Influences on he Sock Marke: An Examinaion of he Effec of Economic Variables on he S&P 500 By Nahan Taulbee I. INTRODUCTION I s he economy supid! This slogan from Bill Clinon s 1992 Presidenial campaign acknowl edges he imporance of he U.S. economy in American poliics. This slogan migh also resonae loudly on Wall Sree and among invesors across he world. In many ways he performance of he economy influences he success of he sock marke and vice versa. This sudy will examine he impac ha various economic facors have on he sock marke. Specifically, i will ask he quesion, How do ineres raes, real GDP, and he Fisher Effec impac he S&P 500?. In addiion, his sudy will assess he impac of hese economic facors on various indusries including a uiliies, ransporaion, financial, and echnology index. The resuls of his sudy will help invesors undersand jus how imporan hese economic variables are in influencing boh he overall marke and major indusries. The following secions of his paper furher examine he issues raised. Secion II offers a heoreical analysis of how real GDP, unemploymen, and he Fisher Effec should impac he S&P 500. Secion III provides informaion on he expeced relaionship beween he economy and he following major indusry caegories: growh, cyclical, defensive, and ineres-sensiive. Secion IV inroduces he research design including he generalized leas squares model. Secion V presens he resuls and examines he appropriae economeric specificaion. Secion VI concludes he sudy and reieraes imporan findings. II. THEORETICAL MODEL Over he pas 40 years a significan amoun of research has been conduced on he overall sock marke. Included in many of hese sudies is he raional expecaions hypohesis ha John Muh developed in 1961. The raional expecaions hypohesis offered a new perspecive on he formaion of prices. The general idea behind his hypohesis is ha economic agens use boh pas experiences and heir expecaions and predicions of he fuure o deermine he price of an asse oday. According o Sephen Sheffrin s book iled Raional Expecaions, Expecaions are raional if, given he economic model, hey will produce acual values of variables ha will, on average, equal he expecaions. The raional expecaions hypohesis does no, however, require ha all economic agens have idenical expecaions. Insead, he weighed average of hese agens forecass will provide he expeced value of he acual variable (Sheffrin, 1996). Like oher research on he sock marke, his sudy will use he raional expecaions hypohesis in he proceeding heoreical model. For his sudy, he economic agens forming expecaions abou he fuure value of sock prices will be sock marke invesors. Because he raional expecaions hypohesis assumes ha invesors ake all informaion ino accoun, boh expecaions variables and coinciden indicaors will be incorporaed ino he model. Coinciden indicaors are variables ha provide an assessmen of economic condiions a he presen ime. For example, he mos recen unemploymen figure released represens he curren amoun of unemploymen in he Unied Saes oday and is, herefore, a coinciden indicaor. The remainder of his secion will examine he variables in he model in more deail. A. The Fisher Effec Irving Fisher found ha real ineres raes were equal o nominal ineres raes minus expeced inflaion. This macroeconomic relaionship is known as he Fisher Effec (Mankiw, 1997). The Fisher Effec is unique in ha i incorporaes expeced inflaion as The Park Place Economis / vol. IX 91
Nahan Taulbee opposed o acual inflaion raes ino he equaion. This is of ineres o many economiss because i allows hem o use raional expecaions models in heir sudies. One such economis, Yu Hsing, sudied he Fisher Effec and discovered ha nominal ineres raes have a non-linear posiive relaionship wih expeced inflaion when he Federal Funds rae was used (1997). These findings will be incorporaed ino he empirical model in Secion IV. The Fisher Effec is primarily an alernaive way of measuring real ineres raes and will be used as a means of relaing ineres raes and inflaion expecaions o sock prices. To fully undersand he relaionship beween he Fisher Effec and sock prices, i is necessary o undersand he individual relaionships beween inflaion expecaions, ineres raes, and he sock marke. 