We have built spreadsheet models of foreign exchange trading strategies. The assignment for this module involves writing a report explaining and evaluating the performance of these strategies (and any...

Introduction-
A quantitative hedge fund is moving into different asset classes apart from the traditional equities and it was us to research into different trading strategies and their performance over the span of last 20 years. We will look into forex trading which are widely popular and these are as follows – 1. Carry trade, 2. PPP value, 3. Order flow. Apart from the historical performance, we will also look at behavior of these strategies in the time of economic depression and try to predict what can happen during the COVID 19.
Carry Trade-
The carry trades strategy works on the premises of the covered interest rate parity. Based on this, ideally the higher interest rate currency should depreciate against the lower interest rate currency due to the interest rate differentials so that the arbitrage opportunities will not arise. However, this condition is not always true and investors can make profits by borrowing the low interest rate currency and investing in high interest rate currency. If a high interest rate currency, after a period of time does not depreciate as much as predicted or rather appreciate the investor or trades will benefit (Jurek, 2014).
As we can see, in the graph, barring a few recession months, overall the carry trades have been largely profitable. In the excel file, we have taken two positions in two currencies based on the percentage of the forward premium. We assume that the currency with the highest forward premium will not depreciate that much and we will end up taking a long position in the future markets in that currency (Burnside, 2011). On the other hand, we will take a short position in the currency with the lowest forward premium or at times with a forward discount.
Carry trades are extremely vulnerable to the crisis times. The reason behind this is that during the crisis, all the currencies do depreciate against the United States Dollar, due to capital outflows and FIIs closing their positions in the other countries. Flight to quality events will lead to depreciation of the currencies and these carry trades will have extreme losses. In the global financial crisis, the cumulative returns dropped my more than 60 percent in the span of 5 to 6 months. Hence, carry trades are negatively skewed due to extreme negative returns. Please find below the return distribution.
As we can see in the graph, the numbers of instances where the positive returns are observed are much higher as compared to the number of months with the negative returns. However, the negative returns are much higher than the positive returns in terms of quantum. This can lead to wealth destruction in few months due to overleveraged trades and can take you out of the markets.
COVID 19
During the times of Pandemic, the carry trades will lead to losses if the strategy is continued. The crisis will increase the cash outflows from the other countries in the search of less volatility and more protection. This will increase the demand for the USD and it will strengthen. We will see the similar situations and similar losses in this strategy as we saw in the 2008.
IMF PPP Value
As per the purchasing price parity, the country with higher inflation rates should depreciate in the long terms and with the lower inflation rates should appreciate. Based on this, the exchange rates can be predicted. Just like the interest rate parity condition, PPP should hold so that arbitrage opportunities do not exist (Middleton, 2005). By arbitrage we mean that, buying a basket of goods from the lower inflation and selling it in another country (Bilson, 1984).
In this strategy, we will take a long position in the currency where we have the highest difference between the spot exchange rate and the rate which justifies the purchasing power parity. We will be short on the USD. On the other hand, we will take a short position in the currency where the difference between the spot exchange rate and the PPP value is the lowest. We will go long on USD. This will be replicated across each month and based on the difference a currency pair will be identified.
As we can see in the graph, this strategy provides superior cumulative returns over the carry trade strategy. The major reason behind this is the dip we see in the global financial crisis, which is much lesser than the carry trade strategy. As we know in the economic terms, prices of goods are sticky and the increase in the prices of the goods is not sharp. This will ensure that during the times of crisis, the currencies with the highest differentials do not see extreme depreciation and the currency with the lowest differentials will not see appreciation or might see some depreciation.
