Savva Shanaev - Academia.edu (original) (raw)

Papers by Savva Shanaev

SSRN Electronic Journal, 2019

SSRN Electronic Journal, 2019

Purpose The purpose of this paper is to study LEGO sets as a potential alternative asset class. A... more Purpose The purpose of this paper is to study LEGO sets as a potential alternative asset class. An exhaustive sample of 10,588 sets is used to generate inferences regarding long-term LEGO performance, its diversification benefits and return determinants. Design/methodology/approach LEGO set performance is studied in terms of equal- and value-weighted portfolios, sorts based on set characteristics and cross-sectional regressions. Findings Over 1966–2018, LEGO value-weighted index accounted for survivorship bias enjoys 1.20% inflation-adjusted return per annum, well below 5.54% for equities. However, the defensive properties of LEGO are considerable, as including 5%–25% of LEGO in a diversified portfolio is beneficial for investors with varying levels of risk aversion. LEGO secondary market is relatively internationalised, with investors from larger economies, countries with higher per capita incomes and less income inequality are shown to trade LEGO more actively. Practical implications LEGO investors derive non-pecuniary utility that is separable from their risk-return profile. LEGO is not exposed to any of the Fama-French factors, however, set-specific size and value effects are also well-pronounced on the LEGO market, with smaller sets and sets with lower price-to-piece ratio exhibiting higher yields. Older sets are also enjoying higher returns, demonstrating a liquidity effect. Originality/value This is the first study to investigate the investment properties of LEGO as an alternative asset class from micro- and macro-financial perspectives that overcomes many survivorship bias limitations prevalent in earlier research. LEGO trading is shown to be an important source of valuable data to enable original robustness checks for prominent theoretical concepts from asset pricing and behavioural finance literature.

SSRN Electronic Journal, 2019

This paper is the first to rigorously test commonly cited simplistic theories of cryptocurrency p... more This paper is the first to rigorously test commonly cited simplistic theories of cryptocurrency pricing, namely, cost-based model and Metcalfe’s law, using causal inferences from the instrumental variables approach on block-level data for six proof-of-work coins. Positive effects of hashrate and transaction count implied by cost-based pricing and Metcalfe’s law, respectively, are non-existent for any of the coins investigated. Negative and insignificant estimators cannot be explained by weak instruments, suggesting previously reported strong positive relationships are spurious due to autocorrelation and endogeneity. The study reinforces the need for a more sophisticated cryptocurrency valuation framework.

SSRN Electronic Journal, 2019

SSRN Electronic Journal, 2019

This study applies Fama-French-style factor loading analysis to cryptocurrency financial performa... more This study applies Fama-French-style factor loading analysis to cryptocurrency financial performance data to determine the originality of 32 reportedly novel consensus algorithms (“proofs”) and 20 hybrid consensus mechanisms as compared to conventional proof-of-work and proof-of-stake using a sample of 302 cryptocurrencies. Only 14 out of 32 new consensus algorithms and 12 out of 20 hybrid mechanisms are found to be truly original. Innovative consensus protocols are not associated with superior returns while original hybrid solutions are. The findings allow investors to select coins with original “proofs” and to explore performance implications of consensus algorithms. For future research, the applicability of market, size, proof and age factors for risk and attribution analysis of cryptocurrency markets is evidenced.

SSRN Electronic Journal, 2018

In this article, an event studies approach is utilized to assess the influence of 51% attacks on ... more In this article, an event studies approach is utilized to assess the influence of 51% attacks on proof-of-work (PoW) cryptocurrency prices. The study uses an exhaustive sample of 14 individual attacks on 13 cryptocurrencies. Across multiple event studies techniques, majority attacks on blockchains are consistently shown to immediately decrease corresponding coin prices by 12% to 15%. Significantly negative price response is robust in various event windows. Coin prices do not recover to pre-attack levels one week after the event. There is evidence of pump-and-dump schemes prior to the 51% attack, however the market demonstrates high efficiency after the attacks. 51% attacks are suggested to be a fundamental risk factor for cryptocurrency investments, primarily characteristic of small PoW coins with low hash rates. TOPIC: Currency Key Findings • 51% attacks on Proof-of-Work cryptocurrencies decrease their market prices by 12.60% on average. • The effect is robust to different measurement techniques and in various event windows. • There is evidence of insider trading and “pump-and-dump” schemes prior to the attacks.