1. Inflaion Expecaions Since he inroducion of he raional expecaions hypohesis, many sudies concerning inflaion expecaions have been compleed including Douglas Pearce s An Empirical Analysis of Expeced Sock Price Movemens in 1984. Using he Livingson survey, a survey of business, governmen, and academic economiss, Pearce found ha prior o 1972, invesors expeced nominal sock prices o rise wih he general price level because hey fel i was a good hedge agains inflaion. However, afer 1972, Pearce found ha he relaionship beween sock prices and inflaion expecaions became less significan. A likely reason for his is he volailiy of he US economy and he inflaion rae increase in he 1970s due o he OPEC crisis (Pearce, 1984). A sudy conduced by Michael Niemira and Philip Klein suppors he changing relaionship beween inflaion expecaions and he sock marke ha Pearce observed afer 1972. They found ha an inverse relaionship exised beween inflaion expecaions and he sock marke when using he leading indicaor of inflaion as heir daa source for inflaion expecaions (Niemira and Klein, 1994). Alhough no reasons were cied, he likely cause of he inverse relaionship beween inflaion expecaions and he sock marke is ha he Federal Reserve will likely change ineres raes in order o influence a poenial change in inflaion. Because his sudy examines he relaionship of he economy and he sock marke since 1972, an inverse relaionship beween inflaion expecaions and he S&P 500 is prediced. The following secion will explain in greaer deail how changes in ineres raes affec sock prices. 2. Ineres Raes William Breen, Lawrence Glosen, and Ravi Jangannahan compleed a sudy of he relaionship beween he Treasury bill rae and he sock marke in heir aricle iled, Economic Significance of Predicable Variaions in Sock Index Reurns. In heir sudy, he auhors found ha an inverse relaionship beween sock index reurns and Treasury bill ineres raes exiss when a value-weighed sock index is used. The reasoning behind his negaive relaionship is ha, when ineres raes rise, he expeced earnings sreams of S&P 500 firms on he whole declines because of he higher cos of borrowing and financing expendiures. Because earnings repors play a dramaic role in sock prices, a rise in ineres raes ha adversely affecs earnings repors will lead o lower sock prices (Breen, Glosen, and Jagannahan, 1989). In summary, he Fisher Effec should have a negaive relaionship wih he S&P 500. B. Gross Domesic Produc (GDP) The fundamenal measure for he performance of he economy is he level of gross domesic produc, or GDP. GDP measures he oal income in an economy earned domesically, including he income earned by foreign-owned facors of producion (Mankiw, 1997). GDP is imporan o he sock marke in ha i serves as a measure of he healh of he economy. As a raional sock marke invesor, a rise in he level of GDP (a posiive growh rae) from one period o he nex would sugges ha firms on he whole are performing posiively. This aggregae performance of firms allows for more reinvesing which should ulimaely lead o higher fuure earnings and sock prices. An increase in GDP from one period o he nex should also increase he level of he sock marke because consumers in general have more purchasing power and would likely devoe more income oward sock marke invesing, ceeris paribus. In his regard, GDP acs as a proxy for he purchasing power abiliy 92 The Park Place Economis / vol. IX
Influences on he Sock Marke of invesors. C. Unemploymen In addiion o GDP, he unemploymen rae is anoher common measure for he healh of he economy. A high unemploymen rae resuls in a lower sense of financial securiy for he unemployed for obvious reasons. However, high unemploymen raes also raise concerns for he employed because heir employmen saus is also in jeopardy in a climae of downsizing and layoffs. This decline in financial securiy by boh he employed and unemployed due o an increase in he unemploymen rae will lead o less invesmen in he sock marke as invesors ry o find safer means of saving heir income. Thus, he unemploymen rae serves as one of he key signals o invesors on he healh of he economy. The prediced sign of he unemploymen coefficien is negaive. III. APPLICATION OF THEORY TO INDUS- TRIES Some secors of he sock marke perform beer han ohers given he same economic condiions. In he recen economic boom, new economy socks such as echnology socks have generally ouperformed old economy socks such as Wal-Mar and he Coca Cola Corporaion. Undersanding he relaionship beween he economy and differen indusries allows invesors o narrow heir focus when deciding where o allocae heir resources. Charles P. Jones, auhor of Invesmens: Analysis and Managemen, believes, Indusry analysis pays because indusries perform very differenly over