COVID 19 –
With this strategy, the negative returns will not be as high as we observed in the carry trade strategy, due to the macroeconomic fundamentals in the countries we take position in. The difference between the carry trade and the order flows strategy is the way we take the position in the currency pairs and accordingly execute trades. The PPP strategy gets impacted lesser to the crisis and hence gives better protection from downside risk (Cho and Doblas-Madrid, 2014)
Order Flows Strategy
The order flow strategy, as compared to the previous two strategies, is rather unidirectional since only one trade is executed. This strategy is a momentum strategy where based on the speculation using the transactions flow or the order flows, a position is taken. When the order flow is huge in the forex markets by a large institution, it is believed that bigger players in the market are putting more money and hence, this trend should continue (Rime, Sarno, and Sojli, 2010). The biggest task here is to obtain the very confidential order flow data, which is not available to everyone (Lyons, 2001)
The performance of the trading strategy, as compared to the other two strategies, is ordinary. The cumulative returns over the given time period is much lesser than the carry trade. However, in the bad economic times. This strategy has given better protection to the trades as compared to the other strategies which eroded the wealth of the trades.
COVID 19
Order flows strategy is a momentum strategy and this will perform better as compared to the other two strategies in the times of crisis. Momentum strategy will look at the volume trades in the given direction and accordingly follow the trend. In the COVID 19 times, based on this strategy, a long position in the USD will take place and its appreciation will lead to profits.
Conclusion
The carry trade strategy provides the highest returns among three strategies. The downside risk of carry trade in the crisis environment is extremely high and hence at this time for better protection, order flow strategy should be used since that gives better protection and it rather follows a trend. On top of this, the order flow strategy takes the position in line with the large players and hence, more sophisticated trades can be placed during the bad economic times. The PPP strategy can also be implemented in the bad economic time, since it shows lesser negative returns as compared to the carry trade.
References
Carry Trades –
Jurek, J.W., 2014. Crash-neutral currency carry trades. Journal of Financial Economics, 113(3), pp.325-347.
Burnside, C., 2011. Carry trades and risk (No. w17278). National Bureau of Economic Research.
PPP –
Bilson, J.F., 1984. Purchasing power parity as a trading strategy. Journal of Finance, pp.715-724.
Middleton, A., 2005. Trading style analysis: a quantitative assessment of the currency industry. The Journal of Alternative Investments, 8(1), pp.14-28.    
Cho, D. and Doblas-Madrid, A., 2014. Trade intensity and purchasing power parity. Journal of International Economics, 93(1), pp.194-209.
Brière, M. and Drut, B., 2009. The revenge of purchasing power parity on carry trades during crises (No. 09-013. RS). ULB--Universite Libre de Bruxelles.
Order flows –
Rime, D., Sarno, L. and Sojli, E., 2010. Exchange rate forecasting, order flow and macroeconomic information. Journal of International Economics, 80(1), pp.72-88.
Lyons, R.K., 2001. New Perspective on FX Markets: Order‐Flow Analysis. International Finance, 4(2), pp.303-320.
