evaluating natural resource investments notwithstanding impressive advances in the theory of finance over the past 2 decades practical procedures for capital budgeting have evolved only slowly the standard technique which has remained unchanged in essentials since it was originally proposed see dean 1951 bierman and smidt 1960 derives from a simple adaptation of the fisher 1907 model of valuation under certainty under this technique expected cash flows from an investment project are discounted at a rate deemed appropriate to their risk and the resulting present value is compared with the cost of the project this standard textbook technique reflects modern theoretical developments only insofar as estimates of the discount rate may be obtained from crude application of single period asset pricing theory but see brennan 1973 bogue and roll 1974 turnbull 1977 constantinides 1978 the inadequacy of this approach to capital budgeting is widely acknowledged although not widely discussed its obvious deficiency is its the evaluation of mining and other natural resource projects is made particularly difficult by the high degree of uncertainty attaching to output prices it is shown that the techniques of continuous time arbitrage and stochastic control theory may be used not only to value such projects but also to determine the optimal policies for developing managing and abandoning them the approach may be adapted to a wide variety of contexts outside the natural resource sector where uncertainty about future project revenues is a paramount concern

pairs trading and outranking the multi step ahead forecasting case abstract pairs trading is a popular speculation strategy several implementation methods are proposed in the literature they can be based on a distance criterion or on co integration this article extends previous research in another direction the combination of forecasting techniques neural networks and multi criteria decision making methods electre iii the key contribution of this paper is the introduction of multi step ahead forecasts it leads to major changes in the trading system and raises new empirical and methodological questions the results of an application based on s p 100 index stocks are promising this methodology could be a powerful tool for pairs selection in a highly non linear environment

behavior of output during currency crises abstract this paper documents the behavior of output and its association with other macroeconomic variables in 195 episodes of currency crises in developing countries during 1970 2000 we find that about 60 of the crises are contractionary while the rest are expansionary crises are one and a half times more likely to be contractionary in emerging markets than in other developing economies the number of contractionary crises or their severity does not increase in the 1990s economies which experience capital inflows in the years prior to the crisis or an increase in external debt burden during the crisis are more likely to slow down during crises while those with restrictions on capital flows prior to the crisis or are more open to international trade are less likely to do so the results are robust to different ways of measuring changes in output during crises

sudden stops sectoral reallocations and the real exchange rate abstract a sudden stop of capital flows into a developing country tends to be followed by a rapid switch from trade deficits to surpluses a depreciation of the real exchange rate and decreases in output and total factor productivity substantial reallocation takes place from the nontraded sector to the traded sector we construct a multisector growth model calibrate it to the mexican economy and use it to analyze mexico s 1994 95 crisis when subjected to a sudden stop the model accounts for the trade balance reversal and the real exchange rate depreciation but it cannot account for the decreases in gdp and tfp extending the model to include labor frictions and variable capital utilization we still find that it cannot quantitatively account for the dynamics of output and productivity without losing the ability to account for the movements of other variables

the circular relationship between inequality leverage and financial crises in this paper we put into perspective the recent literature which points to inequality as a possible cause of credit bubbles by reintegrating it into a more general analysis on the two way relationship between inequality and finance we focus more specifically on situations where high inequalities and widespread access to credit coexist and argue that even when institutions maintain more or less equal access to finance there may be a dynamic positive circular relationship between inequality and financial development however even if there is some evidence in the literature of a positive causal impact of inequality on credit this does not preclude other important cofounding factors the conclusions concerning the distributional impact of finance are more ambiguous a survey of the empirical literature highlights several issues that must be tackled first endogeneity reverse causality and coincidental factors are major concerns second the choice of consistent measurements for the key variables both credit and inequality has strong empirical implications and must be grounded on relevant theoretical channels third those circular dynamics have substantial policy implications for emerging economies since an increasing number face a joint increase in inequality and credit

