Research articles for the 2020-02-10
arXiv
In this paper we propose and analyze a class of stochastic $N$-player games that includes finite fuel stochastic games as a special case. We first derive sufficient conditions for the Nash equilibrium (NE) in the form of a verification theorem, which reveals an essential game component regarding the interaction among players. It is an analytical representation of the conditional optimality condition for NEs, largely missing in the existing literature on stochastic games. The derivation of NEs involves first solving a multi-dimensional free boundary problem and then a Skorokhod problem, where the boundary is "moving" in that it depends on both the changes of the system and the control strategies of other players. Finally, we reformulate NE strategies in the form of controlled rank-dependent stochastic differential equations.
arXiv
We study a financial market where the risky asset is modelled by a geometric It\^o-L\'evy process, with a singular drift term.This can for example model a situation where the asset price is partially controlled by a company which intervenes when the price is reaching a certain lower barrier. See e.g. Jarrow & Protter {JP} for an explanation and discussion of this model in the Brownian motion case. As already pointed out by Karatzas & Shreve {KS} (in the Brownian motion case), this allows for arbitrages in the market. However, the situation in the case of jumps is not clear. Moreover, it is not clear what happens if there is a delay in the system.
In this paper we consider a jump diffusion market model with a singular drift term modelled as the local time of a given process, and with a delay \theta> 0 in the information flow available for the trader. Using white noise calculus we compute explicitly the optimal consumption rate and portfolio in this case and we show that the maximal value is finite as long as \theta> 0. This implies that there is no arbitrage in the market in that case. However, when \theta goes to 0, the value goes to infinity. This is in agreement with the above result that is an arbitrage when there is no delay.
Our model is also relevant for high frequency trading issues. See e.g. Lachapelle et al {LLLL} and the references therein.
SSRN
Who uses mobile money? What is mobile money used for? This paper describes the mobile money adoption patterns following the experimental introduction of mobile money for the first time in rural areas of Southern Mozambique. We use a combination of administrative and household survey data to characterize early and late adopters, as well as their mobile money usage patterns during the three years after mobile money was introduced. We find that a large proportion of the individuals who were offered mobile money services actively adopted this technology. Adopters of mobile money (and early adopters in particular) are more educated than non-adopters, and they are also more likely to already hold a bank account. Positive self-selection of mobile money adopters raises questions about the effectiveness of mobile money as a tool for financial inclusion.
arXiv
This paper develops a dynamic internal fraud model for operational losses in retail banking. It considers public operational losses arising from internal fraud in retail banking within a group of international banks. Additionally, the model takes into account internal factors such as the ethical quality of workers and the risk controls set by bank managers. The model is validated by measuring the impact of macroeconomic indicators such as GDP growth and the corruption perception upon the severity and frequency of losses implied by the model. In general,results show that internal fraud losses are pro-cyclical, and that country specific corruption perceptions positively affects internal fraud losses. Namely, when a country is perceived to be more corrupt, retail banking in that country will feature more severe internal fraud losses.
SSRN
This paper studies the effect of low interest rates on financial intermediation and the transmission of monetary policy. Using U.S. bank- and branch-level data, I document two new facts: first, the long-run decline in bond rates has not been fully passed through to loan rates; second, the short-run pass-through of policy rates to loan rates is lower at lower rates. To explain these facts, I build a model in which banks provide both credit and liquidity, and the nominal interest rate affects the composition of bank interest income between loan and deposit spreads. In the long run, a decline in the equilibrium real rate r* compresses deposit spreads but increases loan spreads. In the short run, the sensitivity of output to monetary shocks is dampened relative to a benchmark with perfect pass-through, and even more so the lower r* is: I find a dampening that grows from 20% to 32% as r* falls from 3% to -1%. A higher inflation target can redistribute from depositors to borrowers and enhance monetary policy transmission.
