We have built spreadsheet models of foreign exchange trading strategies. The assignment for this...

Question

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 others you care to examine):
Assignment
You have been hired as a researcher in a quantitative hedge fund that until now has only considered equity market strategies. The fund has expanded and intends to develop foreign exchange strategies. As a preliminary step you have been asked to write a report considering at least three well-established strategies – ca
y trade, fair value (PPP Strategy) and order flows. The report should
iefly explain these strategies to your colleagues, report and evaluate the performance of these strategies based on the data files you have been using (attached excel). The exact definition of the strategies is up to you to determine (and explain), you may wish to consider other cross-sectional sort-based strategies and you may want to consider the strategies independently or in combination(s). Finally, your manager has requested that you comment on how you expect these strategies to perform in the Covid-crisis.
The exact methods used to answer the assignment are up to you. Imagine your manager has told you to do this piece of research and then gone on vacation. Make the best attempt you can, given the instructions you have. If you are unsure exactly what to do, make an intelligent assessment and justify it in the report you write.
Style
The reports are to be written in business style, as if prepared for your manager. The use of graphs and tables is encouraged, where relevant and these are not counted in the report length guidelines so make all graphs and tables large and legible. Full referencing is necessary.
Guidelines
Your manager is busy and does not have time to waste. The target length for each report is four pages of text. Tables and charts are extra. As your manager values conciseness and completeness equally you should aim to include all the things you deem to be important and exclude anything that is not. If your report needs to be longer than four pages because there is just so much stuff you need to include then fine. Similarly, if you feel you can cover what is needed in less than four pages then you can hand in a shorter piece of work. However, your manager (and the marker) may not agree, so this choice will affect your grade.
We have addressed the various strategies in the course. You should therefore make an effort to link your reports to what we have discussed. You could, for example, emphasize where your results confirm (or conflict with) the mainstream view.
Sources
The Ca
y Trade
Ken Froot and Richard Thaler (1990) “Anomalies: Foreign Exchange”, Journal of Economic Perspectives, 4, 179–192.
Craig Burnside (2011) “Ca
y Trades and Risk” NBER working paper No. 17278
John F.O. Bilson XXXXXXXXXXAdventures in the Ca
y Trade CME Group.
Investment banks have realised that they can offer funds that track foreign exchange strategies to investors. One group of funds which follow the performance of the cu
ency ca
y trade are Deutsche Bank’s Harvest Indices. For more information read XXXXXXXXXXdb Cu
ency Harvest, Deutsche bank.
Craig Burnside (2011) “Ca
y Trades and Risk” NBER, working paper No. 17278.
Lukas Menkhoff, Lucio Sarno, Maik Schmeling and Andreas Schrimpf (2011) “The Risk in Ca
y Trades” The Journal of Finance and alternative description: http:
voxeu.org/article
isk-ca
y-trades
Norges Bank Investment Management (2014) “The Cu
ency Ca
y Trade”, Discussion Note 03/2014
Fair Value Model (PPP Strategy)
Menzie Chinn (2011) “Macro Approaches to Foreign Exchange Determination” Working Paper Series, La Follette School Working Paper No XXXXXXXXXX, University of Wisconsin-Madison
(2017) “Our Big Mac index of global cu
encies reflects the dollar’s strength” The Economist
Richard Meese and Kenneth Rogoff (1984) “Empirical Exchange Rate Models of the Seventies: Do they Fit Out of Sample?” Journal of International Economics, 3-24
Jan Annaert and Marc De Ceuster (1997) “The Big Mac: More than just a Junk Asset Allocator?” International Review of Financial Analysis
Yin Wong Cheung, Menzie Chinn and Antonio Garcia “Empirical exchange rate models of the nineties: are any fit to survive?” Journal of International Money and Finance, 24
Yin Wong Cheung, Menzie Chinn, Antonio Garcia and Yi Zhang (2017) “Exchange Rate Redux: New Models, New Data, New Cu
encies”, European Central Bank, working paper 2018
Robert Cumby (1996) “Forecasting exchange rates and relative prices with the hamburger standard: Is what you want what you get with McParity?”, NBER, working paper 5675 (http:
faculty.georgetown.edu/cumby
papers
igmac97.pdf)
Michael Melvin, John Prins, Duncan Sand, Forecasting Exchange Rates: An Investor Perspective
Order Flow
Martin Evans (2006) “Foreign Exchange Market Microstructure” mimeo
Martin Evans and Richard Lyons (2006) “Understanding Order Flow”,International Journal of Finance and Economics
Mintao Fan and Richard Lyons (2003) “Customer Trades and Extreme Events in Foreign Exchange” in Monetary History, Exchange Rates and Financial Markets: Essays in Honour of Charles Goodhart
Martin Evans and Richard Lyons (2002) “Order Flow and Exchange Rate Dynamics” Journal of Political Economy, XXXXXXXXXX
Ian Marsh and Ceire O’Rourke (2004) “Customer Order Flows in Foreign Exchange Markets: Do They Really Contain Information?” mimeo
Martin Evans and Richard Lyons (2005) “Meese-Rogoff Redux: Micro-Based Exchange Rate Forecasting” American Economic Review”
Lucas Menkhoff et al (2011) “The cross-section of cu
ency order flow portfolios”, mimeo

final-assessment-prompt-gfdvoq4t.docx international-finance-working-filefor-final-1t55gxdg.xlsx