Carry Returns
36160    36189    36217    36250    36280    36311    36341    36371    36403    36433    36462    36494    36525    36556    36585    36616    36644    36677    36707    36738    36769    36798    36830    36860    36889    36922    36950    36980    37011    37042    37071    37103    37134    37162    37195    37225    37256    37287    37315    37344    37376    37407    37435    37468    37498    37529    37560    37589    37621    37652    37680    37711    37741    37771    37802    37833    37862    37894    37925    37953    37986    38016    38044    38077    38107    38138    38168    38198    38230    38260    38289    38321    38352    38383    38411    38442    38471    38503    38533    38562    38595    38625    38656    38686    38716    38748    38776    38807    38835    38868    38898    38929    38960    38989    39021    39051    39080    39113    39141    39171    39202    39233    39262    39294    39325    39353    39386    39416    39447    39478    39507    39538    39568    39598    39629    39660    39689    39721    39752    39780    39813    39843    39871    39903    39933    39962    39994    40025    40056    40086    40116    40147    40178    40207    40235    40268    40298    40329    40359    40389    40421    40451    40480    40512    40543    40574    40602    40633    40662    40694    40724    40753    40786    40816    40847    40877    40907    40939    40968    40998    41029    41060    41089    41121    41152    41180    41213    41243    41274    41305    41333    41362    41394    41425    41453    41486    41516    41547    41578    41607    41639    41670    41698    41729    41759    41789    41820    41851    41880    41912    41943    41971    42004    42034    42062    42094    42124    42153    42185    42216    42247    42277    42307    42338    42369    42398    42429    42460    42489    42521    42551    42580    42613    42643    42674    42704    42734    42766    42794    42825    42853    42886    42916    42947    42978    43007    43039    43069    43098    43131    43159    43189    43220    43251    4.8756881343578167    2.5047704356282878    5.3829334732521161    6.0443481054441    7.1745124661773696    7.4775723345029022    3.7832254442007782    -1.0025248288649362    -2.1841684680855802    -4.8821287532525126    -9.2436759073053931    -8.2702031150553079    -6.1339510477263355    -5.7107572678122303    -11.009989053660238    -7.1561866032758186    -13.248283699642965    -11.403801632245875    -10.884286130827016    -15.408180837299357    -13.589301451238661    -14.329266812189273    -11.970568152049704    -3.3405683886564792    -1.1556601497544721    -0.96285234850900792    4.4204825518618511    3.5852920683962242    -2.3659589100563707    3.4032530475383083    6.2947712434702705    5.1345364849980895    5.7875514315422425    8.973982939241866    9.5793971743010147    16.018906531574114    17.148896173597457    19.835923369582094    20.317699942845163    22.633744358481827    24.598827152178611    28.23504067323092    27.234194301985465    27.995882989080652    32.849654165128946    33.786579670176451    35.909255773258344    38.911604480437326    40.244669446711377    36.188941501862487    36.540837546193742    38.523586560221574    42.468649321116374    44.728740376135768    44.626625830908864    41.356657329353567    40.307051843872074    42.550860459143522    46.515351558795608    47.559410102198761    48.876316555742825    53.862848860728228    48.374693363325441    49.190656798594937    50.278629582496599    50.535624367779789    52.960129417397404    55.415452119934962    59.354281118324074    57.399867550838323    59.318922545819355    60.42238210207433    60.414112531441042    64.231152360166007    65.118312927471038    66.4238024096299    66.112396208333863    68.020223183056487    67.948020932953341    69.007603622232097    71.706334804193588    75.899816327313403    79.69307989960231    75.846322203737941    76.282058861601897    72.381284681542439    66.890941510906018    68.248505853751865    67.00295451734884    65.477717216620846    67.274238309810656    