Asset Pricing

We present the first assessment of U.S. Okun's Law across time and frequencies, with a set of continuous wavelet tools that allows for estimating Okun's coefficient and the lead/lag of output over unemployment at each moment of time for each cyclical frequency. We find similar results for the gaps and the first differences specifications at business cycles frequencies, but not at medium and long run cycles. Okun's coefficient has increased (in absolute value) since the mid-1960s, except in 1985-1995, and is not particularly sensitive to recessions. The lead of output varies considerably along time and also at the different frequencies.

Questo lavoro si propone di offrire agli operatori una metodologia per la scelta di prezzi e quantità nelle aste dei titoli di Stato, in particolare in quelle dei Buoni Ordinari del Tesoro (BOT). Analogamente a quanto viene suggerito dalla teoria di selezione del portafoglio, si possono configurare tre fasi logicamente distinte: nella prima si stima la distribuzione congiunta dei prezzi minimi e medi di aggiudicazione, nella seconda si determina la frontiera efficiente delle combinazioni prezzi/quantità e nella terza si sceglie sulla frontiera la combinazione che massimizza la funzione di utilità individuale. Il lavoro si concentra sulle prime due fasi e in particolare sulla stima degli input necessari per applicare l’algoritmo proposto da Markowitz per la determinazione dei portafogli efficienti. A tal fine sono stati dapprima esaminati il grado di prevedibilità degli importi offerti all’asta e le relazioni esistenti tra mercato primario e secondario dei BOT. È stato quindi analizzato il contenuto informativo dei rendimenti e delle volatilità implicite osservabili nel mercato secondario dei BTP. Sulla base dei parametri stimati, è stata infine simulata la procedura di diversificazione ottimale delle richieste in sede d’asta. Un’esemplificazione è riportata in Appendice.

In questo lavoro viene analizzato il problema della determinazione delle commissioni di sottoscrizione (standby underwriting fees) all’interno dello schema offerto dalla teoria di valutazione delle opzioni. Le istituzioni finanziarie che offrono il servizio di collocamento-titoli sopportano il rischio di dover acquistare le azioni non collocate, nell’eventualità che la quantità offerta non venga completamente assorbita dal mercato. Per determinare il valore della garanzia offerta dalle istituzioni finanziarie, viene proposto un semplice modello in cui il prezzo d’equilibrio alla fine del periodo d collocamento è log-normale e la curva di domanda delle azioni è soggetta a spostamenti determinati da shocks stocastici. In questo schema, il valore della garanzia è proporzionale al valore di una put “quadratica”, ossia di un derivato il cui payoff è il quadrato di una put ordinaria. Quest’opzione può essere valutata all’interno dello schema teorico di Black e Scholes. La formula chiusa mostra che il valore di una put quadratica è molto maggiore di quello di una put ordinaria e non è semplicemente pari al quadrato di quest’ultima. In questo lavoro viene anche analizzato il problema della “riassicurazione” che nasce quando la commissione di sottoscrizione viene parzialmente trasferita ad un’altra istituzione finanziaria, che fornisce una garanzia sussidiaria. In particolare, vengono esaminati tre diversi accordi negoziali tra le due istituzioni finanziarie, e viene mostrata la ripartizione ottimale della commissione di sottoscrizione tra le due parti. Infine, viene presentata un’applicazione del modello.

Despite the strong growing popularity of Asset Pricing Models, it is difficult to estimate which factor contributes significantly in explaining average excess portfolio returns particularly in emerging equity market. Using an extensive sample over Jan-1994-Dec-2020 period, this paper aims to extend the literature by augmenting Tobin-Q adjusted risk premium with various unconditional standard asset pricing models which seeks to postulate the nexus between expected portfolios stock returns and risk-factors using monthly data of 521 enlisted financial and non-financial firms from Pakistan Stock Exchange. The multiple time-series OLS regression analysis models are employed to analyze Tobin-q risk-factor augmented with various factors models. Fama and French (2015) five-factor model excessively explains average equity returns however, our results reveal that size, value, profitability and particularly Tobin-q factor are significant while market and investment factor are redundant in Paki...

Given different views on the practicality of the multi-factor models in the Chinese stock market, this paper combines this very advanced pricing model with the newly established Chinese board, aiming to explore a pricing model applicable to the Chinese market. The selected data is all the quoted companies in the Sci-Tech Innovation Board from 2020/06/05 to 2022/04/15. The explanatory power of each multi-factor model to the board and their effects on the model are studied. In particular, this paper includes redundancy tests, GRS tests, and regressions. The main conclusions deduced from this experiment are: first, the three-factor model is very significant in all aspects; second, the five-factor model is more significant in some groups, and there is a significant difference after adjustment by the five-factor model-the book-to-market ratio effect and profitability effect. Nonetheless, since many imperfections exist within the system of the Chinese stock market and many regulations might have significant changes in the future, continuing to explore other pricing factors appropriate for the market is still the main research orientation in this field.