SSRN
Credit risk scoring predictions represent an effective guide for lenders to discriminate between potential good (who will repay the loan) and bad (who will default) borrowers in the online social lending market. A common characteristic of such a market is a lower percentage of defaulted borrowers than non-defaulted borrowers; thus, the sample is class imbalanced. Class imbalance may affect the accuracy of default predictions, as classifiers tend to be biased towards the majority class (good borrowers). We analyse the default prediction performance when combining class rebalancing methods with different regression and machine learning techniques. We also propose to combine multiple probability predictions to improve the predictive performance. The analysis is based on a book of loans (with a three-year term) funded in the 2010-2015 period though the online platform of Lending Club. The results show that some measures of predictive accuracy tend to improve when the scoring models are trained using a rebalanced, rather than an imbalanced sample, except when the extreme gradient boosting approach is applied. Finally, we find that combining multiple probability predictions via regularised logistic regression may help to improve the predictive accuracy.
arXiv
We study the effectiveness of a community-level information intervention aimed at improving sanitation using a cluster-randomized controlled trial (RCT) in Nigerian communities. The intervention, Community-Led Total Sanitation (CLTS), is currently part of national sanitation policy in more than 25 countries. While average impacts are exiguous almost three years after implementation at scale, the results hide important heterogeneity: the intervention has strong and lasting effects on sanitation practices in poorer communities. These are realized through increased sanitation investments. We show that community wealth, widely available in secondary data, is a key statistic for effective intervention targeting. Using data from five other similar randomized interventions in various contexts, we find that community-level wealth heterogeneity can rationalize the wide range of impact estimates in the literature. This exercise provides plausible external validity to our findings, with implications for intervention scale-up. JEL Codes: O12, I12, I15, I18.
SSRN
This paper studies the impact of corporate acquisitions - both domestic and cross-border - on the uncertainty faced by acquiring firms. We use data for UK publicly-listed firms from 2004 to 2017 and employ a matching estimator combined with difference-in-differences to control for the endogenous selection of firms into buying other companies. We find that acquisitions exert a large and persistent effect on the volatility of stock returns of acquirers and that this response is crucially determined by the geographic scope of the acquisitions firms undertake. We find that the impact of acquisitions on firm-level uncertainty is characterized by a pecking order: the announcement of a domestic takeover leads to a reduction in the uncertainty faced by the acquirer, while cross-border acquisitions - particularly those involving target firms in emerging markets - engender a positive response in acquirers’ volatility. Our results suggest that acquisitions affect uncertainty because they change firms’ exposure to shocks - as they expand their operation in new markets - and also because they are large and risky investments whose returns take time to materialize.
SSRN
We aim to compare different allocation models to build a portfolio that includes a popular set of alternative risk premia, common to most traditional asset classes. Firstly, we review alternative risk premia, mainly Carry, Value and Momentum, then we create sub--styles and styles portfolios. On each asset class we try to compare in a unified framework different style's definitions, to assess how each choice affects the outcome. Finally we aggregate styles in a composite portfolio. All these steps require several decisions on whether and which risk targeting method to utilize and which allocation model to adopt. We show the main differences and consequences of each decision and how they may affect the final portfolio. Lastly, we cluster different solutions according to a dissimilarity criteria, determining which are the key steps that make strategies actually different from one another.
SSRN
This paper analyses co-movement between Bitcoin exchanges in 34 major countries around the world and the US (the global benchmark) over the period January 24, 2011 - January 7, 2019. More specifically, we run IV regressions to investigate the importance of cultural factors (such as tightness, individualism, trust and risk-taking) following an earlier study by Eun et al. (2015) which had shed light on their importance to explain stock co-movement within individual countries. The results suggest that markets in tighter, more individualistic, trustful and risk-taking societies are more tightly linked to the US one. Further, it appears that culturally looser, collectivistic, trustful and risk-taking countries are more likely to shut down their Bitcoin exchanges compared to other countries. These findings confirm our priors.
arXiv
Crowded trades by similarly trading peers influence the dynamics of asset prices, possibly creating systemic risk. We propose a market clustering measure using granular trading data. For each stock the clustering measure captures the degree of trading overlap among any two investors in that stock. We investigate the effect of crowded trades on stock price stability and show that market clustering has a causal effect on the properties of the tails of the stock return distribution, particularly the positive tail, even after controlling for commonly considered risk drivers. Reduced investor pool diversity could thus negatively affect stock price stability.
SSRN
We adopt Deep Reinforcement Learning algorithms to design trading strategies for continuous futures contracts. Both discrete and continuous action spaces are considered and volatility scaling is incorporated to create reward functions which scale trade positions based on market volatility. We test our algorithms on the 50 most liquid futures contracts from 2011 to 2019, and investigate how performance varies across different asset classes including commodities, equity indices, fixed income and FX markets. We compare our algorithms against classical time series momentum strategies, and show that our method outperforms such baseline models, delivering positive profits despite heavy transaction costs. The experiments show that the proposed algorithms can follow large market trends without changing positions and can also scale down, or hold, through consolidation periods.
