leads CDS markets following aggregate positive news and not so following other news. While difficult to reconcile with standard asset pricing theories, asymmetric price adjustment is common in goods markets, arising from intermediary power. We provide an explanation for this asymmetry based on dealers exploiting informational advantages vis‐à‐vis investors with hedging motives. Consistent with this explanation, we find that the patterns we document are related to firm‐level proxies for hedging demand, as well as economy‐wide measures of information asymmetries.     

On the topology of cryptocurrency markets

Cryptocurrency markets are characterised by high volatility, high returns and comparative immaturity relative to equity and commodity markets. Topological Data Analysis (TDA) persistence norms are effective tools for the analysis of noisy dynamical systems like the cryptocurrency markets. We show how information from the shape of daily return data adds additional inference on activity within the cryptocurrency markets. TDA persistence norms embed volatility and connectedness between coins as well as incorporating information from uncertainty indexes, financial market performance and commodity returns. Our TDA measures are robust to noise and are consistent across a raft of alternative coin selections. Further, we exposit how persistence norms peak to forewarn of crashes and stay low as markets face exogenous shocks. We demonstrate the clear advantages of TDA for the study of cryptocurrency markets and develop the next steps for exploiting the potential of TDA for application to cryptocurrency markets.     

Foreign exchange risk pricing and equity market segmentation in Africa

This work is the first to investigate simultaneously the occurrence of unconditional currency risk pricing and equity market segmentation in Africa’s major stock markets. The multi-factor asset pricing theory provides the theoretical framework for our model. We find strong evidence suggesting that Africa’s equity markets are partially segmented. However, we find insufficient evidence to reject the hypothesis that foreign exchange risk is not unconditionally priced in Africa’s stock markets. This result is robust to alternative foreign exchange rate-adjusted return measures. These findings suggest that international investors can diversify into Africa’s equity markets without worrying about unconditional risks associated with foreign exchange rate fluctuations.     

Consumption habit and international stock returns

We use the consumption-based asset pricing model with habit formation to study the predictability and cross-section of returns from the international equity markets. We find that the predictability of returns from many developed countries' equity markets is explained in part by changing prices of risks associated with consumption relative to habit at the world as well as local levels. We also provide an exploratory investigation of the cross-sectional implications of the model under the complete world market integration hypothesis and find that the model performs mildly better than the traditional consumption-based model, the unconditional and conditional world CAPMs and a three-factor international asset pricing model.     

Do different streams of capital flows affect asset prices differently?

This paper explores the impact of six types of gross capital flows (debt, equity, and banking gross inflows and outflows) on two dimensions: (1) extreme episodes of surges, stops, flights, and retrenchments, and (2) the probability of boom-busts in ASEAN-4 asset markets for the period 1993–2018. To this end, we first decompose gross capital inflows and outflows from Balance of Payments 5 and 6 and show that ASEAN-4 is largely dominated by portfolio flows and a relatively small magnitude of banking flows. However, when we link this decomposition to the extreme episodes, our findings show banking flows are volatile enough to cause greater occurrences of flight and retrenchment episodes while volatile debt flows tend to lead to surge and stop episodes. In the second part, we construct asset price index for ASEAN-4 that can detect boom-busts periods with a minimal noise-to-signal ratio eight quarters ahead. We use heteroscedasticity panel probit and ordinal generalized linear models to show that fundamental variables and banking inflows are statistically significant at increasing likelihood of boom-busts in asset markets. These two findings highlight that although largest percentage of capital flows come through debt and equity markets, the banking channel is of paramount importance in causing extreme episodes of flight and retrenchment as well as boom-busts of asset markets.     

The World Price of Foreign Exchange Risk

Departures from purchasing power parity imply that different countries have different prices for goods when a common numeraire is used. Stochastic changes in exchange rates are associated with changes in these prices and constitute additional sources of risk in asset pricing models. This article investigates whether exchange rate risks are priced in international asset markets using a conditional approach that allows for time variation in the rewards for exchange rate risk. The results for equities and currencies of the world's four largest equity markets support the existence of foreign exchange risk premia.     