statistical arbitrage pairs trading strategies review and outlook this survey reviews the growing literature on pairs trading frameworks i e relative value arbitrage strategies involving two or more securities research is categorized into five groups the distance approach uses nonparametric distance metrics to identify pairs trading opportunities the cointegration approach relies on formal cointegration testing to unveil stationary spread time series the time series approach focuses on finding optimal trading rules for mean reverting spreads the stochastic control approach aims at identifying optimal portfolio holdings in the legs of a pairs trade relative to other available securities the category other approaches contains further relevant pairs trading frameworks with only a limited set of supporting literature finally pairs trading profitability is reviewed in the light of market frictions drawing from a large set of research consisting of over 100 references an in depth assessment of each approach is performed ultimately revealing strengths and weaknesses relevant for further research and for implementation

a real options model to evaluate the effect of environmental policies on the oil sands rate of expansion abstract canadian oil sands hold the third largest recognized oil deposit in the world while the rapidly expanding oil sands industry in western canada has driven economic growth the extraction of the oil comes at a significant environmental cost it is believed that the government policies have failed to keep up with the rapid oil sands expansion creating serious challenges in managing the environmental impacts this paper presents a practical yet financially sound real options model to evaluate the rate of oil sands expansion under different environmental cost scenarios resulting from governmental policies while accounting for oil price uncertainty and managerial flexibilities our model considers a multi plant multi agent setting in which labor costs increase for all agents and impact their optimal strategies as new plants come online our results show that a stricter environmental cost scenario delays investment but leads to a higher rate of expansion once investment begins once constructed a plant is highly unlikely to shut down our model can be used by government policy makers to gauge the impact of policy strategies on the oil sands expansion rate and by oil companies to evaluate expansion strategies based on assumptions regarding market and taxation costs

short term variations and long term dynamics in commodity prices in this article we develop a two factor model of commodity prices that allows meanreversion in short term prices and uncertainty in the equilibrium level to which prices revert although these two factors are not directly observable they may be estimated from spot and futures prices intuitively movements in prices for long maturity futures contracts provide information about the equilibrium price level and differences between the prices for the short and long term contracts provide information about short term variations in prices we show that although this model does not explicitly consider changes in convenience yields over time this short term long term model is equivalent to the stochastic convenience yield model developed in gibson and schwartz 1990 we estimate the parameters of the model using prices for oil futures contracts and apply the model to some hypothetical oil linked assets to demonstrate its use and some of its advantages over the gibson schwartz model

pairs trading performance of a relative value arbitrage rule we test a wall street investment strategy pairs trading with daily data over 1962 2002 stocks are matched into pairs with minimum distance between normalized historical prices a simple trading rule yields average annualized excess returns of up to 11 for self financing portfolios of pairs the profits typically exceed conservative transaction cost estimates bootstrap results suggest that the pairs effect differs from previously documented reversal profits robustness of the excess returns indicates that pairs trading profits from temporary mispricing of close substitutes we link the profitability to the presence of a common factor in the returns different from conventional risk measures wall street has long been interested in quantitative methods of speculation one popular short term speculation strategy is known as pairs trading the strategy has at least a 20 year history on wall street and is among the proprietary statistical arbitrage tools currently used by hedge funds as well as investment banks the concept of pairs trading is disarmingly simple find two stocks whose prices have moved together historically when the spread between them widens short the winner and buy the loser if history repeats itself prices will converge and the arbi

macroeconomic effects of regulation and deregulation in goods and labor markets product and labor market deregulation reduce and redistribute rents leading economic players to adjust to this new distribution it typically comes with distribution and dynamic effects to study these effects we build a macroeconomic model on two central assumptions monopolistic competition in the goods market which determines the size of rents and bargaining in the labor market which determines the distribution of rents product market regulation determines entry costs and the degree of competition labor market regulation determines the bargaining power of workers we show the effects of deregulation we then use our results to discuss the political economy of deregulation and recent macroeconomic evolutions in europe

