Academic literature on the topic 'Financial forecasts'

The transparency of monetary policy in South Africa has increased substantially since the end of the 1990s. But little empirical work has been done to examine the economic benefits of the increased transparency. This paper shows that, in recent years, South African private sector forecasters have become better able to forecast interest rates, are less surprised by reserve bank policy announcements, and are less diverse in the cross-sectional variety of their interest rate forecasts. In addition, there is some evidence that the accuracy of inflation forecasts has increased. The improvements in interest rate and inflation forecasts have exceeded those in real output forecasts, suggesting that increases in monetary policy transparency are likely to have played a role.

ABSTRACT: This study examines whether the market reacts more strongly to earnings forecast revisions when financial analysts supplement their earnings forecasts with sales forecasts. I find that earnings forecast revisions supplemented with sales forecast revisions have a greater impact on security prices than do stand-alone earnings forecast revisions, controlling for the incremental information content in sales forecasts. Supplemented earnings forecasts are more accurate ex post, controlling for other individual analyst characteristics. Results are robust to controlling for earnings persistence and time effects. Taken as a whole, financial analysts are more likely to supplement their earnings forecasts with sales forecasts when they have better information. Supplementary sales forecasts appear to lend credibility to earnings forecasts because financial analysts provide sales forecasts when they are more informed.

Prior studies find that analysts tend to bias their forecasts upward in poor information environments and downward in rich information environments, consistent with attempts to curry favor with management. We find that investors anticipate this behavior by reducing their response to upward forecasts in poor information environments and downward forecasts in rich information environments. Using Hugon and Muslu’s measure of analyst conservatism as an ex ante indicator of individual analysts’ forecast bias tendencies, we show that the stronger return response they find to conservative analysts’ forecast revisions is restricted to poor information environments, where optimistic analyst bias is prevalent. Our results suggest that analysts pay a price in market influence when their forecasts reinforce analysts’ typical forecast bias for the firm’s information environment. Conversely, analysts whose forecasts conflict with the typical bias for the firm are rewarded with larger than average return responses.

This paper examines the effect of earnings transparency on analysts’ target price forecast properties. The issuance of target price forecasts by financial analysts is a very recent event and target price forecasts are regarded as the most summarized and explicit estimate of the postulated future value of the firm.The sample consists of financial analysts’ forecasts of annual target price issued for firms listed on U.S. stock exchanges from 2001 to 2017. We measure each firm’s earnings transparency as the contemporaneous co-movement between firm’s earnings and change in earnings and stock returns, consisting in industry-specific and -neutral components in earnings-returns relation.Our results show that target price forecasts for more transparent earnings are less biased and more tend to attain the actual stock prices. These results demonstrate that earnings transparency is positively related with analysts’ target price forecasts. Our empirical results corroborate that more transparent accounting information help the market participants in forming more accurate and attainable forecasts. Our study extends the body of research studying the relation between analysts’ forecast properties and the usefulness of accounting information by investigation target price forecasts.

Purpose The purpose of this paper is to investigate the effect of non-articulation on analyst earnings forecast quality. The authors look for evidence on the relationship between non-articulation and analyst earnings forecast properties: forecast inaccuracy, forecast dispersion and forecast bias. Design/methodology/approach The empirical tests are primarily based analyst earnings and cash flow forecasts covered by Institutional Broker Estimate System and financial statement information obtained from Compustat North America database. Findings The authors hypothesize and find that non-articulation is positively related to analyst forecast dispersion, forecast accuracy and forecast bias for one-year ahead of earnings. The effects of non-articulation on analyst earnings forecast inaccuracy and bias are neutralized when the analyst issues a cash flow forecast and when such forecast provides accurate information regarding the forecasted firm’s operating cash flow. On the other hand, cash flow forecast issuance alone does not mitigate the negative influence of non-articulation. Research limitations/implications The sample selection procedure limits the generalizability of the findings. Practical implications The findings confirm CFA Institute and prior research asserting that non-articulation deteriorates the quality of earnings forecasts by financial statement users (more specifically, the financial analysts). The authors add to the literature by documenting that accurate cash flow forecasts help analysts mitigate the negative influence of non-articulation on earnings forecast quality. Originality/value It remains an empirical question whether non-articulation between the balance sheet and the statement of cash flows has an effect on financial statement users’ ability to assimilate financial information. The paper highlights the detrimental effect of non-articulation by documenting the relationship between the non-articulation and the quality of earnings expectation.