Journal of Behavioral and Experimental Finance, 2018

Abstract This study investigates the presence of political risk premia among 298 listed companies... more Abstract This study investigates the presence of political risk premia among 298 listed companies from 59 Russian regions over a five-year period (10/2012–09/2017). Using a regional political stability score not available in the literature, this paper applies panel data approach to evidence the pricing of regional political risk in forms of long-term political instability premium (up to 2.20% monthly) and short-term impact-shock premium. The findings indicate that regional political risk is more impactful than countrywide or international risk and that regional political processes are crucial for the understanding of the synchronisation of stock returns with broader markets.

SSRN Electronic Journal, 2019

In this study, a mathematical model of proof-of-work cryptocurrency valuation is developed based ... more In this study, a mathematical model of proof-of-work cryptocurrency valuation is developed based on the concepts of simultaneous equilibria in two mining games, the purchasing power parity in the system of equations of exchange and the network effects of transaction cost optimisation in the economy where agents utilise both conventional and digital currencies to process payments. The model lays the foundation for rigorous long-term proof-of-work cryptocurrency valuation superior to existing approaches that are solely based on variations of Metcalfe’s law or costs of mining. Based on the model, the long-term Bitcoin equilibrium price conditional on current block size limit is 106,whileiftheblocksizelimitisabandoned,theconditionalequilibriumpriceis106, while if the block size limit is abandoned, the conditional equilibrium price is 106,whileiftheblocksizelimitisabandoned,theconditionalequilibriumpriceis6725. Network hashrate is consistent with the no-limit scenario, while the transaction fees are consistent with the status quo, revealing an important source of uncertainty on the market. The developed framework is also applied to the measure the net social value of proof-of-work cryptocurrencies, and Bitcoin long-term social value of equilibrium is shown to be positive at $126,200 per block. The comparison of equilibrium and optimal cases shows that external intervention is not necessary to guarantee socially beneficial outcomes.

The European Journal of Finance, 2020

This study examines the dynamics of ten most notable stock market anomalies through 1926–2018 and... more This study examines the dynamics of ten most notable stock market anomalies through 1926–2018 and assesses the joint impact of academic attention, post-publication decay, data-snooping bias, institutional trading, and time trend on their disappearance. It proposes new and simple measures of academic attention attracted by stock market anomalies using the number of articles published on the relevant topic available via Google Scholar or respective citation counts. The study finds that academic attention is the most dominant factor explaining the diminishing abnormal returns of anomaly-exploiting strategies. The approach developed by this study can also be useful in determining whether a stock return regularity is a behavioural anomaly or a systematic risk factor.

Finance Research Letters, 2021

This study is the first to employ calendar-time portfolio methodology to investigate the impact o... more This study is the first to employ calendar-time portfolio methodology to investigate the impact of 748 ESG rating changes on stock returns of US firms over 2016–2021. While ESG rating upgrades lead to positive yet inconsistently significant abnormal returns of 0.5% per month, downgrades are detrimental to stock performance, leading to statistically significant monthly risk-adjusted returns of -1.2% on average. These findings are more pronounced for ESG leaders than laggards and are robust to various asset-pricing model specifications. The effects of ESG rating levels are modest, with ESG laggards underperforming in risk-adjusted terms.