ime, and invesor performance will be significanly affeced by he paricular indusries in which invesors selec socks (1998 p. 440). Jones also believes ha here is a definie link beween he business cycle and he sock performance of differen indusries and saed he following: Clearly, business cycle analysis for indusries is a logical and worhwhile par of fundamenal securiy analysis. Indusries have varying sensiiviies o he business condiions and ineres rae expecaions a any given ime, and he smar invesor will hink carefully abou hese facors. (p 452) This secion will explore how real GDP, unemploymen, and he Fisher Effec impac he general indusry caegories classified as cyclical, defensive, ineres-sensiive, and growh. A. Cyclical Indusry Cyclical indusries such as capial goods and consumer durables follow he business cycle closely. When he economy prospers, cyclical socks do very well. However, during imes of poor economic condiions and recessions, cyclical socks are likely o suffer more han all non-cyclical socks. For example, during he 1990 recession, cyclical socks declined hree imes more han he S&P 500 (Jones, 1998). The expeced relaionship beween economic growh, unemploymen, and he Fisher Effec on cyclical socks is he same as i is on he overall marke. However, he degree of hese relaionships should vary for cyclical socks relaive o he overall marke because of he fac ha cyclicals are more responsive o he business cycle. B. Defensive Indusry Jus as cyclical indusries are mos affeced by recessions and economic condiions, defensive indusries are leas affeced by he sae of he economy. Examples of defensive indusries include pharmaceuicals, food and beverages, and uiliies (Reilly and Noron, 1999). No maer how bad he economy is, people will coninue o ea, drink, and use basic uiliies. Therefore, as found by Frank Reilly and Edgar Noron, wo finance researchers, Defensive indusries generally mainain heir values during marke declines (1999 p417). The relaionship beween economic facors and he uiliies indusry should be less significan han ha of oher indusries and he overall marke. C. Growh Indusry Earnings of growh indusries are expeced o be much greaer han earnings in all oher indusries. In addiion, growh indusries ofen have increased earnings regardless of he saus of he economy. In he 1980s he major growh indusries were geneic engineering, microcompuers, and new medical devices (Jones, 1998). Today, he major growh indusries are echnology, bioechnology, and Inerne-infrasrucure. I is expeced ha growh indusries will The Park Place Economis / vol. IX 93
Nahan Taulbee perform exremely well when he economy is sound and may coninue o perform well when he economy suffers. Therefore, real GDP, unemploymen, and he Fisher Effec should have a less significan impac on growh socks. D. Ineres-Sensiive Ineres-sensiive socks are mos affeced by expecaions abou changes in ineres raes. Ineres-sensiive indusries include he financial services, banking, real esae, and building indusries (Jones, 1998). For example, if ineres raes increase, individuals are less likely o move or build new homes, which means less business for consrucion companies, real esae agencies, banks, and oher financial services companies. I is hypohesized ha an increase in ineres raes will cause ineres-sensiive indusry s sock price o decline. IV. RESEARCH DESIGN A. Dependen Variables 1. S&P 500 Index (sp500) The S&P 500 index is a major U.S. sock marke index ha consiss of 500 socks. The chief advanage of using he S&P 500 over he more ofen quoed Dow Jones Indusrial Average (DJIA) is ha i is more represenaive of he enire marke because i conains a larger number of socks. In addiion, he S&P 500 index is value-weighed whereas he Dow Jones is a price-weighed index. Thus, high-priced socks carry more weigh wih he DJIA han wih he S&P 500 (Jones, 1998). This sudy will use end-of- monh S&P 500 index values from January, 1972, o Augus, 1999 as he daa source for his dependen variable. The Economagic.com websie will provide he S&P 500 daa. 2. Dow Jones Transporaion Average (Transp) The Dow Jones Transporaion Average (DJT) consiss of 20 airline, rail, and ransporaion services companies ha represen he ransporaion indusry as a whole. [A complee lising of he 20 companies is conained in Appendix A]. The DJT will serve as a proxy for a cyclical indusry because i is plausible o expec less ransporaion during recessions and more ransporaion during boom periods. For insance, when individuals and families are operaing on igh budges, i may no be necessary o pursue a weekend geaway vacaion. Many corporaions operaing on igh budges migh also no decide o send as many employees, if any, on a company rip. Insead, especially wih oday s echnological advancemens, which include videoconferencing, an expensive plane icke during peak hours may no be necessary. Daa for he DJT is end of monh daa from January, 1972, o Augus, 1999. Yahoo! Finance is he source for he daa (www.finance.yahoo.com). 