Purpose The purpose of this paper is to examine the way serial correlation in quarterly earnings forecast errors varies with firm and analyst attributes such as the firm’s industry and the analyst’s experience and brokerage house affiliation. Prior research on financial analysts’ quarterly earnings forecasts has documented serial correlation in forecast errors. Design/methodology/approach Finding that serial correlation in forecast errors is significant and seemingly independent of firm and analyst attributes, the consensus forecast errors are modeled as an autoregressive process. The model of forecast errors that best fits the data is AR(1), and the obtained autoregressive coefficients are used to predict consensus forecast errors. Findings Modeling the consensus forecast errors as an autoregressive process, the present study predicts future consensus forecast errors and proposes a series of refinements to the consensus. Originality/value These refinements were not presented in prior literature and can be useful to financial analysts and investors.

Electricity price forecasting has a paramount effect on generation companies (GenCos) due to the scheduling of the electricity generation scheme according to electricity price forecasts. Inaccurate electricity price forecasts could cause important loss of profits to the suppliers. In this paper, the financial effect of inaccurate electricity price forecasts on a hydro-based GenCo is examined. Electricity price forecasts of five individual and four hybrid forecast models and the ex-post actual prices are used to schedule the hydro-based GenCo using Mixed Integer Linear Programming (MILP). The financial effect measures of profit loss, Economic Loss Index (ELI) and Price Forecast Disadvantage Index (PFDI), as well as Mean Absolute Error (MAE) of the models are used for comparison of the data from 24 weeks of the year. According to the results, a hybrid model, 50% Artificial Neural Network (ANN)–50% Long Short Term Memory (LSTM), has the best performance in terms of financial effect. Furthermore, the forecast performance evaluation methods, such as Mean Absolute Error (MAE), are not necessarily coherent with inaccurate electricity price forecasts’ financial effect measures.

PurposeThe purpose of this research is to introduce a class of FRC (fuzzy random coefficient) volatility models and to study their moment properties. Fuzzy option values and the superiority of fuzzy forecasts over minimum mean‐square forecasts are also discussed in some detail.Design/methodology/approachFuzzy components are assumed to be triangular fuzzy numbers. Buckley's data‐driven method is used to determine the spread of the triangular fuzzy numbers by using standard errors of the estimated parameters.FindingsThe fuzzy kurtosis of various volatility models is obtained in terms of fuzzy coefficients. Fuzzy option values and fuzzy forecasts are illustrated with examples. Fuzzy forecast intervals are narrower than the corresponding MMSE forecast intervals.Originality/valueThis paper will be of value to econometricians and to anyone with an interest in financial volatility models.

Multiperiod-ahead forecasts of returns’ variance are used in most areas of applied finance where long-horizon measures of risk are necessary. Yet, the major focus in the variance forecasting literature has been on one-period-ahead forecasts. In this review, we compare several approaches of producing multiperiod-ahead forecasts within the generalized autoregressive conditional heteroscedastic (GARCH) and realized volatility (RV) families—iterated, direct, and scaled short-horizon forecasts. We also consider the newer class of mixed data sampling (MIDAS) methods. We carry the comparison on 30 assets, comprising equity, Treasury, currency, and commodity indices. While the underlying data are available at high frequency (5 minutes), we are interested in forecasting variances 5, 10, 22, 44, and 66 days ahead. The empirical analysis, which is performed in sample and out of sample with data from 2005 to 2018, yields the following results: Iterated GARCH dominates the direct GARCH approach, and the direct RV is preferred to the iterated RV. This dichotomy of results emphasizes the need foran approach that uses the richness of high-frequency data and, at the same time, produces a direct forecast of the variance at the desired horizon, without iterating. The MIDAS is such an approach, and unsurprisingly, it yields the most precise forecasts of variance both in and out of sample. More broadly, our study dispels the notion that volatility is not forecastable at long horizons and offers an approach that delivers accurate out-of-sample predictions.

We study the rationality of individual and consensus forecasts of macroeconomic and financial variables using the methodology of Coibion and Gorodnichenko (2015), who examine predictability of forecast errors from forecast revisions. We find that individual forecasters typically overreact to news, while consensus forecasts under-react relative to full-information rational expectations. We reconcile these findings within a diagnostic expectations version of a dispersed information learning model. Structural estimation indicates that departures from Bayesian updating in the form of diagnostic overreaction capture important variation in forecast biases across different series, yielding a belief distortion parameter similar to estimates obtained in other settings. (JEL C53, D83, D84, E13, E17, E27, E47)

Thesis (Ph. D.)--University of California, San Diego, 2006.
Title from first page of PDF file (viewed September 20, 2006). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 125-132).