International Trade eJournal, 2020

This study proposes a novel instrumental variable construction procedure based on international t... more This study proposes a novel instrumental variable construction procedure based on international trade concentration that has a sufficiently strong first stage for exchange rate policy choice globally and applies it to revisit the causal effects of exchange rate regimes on macroeconomic outcomes. Fixed exchange rates are shown to cause lower economic growth rates, higher volatility of output and inflation, and higher unemployment, without reducing average inflation. These effects persist even when monetary unions are excluded from the sample, across subsamples with varying levels of per capita income and institutional quality and is robust to alternative regime classifications as well as to property rights, human capital, and trade openness controls.

SSRN Electronic Journal

Financial markets are useful indicators of public beliefs and dispersed knowledge on future outco... more Financial markets are useful indicators of public beliefs and dispersed knowledge on future outcomes and policy efficiency, especially in periods of uncertainty. 51 national stock markets successfully absorb publicly available information regarding COVID-19 and anticipate policy measures being taken to address the pandemic. The financial markets imply national lockdown policies, as well as monetary or fiscal stimuli, are counterproductive measures while targeted regional lockdowns can be effective. The fundamental effect of the pandemic is relatively low, sentiment and irrational panic play a greater role, while the most significant drivers of negative stock returns are policy interventions.

SSRN Electronic Journal

This study fits 22 theoretical distribution functions, four of them originally derived, onto 772 ... more This study fits 22 theoretical distribution functions, four of them originally derived, onto 772 cryptocurrency daily returns with goodness-of-fit evaluated using Cramer-von Mises, Anderson-Darling, Kuiper, Kolmogorov-Smirnov, and Chi-squared tests, as well as a harmonic mean p-value synthetic criterion. Most cryptocurrency return distributions can be sufficiently approximated with a Johnson SU function or an asymmetric power function. Johnson SU, asymmetric Student, and asymmetric Laplace distributions have better fit for larger cryptocurrencies, while error, generalised Cauchy, and Hampel (a Gaussian-Cauchy mixture) distributions are more characteristic of smaller cryptocurrencies, with larger coins demonstrating better overall fit. Less than 8% of sample coins and less than 4% of the top quartile by size do not fit into any of the investigated distributions, three largest “misbehaving” cryptocurrencies being Litecoin, Dogecoin, and Decred. Bitcoin and Ethereum are best modelled with error and asymmetric power law distributions, respectively, with asymmetric power law distributions stable through time. More than 30% of sample cryptocurrencies, and 26% from the top quartile, have infinite theoretical variance, severely limiting the diversification potential with such cryptoassets. Three most prominent infinite-variance coins are Bitcoin SV, Tezos, and ZCash. This study has substantial implications for risk management, portfolio management, and cryptocurrency derivative pricing.

Annals of Tourism Research

The Journal of Alternative Investments

This paper is the first to rigorously test commonly cited simplistic theories of cryptocurrency p... more This paper is the first to rigorously test commonly cited simplistic theories of cryptocurrency pricing, namely, cost-based model and Metcalfe's law, using causal inferences from the instrumental variables approach on block-level data for six proof-of-work coins. Positive effects of hashrate and transaction count implied by cost-based pricing and Metcalfe's law, respectively, are non-existent for any of the coins investigated. Negative and insignificant estimators cannot be explained by weak instruments, suggesting previously reported strong positive relationships are spurious due to autocorrelation and endogeneity. The study reinforces the need for a more sophisticated cryptocurrency valuation framework.

This study applies Fama-French-style factor loading analysis to cryptocurrency financial performa... more This study applies Fama-French-style factor loading analysis to cryptocurrency financial performance data to determine the originality of 32 reportedly novel consensus algorithms ("proofs") and 20 hybrid consensus mechanisms as compared to conventional proof-of-work and proof-of-stake using a sample of 302 cryptocurrencies. Only 14 out of 32 new consensus algorithms and 12 out of 20 hybrid mechanisms are found to be truly original. Innovative consensus protocols are not associated with superior returns while original hybrid solutions are. The findings allow investors to select coins with original "proofs" and to explore performance implications of consensus algorithms. For future research, the applicability of market, size, proof and age factors for risk and attribution analysis of cryptocurrency markets is evidenced.