Given different views on the practicality of the multi-factor models in the Chinese stock market, this paper combines this very advanced pricing model with the newly established Chinese board, aiming to explore a pricing model applicable to the Chinese market. The selected data is all the quoted companies in the Sci-Tech Innovation Board from 2020/06/05 to 2022/04/15. The explanatory power of each multi-factor model to the board and their effects on the model are studied. In particular, this paper includes redundancy tests, GRS tests, and regressions. The main conclusions deduced from this experiment are: first, the three-factor model is very significant in all aspects; second, the five-factor model is more significant in some groups, and there is a significant difference after adjustment by the five-factor model—the book-to-market ratio effect and profitability effect. Nonetheless, since many imperfections exist within the system of the Chinese stock market and many regulations mig...

A two-period (0 and T) Arrow^Debreu economy is set up with a general model of uncertainty. We suppose that an equilibrium exists for this economy. The Arrow-Debreu economy is placed in a Radner [31] setting; agents may trade claims continuously during [0,T]. Under appropriate conditions it is possible to implement the original Arrow-Debreu equilibrium, which may have an infinite dimensional commodity space, in a Radner economy which has only a finite number of securities. This is done by opening the "right" set of securities markets, a set which effectively completes markets for the continuous trading Radner economy.

This paper deals with an analytical framework to provide a measure of overall performance which involves both socioeconomic activities and environmental sustainability using a recent Index of well-being. The composite indicator, created by , is associated with the so called "Magic Square", a diagram stimulated by the work of . From this starting point, we introduce a set of four variables to measure their total impact on the sustainable development of regions. They are: human development index, per capita carbon dioxide, drinkable water and sanitation, and intensity of renewable energy measured as a fraction of the total generated energy. This formal approach is applied to the comparative performance of the USA and China from 2002 to 2012. As expected, environmental, socioeconomic and institutional indicators affect the level of welfare. This being the case, an important lesson to be learned is that careful regulation and policy actions, not just proposals, are required to implement a sustainable and acceptable quality of life. In this article we complete the argument by suggesting that a new paradigm is required to fulfill our desirable objectives, and get more out of our intellectual effort, capabilities and political influence.

We present results on expectation formation in a controlled experimental environment. In each period subjects are asked to predict the next price of a risky asset. The realized market price is derived from an unknown market equilibrium equation with feedback from individual forecasts. In most experiments prices deviate from the benchmark fundamental and bubbles emerge endogenously. These bubbles are inconsistent with rational expectations and seem to be driven by trend chasing behavior or "positive feedback expectations" of the participants. We also analyze individual predictions of participants and …nd that participants within a group tend to coordinate on a common prediction strategy.

Portfolio selection is among the most challenging processes that have recently increased the interest of professionals in the area. The goal of mean-variance portfolio selection is to maximize expected return with minimizing risk. The Markowitz model was employed to solve the linear portfolio selection problem (PSP). However, due to numerous constraints and complexities, the problem is so critical that traditional models are insufficient to provide efficient solutions. Teaching learning-based optimization (TLBO) is a powerful population-based nature-inspired approach to solve optimization problems. This article presents a portfolio selection model using the TLBO approach to maximize the portfolio's Sharpe ratio. The Sharpe ratio combines both expected return and risk. This algorithm models the natural teaching process of the classroom with two main phases, viz., teaching and learning. Performance analysis has been undertaken to investigate the suitability of TLBO based solution approach by comparing it with genetic algorithm (GA) and particle swarm optimization (PSO) on the real datasets, Deutscher Aktienindex (DAX) 100, Hang Seng 31, standard & poor's (S&P) 100, financial times stock exchange (FTSE) 100, and Nikkei 225. The empirical results verify the superiority of the TLBO over GA and PSO.

We use portfolio holdings to show that mutual funds preferentially trade stocks according to the stocks" sentiment betas. Stocks with high sentiment betas are more responsive to investor sentiment and increase (decrease) in value as sentiment increases (decreases). Sentiment-based trades may be motivated by the opportunity to increase fund returns through timing predictability in sentiment, or by management of portfolio risk. Sentiment is mean-reverting, but its level and recent change only partially explain these trades. In contrast, 30 percent of sentiment-based trades are explained by the initial sentiment beta of funds that trade to reduce their tracking error variance.

This work presents a class of models in asset pricing, whose underlying has dynamics of Affine jump diffusion type. We first present Lévy processes with their properties. We then introduce Affine jump diffusion processes which are basically a particular class of Lévy processes. Our motivation for these is driven by the fact that many financial models are built on them. Affine jump diffusion processes present good analytical properties that allow one to get close form formulas for a wide range of option pricing. The approach we use here is based on the paper by Duffie D, Pan J, and Singleton K. An example will show how incorporating parameters such as the volatility of the underlying asset in the model, can influence the resulting price of the financial instrument under consideration. We will also show how this class of models incorporate well known models, specially those used to model interest rates dynamics, like for instance the Vasicek model.