SSRN
A simple formula for non-discriminatory insurance pricing is introduced. This formula is based on the assumption that certain individual (discriminatory) policyholder information is not allowed to be used for insurance pricing. The suggested procedure can be summarized as follows: First, we construct a price that is based on all available information, including discriminatory information. Thereafter, we average out the effect of discriminatory information. This averaging out is done such that discriminatory information can also not be inferred from the remaining non-discriminatory one, thus, neither allowing for direct nor for indirect discrimination.
SSRN
This paper examines how employee earnings at small firms respond to a cash flow shock in the form of a government R&D grant. We use ranking data on applicant firms, which we link to IRS W2 earnings and other U.S. Census Bureau datasets. In a regression discontinuity design, we find that the grant increases average earnings with a rent-sharing elasticity of 0.07 (0.21) at the employee (firm) level. The beneficiaries are incumbent employees who were present at the firm before the award. Among incumbent employees, the effect increases with worker tenure. The grant also leads to higher employment and revenue, but productivity growth cannot fully explain the immediate effect on earnings. Instead, the data and a grantee survey are consistent with a backloaded wage contract channel, in which employees of financially constrained firms initially accept relatively low wages and are paid more when cash is available.
SSRN
This working paper reviews the work of the Financial Stability Oversight Council (FSOC) in terms of identifying potential systemic risk in the nonbank sector under authority from the Dodd-Frank Wall Street Reform Act of 2010. We discuss past efforts by the agencies represented within the FSOC to impose capital requirements on nonbank financial institutions such as insurers, mortgage lenders and servicers. The FSOC Annual Report issued in 2019 is then reviewed and assessed. Finally, recommendations are made to assist the FSOC in better understanding the systemic risks, if any, posed by nonbank companies engaged in lending and loan servicing.
SSRN
The paper examines the capital allocative behavior of internal capital market (ICM) members and their comparable single-segment firms in the euro area. Results indicate that the ICM members exhibit lower relationship between investment and the availability of internal funds, lower impact of financial flexibility, and lower levels of underinvestment and overinvestment behavior, than their peers. Results document that headquarters’ monitoring and managerial discretion, cost of capital, financial flexibility, informational asymmetries and asset lumpiness appear to be significant determinants of investment behavior.
SSRN
The paper examines firms’ financing behavior of internal capital market (ICM) members and their comparable single-segment firms in the euro area, in terms of capital structure, cost of capital, and the speed of adjustment towards preferred capital structure. Results indicate that both ICM members and single-segment comparable firms have preferred target capital structures proxied by industry’s leverage ratio median, and that subsidiary firms are significantly more leveraged and exhibit lower cost of capital than their counterparts. Results also document that ICM members adjust dynamically their capital structures to their preferred leverage ratios at a slower speed than stand-alone firms. Findings suggest that ICM membership mitigates incentive and informational problems.
SSRN
Distinguishing two components of the preference for geographical proximity â€" the domestic country bias assessing investors’ holdings within the domestic market, and the foreign country bias assessing investors’ bilateral holdings within a particular host, I document a number of stylized facts related to international equity portfolios. First, investors in emerging countries hold systematically larger shares in their local markets compared to investors in developed countries. Second, while investors generally allocate trivial shares to most of the available destinations and completely disregard the remaining ones, I report several positive country bias ratios suggesting that the source country's investors overweigh the destination market. Third, the portfolio equity held in only a small number of destination markets generates much of countries’ existing foreign assets. I refer to this observation as the geographical shrinkage suggesting that the domestic bias coexists with an equally imperfect diversification of investors’ foreign asset holdings.
SSRN
Environmental, Social, and Governance (ESG) signals are an important part of factor-based investing strategies as they can stem from the same economic rationales as general factor premiums. Because factors are broad and diversified, building portfolios by jointly optimizing factor exposures with ESG and carbon outcomes results in similar historical performance as benchmark factor portfolios which do not include those considerations. We show how sustainable signals, which often involve alternative data, can be integrated in the definitions of factors themselves: we offer two examples on green intangible value and corporate culture quality which enhance traditional financial value and quality factors, respectively.
SSRN
Limited access to finance is one of the major barriers for women entrepreneurs in Africa. This paper presents a model of start-ups in which firms' sales and profits depend on their productivity and access to credit. However, due to the lack of collateral assets such as land, female entrepreneurs have more constrained access to credit than do men. Testing the model on data from the World Bank Enterprise Surveys in Eswatini, Lesotho, and Zimbabwe, we find land ownership to be important for female entrepreneurial performance in terms of sales levels. This finding suggests that the small Southern African economies would benefit from removing obstacles to women's land tenure and enabling financial institutions to lend against movable collateral. While land ownership is linked with higher sales levels, it seems less critical for sales growth and innovation where access to short term loans for working capital seems to be key.