76.378336169659562    77.376964917385791    79.775200766288989    81.342994263057236    87.877852970128586    87.430798499862306    87.801552031680558    90.102007567546607    95.78146347038016    97.606511684624948    104.26206493618417    100.78041056524515    89.65964662805294    96.955557107080153    99.622097711969758    96.114721114533708    97.888411130336337    95.436348463715234    96.293457254761449    90.500667995329096    95.485408325353589    97.395188415234884    95.674096084018672    94.468594831375313    91.551251857564154    84.788834632344148    64.130624151695912    55.534022585775546    49.308056546734257    34.730108125045795    42.389553994788322    48.633428019505502    54.677274429786138    60.483699918326785    62.806314114249801    64.534921558601681    64.392815898402162    67.394994007283117    70.874091642200668    70.494831407866457    71.968303185541444    73.080710055773608    75.894036795447605    76.837735523426247    80.9821332625596    77.883783050233788    72.111318335242032    77.365330051969607    72.970961187298954    81.301295958248758    83.599375545484207    85.717216722261156    86.131437369728289    84.609661689566337    86.00626339517548    86.401733664722983    90.325243301157201    88.185728153152482    87.806534253478148    84.180727809165859    84.418298412129772    87.102058615406008    92.123331819643283    88.874845209746269    91.840540117806441    94.188275985629218    94.13909422179043    90.651993652539758    91.935219912475304    92.072818035917209    95.308104563920779    101.4040700002643    97.790403548961947    96.758105265283291    96.166741240484583    96.702269247380229    95.185598969446417    95.421651620831113    97.481606579078615    101.35862200805818    98.564876015077473    92.611929231351994    86.825698554831007    82.93088915060703    81.095706718171357    86.073508035475641    85.281601642166976    83.921666846464149    83.807758373504583    84.477562681058927    86.140454012035661    89.868347640008551    88.79217974210259    89.429144620439544    92.005840585726787    91.728235152825988    92.165945041153279    89.583184859916514    90.450331352656889    97.374566640280165    98.349399262839583    83.632665396605958    91.223936571584588    93.216151347780212    91.565260901146644    87.371496436442627    81.738095073255863    83.146763297668954    79.330128029960505    81.698665352442887    88.514385224267286    90.377795740304478    92.041113892095382    89.070948599667588    88.413936503572245    90.011033560159802    91.103923081950626    91.757135455390056    95.185343018198168    96.001563488771311    98.568553028338101    97.77644286424821    98.442440612039888    100.7440867291606    99.245851633798608    101.63484534897358    101.98872608410596    98.826024452703578    96.719541082509693    97.481950292147914    99.841392728523388    103.22233424326321    98.506820735075394    100.37757135074213    98.239909432093086    97.180598323781524    100.32354518437421    99.857519676103536    99.308513930788351    100.83186775322405    102.0448254930068    101.20768194666358    99.138072826176057    31 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2018    4.875688134357814E-2    -2.3709176987295244E-2    2.8781630376238265E-2    6.6141463219198116E-3    1.1301643607332768E-2    3.0305986832552811E-3    -3.6943468903021248E-2    -4.7857502730657142E-2    -1.181643639220642E-2    -2.6979602851669338E-2    -4.3615471540528805E-2    9.7347279225008521E-3    2.1362520673289698E-2    4.2319377991410501E-3    -5.2992317858479965E-2    3.8538024503844082E-2    -6.0920970963671439E-2    1.8444820673970908E-2    5.1951550141886571E-3    -4.5238947064723423E-2    1.81887938606069E-2    -7.3996536095060073E-3    2.3586986601395576E-2    8.6299997633932257E-2    2.1849082389020058E-2    1.9280780124546482E-3    5.3833349003708619E-2    -8.3519048346563096E-3    -5.9512509784525935E-2    5.7692119575946776E-2    2.8915181959319636E-2    -1.1602347584721784E-2    6.5301494654415038E-3    3.1864315076996164E-2    6.0541423505915404E-3    6.4395093572731099E-2    