Over the past decade, multifactor models have shown enhanced capability compared to single-factor models in explaining asset return variability. Given the common assertion that higher risk tends to yield higher returns, this study empirically examines the augmented human capital six-factor model's performance on thirty-two portfolios of non-financial firms sorted by size, value, profitability, investment, and labor income growth in the Indian market over the period July 2010 to June 2023. Moreover, the current study extends the Fama and French five-factor model by incorporating a human capital proxy by labor income growth as an additional factor thereby proposing an augmented six-factor asset pricing model (HC6FM). The Fama and MacBeth two-step estimation methodology is employed for the empirical analysis. The results reveal that small-cap portfolios yield significantly higher returns than large-cap portfolios. Moreover, all six factors significantly explain the time-series variation in excess portfolio returns. Our findings reveal that the Indian stock market experienced heightened volatility during the COVID-19 pandemic, leading to a decline in the six-factor model's efficiency in explaining returns. Furthermore, Gibbons, Ross, and Shanken (GRS) test results reveal mispricing of portfolio returns during COVID-19, with a stronger rejection of portfolio efficiency across models. However, the HC6FM consistently shows lower pricing errors and better performance, specifically during and after the pandemic era. Overall, the results offer important insights for policymakers, investors, and portfolio managers in optimizing portfolio selection, particularly during periods of heightened market uncertainty.

We study the permit price volatility-trading activity link in the EU ETS Phase I. We focus on the contrasting roles of different market players. We show that the relation was overall positive, mainly due to energy providers. Many other players remained inactive and traded more when volatility was lower. Policies for the engagement of less active traders could increase market efficiency.

Purpose- The prime objective of this study was to find the co-movement between the Canadian credit default swaps market, the Stock market and volatility index (TSX 60 Index) Design/ Methodology- To achieve this purpose, daily data containing 2870 observations starting from the 1st of January 2009 to the 30th of December 2019 were analyzed. This study employed the wavelet approach to present results in short-term, medium-term, long-term, and very long time. Findings- The findings of this study showed a negative correlation between the CDS market, stock market, and the TSX 60 index in the short-term as well as in the long-term term, while in medium-term and very long-term period correlation is strongly positive. The wavelet co-movement results in the short-term and long-term were negative, while this relationship in the medium-term and very long-term period was strongly positive. Practical Implications- This research provides simultaneous valuable information for investment decisions ...

Put option is a contract to sell some underlying assets in the future with a certain price. On European put options, selling only can be exercised at maturity date. Behavior of European put options price can be modeled by using the Black-Scholes model which provide an analytical solution. Numerical approximation such as binomial tree, explicit and implicit finite difference methods also can be used to solve Black-Scholes model. Some numerical methods are applied and compared with the analytical solution to determine the best numerical method. The results show that numerical approximations using the binomial tree is more accurate than explicit and implicit finite difference method in pricing European put options. Moreover when the value of T is higher then the error obtained is also higher, while the error obtained is lower when the value of N is higher. The value of T and N cause the increase of the computation time. When the value of T is higher the computation time is lower, while computation time is higher if the value of N is higher. Overall, the lowest computation time is obtained by using an explicit finite difference method with an exceptional as the value of T is big and the value of N is small. The lowest computation time is obtained by using a binomial tree method.

We find that firms experiencing improvements in crowdsourced employer ratings significantly outperform firms with declines. The return effect is concentrated among reviews from current employees, stronger among early firm reviews, and also stronger when the employee works in the headquarters state. Decomposing employer ratings, we find the return effect is related to changing employee assessments of career opportunities and views of senior management. It is unrelated to work-life balance. Changing employer reviews predict contemporaneous growth in sales and profitability and help forecast one-quarter ahead earnings announcement surprises. The evidence is consistent with employee reviews revealing fundamental information about the firm. JEL Classifications: G14

Problem/Relevance: Measuring the risk of an asset and the economic forces driving the price of the risk is a challengingtask that preoccupied the asset pricing literature for decades. However, there exists no consensus on the integrated asset pricing framework among the financial economists in the contemporaneous asset pricing literature. Thus, we consider and study this research problem that has greater relevance in pricing the risks of an asset. In this backdrop, we develop an integrated equilibrium asset pricing model in an intertemporal (ICAPM) framework. Research Objective/Questions: Broadly we have two research objectives. First, we examine the joint dynamics of the human capital component and common factors in approximating the variation in asset return predictability. Second, we test whether the human capital component is the unaccounted and the sixth pricing factor of FF five-factor asset pricing model. Additionally, we assess the economic and statistical significance of th...