Kushal · Accepted Answer

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	1.408668224413042E-2	-3.8166352677084604E-2	2.3685373224824322E-2	6.8157198718242953E-2	1.8634105160372706E-2	1.6633181517908338E-2	-2.9701652924277237E-2	-6.5701209609536418E-3	1.5970970565875597E-2	1.0928895217908165E-2	6.53212373439397E-3	3.428207562808229E-2	8.1622047057299668E-3	2.5669895395668163E-2	-7.92110164089831E-3	6.6599774779169396E-3	2.301646117120653E-2	-1.4982350953619255E-2	2.3889937151749495E-2	3.5388073513237459E-3	-3.162701631402353E-2	-2.1064833701938665E-2	7.6240920963813741E-3	2.3594424363755105E-2	3.3809415147398519E-2	-4.7155135081878533E-2	1.8707506156667893E-2	-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December 1998	29 January 1999	26 February 1999	31 March 1999	30 April 1999	31 May 1999	30 June 1999	30 July 1999	31 August 1999	30 September 1999	29 October 1999	30 November 1999	31 December 1999	31 January 2000	29 February 2000	31 March 2000	28 April 2000	31 May 2000	30 June 2000	31 July 2000	31 August 2000	29 September 2000	31 October 2000	30 November 2000	29 December 2000	31 January 2001	28 February 2001	30 March 2001	30 April 2001	31 May 2001	29 June 2001	31 July 2001	31 August 2001	28 September 2001	31 October 2001	30 November 2001	31 December 2001	31 January 2002	28 February 2002	29 March 2002	30 April 2002	31 May 2002	28 June 2002	31 July 2002	30 August 2002	30 September 2002	31 October 2002	29 November 2002	31 December 2002	31 January 2003	28 February 2003	31 March 2003	30 April 2003	30 May 2003	30 June 2003	31 July 2003	29 August 2003	30 September 2003	31 October 2003	28 November 2003	31 December 2003	30 January 2004	27 February 2004	31 March 2004	30 April 2004	31 May 2004	30 June 2004	30 July 2004	31 August 2004	30 September 2004	29 October 2004	30 November 2004	31 December 2004	31 January 2005	28 February 2005	31 March 2005	29 April 2005	31 May 2005	30 June 2005	29 July 2005	31 August 2005	30 September 2005	31 October 2005	30 November 2005	30 December 2005	31 January 2006	28 February 2006	31 March 2006	28 April 2006	31 May 2006	30 June 2006	31 July 2006	31 August 2006	29 September 2006	31 October 2006	30 November 2006	29 December 2006	31 January 2007	28 February 2007	30 March 2007	30 April 2007	31 May 2007	29 June 2007	31 July 2007	31 August 2007	28 September 2007	31 October 2007	30 November 2007	31 December 2007	31 January 2008	29 February 2008	31 March 2008	30 April 2008	30 May 2008	30 June 2008	31 July 2008	29 August 2008	30 September 2008	31 October 2008	28 November 2008	31 December 2008	30 January 2009	27 February 2009	31 March 2009	30 April 2009	29 May 2009	30 June 2009	31 July 2009	31 August 2009	30 September 2009	30 October 2009	30 November 2009	31 December 2009	29 January 2010	26 February 2010	31 March 2010	30 April 2010	31 May 2010	30 June 2010	30 July 2010	31 August 2010	30 September 2010	29 October 2010	30 November 2010	31 December 2010	31 January 2011	28 February 2011	31 March 2011	29 April 2011	31 May 2011	30 June 2011	29 July 2011	31 August 2011	30 September 2011	31 October 2011	30 November 2011	30 December 2011	31 January 2012	29 February 2012	30 March 2012	30 April 2012	31 May 2012	29 June 2012	31 July 2012	31 August 2012	28 September 2012	31 October 2012	30 November 2012	31 December 2012	31 January 2013	28 February 2013	29 March 2013	30 April 2013	31 May 2013	28 June 2013	31 July 2013	30 August 2013	30 September 2013	31 October 2013	29 November 2013	31 December 2013	31 January 2014	28 February 2014	31 March 2014	30 April 2014	30 May 2014	30 June 2014	31 July 2014	29 August 2014	30 September 2014	31 October 2014	28 November 2014	31 December 2014	30 January 2015	27 February 2015	31 March 2015	30 April 2015	29 May 2015	30 June 2015	31 July 2015	31 August 2015	30 September 2015	30 October 2015	30 November 2015	31 December 2015	29 January 2016	29 February 2016	31 March 2016	29 April 2016	31 May 2016	30 June 2016	29 July 2016	31 August 2016	30 September 2016	31 October 2016	30 November 2016	30 December 2016	31 January 2017	28 February 2017	31 March 2017	28 April 2017	31 May 2017	30 June 2017	31 July 2017	31 August 2017	29 September 2017	31 October 2017	