separating the signal from the noise financial machine learning for twitter abstract most statistical arbitrage strategies in the academic literature solely rely on price time series by contrast alternative data sources are of growing importance for professional investors we contribute to bridging this gap by assessing the price predictive value of millions of tweets on intraday returns of the s p 500 constituents from 2014 and 2015 for this purpose we design a machine learning system addressing specific challenges inherent to this task at first building on the literature of financial dictionaries we engineer domain specific features along three categories i e directional indicators relevance indicators and meta features next we leverage a random forest to extract the relationship between these features and subsequent stock returns in a low signal to noise setting for performance evaluation we run a rigorous event based backtesting study across all tweets and stocks we find annualized returns of 6 4 percent and a sharpe ratio of 2 2 after transaction costs finally we illuminate the machine learning black box and unveil sources of profitability first results are both driven and limited by the temporal clustering of tweets i e the majority of profits stem from tweets clustered closely together in time corresponding to high event situations second the importance of included features follows an economic rationale e g tweets with positive sentiment tend to yield positive returns and vice versa third we find that stocks of medium market capitalization and from the consumer and technology sectors contribute most to our results which we interpret as a trade off between tweet coverage and tweet relevance

pairs selection and outranking an application to the s p 100 index pairs trading is a popular quantitative speculation strategy this article proposes a general and flexible framework for pairs selection the method uses multiple return forecasts based on bivariate information sets and multi criteria decision techniques our approach can be seen as a sort of forecast combination but the output of the method is a ranking it helps to detect potentially under and overvalued stocks a first application with s p 100 index stocks provides promising results in terms of excess return and directional forecasting

option valuation of claims on real assets the case of offshore petroleum leases this paper extends financial option theory by developing a methodology for the valuation of claims on a real asset an offshore petroleum lease several theoretical and practical problems not present in applying option pricing theory to financial assets are addressed most importantly we show the necessity of combining option pricing techniques with a model of equilibrium in the market for the underlying asset petroleum reserves the advantages of this approach over conventional discounted cash flow techniques are emphasized the methodological development provides important insights for both company behavior and government policy promising empirical results are reported

the valuation of forestry resources under stochastic prices and inventories a contingent claims approach to capital budgeting may be preferable to traditional methods where uncertainty and managers strategic reactions to changing conditions are impor tant as an example of such a case we solve the classical problem of the duration of an investment in forestry resources i e when to cut down the trees in the general case of stochastic output prices and stochastic natural growth rate and timber inventories a con tingent claims approach is used to value the forestry resources as a function of 1 sto chastic prices and inventories and 2 an asymmetric optimal production policy that incorporates the option to halt timber production temporarily i introduction classical capital budgeting techniques are based on the assumption that fu ture cash flows follow a rigid pattern and can be accurately predicted far into the future on the basis of such cash flow predictions the project is either accepted or rejected the uncertainty in the project and management s strategic reactions to changing conditions are dealt with only superficially at best a risk adjusted interest rate is employed and various deterministic scenarios are plotted out in situations where uncertainty and management s strategic reactions to it are im portant the classical technique is apt to lead to wrong decisions the technology needed to deal with such problems more accurately is becoming available the purpose of this paper is to present a stylized example of how it can be used our example is a general solution to the classical duration problem of the optimal control of a long term renewable resource investment such as forestry resources i e when to chop down a tree 1 if the prices and the natural growth rate of the inventory of forest timber are assumed to be deterministic the optimal control is very simple to derive but when both the price and inventory of timber are stochastic the problem becomes both stochastic and asymmetric the asym

the decline of the labor income share in mexico 1990 2015 abstract the paper studies the decline of the labor income share lis in mexico during the period 1990 2015 the decline is mostly explained by reductions within the economy s major sectors including manufacturing tradables and non tradables rather than by a recomposition of value added towards sectors with low labor shares in contrast to agriculture where lis fell due to a shift of labor force from self employment to wage employment in other major areas of the economy the fall in lis is explained by reductions within the wage employment sector econometric estimations indicate that parallel declines in the wage share and relative productivity of non tradables and in the us manufacturing labor share all played a large role in the reduction of the manufacturing wage share in mexico more generally the analysis suggests that the lagging productivity of the economy s informal non tradable sector itself a reflection of the country s low aggregate rate of economic growth is a crucial factor in the fall of lis in the formal sectors the paper concludes by discussing possible explanations for the paradox of the slow rate of economic growth in mexico despite the rise in the profit share