We study the international stock returns across Europe, Asia Pacific, North America, US, Japan, Global, and Global excluding US. We find there are value premiums in average stock returns across the regions. There is momentum return in all the regions except for Japan. With the exception of Japan, profitability and investment premiums in average stock returns exist across the regions. Further, the value, momentum, and profitability premiums vary with the firm size and premiums decrease from smaller to bigger stocks excluding Japan. We examine whether empirical asset pricing models capture the value, momentum, profitability, and investment pattern in international average returns, and the integration of the asset prices across the regions. We reject the global integrated pricing approach. The performance of local Carhart four-factor model is relatively better than the variant models in approximating the returns on Japanese size-B/M and size-momentum portfolios. Similarly, the FF five-factor model performs better than the variant models in approximating the returns on Asia Pacific, North American, and Japanese size-profitability portfolios. In addition, FF five-factor model performs relatively better in approximating the returns on European and Japanese size-investment portfolios.

The present study introduce the human capital component to the Fama and French five-factor model proposing an equilibrium six-factor asset pricing model. The study employs an aggregate of four sets of portfolios mimicking size and industry with varying dimensions. The first set consists of three set of six portfolios each sorted on size to B/M, size to investment, and size to momentum. The second set comprises of five index portfolios, third, a four-set of twenty-five portfolios each sorted on size to B/M, size to investment, size to profitability, and size to momentum, and the final set constitute thirty industry portfolios. To estimate the parameters of six-factor asset pricing model for the four sets of variant portfolios, we use OLS and Generalized method of moments based robust instrumental variables technique (IVGMM). The results obtained from the relevance, endogeneity, overidentifying restrictions, and the Hausman's specification, tests indicate that the parameter estimates of the six-factor model using IVGMM are robust and performs better than the OLS approach. The human capital component shares equally the predictive power alongside the factors in the framework in explaining the variations in return on portfolios. Furthermore, we assess the t-ratio of the human capital component of each IVGMM estimates of the six-factor asset pricing model for the four sets of variant portfolios. The t-ratio of the human capital of the eighty-three IVGMM estimates are more than 3.00 with reference to the standard proposed by . This indicates the empirical success of the six-factor asset-pricing model in explaining the variation in asset returns.

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PurposeThe purpose of the study is to examine the dynamics in the troika of asset pricing, volatility, and the business cycle in the US and Japan.Design/methodology/approachThe study uses a six-factor asset pricing model to derive the realized volatility measure for the GARCH-type models.FindingsThe comprehensive empirical investigation led to the following conclusion. First, the results infer that the market portfolio and human capital are the primary discounting factors in asset return predictability during various phases of the subprime crisis phenomenon for the US and Japan. Second, the empirical estimates neither show any significant impact of past conditional volatility on the current conditional volatility nor any significant effect of subprime crisis episodes on the current conditional volatility in the US and Japan. Third, there is no asymmetric volatility effect during the subprime crisis phenomenon in the US and Japan except the asymmetric volatility effect during the pos...

This paper investigates the impact of Environmental, Social, and Governance (ESG) factors on asset pricing using a Generalized Method of Moments (GMM) estimation framework. The study aims to determine whether ESG scores are priced in financial markets, influencing risk-adjusted returns of assets. This study analyzes a panel of 100 publicly listed firms of China over a five-year period from 2019 to 2023. The firms are selected based on their availability of ESG scores from leading data providers (MSCI, Bloomberg) and financial data from widely used sources such as Compustat and CRSP. We find a significant negative relationship between ESG scores and excess returns. Specifically, firms with higher ESG ratings tend to exhibit lower excess returns, indicating that investors may accept lower returns in exchange for sustainability and reduced risk exposure. While traditional factors such as the market, size (SMB), and value (HML) continue to play significant roles in asset pricing, ESG factors are shown to influence returns in a manner consistent with risk-reduction theories. This study contributes to the growing literature on ESG investing, providing empirical evidence of ESG's role in asset pricing. The findings suggest that while ESG investing does not necessarily generate superior returns, it offers a riskreducing strategy that aligns with investor preferences for ethical and sustainable business practices. The paper concludes with implications for investors, policymakers, and future research on the integration of ESG in financial markets.

This paper examines one type of calendar effect in financial markets, seasonal variation in the return on stocks. The effect analyzed is referred to as the Halloween Effect or Sell in May and Go Away. This refers to the finding that stock markets tend to return considerably less in the six months beginning in May than in the other half of the year. This effect has persisted over time and is seemingly large enough to be economically significant. The alternative, but somewhat overlapping hypothesis, that seasonal affective disorder, SAD, creates seasonal variation in the return on stocks is also addressed. Based on daily data from 75 stock markets during the period 2000-2014 there is a strong calendar effect in a large majority of the markets as the period from November to April witnesses higher returns than do the other six months of the year. However, there is only weak evidence that SAD had any effect on stock prices. The paper shows that Halloween Effect seems to be remarkably consistent, even after being widely discussed, and both statistically and economically significant. However, it remains unexplained. The SAD hypothesis finds less support in the data and seems of limited relevance economically.