SSRN
We present a portable model of distorted learning which embodies Tversky and Kahneman’s (1971) “belief in the law of small numbers.†When adjusting beliefs in response to new information the decision maker overweights the sample, updating as if the sample size were inflated. The degree of distortion is embodied in a single parameter specific to the agent and not to the particular stochastic setting. We show that the beliefs of such an agent preserve many dynamic properties of fully rational Bayesian beliefs. Though exaggerated likelihood delivers similar predictions to diagnostic expectations in a static setting, the models imply dramatically different belief dynamics. We present examples of distorted Kalman filtering in a Gaussian environment as well as a non-linear setting with stochastic volatility.
SSRN
We use forward-looking Morningstar Analyst Ratings to infer a distribution of expected abnormal returns (alphas) for mutual funds. We benchmark analysts' expectations against expectations obtained from an estimation of a rational model of fund performance. Compared with the rational learner, we find a larger dispersion in analysts' expectations, that analysts' expectations increase less with perceived managerial skill, and that analysts' expectations increase --- as opposed to decrease --- with fund size. The equal-weighted industry alpha is negative, whereas the value-weighted alpha is positive, indicating that analysts believe that the industry is too large in terms of the number of funds but too small in terms of total assets.
SSRN
Commodity is one of the most volatile markets and forecasting its volatility is an issue of paramount importance. Based on a high-frequency futures price dataset of 22 commodities and by employing fractional stochastic volatility and heterogeneous autoregressive (HAR) models, we confirm that the volatility of commodity markets is rough and volatility components over different horizons are economically and statistically significant. Long memory with anti-persistence is evident across all commodities, with weekly volatility dominating in the energy markets and monthly volatility leading the other commodity markets. Fractional stochastic volatility models have a marginal advantage in monthly forecasts, while HAR models consistently outperform in short horizons.
SSRN
This paper examines foreign investors' equity-level transactions in an emerging stock market, the Istanbul Stock Exchange, for the period 1997â€"2008 to derive insights into the debate on information asymmetries between domestic and foreign investors and the home bias puzzle. The analysis suggests two important findings. First, foreign investors do not consider the market portfolio of domestic securities as predicted by standard theories of international portfolio diversification. Second, the firm's size and the expected return are central to explain foreign investors' equity trades. The results are consistent with models based upon the hypothesis of differential information between foreign and domestic investors.
SSRN
This paper investigates whether interbank network topology influences the impact of monetary policy announcements on bank cumulative abnormal returns (CAR's). Although recent studies have emphasized the channels of non-conventional monetary policy actions and the sensitivity of bank stock prices to "News", how such reaction could be influenced by the shape of bank networks remains an open issue. We look at how banks' interconnectedness within interbank loan and deposit networks affects investors' expectations of future bank performance in response to monetary policy "News". Our sample consists of commercial, investment, real estate and mortgage banks in 10 Euro-zone countries. Our results show that the stock prices of banks with stronger local network positions are less sensitive to monetary policy announcements while those of banks with stronger system-wide positions are more sensitive to them.
SSRN
Many believe that investors can contribute to a more sustainable world by divesting from firms with the worst sustainability profiles. However, exclusion comes down to a transfer of ownership from sustainability-minded investors to other investors, and it is not obvious how this is supposed to lead to changes for the better in society. This article critically examines the arguments for exclusion and concludes that the effectiveness of exclusion policies is questionable. Investors may well achieve more by exerting influence as an active shareholder, through voting and engaging with firms.
arXiv
The original Kelly criterion provides a strategy to maximize the long-term growth of winnings in a sequence of simple Bernoulli bets with an edge, that is, when the expected return on each bet is positive. The objective of this work is to consider more general models of returns and the continuous time, or high frequency, limits of those models.
SSRN
We present evidence for the euro area of a risk-taking channel of monetary policy induced by a low interest rate environment in the aftermath of the financial crisis. Specifically, our dataset covers the period 2009â€"2017 and analyzes the interdependencies between loan risk, interest rates, and the degree of leverage in banks’ balance sheets. Based on dynamic panel techniques, we find that loan risk (measured ex-ante and ex-post) is negatively associated with variations in interest rates. This negative relationship is most pronounced for banks with relatively high levels of leverage, which is consistent with a search for yield effect. We show that bank liquidity and industry concentration both influence the intensity of the search for yield effect. Eventually, we identify nonlinearities depending on the level of bank capitalization.