1.1299896420233324E-2    2.687027195984637E-2    4.8177657326307077E-3    2.3160444156366644E-2    1.9650827936967818E-2    3.6362135210523228E-2    -1.0008463712454674E-2    7.6168868709518556E-3    4.8537711760483049E-2    9.3692550504749228E-3    2.1226761030818997E-2    3.0023487071790367E-2    1.3330649662740113E-2    -4.0557279448488748E-2    3.5189604433122357E-3    1.9827490140278403E-2    3.9450627608948019E-2    2.2600910550193198E-2    -1.0211454522688346E-3    -3.2699685015552205E-2    -1.0496054854815196E-2    2.2438086152715031E-2    3.9644910996520399E-2    1.0440585434031313E-2    1.3169064535441033E-2    4.9865323049853694E-2    -5.488155497402758E-2    8.1596343526944559E-3    1.0879727839017028E-2    2.5699478528315445E-3    2.4245050496176535E-2    2.4553227025374991E-2    3.9388289983891767E-2    -1.954413567485741E-2    1.9190549949809954E-2    1.1034595562549543E-2    -8.2695706332736041E-5    3.8170398287249718E-2    8.8716056730511195E-3    1.305489482158817E-2    -3.1140620129602725E-3    1.9078269747225762E-2    -7.2202250103153842E-4    1.0595826892786764E-2    2.6987311819616056E-2    4.1934815231197908E-2    3.7932635722889074E-2    -3.8467576958643612E-2    4.3573665786401095E-3    -3.9007741800595797E-2    -5.4903431706363248E-2    1.3575643428458961E-2    -1.2455513364031001E-2    -1.5252373007279107E-2    1.7965210931897291E-2    9.1040978598490363E-2    9.9862874772615462E-3    2.3982358489031519E-2    1.5677934967682439E-2    6.5348587070713837E-2    -4.4705447026631151E-3    3.707535318182742E-3    2.3004555358660916E-2    5.6794559028334191E-2    1.8250482142449065E-2    6.6555532515592208E-2    -3.481654370939119E-2    -0.11120763937192141    7.2959104790272566E-2    2.6665406048896445E-2    -3.5073765974360682E-2    1.7736900158026203E-2    -2.4520626666211714E-2    8.5710879104621551E-3    -5.7927892594323571E-2    4.9847403300244814E-2    1.9097800898813466E-2    -1.7210923312162729E-2    -1.2055012526434039E-2    -2.9173429738110435E-2    -6.7624172252200243E-2    -0.20658210480648265    -8.5966015659203809E-2    -6.2259660390412863E-2    -0.14577948421688491    7.6594458697425538E-2    6.243874024717172E-2    6.0438464102806871E-2    5.806425488540598E-2    2.3226141959230145E-2    1.7286074443518928E-2    -1.4210566019948676E-3    3.00217810888092E-2    3.4790976349175509E-2    -3.79260234334209E-3    1.4734717776749937E-2    1.112406870232175E-2    2.8133267396739853E-2    9.4369872797872012E-3    4.1443977391333167E-2    -3.0983502123258344E-2    -5.7724647149917624E-2    5.2540117167276329E-2    -4.3943688646707169E-2    8.3303347709497655E-2    2.2980795872355686E-2    2.1178411767768211E-2    4.1422064746720055E-3    -1.5217756801619717E-2    1.3966017056090636E-2    3.9547026954754247E-3    3.9235096364342519E-2    -2.1395151480046073E-2    -3.7919389967444803E-3    -3.6258064443122892E-2    2.3757060296395044E-3    2.6837602032762781E-2    5.0212732042372921E-2    -3.2484866098971207E-2    2.9656949080602086E-2    2.3477358678227783E-2    -4.918176383882783E-4    -3.4871005692506368E-2    1.2832262599355097E-2    1.3759812344190381E-3    3.2352865280035739E-2    6.0959654363435006E-2    -3.6136664513023588E-2    -1.032298283678652E-2    -5.9136402479861641E-3    5.3552800689550817E-3    -1.5166702779337272E-2    2.3605265138460785E-3    2.0599549582474921E-2    3.8770154289796306E-2    -2.793745992980709E-2    -5.9529467837254935E-2    -5.7862306765208996E-2    -3.8948094042240561E-2    -1.8351824324356253E-2    4.9778013173042784E-2    -7.9190639330870283E-3    -1.3599347957027857E-2    -1.1390847295949247E-3    6.6980430755419207E-3    1.6628913309768234E-2    3.7278936279728531E-2    -1.0761678979059719E-2    6.3696487833695553E-3    2.5766959652872859E-2    -2.7760543290077377E-3    4.3770988832723956E-3    -2.5827601812367859E-2    8.671464927404858E-3    6.9242352876231678E-2    9.7483262255940728E-3    -0.14716733866233625    7.5912711749787171E-2    1.9922147761955566E-2    -1.6508904466336266E-2    -4.1937644647039418E-2    -5.6334013631867519E-2  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