What determined the value of South African assets after the unbanning of the African National Congress (ANC) and the release of Nelson Mandela? Economic or political events? This paper employs a dynamic version of the APT model for the period from 1991 to 1998 to determine whether the increase in volatility on the JSE changed the specification of the APT model as it applied to the Financial & Industrial Index of the Johannesburg Securities Exchange (JSE). The finding is that political events in late 1991, and economic events in mid 1994, changed APTM's specification. This would indicate that during periods of profound political change, political events drive stock market prices (JEL G310).

Purpose-Financial agents pay a great attention to the relationship between credit default swaps (CDS) and other financial assets. Being considered as a financial asset and then as a possible component of a portfolio, CDS's relationship with other financial assets is crucial in order to compose an efficient portfolio which should contain the least correlated assets. Our study, provide a different approach than the bulk of existing literature which consider the relation between returns/levels or between volatilities and their impact on the volatility (leverage effects) as well as volatilities may affect returns/levels/rates in BIST100 by focusing on several economic and financial determinants for the investment horizon of investors and policymakers for their decision-making processes. Methodology-We investigate the relationship between sovereign CDS spread (level and volatility) and (return/level and volatility) of financial series (bond yield, currency exchange, stock index) by applying wavelet coherence analysis to capture the interrelation between economic and financial determinants during different investment horizons due to the account of the time-frequency domain. Findings-According to empirical results, firstly, the direction of causality between series depends on the frequency domain. A series may cause the other series at medium term and may be influenced by this second series at short term. Secondly, the relationship between the CDS spread (volatility) and retained financial series changes through time while depending the type of financial asset. Lastly, the interconnectedness between returns/rates/levels is different from the relationship between volatilities and between returns/rates/levels and volatilities. Conclusion-Our findings show that the CDS 2-year spread and interest rates have a positive relationship most of the time in the medium term, mostly in the 2017-2019 period, while CDS spreads and the USDTRY have similar impacts in the medium and early long term. Despite having previously observed such a positive relationship between CDS and other economic determinants, CDS spreads have a negative impact on stock exchange returns in the medium term, spanning nearly a decade from 2008 to 2016.

In this article, the author defends the idea that one of the positive results of modern economic analysis is the conviction that there is no natural law in economics. Thus, the most thorough scientific research which has tried to provide an analytical foundation for the mythical invisible hand, the "general equilibrium paradigm," has finally shown that such an equilibration process cannot be formally demonstrated. Hence, we can say that economists cannot demonstrate the existence of a law of "supply and demand" but, more simply, can assert that some causal but contingent relations may exist between price, supply and demand. According to this result, the critical approach of Kenneth John Arrow concludes with the necessity of social and moral rule (for the good functioning of the market). It is, thus, necessary to assume the contingent nature of economic rules, and the absence of natural law, and consequently, to modify economists' theoretical model.

High levels of volatility, which reflect fluctuations in the price of a financial asset or instrument, lead investors to monitor global markets more closely. The VIX index, closely followed by global investors, signals expectations of increased market volatility when it is at high levels and decreased volatility when it is at low levels. Increases in the VIX index lead to an increase in CDS premiums, which represent a country's risk premium. The relationship between the VIX index, which is a global risk indicator, and the BIST 100 index is highly significant for investors operating in Türkiye's capital markets. This study examines the relationships between CDS premiums, the VIX index, and the BIST 100 index using the Wavelet Coherence Analysis method. The analysis results reveal that the relationship between VIX and CDS varies in intensity and direction over time. Furthermore, it can be seen that the relationship between the VIX and BIST variables is very strong in both the short and long term, with a negative direction from the VIX variable to the BIST variable. Moreover, the CDS variable was found to negatively impact the BIST index during the shortterm period of 2019-2021.

Some risky activities are optional, for example motoring. Participation in them is most attractive for good risks, creating a tendency for advantageous selection in the associated insurance market. Taxing insurance consequently yields e¢ ciency gains when type is hidden. Results are strengthened if optimism is present. Finally, endogenising participation implies that the standard "positive correlation" test for the presence of policy relevant asymmetric information may fail.

We consider a general GMM framework where weaker patterns of identi cation may arise: typically, the data generating process is allowed to depend on the sample size. We are interested in providing inference about the identi cation of the structural parameter. First, we propose a consistent Hausman-type test to test whether additional moment conditions enhance its identi cation. Failing to reject the null means that we consider that the candidate additional moment restrictions are useless to improve the strength of identi cation of the structural parameter. Second, for a given set of moment conditions, we propose a J-type test of the null that the structural parameter is not strongly identi ed. In other words, it is only as long as that the null cannot be rejected that it remains necessary to resort to alternative (nearly) weak identi cation asymptotics. The above testing strategy is developed for both unconditional and conditional moment restrictions and illustrated with the Epstein...