Dynamic correlations and volatility effects in the Balkan equity markets

This paper investigates the presence of time-varying comovements, volatility implications and dynamic correlations in major Balkan and leading mature equity markets, in order to provide quantified responses to international asset allocation decisions. Since asset returns and correlation dynamics are critical inputs in asset pricing, portfolio management and risk hedging, emphasis is placed on the respective (constant and dynamic) equity market correlations produced by alternative multivariate GARCH forms, the Constant Conditional Correlation and the Asymmetric Dynamic Conditional Correlation models. The Balkan stock markets are seen to exhibit time-varying correlations as a peer group, although correlations with the mature markets remain relatively modest. In conjunction with sensitivity analysis on the asymmetric variance–covariance matrix, active portfolio diversification to the Balkan equity markets indicates to potentially improve investors’ risk-return trade-off.     

Local risk factors in emerging markets: Are they separately priced?

We provide new evidence on the pricing of local risk factors in emerging stock markets. We investigate whether there is a significant local currency premium together with a domestic market risk premium in equity returns within a partial integration asset pricing model. Given previous evidence on currency risk, we conduct empirical tests in a conditional setting with time-varying prices of risk. Our main results support the hypothesis of a significant exchange risk premium related to the local currency risk. Exchange rate and domestic market risks are priced separately for our sample of seven emerging markets. The empirical evidence also suggests that although statistically significant, local currency risk is on average smaller than domestic market risk but it increases substantially during crises periods, when it can be almost as large as market risk. Disentangling these two factors is thus important in tests of international asset pricing for emerging markets.     

Liquidity in the cryptocurrency market and commonalities across anomalies

We examine how liquidity affects cryptocurrency market efficiency and study commonalities in anomaly performance in cryptocurrency markets. Based on the unique features of cryptocurrencies, we build a model with anonymous traders valuing cryptocurrencies as payments for goods and investment assets, and find that decreases in funding liquidity translate into lower asset liquidity in the cryptocurrency market. Empirically, we observe that many widely recognized stock market anomalies also exist in the cryptocurrency market, although some have opposite long and short legs. We also find evidence that a decrease in cryptocurrency liquidity enhances anomalous returns while preventing the cryptocurrency market from achieving efficiency.     

Pricing options in incomplete equity markets via the instantaneous Sharpe ratio

We use a continuous version of the standard deviation premium principle for pricing in incomplete equity markets by assuming that the investor issuing an unhedgeable derivative security requires compensation for this risk in the form of a pre-specified instantaneous Sharpe ratio. First, we apply our method to price options on non-traded assets for which there is a traded asset that is correlated to the non-traded asset. Our main contribution to this particular problem is to show that our seller/buyer prices are the upper/lower good deal bounds of Cochrane and Saá-Requejo (J Polit Econ 108:79–119, 2000) and of Björk and Slinko (Rev Finance 10:221–260, 2006) and to determine the analytical properties of these prices. Second, we apply our method to price options in the presence of stochastic volatility. Our main contribution to this problem is to show that the instantaneous Sharpe ratio, an integral ingredient in our methodology, is the negative of the market price of volatility risk, as defined in Fouque et al. (Derivatives in financial markets with stochastic volatility. Cambridge University Press, 2000).     

Limited arbitrage between equity and credit markets

We document that short-horizon pricing discrepancies across firms' equity and credit markets are common and that an economically significant proportion of these are anomalous, indicating a lack of integration between the two markets. Proposing a statistical measure of market integration, we investigate whether equity–credit market integration is related to impediments to arbitrage. We find that time variation in integration across a firm's equity and credit markets is related to firm-specific impediments to arbitrage such as liquidity in equity and credit markets and idiosyncratic risk. Our evidence provides a potential resolution to the puzzle of why Merton model hedge ratios match empirically observed stock-bond elasticities (Schaefer and Strebulaev, 2008) and yet the model is limited in its ability to explain the integration between equity and credit markets (Collin-Dufresne, Goldstein, and Martin, 2001).     

Cryptocurrency returns under empirical asset pricing

This study examines the predictability of cryptocurrency returns based on investors' risk premia. Prior studies that have examined the predictability of cryptocurrencies using various economic risk factors have reported mixed results. Our out-of-sample evidence identifies the existence of a significant return predictability of cryptocurrencies based on the cryptocurrency market risk premium. Consistent with capital asset pricing theory (CAPM), our results show that investors often require higher positive returns before taking on any additional risks, particularly in terms of riskier assets like cryptocurrencies. Tests involving the CAPM model demonstrates that the three largest cryptocurrencies have significant exposures to the proposed market factor with insignificant intercepts, demonstrating that the market factor explains average cryptocurrency returns very well.     