In this thesis, I study three aspects of sell-side analysts’ stock price forecasts, henceforth target prices: analyst teams’ target price forecast characteristics, analysts’ use of information to revise target prices, and determinants of target price disagreement between analysts.The first essay studies the target price forecast performance of team analysts in the UK and finds that teams issue timelier but not less accurate target prices. Unlike evidence from previous studies, my findings suggest that analyst teamwork may improve forecast timeliness without sacrificing forecast accuracy. However, market reactions to team target price revisions are not significantly different from those to individual analyst target price revisions, suggesting that although target prices issued by analyst teams are timelier and not less accurate than those of individual analysts, investors do not consider analyst team target prices more informative. I conjecture that analysts may work in teams to meet the demand to cover more companies while maintaining the quality of research by individual team members rather than to issue more informative reports.In the second essay, I study how analysts revise their target prices in response to new information implicit in recent market returns, stock excess returns and other analysts’ target price revisions. The results suggest that analysts’ target price revisions are significantly influenced by market returns, stock excess return and other analysts’ target price revisions. I also find that the correlation between target price revisions and stock excess returns is significantly higher when the news implicit in these returns is bad rather than good. I conjecture that analysts discover more bad news from the information in stock excess returns because firms tend to withhold bad news, disclosing it only when it becomes inevitable, while they disclose good news early. Using a new measure of bad to good news concentration, I show that the asymmetric responsiveness of target price revisions to positive and negative stock excess returns is significant for firms with the highest concentration of bad news but is insignificant for firms with the lowest concentration of bad news. I argue that firms with the highest concentration of bad news are more likely to withhold and accumulate bad news. The findings, therefore, support my hypothesis that analysts discover more bad news than good news from stock returns because firms tend to withhold bad news, disclosing it only when it is inevitable. The third essay examines the determinants of analyst target price disagreement. I find that while disagreement in short-term earnings and in long-term earnings growth forecasts are significant determinants, recent 12-month idiosyncratic return volatility has the strongest explanatory power for target price disagreement. The findings suggest that target price disagreement is driven not only by analyst disagreement about short-term earnings and long-term earnings growth, but also by differences in analysts’ opinions about the impact of recent firm-specific events on value drivers beyond short-term future earnings and long-term growth, which are eventually reflected in past idiosyncratic return volatility.

Cette thèse, constituée de trois papiers de recherche, est organisée autour de la construction d’indicateurs de crises financières dont les signaux sont ensuite utilisés pour l’élaboration de stratégies de trading algorithmique. Le premier papier traite de l’établissement d’un cadre de travail permettant la construction des indicateurs de crises financière. Le pouvoir de prédiction de nos indicateurs est ensuite démontré en utilisant l’un d’eux pour construire une stratégie de type protective-put active qui est capable de faire mieux en termes de performances qu’une stratégie passive ou, la plupart du temps, que de multiples réalisations d’une stratégie aléatoire. Le second papier va plus loin dans l’application de nos indicateurs de crises à la création de stratégies de trading algorithmique en utilisant le signal combiné d’un grand nombre de nos indicateurs pour gouverner la composition d’un portefeuille constitué d’un mélange de cash et de titres d’un ETF répliquant un indice equity comme le SP500. Enfin, dans le troisième papier, nous construisons des indicateurs de crises financières en utilisant une approche complètement différente. En étudiant l’évolution dynamique de la distribution des spreads des composantes d’un indice CDS tel que l’ITRAXXX Europe 125, une bande de Bollinger est construite autour de la fonction de répartition de la distribution empirique des spreads, exprimée sur une base de deux distributions log-normales choisies à l’avance. Le passage par la fonction de répartition empirique de la frontière haute ou de la frontière basse de cette bande de Bollinger est interprétée en termes de risque et permet de produire un signal de trading
This thesis is constituted of three research papers and is articulated around the construction of financial crisis indicators, which produce signals, which are then applied to devise successful systematic trading strategies. The first paper deals with the establishment of a framework for the construction of our financial crisis indicators. Their predictive power is then demonstrated by using one of them to build an active protective-put strategy, which is able to beat in terms of performance a passive strategy as well as, most of the time, multiple paths of a random strategy. The second paper goes further in the application of our financial crisis indicators to the elaboration of systematic treading strategies by using the aggregated signal produce by many of our indicators to govern a portfolio constituted of a mix of cash and ETF shares, replicating an equity index like the SP500. Finally, in the third paper, we build financial crisis indicators by using a completely different approach. By studying the dynamics of the evolution of the distribution of the spreads of the components of a CDS index like the ITRAXX Europe 125, a Bollinger band is built around the empirical cumulative distribution function of the distribution of the spreads, fitted on a basis constituted of two lognormal distributions, which have been chosen beforehand. The crossing by the empirical cumulative distribution function of either the upper or lower boundary of this Bollinger band is then interpreted in terms of risk and enables us to construct a trading signal

Analysts are a major source of information in equity markets. Therefore, their earnings forecasts and stock recommendations are likely to be important for understanding how equity markets work. Analysts' earnings forecasts arc generally, optimistic and their buy/hold/sell recommendations influence stock prices. However, whether (and how) they underreact or overreact to information Is not yet clear. The present thesis discusses tile underreaction/overreaction issues and examines the information contents of analysts' recommendations.