We study the asymptotic properties of the standard GMM estimator when additional moment restrictions, weaker than the original ones, are available. We provide conditions under which these additional weaker restrictions improve the efficiency of the GMM estimator. To detect "spurious" identification that may come from invalid moments, we rely on the Hansen J-test that assesses the compatibility between existing restrictions and additional ones. Our simulations reveal that the J-test has good power properties and that its power increases with the weakness of the additional restrictions. Our theoretical characterization of the J-test provides some intuition for why that is.

One of the main concerns of investors is the evaluation of the return on investment, which is conducted using various models such as the CAPM (single-factor model), Fama-French three/five-factor models, and Roy and Shijin’s six-factor model and other models known as multi-factor models. Despite the widespread use of these models, their major drawbacks include sensitivity to unexpected changes, sudden shocks, high turbulence of price bubble, and so on. To eliminate such negatives, the multi-factor model using the penalty function method is used, in which, instead of averaging, the optimization and avoidance of the effects of abnormal changes and other factors affecting the capital market are considered. In order to evaluate stock returns, it is possible to select effective factors, to simulate and develop a model appropriate to the conditions governing the capital market in Iran. In the present study, by forming portfolios of investments and identifying and refining effective factors...

The classical Black-Scholes-Merton framework describes a world in which options can be replicated exactly by continuous trading in the underlying asset. Once a proportional transaction fee is levied on every trade, the theoretical cornerstone of perfect replication collapses: continuous rebalancing becomes prohibitively expensive, and the practitioner must decide when to trade and how much to trade. Building upon John C. Hull's textbook exposition, this paper returns to the continuous-time ∆-hedge partial differential equation and develops a marginal-cost-benefit rule that triggers rebalancing when the instantaneous reduction in hedging variance exactly equals the incremental transaction cost. Unlike fixed-interval strategies (Leland, 1985) or the no-transaction regions derived from full impulse-control methods (Davis and Norman, 1990; Shreve and Soner, 1994), the proposed rule yields an explicit, state-dependent threshold that adapts to volatility, option gamma, and prevailing fee levels. We provide a rigorous derivation, establish the connection to classic band models, and illustrate the rule's practical advantages through Monte Carlo simulation and a highfrequency back-test on S&P 500 index options. The evidence indicates that our rule reduces combined hedging error and cost by 15-25% relative to best-practice benchmarks, offering a transparent and computationally light alternative for traders confronting market frictions.

This study applies broad approach to analyse the impact of corporate tax avoidance on earnings manipulation in Nigeria. Added to that, the study also investigates whether earnings management plays any moderating role in the relationship between corporate tax avoidance on earnings manipulation. The study uses unbalanced panel data of 116 quoted companies in Nigeria from the period 2009 to 2016. The linear dynamic panel models designed for the study were estimated using one-step different Generalised Method of Moment (GMM) technique. The main findings are in two folds. First, the study indicates that the impact of corporate tax avoidance is positive and statistically significant on earnings manipulation. Secondly, the study provides evidence which suggests that earnings management significantly moderated the relationship between corporate tax avoidance and earnings manipulation. Unlike previous studies which investigated the effect of corporate tax avoidance on earnings manipulation using a single tax factor, this study is novel in applying corporate tax avoidance to estimate the impact of tax aggressiveness on earnings manipulation. Furthermore, the study also fills knowledge gap in the literature by providing new evidence indicating that earnings management plays significant role in the relationship between corporate tax avoidance and earnings manipulation.

This study applies broad approach to analyse the impact of corporate tax avoidance on earnings manipulation in Nigeria. Added to that, the study also investigates whether earnings management plays any moderating role in the relationship between corporate tax avoidance on earnings manipulation. The study uses unbalanced panel data of 116 quoted companies in Nigeria from the period 2009 to 2016. The linear dynamic panel models designed for the study were estimated using one-step different Generalised Method of Moment (GMM) technique. The main findings are in two folds. First, the study indicates that the impact of corporate tax avoidance is positive and statistically significant on earnings manipulation. Secondly, the study provides evidence which suggests that earnings management significantly moderated the relationship between corporate tax avoidance and earnings manipulation. Unlike previous studies which investigated the effect of corporate tax avoidance on earnings manipulation using a single tax factor, this study is novel in applying corporate tax avoidance to estimate the impact of tax aggressiveness on earnings manipulation. Furthermore, the study also fills knowledge gap in the literature by providing new evidence indicating that earnings management plays significant role in the relationship between corporate tax avoidance and earnings manipulation.