currency crises are they all the same abstract the plethora of currency crises around the world has fueled many theories on the causes of speculative attacks the first generation models focus on fiscal problems while the second generation models emphasize countercyclical policies and self fulfilling crises in the 1990s models pinpoint to financial excesses with the crisis of argentina in 2001 models of sovereign default have become popular again while the theoretical literature has emphasized variety the empirical literature has supported the one size fits all models this paper contributes to the empirical literature by assessing whether the crises of the last 30 years are of different varieties

deep learning with long short term memory networks for financial market predictions abstract long short term memory lstm networks are a state of the art technique for sequence learning they are less commonly applied to financial time series predictions yet inherently suitable for this domain we deploy lstm networks for predicting out of sample directional movements for the constituent stocks of the s p 500 from 1992 until 2015 with daily returns of 0 46 percent and a sharpe ratio of 5 8 prior to transaction costs we find lstm networks to outperform memory free classification methods i e a random forest raf a deep neural net dnn and a logistic regression classifier log the outperformance relative to the general market is very clear from 1992 to 2009 but as of 2010 excess returns seem to have been arbitraged away with lstm profitability fluctuating around zero after transaction costs we further unveil sources of profitability thereby shedding light into the black box of artificial neural networks specifically we find one common pattern among the stocks selected for trading they exhibit high volatility and a short term reversal return profile leveraging these findings we are able to formalize a rules based short term reversal strategy that yields 0 23 percent prior to transaction costs further regression analysis unveils low exposure of the lstm returns to common sources of systematic risk also compared to the three benchmark models

modeling and predicting the cboe market volatility index abstract this paper performs a thorough statistical examination of the time series properties of the daily market volatility index vix from the chicago board options exchange cboe the motivation lies not only on the widespread consensus that the vix is a barometer of the overall market sentiment as to what concerns investors risk appetite but also on the fact that there are many trading strategies that rely on the vix index for hedging and speculative purposes preliminary analysis suggests that the vix index displays long range dependence this is well in line with the strong empirical evidence in the literature supporting long memory in both options implied and realized variances we thus resort to both parametric and semiparametric heterogeneous autoregressive har processes for modeling and forecasting purposes our main findings are as follows first we confirm the evidence in the literature that there is a negative relationship between the vix index and the s p 500 index return as well as a positive contemporaneous link with the volume of the s p 500 index second the term spread has a slightly negative long run impact in the vix index when possible multicollinearity and endogeneity are controlled for finally we cannot reject the linearity of the above relationships neither in sample nor out of sample as for the latter we actually show that it is pretty hard to beat the pure har process because of the very persistent nature of the vix index

deep neural networks gradient boosted trees random forests statistical arbitrage on the s p 500 abstract in recent years machine learning research has gained momentum new developments in the field of deep learning allow for multiple levels of abstraction and are starting to supersede well known and powerful tree based techniques mainly operating on the original feature space all these methods can be applied to various fields including finance this paper implements and analyzes the effectiveness of deep neural networks dnn gradient boosted trees gbt random forests raf and several ensembles of these methods in the context of statistical arbitrage each model is trained on lagged returns of all stocks in the s p 500 after elimination of survivor bias from 1992 to 2015 daily one day ahead trading signals are generated based on the probability forecast of a stock to outperform the general market the highest k probabilities are converted into long and the lowest k probabilities into short positions thus censoring the less certain middle part of the ranking empirical findings are promising a simple equal weighted ensemble ens1 consisting of one deep neural network one gradient boosted tree and one random forest produces out of sample returns exceeding 0 45 percent per day for k 10 prior to transaction costs irrespective of the fact that profits are declining in recent years our findings pose a severe challenge to the semi strong form of market efficiency

currency crises and the labour share this paper analyses the impact of currency crises on the labour share and identifies two main types of channel within and across sector effects first crises erode the bargaining power of workers so that within sectors crises lower the labour share nevertheless structural changes occurring during currency crises may change the aggregate level of the labour share if sectors differ in their capital intensities we perform estimations on manufacturing sectoral panel data for 20 countries we conclude that currency crises lower the aggregate manufacturing labour share by around 2 percentage points and that this decline reflects mostly changes within manufacturing subsectors