This thesis consists of three empirical chapters that investigate the nature, reasons and consequences of financial analysts’ forecasts in London Stock Exchange. The first empirical chapter examines the rationality and accuracy of financial analysts’ forecasts. Results show that analyst forecasts are overall optimistic, but not as extreme as the literature suggests. However, analysts seem to converge to a more rational position the closer they get to the announcement date. Despite no evidence of relationship is found between forecast error and prior year change in earnings per share, analysts are believed to be systematically revising their forecasts downwards as the time approaches the earnings’ announcement date. The second empirical chapter attempts to study the factors that contribute to the forecast error and in particular earnings management. Results show that earnings management positively affects the magnitude of the forecast error, that is, when earnings are manipulated the forecast error appears to be bigger. However, this positive impact appears to be driven by accruals earnings management and not by real earnings management. Moreover, forecasts seem to be more optimistic for companies that manage their earnings downwards through accruals. These findings reveal that analysts may not be as biased as the literature claim, instead, they are probably victims of earnings management. The third empirical chapter examines whether financial analysts’ forecast is a major component of market sentiment and tests how this contribution can affect cross sectional returns. Results confirm that analysts releasing higher than average earnings per share forecasts lead to higher sentiment levels. Inconsistent with previous literature, short term stock returns are significantly positively affected by sentiment levels, but growth stocks appear to be more sensitive to shifts in sentiment than value stocks.

This study examines the Chicago Board Option Exchange (CBOE) Volatility Index (VIX) which is the implied volatility calculated from short-term option prices on the Standards & Poor’s 500 stock index (S&P 500). Findings suggest VIX overestimates average volatility by approximately 3% but explains 55% of S&P 500’s proceeding month’s volatility. The implied volatility (IV) from options on the VIX add additional explanatory power for the S&P’s 500 proceeding kurtosis values (a measure of tail risk). The VIX option’s volatility smirks did not add additional explanatory power for explaining the S&P 500 volatility or kurtosis. A simple trading rule based on buying the S&P 500 whether the VIX, IV from the options on the VIX, and the VIX option’s volatility smirk decline over the preceding month results in an additional 0.96% return in the following month. However, this only occurs approximately 10% of the time and does not outperform a simple buy-and-hold strategy as the strategy has the investor out of the market the majority of the time.

AbstractForecasting economic and financial variables is a challenging task for several reasons, such as the low signal-to-noise ratio, regime changes, and the effect of volatility among others. A recent trend is to extract information from news as an additional source to forecast economic activity and financial variables. The goal is to evaluate if news can improve forecasts from standard methods that usually are not well-specified and have poor out-of-sample performance. In a currently on-going project, our goal is to combine a richer information set that includes news with a state-of-the-art machine learning model. In particular, we leverage on two recent advances in Data Science, specifically on Word Embedding and Deep Learning models, which have recently attracted extensive attention in many scientific fields. We believe that by combining the two methodologies, effective solutions can be built to improve the prediction accuracy for economic and financial time series. In this preliminary contribution, we provide an overview of the methodology under development and some initial empirical findings. The forecasting model is based on DeepAR, an auto-regressive probabilistic Recurrent Neural Network model, that is combined with GloVe Word Embeddings extracted from economic news. The target variable is the spread between the US 10-Year Treasury Constant Maturity and the 3-Month Treasury Constant Maturity (T10Y3M). The DeepAR model is trained on a large number of related GloVe Word Embedding time series, and employed to produce point and density forecasts.

In January 2020, the International Monetary Fund (IMF) predicted that the world economy would grow by 3.3% in 2020. However, in its latest forecasts, in April, it predicts a contraction of 3.0%, without growth prospects and with numerous risks. The World bank even forecasts a 3.6% contraction in 2020. These forecasts are already seen as overestimates. Most baseline forecast envisions the deepest global recession since World War II. This study analyzes various economics impacts of the COVID-19 on a global scale. If the global recession expected due to the effects of the coronavirus (COVID-19) would lead to a decline in growth rate of global gross domestic product (GDP) between 2.0% and 10.% in all countries in 2020, the number of unemployed people in the net food importer countries would increase between 14.4 million and 80.3 million; the biggest part of the increase would occur in low-income countries. As the pandemic has shown its most severe impact on the largest world economies, the study considers the developments in United States, Euro Area, Japan and China. The recessions in these parts of the world spreads to the other countries and one should primarily consider these regions. Next we consider the trends in global trades, financial markets, and commodity markets. In association with the four regions of the global economy and trends in global trade, financial markets and commodity markets we consider recent developments in emerging markets.