Investors face difficulties in spotting lucrative investment opportunities and determining whether to purchase or sell shares due to the securities market's extreme volatility. For investors, the performance of many industries adds even another level of complication. By employing technical analysis methods to help investors make educated judgments about building an ideal portfolio, this study seeks to solve these problems. The application of Sharpe's Single Index Model to the construction of a portfolio for Bank Nifty stocks with the goal of optimizing returns and reducing risks is the specific subject of this study. Twelve equities from the NIFTY 50 index, chosen from the banking, cement, power, and steel industries, are analysed in this study. The research is based on secondary data from reputable sources, including the National Stock Exchange (NSE), Money control, firm annual reports, and different publications. Descriptive research methodologies are used in this study to analyse the performance of the ideal portfolio, determine the proper proportions for each stock in the portfolio, and measure risk and return for the chosen stocks. The principal aim is to assist investors in making logical investment choices by building an ideal portfolio, figuring out investment ratios, and assessing its risk-return characteristics. For portfolio optimization, the study also seeks to improve practical understanding of the Sharpe Single Index Model.

This paper examines the volatility and performance of the U.S. stock market in light of ongoing debates about informational efficiency. By applying Monte Carlo simulations and regression models to the S&P 500 index, the analysis shows that both annual returns and volatility can be largely explained by fundamental variables known in advance. The results expose the practical difficulty of distinguishing between risk (randomness) and true uncertainty, as both affect the expected rate of return. Importantly, the study identifies an implicit valuation convention that makes short-term market performance partially predictable-a finding that contrasts with the long-term orientation of Shiller's cyclically adjusted P/E ratio (CA-PE). These insights challenge the semi-strong form of market efficiency as defined by Fama, and point to new opportunities for informed investors who can recognize and interpret prevailing market conventions.

Recent evidence suggests that all asset returns are predictable to some extent with excess returns on real estate relatively easier to forecast. This raises the issue of whether we can successfully exploit this level of predictability using various market timing strategies to realize superior performance over a buy-and-hold strategy. We find that the level of predictability associated with real estate leads to moderate success in market timing, although this is not necessarily the case for the other asset classes examined in general. Besides this, real estate stocks typically have higher trading profits and higher mean risk-adjusted excess returns when compared to small stocks as well as large stocks and bonds even though most real estate stocks are small stocks.

Why do risk premia vary over time? We examine this problem theoretically and empirically by studying the effect of market belief on risk premia. Individual belief is taken as a fundamental, primitive, state variable. Market belief is observable, it is central to the empirical evaluation and we show how to measure it. Our asset pricing model is familiar from the noisy REE literature but we adapt it to an economy with diverse beliefs. We derive equilibrium asset prices and implied risk premium. Our approach permits a closed form solution of prices hence we trace the exact effect of market belief on the time variability of asset prices and risk premia. We test empirically the theoretical conclusions. Our main result is that, above the effect of business cycles on risk premia, fluctuations in market belief have significant independent effect on the time variability of risk premia. We study the premia on long positions in Federal Funds Futures, 3-month and 6-month Treasury Bills. The annual mean risk premium on holding such assets for 1-12 months is about 40-60 basis points and we find that, on average, the component of market belief in the risk premium exceeds 50% of the mean. Since time variability of market belief is large, this component frequently exceeds 50% of the mean premium. This component is larger the shorter is the holding period of an asset and it dominates the premium for very short holding returns of less than 2 months. As to the structure of the premium we show that when the market holds abnormally favorable belief about the future payoff of an asset the market views the long position as less risky hence the risk premium on that asset declines. More generally, periods of market optimism (i.e. "bull" markets) are shown to be periods when the market risk premium is low while in periods of pessimism (i.e. "bear" markets) the market's risk premium is high. Fluctuations in risk premia are thus inversely related to the degree of market optimism about future prospects of asset payoffs. This effect is strong and economically very significant.

In dynamic stochastic general equilibrium (DSGE) models, the household's labor margin as well as consumption margin affects Arrow-Pratt risk aversion. This paper derives simple, closed-form expressions for risk aversion that take into account the household's labor margin. Ignoring the labor margin can lead to wildly inaccurate measures of the household's true attitudes toward risk. We show that risk premia on assets computed using the stochastic discount factor are proportional to Arrow-Pratt risk aversion, so that measuring risk aversion correctly is crucial for understanding asset prices. Closed-form expressions for risk aversion in DSGE models with generalized recursive preferences and internal and external habits are also derived.

We investigate the effects of U.S. monetary policy on asset prices using a high-frequency event-study analysis. We test whether these effects are adequately captured by a single factor-changes in the federal funds rate target-and find that they are not. Instead, we find that two factors are required. These factors have a structural interpretation as a "current federal funds rate target" factor and a "future path of policy" factor, with the latter closely associated with Federal Open Market Committee statements. We measure the effects of these two factors on bond yields and stock prices using a new intraday data set going back to 1990. According to our estimates, both monetary policy actions and statements have important but differing effects on asset prices, with statements having a much greater impact on longer-term Treasury yields. JEL Codes: E52, E58, E43, G14. * We thank Ben Bernanke, Ken Kuttner, Jon Faust, Jonathan Wright, two anonymous referees, and seminar participants at Bilkent, Koç, and Sabancı Universities, the Central Bank of Turkey, and the Federal Reserve Bank of San Francisco for valuable discussions, comments, and suggestions.