3. Dow Jones Uiliies Index (Uiliy) The Dow Jones Uiliy Index (DJU) includes various uiliies companies including major energy and elecriciy providers hroughou he U.S. [Appendix B conains a complee lising of he 15 companies ha make up he DJU]. The DJU will serve as a proxy for he defensive indusry because of he fac ha uiliies are used regardless of he saus of he economy. Daa for he DJU is end of monh daa from January, 1972, o Augus, 1999. Yahoo! Finance is he source for he daa (www.finance.yahoo.com). 4. Pacific Exchange Technology Index (Tech) The Pacific Exchange Technology Index (PSE) includes end-of-monh daa from February, 1984, o Augus, 1999. The PSE will serve as a proxy for a growh indusry index. The PSE will be used over oher growh indices because of he difficuly of obaining inexpensive hisorical daa on growh indusries. Yahoo! Finance is he source for he daa (www.finance.yahoo.com). 5. Financial Services Index (Financial) The Fideliy Selec Brokerage & Invesmen Fund (FSLBX) is a muual fund ha includes several major brokerage and financial services companies including Morgan Sanley Dean Wier, Charles Schwab, Merrill Lynch, and American Express. The fund has been in exisence since January, 1987, and will serve as a proxy for an ineres-sensiive indusry index. Due o he lack of free hisorical daa for a major financial sock index, his sudy will use FSLBX 94 The Park Place Economis / vol. IX
Influences on he Sock Marke fund. The FSLBX fund provides end of monh hisorical daa ha can be obained from he Yahoo! Finance websie (www.finance.yahoo.com). B. Independen Variables 1. Real GDP () Real GDP will be used insead of nominal GDP because real GDP values he oal oupu of he economy measured a consan prices. Therefore, real GDP changes from year o year if he quaniies produced change. Theory suggess ha real GDP should have a posiive significan impac on he performance of mos sock indices. However, heory also suggess ha he magniude of real GDP s impac should vary across sock indices. For example, real GDP should have a greaer effec on growh indusries han on cyclical and ineres-sensiive indusries. The real GDP daa is indexed for 1992 dollars and is supplied by he economagic.com websie (www.economagic.com). 2. Unemploymen () The unemploymen rae is announced monhly and is simply a measure of he percenage of he civilian labor force ha is no employed. As discussed in he heoreical model, he expeced sign of he coefficien is negaive. The economagic.com websie will provide he unemploymen daa. 3. Fisher Effec () The Fisher Effec is a measure of real ineres raes using nominal ineres raes minus inflaion expecaions. The hree-monh Treasury bill rae will be used as a proxy for nominal ineres raes. This rae was chosen over oher ineres raes because i is highly recognized by sock marke paricipans and because i acs as a caalys for changes in oher ineres raes ha affec he abiliy of individuals and firms o borrow. The economagic.com websie is he source of he hree-monh Treasury bill rae (www.economagic.com). Meanwhile, inflaion expecaions is measured by he inflaion forecass of hose paricipans in he aforemenioned Livingson survey. The Livingson survey, which began in 1946, has been conduced every June and December. The paricipans provide a one-monh, six-monh, and welve-monh forecas of he inflaion rae. This paper will use a moving average of he Livingson survey paricipans sixmonh inflaion forecas as a proxy for he inflaion expecaions explanaory variable (Livingson Survey). The purpose of he moving average is o make he inflaion expecaions daa consisen wih oher monhly daa. C. Generalized Leas Squares Models In order o es he hypohesis discussed in prior secions, regression analysis using double log generalized leas squares (GLS) equaions will be used. Double log equaions are used o assis in he inerpreaion of he resuls. GLS equaions are used because of he exisence of serial correlaion in all ordinary leas squares (OLS) regressions ha were conduced. The following five seps explain how GLS equaions were achieved (Gujarai, 1988): 1. Using he Saisical Package for he Social Sciences (SPSS), an OLS regression was run and produced a coefficien (B) for all independen variables. 