The growing airline transportation in the world and Turkey in recent years has increased the importance of airline passenger and cargo transportation operations and has brought intense competition in the domestic and international airlines market. Under intense competition, it is of utmost importance to capture the sustainable success of an ever-evolving and growing market by accurately assessing the financial performance and risks of businesses. In addition to the financial ratios generally used in all sectors, a number of indicators specific to the airline industry are used to assess the financial status of companies operating in the airline industry. These ratios and indicators will be calculated to compare for past periods and years, to assess risks for the future, to make forecasts, to report, to be able to see the financial status of the business concerned and to plan and make decisions in a more healthy and accurately. In this paper, after literature review, one of the most important financial risk evaluation model Altman Z’’ score is examined and an application with Turkish Airlines’ quarterly last 3 years financial data is evaluated.

Integrated analysis of reservoir and production system models for field development can improve production forecasts. This integration allows the evaluation and optimization of parameters of both systems for both financial return and accurate production prediction. This work evaluates the presence and position of manifolds and their influence on production. We use a Brazilian benchmark case to perform an integrated analysis of oilfield production evaluating the influence of various aspects of manifold systems to increase financial return. The results showed that integrated analysis of optimized manifold locations and the number of connected wells improved financial return. Thus, we recommend the inclusion of this integrated production modeling in field management.

According to the World Health Organization, the new coronavirus, which first appeared in the Chinese city of Wuhan in December last year, infected more than 110,000 people in at least 110 countries and territories of the world. The virus outbreak has become one of the most serious threats to the global economy and financial markets. Large institutions and banks have reduced their forecasts for the global economy, and the Organization for Economic Co-operation and Development is one of the last countries to do so. Meanwhile, concerns about the impact of coronavirus on the global economy have stirred markets around the world: stock prices and bond yields have plummeted. The continued spread of the new coronavirus has become one of the biggest threats to the global economy and financial markets.

For more than a year, the Caribbean economics team at the Inter-American Development Bank (IDB) has focused on the potential implications of the COVID-19 pandemic for lives and livelihoods across the region. The pandemic is still with us, but there is hope that the cycles of lockdowns and containment measures will eventually come to an end as vaccination programs progress, even if unevenly, across the region. However, the availability of vaccine supply remains a concern, and the pandemic continues to pose a constraint for the recovery of key sectors such as tourism and local services sectors. This edition of the Caribbean Quarterly Bulletin focuses on two topics: (1) forecasts of key macroeconomic variables, based on the April 2021 WEO, and (2) financial sector risks. In general, regional economies are embarking on a fragile path to recovery. Continued progress with vaccination programs, credible medium-term fiscal programs, and continued attention to financial vulnerabilities will be needed to push that path to recovery forward.