30 November 2017	29 December 2017	31 January 2018	28 February 2018	30 March 2018	30 April 2018	31 May 2018	4.875688134357814E-2	2.5047704356282896E-2	5.3829334732521161E-2	6.0443481054440973E-2	7.174512466177374E-2	7.4775723345029022E-2	3.7832254442007773E-2	-1.0025248288649369E-2	-2.1841684680855789E-2	-4.8821287532525126E-2	-9.2436759073053931E-2	-8.2702031150553079E-2	-6.1339510477263381E-2	-5.7107572678122331E-2	-0.1100998905366023	-7.1561866032758215E-2	-0.13248283699642965	-0.11403801632245875	-0.10884286130827009	-0.15408180837299351	-0.13589301451238661	-0.14329266812189262	-0.11970568152049704	-3.3405683886564785E-2	-1.1556601497544727E-2	-9.6285234850900792E-3	4.420482551861854E-2	3.5852920683962231E-2	-2.3659589100563705E-2	3.4032530475383072E-2	6.2947712434702707E-2	5.1345364849980923E-2	5.7875514315422427E-2	8.9739829392418591E-2	9.5793971743010131E-2	0.16018906531574123	0.17148896173597455	0.19835923369582092	0.20317699942845163	0.22633744358481828	0.24598827152178609	0.28235040673230932	0.27234194301985465	0.2799588298908065	0.32849654165128955	0.33786579670176448	0.35909255773258347	0.38911604480437384	0.40244669446711395	0.3618894150186252	0.36540837546193744	0.38523586560221584	0.42468649321116386	0.44728740376135706	0.44626625830908823	0.41356657329353602	0.40307051843872083	0.42550860459143586	0.46515351558795626	0.47559410102198757	0.4887631655574286	0.5386284886072823	0.48374693363325472	0.49190656798594917	0.50278629582496626	0.50535624367779786	0.52960129417397439	0.55415452119934938	0.59354281118324115	0.57399867550838368	0.59318922545819364	0.60422382102074312	0.60414112531441044	0.64231152360166011	0.65118312927471123	0.6642380240962994	0.66112396208333912	0.68020223183056494	0.67948020932953335	0.69007603622232017	0.71706334804193617	0.75899816327313407	0.79693079899602315	0.75846322203737948	0.76282058861601953	0.72381284681542368	0.66890941510906043	0.6824850585375194	0.67002954517348834	0.65477717216620923	0.67274238309810652	0.76378336169659689	0.77376964917385838	0.79775200766288989	0.81342994263057233	0.87877852970128623	0.87430798499862306	0.87801552031680585	0.90102007567546671	0.9578146347038009	0.97606511684624997	1.0426206493618422	1.0078041056524509	0.89659646628052947	0.96955557107080204	0.99622097711969848	0.96114721114533785	0.97888411130336406	0.95436348463715237	0.9629345725476145	0.90500667995329098	0.95485408325353582	0.97395188415234935	0.95674096084018667	0.94468594831375263	0.9155125185756422	0.8478883463234419	0.64130624151695925	0.55534022585775544	0.49308056546734258	0.34730108125045767	0.4238955399478832	0.48633428019505492	0.54677274429786182	0.60483699918326783	0.62806314114249795	0.64534921558601688	0.643928158984022	0.67394994007283116	0.70874091642200665	0.70494831407866454	0.71968303185541449	0.73080710055773623	0.75894036795447606	0.7683773552342632	0.80982133262559641	0.77883783050233801	0.72111318335242036	0.77365330051969672	0.72970961187298955	0.8130129595824872	0.83599375545484289	0.85717216722261114	0.86131437369728314	0.8460966168956634	0.86006263395175409	0.86401733664722946	0.90325243301157199	0.88185728153152587	0.87806534253478141	0.84180727809165856	0.84418298412129811	0.87102058615406086	0.92123331819643384	0.88874845209746267	0.9184054011780648	0.94188275985629255	0.94139094221790431	0.90651993652539797	0.91935219912475308	0.92072818035917214	0.95308104563920792	1.014040700002643	0.97790403548961946	0.9675810526528329	0.96166741240484677	0.9670226924738019	0.95185598969446461	0.95421651620831072	0.97481606579078561	1.0135862200805819	0.98564876015077474	0.92611929231351975	0.86825698554831077	0.82930889150607023	0.81095706718171401	0.86073508035475677	0.85281601642166971	0.83921666846464182	0.83807758373504693	0.84477562681058882	0.86140454012035705	0.89868347640008561	0.88792179742102584	0.89429144620439538	0.92005840585726828	0.91728235152826054	0.92165945041153297	0.89583184859916509	0.90450331352656999	0.97374566640280169	0.98349399262839576	0.83632665396605954	0.91223936571584674	0.93216151347780229	0.

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...

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