SSRN
We present evidence that market sentiment is positively priced in the cross-section of stock returns in low-sentiment periods. We estimate individual stock exposure to market sentiment and find that, in periods of low market sentiment, stocks in the highest sentiment beta quintile generate a 0.66% higher ex-post monthly return, on average, relative to stocks in the lowest sentiment beta quintile. However, this return spread is no longer significant in medium- or high-sentiment periods. This is consistent with asymmetric pricing wherein overpricing in high-sentiment periods is more prevalent than underpricing in low-sentiment periods due to short-sale constraints.
arXiv
In a general one-sided limit order book where the unaffected price process follows a Levy process, we consider the problem for an investor with constant absolute risk aversion to optimally liquidate a given large position of shares. Since liquidation normally takes place within a short period of time, modelling the risk as a Levy process should provide a realistic model with good statistical fit to observed market data, thus providing a realistic reflection of the investors market risk. We can reduce the optimisation problem to a deterministic two-dimensional singular problem, to which we are able to derive an explicit solution in terms of the model data. In particular we find an expression for the optimal intervention boundary, which completely characterise the optimal liquidation strategy.
arXiv
We consider an optimal liquidation problem with infinite horizon in the Almgren-Chriss framework, where the unaffected asset price follows a Levy process. The temporary price impact is described by a general function which satisfies some reasonable conditions. We consider an investor with constant absolute risk aversion, who wants to maximise the expected utility of the cash received from the sale of his assets, and show that this problem can be reduced to a deterministic optimisation problem which we are able to solve explicitly. In order to compare our results with exponential Levy models, which provides a very good statistical fit with observed asset price data for short time horizons, we derive the (linear) Levy process approximation of such models. In particular we derive expressions for the Levy process approximation of the exponential Variance-Gamma Levy process, and study properties of the corresponding optimal liquidation strategy. We then provide a comparison of the liquidation trajectories for reasonable parameters between the Levy process model and the classical Almgren-Chriss model. In particular, we obtain an explicit expression for the connection between the temporary impact function for the Levy model and the temporary impact function for the Brownian motion model (the classical Almgren-Chriss model), for which the optimal liquidation trajectories for the two models coincide.
SSRN
It is commonly argued that crises open up a window of opportunity to implement policies that otherwise would not have the necessary political backing. The argument goes that the political cost of deep reforms declines as crises unravel structural problems that need to be urgently rectified and the public is more willing to bear the pains associated with such reforms. This paper casts doubt on this prevalent view by showing that not only the crises-reforms nexus is unfounded in the data, but rather crises are associated with slowing structural reforms depending on the institutional environment. In particular, we look at measures of reforms in international trade, agriculture, network industries, and financial markets. We find that, after a financial crisis, democracies neither open nor close their economy. On the contrary, autocracies reduce reforms in multiple economic sectors, as the fear of regime change lead non-democratic rulers to please vested economic interests.
SSRN
We study the effects on financial markets and real economic activity of changes in risk related to political events and policy announcements in Italy during the 2013-2019 period that saw the rise to power of populist parties. We focus on events that have implications for budgetary policy, debt sustainability and for Euro membership. We use changes in the Credit Default Swaps (CDS) spread on governments bonds around those dates as an instrument for shocks to policy and institutional risk â€" political risk for short â€" in the context of Local Projections - IV.We show that shocks associated with the rise of populist forces or their policies have adverse and sizable effects on financial markets. These negative effects were moderated by European institutions and domestic constitutional constraints. In addition, Italian political developments generate international spillover effects on the spreads of some other euro-zone countries. Finally, political risk shocks have a negative impact on the real economy, although the accommodating stance of monetary policy helped in cushioning their effect.
arXiv
In this paper we present formulas for the valuation of debt and equity of firms in a financial network under comonotonic endowments. We demonstrate that the comonotonic setting provides a lower bound and Jensen's inequality provides an upper bound to the price of debt under Eisenberg-Noe financial networks with consistent marginal endowments. Such financial networks encode the interconnection of firms through debt claims. The proposed pricing formulas consider the realized, endogenous, recovery rate on debt claims. Special consideration is given to the CAPM setting in which firms invest in correlated portfolios. We provide theoretical and empirical justifications for comonotonic endowments in the financial sector.