1.1 Macroeconomic summary Economic recovery has consistently outperformed the technical staff’s expectations following a steep decline in activity in the second quarter of 2020. At the same time, total and core inflation rates have fallen and remain at low levels, suggesting that a significant element of the reactivation of Colombia’s economy has been related to recovery in potential GDP. This would support the technical staff’s diagnosis of weak aggregate demand and ample excess capacity. The most recently available data on 2020 growth suggests a contraction in economic activity of 6.8%, lower than estimates from January’s Monetary Policy Report (-7.2%). High-frequency indicators suggest that economic performance was significantly more dynamic than expected in January, despite mobility restrictions and quarantine measures. This has also come amid declines in total and core inflation, the latter of which was below January projections if controlling for certain relative price changes. This suggests that the unexpected strength of recent growth contains elements of demand, and that excess capacity, while significant, could be lower than previously estimated. Nevertheless, uncertainty over the measurement of excess capacity continues to be unusually high and marked both by variations in the way different economic sectors and spending components have been affected by the pandemic, and by uneven price behavior. The size of excess capacity, and in particular the evolution of the pandemic in forthcoming quarters, constitute substantial risks to the macroeconomic forecast presented in this report. Despite the unexpected strength of the recovery, the technical staff continues to project ample excess capacity that is expected to remain on the forecast horizon, alongside core inflation that will likely remain below the target. Domestic demand remains below 2019 levels amid unusually significant uncertainty over the size of excess capacity in the economy. High national unemployment (14.6% for February 2021) reflects a loose labor market, while observed total and core inflation continue to be below 2%. Inflationary pressures from the exchange rate are expected to continue to be low, with relatively little pass-through on inflation. This would be compatible with a negative output gap. Excess productive capacity and the expectation of core inflation below the 3% target on the forecast horizon provide a basis for an expansive monetary policy posture. The technical staff’s assessment of certain shocks and their expected effects on the economy, as well as the presence of several sources of uncertainty and related assumptions about their potential macroeconomic impacts, remain a feature of this report. The coronavirus pandemic, in particular, continues to affect the public health environment, and the reopening of Colombia’s economy remains incomplete. The technical staff’s assessment is that the COVID-19 shock has affected both aggregate demand and supply, but that the impact on demand has been deeper and more persistent. Given this persistence, the central forecast accounts for a gradual tightening of the output gap in the absence of new waves of contagion, and as vaccination campaigns progress. The central forecast continues to include an expected increase of total and core inflation rates in the second quarter of 2021, alongside the lapse of the temporary price relief measures put in place in 2020. Additional COVID-19 outbreaks (of uncertain duration and intensity) represent a significant risk factor that could affect these projections. Additionally, the forecast continues to include an upward trend in sovereign risk premiums, reflected by higher levels of public debt that in the wake of the pandemic are likely to persist on the forecast horizon, even in the context of a fiscal adjustment. At the same time, the projection accounts for the shortterm effects on private domestic demand from a fiscal adjustment along the lines of the one currently being proposed by the national government. This would be compatible with a gradual recovery of private domestic demand in 2022. The size and characteristics of the fiscal adjustment that is ultimately implemented, as well as the corresponding market response, represent another source of forecast uncertainty. Newly available information offers evidence of the potential for significant changes to the macroeconomic scenario, though without altering the general diagnosis described above. The most recent data on inflation, growth, fiscal policy, and international financial conditions suggests a more dynamic economy than previously expected. However, a third wave of the pandemic has delayed the re-opening of Colombia’s economy and brought with it a deceleration in economic activity. Detailed descriptions of these considerations and subsequent changes to the macroeconomic forecast are presented below. The expected annual decline in GDP (-0.3%) in the first quarter of 2021 appears to have been less pronounced than projected in January (-4.8%). Partial closures in January to address a second wave of COVID-19 appear to have had a less significant negative impact on the economy than previously estimated. This is reflected in figures related to mobility, energy demand, industry and retail sales, foreign trade, commercial transactions from selected banks, and the national statistics agency’s (DANE) economic tracking indicator (ISE). Output is now expected to have declined annually in the first quarter by 0.3%. Private consumption likely continued to recover, registering levels somewhat above those from the previous year, while public consumption likely increased significantly. While a recovery in investment in both housing and in other buildings and structures is expected, overall investment levels in this case likely continued to be low, and gross fixed capital formation is expected to continue to show significant annual declines. Imports likely recovered to again outpace exports, though both are expected to register significant annual declines. Economic activity that outpaced projections, an increase in oil prices and other export products, and an expected increase in public spending this year account for the upward revision to the 2021 growth forecast (from 4.6% with a range between 2% and 6% in January, to 6.0% with a range between 3% and 7% in April). As a result, the output gap is expected to be smaller and to tighten more rapidly than projected in the previous report, though it is still expected to remain in negative territory on the forecast horizon. Wide forecast intervals reflect the fact that the future evolution of the COVID-19 pandemic remains a significant source of uncertainty on these projections. The delay in the recovery of economic activity as a result of the resurgence of COVID-19 in the first quarter appears to have been less significant than projected in the January report. The central forecast scenario expects this improved performance to continue in 2021 alongside increased consumer and business confidence. Low real interest rates and an active credit supply would also support this dynamic, and the overall conditions would be expected to spur a recovery in consumption and investment. Increased growth in public spending and public works based on the national government’s spending plan (Plan Financiero del Gobierno) are other factors to consider. Additionally, an expected recovery in global demand and higher projected prices for oil and coffee would further contribute to improved external revenues and would favor investment, in particular in the oil sector. Given the above, the technical staff’s 2021 growth forecast has been revised upward from 4.6% in January (range from 2% to 6%) to 6.0% in April (range from 3% to 7%). These projections account for the potential for the third wave of COVID-19 to have a larger and more persistent effect on the economy than the previous wave, while also supposing that there will not be any additional significant waves of the pandemic and that mobility restrictions will be relaxed as a result. Economic growth in 2022 is expected to be 3%, with a range between 1% and 5%. This figure would be lower than projected in the January report (3.6% with a range between 2% and 6%), due to a higher base of comparison given the upward revision to expected GDP in 2021. This forecast also takes into account the likely effects on private demand of a fiscal adjustment of the size currently being proposed by the national government, and which would come into effect in 2022. Excess in productive capacity is now expected to be lower than estimated in January but continues to be