2. Rho (p) was calculaed by aking [1 - (Durbin Wason saisic/2)]. 3. The dependen variable was ransformed using he following equaion: Dependen variable - p*(dependen variable -1). 4. All explanaory variables were ransformed using he following equaion: B*(1-p)*[independen variable - p*(independen variable -1)] 5. A new regression was run for each model using all ransformed variables. Because his sudy focuses on he impac of economic facors on he overall sock marke as well as four major indusry caegories, five regression equaions are used. The following five regression equaions include double log ransformaions as saed previously: Model 1 (overall marke): sp500 = a + b1() + b2 () + b3 () + error Model 2 (cyclical indusry): ransp = a + b1() The Park Place Economis / vol. IX 95
Nahan Taulbee Table 1: Summary of Variables Variable sp500 Transp Uiliy ech financial Type Dependen Dependen Dependen Independen Independen Descripio n The Sandard & Poors 500 index; Index for overall sock marke The Dow Jones Transporaion Average; An example of a cyclical index The Dow Jones Uiliies Average; An example of a defensive index The Pacific Exchange Technology index; An example of a growh index The Fideliy Selec Brokerage & Invesmen muual fund; An example of an ineres-sensiive index I ndependen Real Gross Domesic Produc in he U.S. Independen Independen Percenage of he civilian labor force no employe d Real ineres rae measure ha facors inflaion expecaions wih nominal ineres raes + b2 () + b3 () + error Model 3 (defensive indusry): uiliy = a + b1() + b2 () + b3 () + error Model 4 (growh indusry): ech = a + b1() + b2 () + b3 () + error Model 5 (ineres-sensiive indusry): financial = a + b1() + b2 () + b3 () + error Table 1 provides a reminder for all variables in he preceding equaions. A. Model 1: Overall Marke Model 1 performed he bes when compared o he oher models. This is no surprising because of he comparison of broad macroeconomic facors wih a broad sock index. As Table 2 shows, he adjused R 2 was.669 which means ha he model explained abou 67% of he variaion in he S&P 500. In addiion, real GDP was significan o he.001 level and had he correc sign. Unemploymen was significan o he.10 level and also had he correc sign. The Fisher Effec, however, was no significan. One explanaion for he insignificance of he Fisher variable is ha he ransformaion of inflaion expecaions from semiannual o monhly daa was no an accurae means of incorporaing invesor s inflaion fears ino heir deerminaion of real ineres raes. Variable *** Significan o he.001 level * Significan o he.10 level Table 2: Regression Resuls for S&P 500 Adjused R 2 :.669 Sample Size: 327 Coefficien Tes Saisi c Prob Value Expeced Sign 13.593 24.356 *** 0 Posiiv e - 19.348-1.776 * 0.077 1.514 1.216 0.225 96 The Park Place Economis / vol. IX
Influences on he Sock Marke Variable Table 3: Regression Resuls for Transporaion Index Adjused R 2 :.509 Sample Size: 327 Coefficien Tes Saisi c Prob Valu e Expeced Sign 13.605 17.802 *** 0 Posiiv e 38.804 2.466 ** 0.014 1.612 0.717 0.474 *** Significan o he.001 level ** Significan o he.05 level The coefficien values sugges ha for a 1.0% increase in real GDP in a monh, he S&P 500 is expeced o increase by 13.59%. Meanwhile, he inerpreaion of changes in he unemploymen rae is more difficul. The difficuly resuls from aking he elasiciy of a variable already saed as a percenage. A more complex simulaion suggess ha if he unemploymen rae rises from 5% o 6.25% in a monh, he S&P 500 is expeced o fall by over 19%, holding all oher hings consan. I may be difficul o believe ha a major sock index would rise by 13.59% or fall by 19% if real GDP and unemploymen rise by 1% and 1.25%, respecively. However, i is also difficul o accep ha real GDP would rise by 1% and he unemploymen rae would increase by 1.25% in jus one monh. Dividing hese elasiciies by 10 provides more reasonable inerpreaions. For example, if real GDP rises by.10 % (1%/10), he S&P 500 is expeced o rise by 1.359% (13.59%/10), holding all else consan. Similarly, if he unemploymen rae rises from 5% o 5.125%, he S&P 500 is expeced o fall by 1.9%, holding all else consan. B. Model 2: Cyclical Indusries Resuls from Model 2 sugges ha boh real GDP and unemploymen raes have a posiive, significan influence on cyclical indusries. The