SSRN
The SWIM package implements a flexible sensitivity analysis framework, based primarily on results and tools developed by Pesenti et al. (2019). SWIM provides a stressed version of a stochastic model, subject to model components (random variables) fulfilling given probabilistic constraints (stresses). Possible stresses can be applied on moments, probabilities of given events, and risk measures such as Value-at-Risk and Expected Shortfall. SWIM operates upon a single set of simulated scenarios from a stochastic model, returning scenario weights, which encode the required stress and allow monitoring the impact of the stress on all model components. The scenario weights are calculated to minimise the relative entropy with respect to the baseline model, subject to the stress applied. As well as calculating scenario weights, the package provides tools for the analysis of stressed models, including plotting facilities and evaluation of sensitivity measures. SWIM does not require additional evaluations of the simulation model or explicit knowledge of its underlying statistical and functional relations; hence it is suitable for the analysis of black box models. The capabilities of SWIM are demonstrated through a case study of a credit portfolio model.
arXiv
First, we consider the problem of hedging in complete binomial models. Using the discrete-time F\"ollmer-Schweizer decomposition, we demonstrate the equivalence of the backward induction and sequential regression approaches. Second, in incomplete trinomial models, we examine the extension of the sequential regression approach for approximation of contingent claims. Then, on a finite probability space, we investigate stability of the discrete-time F\"ollmer-Schweizer decomposition with respect to perturbations of the stock price dynamics and, finally, perform its asymptotic analysis under simultaneous perturbations of the drift and volatility of the underlying discounted stock price process, where we prove stability and obtain explicit formulas for the leading order correction terms.
arXiv
The present paper addresses the issue of the stochastic control of the optimal dynamic reinsurance policy and dynamic dividend strategy, which are state-dependent, for an insurance company that operates under multiple insurance lines of business. The aggregate claims model with a thinning-dependence structure is adopted for the risk process. In the optimization method, the maximum of the cumulative expected discounted dividend payouts with respect to the dividend and reinsurance strategies are considered as value function. This value function is characterized as the smallest super Viscosity solution of the associated Hamilton-Jacobi- Bellman (HJB) equation. The finite difference method (FDM) has been utilized for the numerical solution of the value function and the optimal control strategy and the proof for the convergence of this numerical solution to the value function is provided. The findings of this paper provide insights for the insurance companies as such that based upon the lines in which they are operating, they can choose a vector of the optimal dynamic reinsurance strategies and consequently transfer some part of their risks to several reinsurers.
SSRN
Keynes argued that the short-term interest rate is the main driver of the long-term interest rate.This paper empirically models the relationship between short-term interest rates and long-termgovernment securities yields in Canada, after controlling for other important financial variables.The statistical analysis uses high-frequency daily data from 1990 to 2018. It applies both thecointegration technique and Granger causality within the vector error correction (VEC)framework. The empirical results suggest that the action of the monetary authority is animportant determinant of Canadian government securities yields, which supports the Keynesianperspective. These findings have important implications for investors, financial analysts, andpolicymakers.
SSRN
To value shares there are two usual methods that, if properly applied, provide the same value: 1/ Present value of expected free cash flows (FCF) discounted with the WACC rate and then, subtract the value of debt; and 2/ Present value of expected equity cash flows (ECF) discounted with the Ke rate (required return to equity). Both valuations must provide the same result because both methods analyze the same reality under the same hypotheses; they differ only in the cash flows taken as the starting point for the valuation.But in many valuations performed by investment banks, analysts, consultants, finance professors… both methods do not provide the same value.This paper presents a real valuation performed by a well-known investment bank, with two very different values: €6,9 million using method 1/, and €4,2 million using method 2/.
RePEC
In this paper, we explore the drivers of house prices in Norway, using a cross-country panel framework. Empirical results confirm that house prices are determined by numerous demand and supply factors, including income, demographics, macroeconomic conditions, stock of housing and institutional features. The results suggest that high and rising house prices in Norway are principally driven by market fundamentals – high household incomes, wealth, low interest rates and a growing population. Yet, despite strong fundamentals, comparing predicted house prices as estimated by the model and observed house prices suggests that house prices in Norway have been overvalued to a degree since the global financial crisis. Some structural and regulatory features of the Norwegian housing market also put upward pressure on prices: the favourable tax treatment of home ownership, strict rent controls and lax tenant-landlord regulations. Improving further the responsiveness of housing supply to demand could also ease price pressures.