An International Asset Pricing Model with Time-Varying Hedging Risk

This paper employs a two-factor international equilibrium asset pricing model to examine the pricing relationships among the world's five largest equity markets. In addition to the traditional market factor premium, a hedging factor premium is included as the second factor to explain the relationship between risks and returns in the international stock markets. Moreover, a GARCH parameterization is adopted to characterize the general dynamics of the conditional second moments. The results suggest that the additional hedging risk premium is needed to explain rates of return on international equities. Furthermore, the restriction that the coefficient on the hedge-portfolio covariance is one smaller than the coefficient on the market-portfolio covariance can not be rejected. This suggests that the intertemporal asset pricing model proposed by Campbell (1993) can be used to explain the returns on the five largest stock market indices.     

Characterizing Predictable Components in Excess Returns on Equity and Foreign Exchange Markets

The paper first characterizes the predictable components in excess rates of returns on major equity and foreign exchange markets using lagged excess returns, dividend yields, and forward premiums as instruments. Vector autoregressions (VARs) demonstrate one-step-ahead predictability and facilitate calculations of implied long-horizon statistics, such as variance ratios. Estimation of latent variable models then subjects the VARs to constraints derived from dynamic asset pricing theories. Examination of volatility bounds on intertemporal marginal rates of substitution provides summary statistics that quantify the challenge facing dynamic asset pricing models.     

Probability weighting and default risk: a possible explanation for distressed stock puzzles

This paper suggests incorporating investor probability weighting and the default risk of individual firms into a consumption-based asset pricing model. The extended model provides a unified explanation for several anomalous patterns observed in financial markets. The analysis addresses not only widely recognized asset pricing puzzles, such as the equity premium puzzle, but also less-studied anomalies on financially distressed stocks. The simulation, under which the model is calibrated according to U.S. historical data, shows that a combination of mild overweighting of probability on tail events and nonlinearity of equity values caused by default risk has the potential to resolve these patterns.     

A Test of the Modigliani‐Miller Invariance Theorem and Arbitrage in Experimental Asset Markets

Modigliani and Miller show that the total market value of a firm is unaffected by a repackaging of asset return streams to equity and debt if pricing is arbitrage‐free. We investigate this invariance theorem in experimental asset markets, finding value‐invariance for assets of identical risks when returns are perfectly correlated. However, exploiting price discrepancies has risk when returns have the same expected value but are uncorrelated, in which case the law of one price is violated. Discrepancies shrink in consecutive markets, but persist even with experienced traders. In markets where overall trader acuity is high, assets trade closer to parity.     

Searching for safe-haven assets during the COVID-19 pandemic

The ongoing COVID-19 pandemic has shaken the global financial system and caused great turmoil. Facing unprecedented risks in the markets, people have increasing needs to find a safe haven for their investments. Given that the nature of this crisis is a combination of multiple problems, it is substantially different from all other financial crises known to us. It is therefore urgent to re-evaluate the safe-haven role of some traditional asset types, namely, gold, cryptocurrency, foreign exchange and commodities. This paper introduces a sequential monitoring procedure to detect changes in the left-quantiles of asset returns, and to assess whether a tail change in the equity index can be offset by introducing a safe-haven asset into a simple mean-variance portfolio. The sample studied covers a training period between August–December 2019 and a testing period of December 2019–March 2020. Furthermore, we calculate the cross-quantilogram between pair-wise asset returns and compare their directional predictability on left-quantiles in both normal market conditions and the COVID-19 period. The main results show that the role of safe haven becomes less effective for most of the assets considered in this paper, while gold and soybean commodity futures remain robust as safe-haven assets during this pandemic.     

Predictable risk and returns in emerging markets

The emergence of new equity markets in Europe, Latin America,Asia, the Mideast and Africa provides a new menu of opportunitiesfor investors. These markets exhibit high expected returns aswell as high volatility. Importantly, the low correlations withdeveloped countries' equity markets significantly reduces theunconditional portfolio risk of a world investor. However, standardglobal asset pricing models, which assume complete integrationof capital markets, fail to explain the cross section of averagereturns in emerging countries. An analysis of the predictabilityof the returns reveals that emerging market returns are morelikely than developed countries to be influenced by local information.     

Cryptocurrencies: Stylized facts on a new investible instrument

We present stylized facts on the asset pricing properties of cryptocurrencies: summary statistics on cryptocurrency return properties and measures of common variation for secondary market returns on 222 digital coins. In our sample, secondary market returns of all other currencies are strongly correlated with Bitcoin returns. We also provide some investment characteristics of a sample of 64 initial coin offerings.