Fisher Effec was no significan in his model. Table 3 presens he resuls from he regression. Alhough he posiive impac of real GDP on cyclical indusries is no unexpeced, he posiive relaionship beween unemploymen raes and cyclical indusries is puzzling. The only plausible explanaion for his resul is ha he represenaive cyclical sock index, he Dow Jones Transporaion Average (DJTA), is no really a cyclical index. A closer examinaion of Appendix A suggess ha he companies ha make up he DJTA are more business-oriened han vacaioner-oriened. For example, only 30% of he DJTA are airline companies whose passengers migh be sensiive o higher unemploymen raes. In addiion, his finding assumes ha he passengers are vacaion or leisure ravelers ha would be more affeced by higher unemploymen raes. However, mos airline passengers are raveling for business purposes and are under ime consrains o conduc heir business. Perhaps a more represenaive cyclical sock index would have been one ha examined he enerainmen in- Variable Table 4: Regression Resuls for Uiliies Index Adjused R 2 :.22 Sample Size: 327 Coefficien Tes Saisi c Prob Valu e *** Significan o he.001 level ** Significan o he.01 level Expeced Sign 15.671 8.763 *** 0 Posiiv e -50.794-1.506 0.133 7.381 2.908 ** 0.004 Posiiv e The Park Place Economis / vol. IX 97
Variable Table 5: Regression Resuls for Technology Index Adjused R 2 :.154 Sample Size: 182 Coefficien Nahan Taulbee Tes Saisi c Prob Valu e Expeced Sign 16.903 5.582 *** 0 Posiiv e -9.431-0.417 0.677 15.335 1.253 0.212 *** Significan o he.001 level dusry. C. Model 3: Defensive Indusries Because defensive indusries are leas affeced by he economy, i would be expeced ha he hree economic independen variables would have a less significan influence on hese indusries. Resuls from he GLS regression show ha real GDP and he Fisher Effec had a significan, posiive impac on he represenaive defensive sock index, he Dow Jones Uiliies Average (DJUA). Furher analysis suggess ha i is no unexpeced ha he Fisher Effec has a posiive relaionship wih he DJUA. Because he Fisher Effec measures ineres raes adjused for inflaion expecaions, i makes sense ha invesors would shif heir funds o defensive indusries when hey fear inflaion and higher ineres raes. I does no make sense, hough, ha here is a large, significan relaionship beween real GDP and he DJUA. As Table 4 shows, a 1% increase in real GDP would cause he DJUA o rise by 15.67%. Similarly, a 1% decline in real GDP would cause he DJUA o fall by 15.67%. Because he DJUA consiss of many companies ha provide elecriciy, i is plausible ha elecriciy consumpion varies wih he performance of he economy (as measured by real GDP). Unemploymen was no significan in his model. D. Model 4: Growh Indusries Resuls from Model 4 suggess ha only real GDP has a significan impac on growh indusries. As Table 5 shows, a 1% increase in real GDP causes he Pacific Exchange Technology Index (PETI), he represenaive growh index, o rise by almos 17%. This large increase in he PETI given a 1% increase in real GDP is no surprising because growh indusries are supposed o perform beer han he sock marke in general. Model 1 shows ha he overall marke will rise by13.59% given a 1% increase in real GDP, a smaller increase han ha of growh indusries. Unemploymen and he Fisher Effec may no have been significan because he daa period for Model 4 (1984-1999) did no include he volailiy of ineres rae and unemploymen in he 1970s and early 1980s. E. Model 5: Ineres-Sensiive Indusries As Table 6 indicaes, only real GDP had a significan influence on ineres-sensiive indusries. I is raher surprising ha he Fisher Effec was no significan in his model given ha ineres-sensiive indusries are highly responsive o flucuaions in ineres raes. However, he dependen variable used o represen ineres-sensiive indusries, he Fideliy Selec Variable Table 6: Regression Resuls for Financial Index Adjused R 2 :.449 Sample Size: 147 Coefficien Tes Saisi c *** Significan o he.001 level Prob Valu e Expeced Sign 9.899 9.774 *** 0 Posiiv e 0.902 0.199 0.843 0.08087 0.066 0.948 98 The Park Place Economis / vol. IX