SSRN Electronic Journal, 2019

SSRN Electronic Journal, 2019

Purpose The purpose of this paper is to study LEGO sets as a potential alternative asset class. A... more Purpose The purpose of this paper is to study LEGO sets as a potential alternative asset class. An exhaustive sample of 10,588 sets is used to generate inferences regarding long-term LEGO performance, its diversification benefits and return determinants. Design/methodology/approach LEGO set performance is studied in terms of equal- and value-weighted portfolios, sorts based on set characteristics and cross-sectional regressions. Findings Over 1966–2018, LEGO value-weighted index accounted for survivorship bias enjoys 1.20% inflation-adjusted return per annum, well below 5.54% for equities. However, the defensive properties of LEGO are considerable, as including 5%–25% of LEGO in a diversified portfolio is beneficial for investors with varying levels of risk aversion. LEGO secondary market is relatively internationalised, with investors from larger economies, countries with higher per capita incomes and less income inequality are shown to trade LEGO more actively. Practical implications LEGO investors derive non-pecuniary utility that is separable from their risk-return profile. LEGO is not exposed to any of the Fama-French factors, however, set-specific size and value effects are also well-pronounced on the LEGO market, with smaller sets and sets with lower price-to-piece ratio exhibiting higher yields. Older sets are also enjoying higher returns, demonstrating a liquidity effect. Originality/value This is the first study to investigate the investment properties of LEGO as an alternative asset class from micro- and macro-financial perspectives that overcomes many survivorship bias limitations prevalent in earlier research. LEGO trading is shown to be an important source of valuable data to enable original robustness checks for prominent theoretical concepts from asset pricing and behavioural finance literature.

SSRN Electronic Journal, 2019

This paper is the first to rigorously test commonly cited simplistic theories of cryptocurrency p... more This paper is the first to rigorously test commonly cited simplistic theories of cryptocurrency pricing, namely, cost-based model and Metcalfe’s law, using causal inferences from the instrumental variables approach on block-level data for six proof-of-work coins. Positive effects of hashrate and transaction count implied by cost-based pricing and Metcalfe’s law, respectively, are non-existent for any of the coins investigated. Negative and insignificant estimators cannot be explained by weak instruments, suggesting previously reported strong positive relationships are spurious due to autocorrelation and endogeneity. The study reinforces the need for a more sophisticated cryptocurrency valuation framework.

SSRN Electronic Journal, 2019

SSRN Electronic Journal, 2019

This study applies Fama-French-style factor loading analysis to cryptocurrency financial performa... more This study applies Fama-French-style factor loading analysis to cryptocurrency financial performance data to determine the originality of 32 reportedly novel consensus algorithms (“proofs”) and 20 hybrid consensus mechanisms as compared to conventional proof-of-work and proof-of-stake using a sample of 302 cryptocurrencies. Only 14 out of 32 new consensus algorithms and 12 out of 20 hybrid mechanisms are found to be truly original. Innovative consensus protocols are not associated with superior returns while original hybrid solutions are. The findings allow investors to select coins with original “proofs” and to explore performance implications of consensus algorithms. For future research, the applicability of market, size, proof and age factors for risk and attribution analysis of cryptocurrency markets is evidenced.

SSRN Electronic Journal, 2018

In this article, an event studies approach is utilized to assess the influence of 51% attacks on ... more In this article, an event studies approach is utilized to assess the influence of 51% attacks on proof-of-work (PoW) cryptocurrency prices. The study uses an exhaustive sample of 14 individual attacks on 13 cryptocurrencies. Across multiple event studies techniques, majority attacks on blockchains are consistently shown to immediately decrease corresponding coin prices by 12% to 15%. Significantly negative price response is robust in various event windows. Coin prices do not recover to pre-attack levels one week after the event. There is evidence of pump-and-dump schemes prior to the 51% attack, however the market demonstrates high efficiency after the attacks. 51% attacks are suggested to be a fundamental risk factor for cryptocurrency investments, primarily characteristic of small PoW coins with low hash rates. TOPIC: Currency Key Findings • 51% attacks on Proof-of-Work cryptocurrencies decrease their market prices by 12.60% on average. • The effect is robust to different measurement techniques and in various event windows. • There is evidence of insider trading and “pump-and-dump” schemes prior to the attacks.