significant and affected by high levels of uncertainty, as reflected in the wide forecast intervals. The possibility of new waves of the virus (of uncertain intensity and duration) represents a significant downward risk to projected GDP growth, and is signaled by the lower limits of the ranges provided in this report. Inflation (1.51%) and inflation excluding food and regulated items (0.94%) declined in March compared to December, continuing below the 3% target. The decline in inflation in this period was below projections, explained in large part by unanticipated increases in the costs of certain foods (3.92%) and regulated items (1.52%). An increase in international food and shipping prices, increased foreign demand for beef, and specific upward pressures on perishable food supplies appear to explain a lower-than-expected deceleration in the consumer price index (CPI) for foods. An unexpected increase in regulated items prices came amid unanticipated increases in international fuel prices, on some utilities rates, and for regulated education prices. The decline in annual inflation excluding food and regulated items between December and March was in line with projections from January, though this included downward pressure from a significant reduction in telecommunications rates due to the imminent entry of a new operator. When controlling for the effects of this relative price change, inflation excluding food and regulated items exceeds levels forecast in the previous report. Within this indicator of core inflation, the CPI for goods (1.05%) accelerated due to a reversion of the effects of the VAT-free day in November, which was largely accounted for in February, and possibly by the transmission of a recent depreciation of the peso on domestic prices for certain items (electric and household appliances). For their part, services prices decelerated and showed the lowest rate of annual growth (0.89%) among the large consumer baskets in the CPI. Within the services basket, the annual change in rental prices continued to decline, while those services that continue to experience the most significant restrictions on returning to normal operations (tourism, cinemas, nightlife, etc.) continued to register significant price declines. As previously mentioned, telephone rates also fell significantly due to increased competition in the market. Total inflation is expected to continue to be affected by ample excesses in productive capacity for the remainder of 2021 and 2022, though less so than projected in January. As a result, convergence to the inflation target is now expected to be somewhat faster than estimated in the previous report, assuming the absence of significant additional outbreaks of COVID-19. The technical staff’s year-end inflation projections for 2021 and 2022 have increased, suggesting figures around 3% due largely to variation in food and regulated items prices. The projection for inflation excluding food and regulated items also increased, but remains below 3%. Price relief measures on indirect taxes implemented in 2020 are expected to lapse in the second quarter of 2021, generating a one-off effect on prices and temporarily affecting inflation excluding food and regulated items. However, indexation to low levels of past inflation, weak demand, and ample excess productive capacity are expected to keep core inflation below the target, near 2.3% at the end of 2021 (previously 2.1%). The reversion in 2021 of the effects of some price relief measures on utility rates from 2020 should lead to an increase in the CPI for regulated items in the second half of this year. Annual price changes are now expected to be higher than estimated in the January report due to an increased expected path for fuel prices and unanticipated increases in regulated education prices. The projection for the CPI for foods has increased compared to the previous report, taking into account certain factors that were not anticipated in January (a less favorable agricultural cycle, increased pressure from international prices, and transport costs). Given the above, year-end annual inflation for 2021 and 2022 is now expected to be 3% and 2.8%, respectively, which would be above projections from January (2.3% and 2,7%). For its part, expected inflation based on analyst surveys suggests year-end inflation in 2021 and 2022 of 2.8% and 3.1%, respectively. There remains significant uncertainty surrounding the inflation forecasts included in this report due to several factors: 1) the evolution of the pandemic; 2) the difficulty in evaluating the size and persistence of excess productive capacity; 3) the timing and manner in which price relief measures will lapse; and 4) the future behavior of food prices. Projected 2021 growth in foreign demand (4.4% to 5.2%) and the supposed average oil price (USD 53 to USD 61 per Brent benchmark barrel) were both revised upward. An increase in long-term international interest rates has been reflected in a depreciation of the peso and could result in relatively tighter external financial conditions for emerging market economies, including Colombia. Average growth among Colombia’s trade partners was greater than expected in the fourth quarter of 2020. This, together with a sizable fiscal stimulus approved in the United States and the onset of a massive global vaccination campaign, largely explains the projected increase in foreign demand growth in 2021. The resilience of the goods market in the face of global crisis and an expected normalization in international trade are additional factors. These considerations and the expected continuation of a gradual reduction of mobility restrictions abroad suggest that Colombia’s trade partners could grow on average by 5.2% in 2021 and around 3.4% in 2022. The improved prospects for global economic growth have led to an increase in current and expected oil prices. Production interruptions due to a heavy winter, reduced inventories, and increased supply restrictions instituted by producing countries have also contributed to the increase. Meanwhile, market forecasts and recent Federal Reserve pronouncements suggest that the benchmark interest rate in the U.S. will remain stable for the next two years. Nevertheless, a significant increase in public spending in the country has fostered expectations for greater growth and inflation, as well as increased uncertainty over the moment in which a normalization of monetary policy might begin. This has been reflected in an increase in long-term interest rates. In this context, emerging market economies in the region, including Colombia, have registered increases in sovereign risk premiums and long-term domestic interest rates, and a depreciation of local currencies against the dollar. Recent outbreaks of COVID-19 in several of these economies; limits on vaccine supply and the slow pace of immunization campaigns in some countries; a significant increase in public debt; and tensions between the United States and China, among other factors, all add to a high level of uncertainty surrounding interest rate spreads, external financing conditions, and the future performance of risk premiums. The impact that this environment could have on the exchange rate and on domestic financing conditions represent risks to the macroeconomic and monetary policy forecasts. Domestic financial conditions continue to favor recovery in economic activity. The transmission of reductions to the policy interest rate on credit rates has been significant. The banking portfolio continues to recover amid circumstances that have affected both the supply and demand for loans, and in which some credit risks have materialized. Preferential and ordinary commercial interest rates have fallen to a similar degree as the benchmark interest rate. As is generally the case, this transmission has come at a slower pace for consumer credit rates, and has been further delayed in the case of mortgage rates. Commercial credit levels stabilized above pre-pandemic levels in March, following an increase resulting from significant liquidity requirements for businesses in the second quarter of 2020. The consumer credit portfolio continued to recover and has now surpassed February 2020 levels, though overall growth in the portfolio remains low. At the same time, portfolio projections and default indicators have increased, and credit establishment earnings have come down. Despite this, credit disbursements continue to recover and solvency indicators remain well above regulatory minimums. 1.2 Monetary policy decision In its meetings in March and April the BDBR left the benchmark interest rate unchanged at 1.75%.