the personal and the factor distributions of income in a cross section of countries abstract the shares of capital and labour in national income vary substantially both over time and across countries this paper shows that the factor distribution of income is an essential determinant of the personal distribution of income we use cross country and panel data for a group of developed and developing countries to show that a larger labour share is associated with a lower gini coefficient of personal incomes this effect is not only statistically significant but also economically important an increase in the labour share in mexico to that observed in the us would reduce the gini coefficient of the former by between two and five points

a real options approach to the valuation of a forestry investment abstract the theory of real options is used to model the optimal tree harvesting decision the value of the option to harvest is estimated using a dynamic programming approach and a general numerical solution technique suitable for any type of stochastic process for prices the conditions under which the optimal harvest time is independent of price are examined in addition the impact of assuming future lumber prices are mean reverting is considered it is found that option value and optimal cutting time are significantly different under the mean reversion assumption compared to geometric brownian motion

labour market institutions and the personal distribution of income in the oecd we examine what determines differences across countries and over time in the distribution of personal incomes in the oecd we first model the wage determination process and show that unemployment the labour share and the wage differential are all functions of labour market institutions next we show that in a model economy with only four types of agents capitalists skilled and unskilled workers and unemployed the gini coefficient of personal incomes can be expressed as a function of the above three variables labour market institutions hence affect income inequality though the sign of their impact is ambiguous stronger unions and or a more generous unemployment benefit tend to reduce inequality through reduced wage differentials a higher labour share and also higher unemployment we then use a panel of oecd countries for the period 1970 96 to examine these effects we find first that the labour share remains an important aspect of overall inequality patterns and second that stronger unions and a more generous unemployment benefit tend to reduce income inequality high capital labour ratios also emerge as a strong equalising factor which has in part offset the impact of increasing wage inequality on the us distribution of personal incomes

the dynamics of crude oil price differentials abstract crude oil price differentials are modelled as a two regime threshold autoregressive tar process using the method proposed by caner and hansen caner m hansen b e threshold autoregression with a unit root econometrica 2001 69 1555 1596 while standard unit root tests suggest that the prices of crude oil of different varieties move closely together such that their price differential is stationary the tar results indicate strong evidence of threshold effects in the adjustment process to the long run equilibrium these findings suggest that crude oil prices are linked and thus at the very general level the oil market is one great pool adelman m a international oil agreements the energy journal 1984 5 1 9 however differences in the dynamics of adjustment suggest that within this one pool oil markets are not necessarily integrated in every time period and hence the dynamics of crude oil price differentials may not follow a stationary process at all times although the development of a liquid futures market around the crude oil benchmarks has helped make some distant markets more unified arbitrage is not costless or risk free and temporary breakdowns in the benchmarks can lead to decoupling of crude oil prices

on solving the multirotational timber harvesting problem with stochastic prices a linear complementarity formulation this article develops a two factor real options model of the harvesting decision over infinite rotations assuming a known stochastic price process and using a rigorous hamilton jacobi bellman methodology the harvesting problem is formulated as a linear complementarity problem that is solved numerically using a fully implicit finite difference method this approach is contrasted with the markov decision process models commonly used in the literature the model is used to estimate the value of a representative stand in ontario s boreal forest both when there is complete flexibility regarding harvesting time and when regulations dictate the harvesting date

the impact of spatial price differences on oil sands investments abstract in this article a two factor real options model is developed to examine the impact spatial price differences have on the value of an oil sands project and the incentive to invest large volatile price differences between locations can emerge when demand to ship exceeds capacity limits this may have a significant impact on production investment and policy in exporting regions here we assume the price difference between two locations follows a stationary process implying crude oil markets are integrated as oil prices in different locations move together the investment decision is formulated as a linear complementarity problem that is solved numerically using a fully implicit finite difference method results show the value of an oil sands project and the incentive to invest in a new project will increase when the mean price difference decreases surprisingly the standard deviation of the price difference has very little impact on project value or the incentive to invest