Journal of Behavioral and Experimental Finance, 2018

Abstract This study investigates the presence of political risk premia among 298 listed companies... more Abstract This study investigates the presence of political risk premia among 298 listed companies from 59 Russian regions over a five-year period (10/2012–09/2017). Using a regional political stability score not available in the literature, this paper applies panel data approach to evidence the pricing of regional political risk in forms of long-term political instability premium (up to 2.20% monthly) and short-term impact-shock premium. The findings indicate that regional political risk is more impactful than countrywide or international risk and that regional political processes are crucial for the understanding of the synchronisation of stock returns with broader markets.

SSRN Electronic Journal, 2019

In this study, a mathematical model of proof-of-work cryptocurrency valuation is developed based ... more In this study, a mathematical model of proof-of-work cryptocurrency valuation is developed based on the concepts of simultaneous equilibria in two mining games, the purchasing power parity in the system of equations of exchange and the network effects of transaction cost optimisation in the economy where agents utilise both conventional and digital currencies to process payments. The model lays the foundation for rigorous long-term proof-of-work cryptocurrency valuation superior to existing approaches that are solely based on variations of Metcalfe’s law or costs of mining. Based on the model, the long-term Bitcoin equilibrium price conditional on current block size limit is 106,whileiftheblocksizelimitisabandoned,theconditionalequilibriumpriceis106, while if the block size limit is abandoned, the conditional equilibrium price is 106,whileiftheblocksizelimitisabandoned,theconditionalequilibriumpriceis6725. Network hashrate is consistent with the no-limit scenario, while the transaction fees are consistent with the status quo, revealing an important source of uncertainty on the market. The developed framework is also applied to the measure the net social value of proof-of-work cryptocurrencies, and Bitcoin long-term social value of equilibrium is shown to be positive at $126,200 per block. The comparison of equilibrium and optimal cases shows that external intervention is not necessary to guarantee socially beneficial outcomes.

The European Journal of Finance, 2020

This study examines the dynamics of ten most notable stock market anomalies through 1926–2018 and... more This study examines the dynamics of ten most notable stock market anomalies through 1926–2018 and assesses the joint impact of academic attention, post-publication decay, data-snooping bias, institutional trading, and time trend on their disappearance. It proposes new and simple measures of academic attention attracted by stock market anomalies using the number of articles published on the relevant topic available via Google Scholar or respective citation counts. The study finds that academic attention is the most dominant factor explaining the diminishing abnormal returns of anomaly-exploiting strategies. The approach developed by this study can also be useful in determining whether a stock return regularity is a behavioural anomaly or a systematic risk factor.

Finance Research Letters, 2021

This study is the first to employ calendar-time portfolio methodology to investigate the impact o... more This study is the first to employ calendar-time portfolio methodology to investigate the impact of 748 ESG rating changes on stock returns of US firms over 2016–2021. While ESG rating upgrades lead to positive yet inconsistently significant abnormal returns of 0.5% per month, downgrades are detrimental to stock performance, leading to statistically significant monthly risk-adjusted returns of -1.2% on average. These findings are more pronounced for ESG leaders than laggards and are robust to various asset-pricing model specifications. The effects of ESG rating levels are modest, with ESG laggards underperforming in risk-adjusted terms.