Recent legislation on Minimum Taxation (Pillar 2 and the GloBE Rules) and the BEFIT proposal from the EU Commission have brought attention to the differences in Effective Tax Rates (ETRs) across individual companies, corporate groups, and countries. Consequently, this growing pressure for fiscal convergence has also rekindled interest among academics and regulators in the relationship between book income and taxable income, commonly referred to as Book-Tax Differences (BTD). Our research contributes to this debate by examining the current European context, analyzing the financial statements of over 420,000 companies and assessing the BTDs and ETRs across 23 countries, revealing significant differences. The factors influencing these differences across countries seem to stem from the interaction between the accounting and financial reporting practices adopted in each State, which, in turn, derive from their respective national fiscal policies. In our view, this study may support scholars and regulators to further explore the potential for corporate tax convergence in Europe through the progressive alignment of ETRs. This "soft approach" could offer substantial benefits: it allows companies to continue preparing their financial statements in accordance with national accounting principles, which are subsequently reconciled through BTDs. Simultaneously; it enables individual countries to maintain autonomy in their fiscal policies, primarily by setting their own nominal Tax Rates (TRs) and implementing various incentives by the regulation of BTDs.

Recent legislation on Minimum Taxation (Pillar 2 and the GloBE Rules) and the BEFIT proposal from the EU Commission have brought attention to the differences in Effective Tax Rates (ETRs) across individual companies, corporate groups, and countries. Consequently, this growing pressure for fiscal convergence has also rekindled interest among academics and regulators in the relationship between book income and taxable income, commonly referred to as Book-Tax Differences (BTD). Our research contributes to this debate by examining the current European context, analyzing the financial statements of over 420,000 companies and assessing the BTDs and ETRs across 23 countries, revealing significant differences. The factors influencing these differences across countries seem to stem from the interaction between the accounting and financial reporting practices adopted in each State, which, in turn, derive from their respective national fiscal policies. In our view, this study may support scholars and regulators to further explore the potential for corporate tax convergence in Europe through the progressive alignment of ETRs. This "soft approach" could offer substantial benefits: it allows companies to continue preparing their financial statements in accordance with national accounting principles, which are subsequently reconciled through BTDs. Simultaneously; it enables individual countries to maintain autonomy in their fiscal policies, primarily by setting their own nominal Tax Rates (TRs) and implementing various incentives by the regulation of BTDs.

Dengan ini saya menyatakan dengan sesungguhnya bahwa dalam skripsi ini tidak terdapat keseluruhan atau sebagian tulisan orang lain yang saya ambil dengan cara menyalin dan meniru dalam rangkaian kalimat atau simbol yang menunjukkan gagasan, pendapat, ataupun pemikiran dari penulis lain yang saya akui seolah-olah sebagai tulisan saya sendiri dan tidak tedapat sebagian atau keseluruhan tulisan yang saya ambil, tiru atau salin dari orang lain tanpa memberikan pengakuan pada penulis aslinya. Apabila saya melakukan hal tersebut diatas baik sengaja ataupun tidak, dengan ini saya menyatakan menarik skripsi yang saya ajukan sebagai tulisan saya sendiri. Bila kemudian terbukti bahwa saya ternyata melakukan tindakan menyalahi atau meniru tulisan orang lain seolah-olah hasil pemikiran saya sendiri, berarti gelar dan ijazah yang telah diberikan universitas batal saya terima.

This study establishes a novel mathematical framework for stochastic maintenance optimization in production systems by integrating Markov decision processes (MDPs) with convex programming theory. We develop a Z-transformation-based dual-space decomposition method to reconstruct MDPs into a solvable linear programming form, resolving the inherent instability of traditional models caused by uncertain initial conditions and non-stationary state transitions. The proposed approach introduces three mathematical innovations: (i) a spectral clustering mechanism that reduces state-space dimensionality while preserving Markovian properties, (ii) a Lagrangian dual formulation with adaptive penalty functions to handle operational constraints, and (iii) a warm start algorithm accelerating convergence in high-dimensional convex optimization. Theoretical analysis proves that the derived policy achieves stability in probabilistic transitions through martingale convergence arguments, demonstrating structural invariance to initial distributions. Experimental validations on production processes reveal that our model reduces long-term maintenance costs by 36.17% compared to Monte Carlo simulations (1500 vs. 2350 average cost) and improves computational efficiency by 14.29% over Q-learning methods. Sensitivity analyses confirm robustness across Weibull-distributed failure regimes (shape parameter 𝛽∈
[1.2, 4.8]) and varying resource constraints.