The Colombian financial system has not suffered major structural disruptions during these months of deep economic contraction and has continued to carry out its basic functions as usual, thus facilitating the economy's response to extreme conditions. This is the result of the soundness of financial institutions at the beginning of the crisis, which was reflected in high liquidity and capital adequacy indicators as well as in the timely response of various authorities. Banco de la República lowered its policy interest rates 250 points to 1.75%, the lowest level since the creation of the new independent bank in 1991, and provided ample temporary and permanent liquidity in both pesos and foreign currency. The Office of the Financial Superintendent of Colombia, in turn, adopted prudential measures to facilitate changes in the conditions for loans in effect and temporary rules for rating and loan-loss provisions. Finally, the national government expanded the transfers as well as the guaranteed credit programs for the economy. The supply of real credit (i.e. discounting inflation) in the economy is 4% higher today than it was 12 months ago with especially marked growth in the housing (5.6%) and commercial (4.7%) loan portfolios (2.3% in consumer and -0.1% in microloans), but there have been significant changes over time. During the first few months of the quarantine, firms increased their demands for liquidity sharply while consumers reduced theirs. Since then, the growth of credit to firms has tended to slow down, while consumer and housing credit has grown. The financial system has responded satisfactorily to the changes in the respective demands of each group or sector and loans may grow at high rates in 2021 if GDP grows at rates close to 4.6% as the technical staff at the Bank expects; but the forecasts are highly uncertain. After the strict quarantine implemented by authorities in Colombia, the turmoil seen in March and early April, which was evident in the sudden reddening of macroeconomic variables on the risk heatmap in Graph A,[1] and the drop in crude oil and coal prices (note the high volatility registered in market risk for the region on Graph A) the local financial markets stabilized relatively quickly. Banco de la República’s credible and sustained policy response played a decisive role in this stabilization in terms of liquidity provision through a sharp expansion of repo operations (and changes in amounts, terms, counterparties, and eligible instruments), the purchases of public and private debt, and the reduction in bank reserve requirements. In this respect, there is now abundant aggregate liquidity and significant improvements in the liquidity position of investment funds. In this context, the main vulnerability factor for financial stability in the short term is still the high degree of uncertainty surrounding loan quality. First, the future trajectory of the number of people infected and deceased by the virus and the possible need for additional health measures is uncertain. For that reason, there is also uncertainty about the path for economic recovery in the short and medium term. Second, the degree to which the current shock will be reflected in loan quality once the risk materializes in banks’ financial statements is uncertain. For the time being, the credit risk heatmap (Graph B) indicates that non-performing and risky loans have not shown major deterioration, but past experience indicates that periods of sharp economic slowdown eventually tend to coincide with rises in non-performing loans: the calculations included in this report suggest that the impact of the recession on credit quality could be significant in the short term. This is particularly worrying since the profitability of credit establishments has been declining in recent months, and this could affect their ability to provide credit to the real sector of the economy. In order to adopt a forward-looking approach to this vulnerability, this Report presents several stress tests that evaluate the resilience of the liquidity and capital adequacy of credit institutions and investment funds in the event of a hypothetical scenario that seeks to simulate an extreme version of current macroeconomic conditions. The results suggest that even though there could be strong impacts on the credit institutions’ volume of credit and profitability under such scenarios, aggregate indicators of total and core capital adequacy will probably remain at levels that are above the regulatory limits over the horizon of a year. At the same time, the exercises highlight the high capacity of the system's liquidity to face adverse scenarios. In compliance with its constitutional objectives and in coordination with the financial system's security network, Banco de la República will continue to closely monitor the outlook for financial stability at this juncture and will make the decisions that are necessary to ensure the proper functioning of the economy, facilitate the flow of sufficient credit and liquidity resources, and further the smooth operation of the payment systems. Juan José Echavarría Governor