International Trade eJournal, 2020

This study proposes a novel instrumental variable construction procedure based on international t... more This study proposes a novel instrumental variable construction procedure based on international trade concentration that has a sufficiently strong first stage for exchange rate policy choice globally and applies it to revisit the causal effects of exchange rate regimes on macroeconomic outcomes. Fixed exchange rates are shown to cause lower economic growth rates, higher volatility of output and inflation, and higher unemployment, without reducing average inflation. These effects persist even when monetary unions are excluded from the sample, across subsamples with varying levels of per capita income and institutional quality and is robust to alternative regime classifications as well as to property rights, human capital, and trade openness controls.

SSRN Electronic Journal

Financial markets are useful indicators of public beliefs and dispersed knowledge on future outco... more Financial markets are useful indicators of public beliefs and dispersed knowledge on future outcomes and policy efficiency, especially in periods of uncertainty. 51 national stock markets successfully absorb publicly available information regarding COVID-19 and anticipate policy measures being taken to address the pandemic. The financial markets imply national lockdown policies, as well as monetary or fiscal stimuli, are counterproductive measures while targeted regional lockdowns can be effective. The fundamental effect of the pandemic is relatively low, sentiment and irrational panic play a greater role, while the most significant drivers of negative stock returns are policy interventions.

SSRN Electronic Journal

This study fits 22 theoretical distribution functions, four of them originally derived, onto 772 ... more This study fits 22 theoretical distribution functions, four of them originally derived, onto 772 cryptocurrency daily returns with goodness-of-fit evaluated using Cramer-von Mises, Anderson-Darling, Kuiper, Kolmogorov-Smirnov, and Chi-squared tests, as well as a harmonic mean p-value synthetic criterion. Most cryptocurrency return distributions can be sufficiently approximated with a Johnson SU function or an asymmetric power function. Johnson SU, asymmetric Student, and asymmetric Laplace distributions have better fit for larger cryptocurrencies, while error, generalised Cauchy, and Hampel (a Gaussian-Cauchy mixture) distributions are more characteristic of smaller cryptocurrencies, with larger coins demonstrating better overall fit. Less than 8% of sample coins and less than 4% of the top quartile by size do not fit into any of the investigated distributions, three largest “misbehaving” cryptocurrencies being Litecoin, Dogecoin, and Decred. Bitcoin and Ethereum are best modelled with error and asymmetric power law distributions, respectively, with asymmetric power law distributions stable through time. More than 30% of sample cryptocurrencies, and 26% from the top quartile, have infinite theoretical variance, severely limiting the diversification potential with such cryptoassets. Three most prominent infinite-variance coins are Bitcoin SV, Tezos, and ZCash. This study has substantial implications for risk management, portfolio management, and cryptocurrency derivative pricing.

Annals of Tourism Research

The Journal of Alternative Investments

This paper is the first to rigorously test commonly cited simplistic theories of cryptocurrency p... more This paper is the first to rigorously test commonly cited simplistic theories of cryptocurrency pricing, namely, cost-based model and Metcalfe's law, using causal inferences from the instrumental variables approach on block-level data for six proof-of-work coins. Positive effects of hashrate and transaction count implied by cost-based pricing and Metcalfe's law, respectively, are non-existent for any of the coins investigated. Negative and insignificant estimators cannot be explained by weak instruments, suggesting previously reported strong positive relationships are spurious due to autocorrelation and endogeneity. The study reinforces the need for a more sophisticated cryptocurrency valuation framework.

This study applies Fama-French-style factor loading analysis to cryptocurrency financial performa... more This study applies Fama-French-style factor loading analysis to cryptocurrency financial performance data to determine the originality of 32 reportedly novel consensus algorithms ("proofs") and 20 hybrid consensus mechanisms as compared to conventional proof-of-work and proof-of-stake using a sample of 302 cryptocurrencies. Only 14 out of 32 new consensus algorithms and 12 out of 20 hybrid mechanisms are found to be truly original. Innovative consensus protocols are not associated with superior returns while original hybrid solutions are. The findings allow investors to select coins with original "proofs" and to explore performance implications of consensus algorithms. For future research, the applicability of market, size, proof and age factors for risk and attribution analysis of cryptocurrency markets is evidenced.