Influences on he Sock Marke Brokerage and Invesmen Muual Fund, may have been he shorcoming for his model. A major financial sock index would likely have been more represenaive han he Fideliy fund ha was used. Anoher shorcoming of he dependen variable is ha is daa period was 1987-1999, which was a period of sabiliy of ineres raes. Finally, because only he bes socks are seleced and reained in a muual fund in order o mee he goals of a fund manager, i is no surprising ha all hree independen variables had a posiive coefficien. VI. CONCLUSION Does he economy acually have a significan influence on he performance of he sock marke? If so, how can invesors benefi from significan relaionships beween he economy and he sock marke? Resuls from his sudy show ha real GDP is he greaes economic deerminan of sock prices. For he overall sock marke and he four indusries examined, real GDP had a significan posiive influence on he represenaive sock indices. Bu can invesors increase heir rae of reurn during periods of rising GDP levels? A comparison of he real GDP coefficiens for he differen models, as seen in Table 7, indicaes ha during a booming economy invesors will maximize heir reurn by enering growh indusries. Table 7 shows ha he nex bes indusry o ener during good economic imes is defensive indusries. However, as menioned earlier, defensive indusries should no be grealy affeced by he busi- ness cycle. The high coefficien value for defensive indusries may be a resul of no having a sock index ha conained solely defensive socks. Table 7 also shows a srong correlaion beween he represenaive cyclical index and he overall marke. A 1% increase in real GDP over a monh will cause he S&P 500 o increase by 13.59% and he Dow Jones Transporaion Average o rise by 13.60%. This finding suppors a likely assumpion ha he overall marke is raher cyclical and follows he business cycle closely. Ineres-sensiive indusries are leas affeced by a change in real GDP, as shown by he 9.90 bea value. This finding is no surprising given ha ineres-sensiive indusries are mainly responsive o changes in ineres raes. Anoher finding suggess ha rising unemploymen raes significanly reduce he performance of he overall sock marke. Bu, indusry analysis suggess ha unemploymen does no influence which indusries o inves in. Finally, his sudy shows ha defensive indusries perform well during imes of inflaion fears and ineres rae uncerainy. Relaively unaffeced defensive sock indices during a recen marke crash (April 14, 2000) suppors his finding ha defensive indusries excel when invesors fear inflaion [Noe: The Consumer Price Index was higher han expeced which riggered he downward spiral of he sock marke on April 14, 2000]. In conclusion, he economy, especially real GDP, is a major deerminan of he performance of he sock marke. The resuls of his sudy provide invesors Table 7: Comparison of Real GDP s Impac on Differen Sock Indices Model Overall marke Cyclical Indusries Defensive Indusries Growh Indusries sock Ineres-Sensiive Indusries Dependen Variabl e Coefficien (Bea) T-Saisic S&P 500 13.593 24.356 0 Dow Jones Average Dow Jones Average Transporaion Uiliies Pacific Exchange Technology Index Fideliy Selec Brokerage and Invesmen Fund 13.605 17.802 0 15.671 8.763 0 16.903 5.582 0 9.899 9.774 0 Significance Level The Park Place Economis / vol. IX 99
Nahan Taulbee wih he ools o make wise porfolio decisions given heir oulook for he fuure of he economy. If invesors are opimisic abou fuure oupu growh (rises in real GDP), hey should concenrae heir funds ino growh indusries in order o maximize heir reurn on invesmen. So, are Presiden Clinon s famous words I s he economy supid applicable o he performance of he sock marke? The findings in his sudy sugges ha he answer o his quesion is a simple and sraighforward Yes. Yahoo! Finance. Available URL: hp:// finance.yahoo.com/m1?u REFERENCES Breen, William, Glosen, Lawrence, and Jagannahan, Ravi. Economic Significance of Predicable Variaions in Sock Index Reurns. The Journal of Finance. Volume 45 (5). December 1989. 1177-1189 Economagic.com: Economic Time Series Page. Available URL: hp://www.economagic.com/ Gujarai, Damordar N. Basic Economerics (2 nd ed.). New York: McGraw- Hill, Inc., 1988. Jones, Charles P. Invesmens: Analysis and Managemen (6 h ed.). Wiley. 1998 Mankiw, Gregory N. Macroeconomics. New York: Worh Publishers, 1997. Niemira, Michael P., and Klein, Philip A. Forecasing Financial and Economic Cycles. New York: John Wiley and Sons, Inc., 1994 Pearce, Douglas. An Empirical Analysis of Expeced Sock Price Movemens. Journal of Money, Credi, and Banking. Volume 16 (3). Augus 1984. 317-327 Reilly, Frank K., and Noron, Edgar A. Invesmens (5 h ed.). Orlando, Florida: The Dryden Press, 1999 Sheffrin, Seven M. Raional Expecaions. New York: The Cambridge Universiy Press, 1996 100 The Park Place Economis / vol. IX